10-Intergrade Example
【600题】微臣数学ONE PASS Pro讲义 2020.6
It's also figuring out whY.
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微臣 GRE 数学 600 题 使用说明
本资料题目源自 GRE Official Guide、过往 GRE 考试题目、针对知识点讲解的改编题
目，以及最新的 2019 年-2020 年 GRE 考试题目。
第五节.
数据分析........................................................................................................................................... 34
最后建议同学们不要仅仅为了把 600 题做完就一天狂刷 100 多道。做每道题要保证效
果，思考题目中有哪些知识点和技巧。有线下 325 班的同学说，课上听懂的题目，隔两周
不复习，当时跳进去的坑现在还会往里跳。对于数学题而言，做过的题目，尤其是精讲过
的题目重做的意义，比盲目做新题的意义要大得多。所以在时间有限的前提下，优先重做
第一章精选 200 题，作为 GRE 数学 ONE PASS 班上课使用的内容，是针对六大专题：
算术、代数、几何、数据分析、应用题与图表题、陷阱题与解题技巧的最典型的题目，难
度等级为 3-5。建议同学们在结课后至少再做一遍这部分练习。
第二章综合练习 300 题，包括基础练习和进阶练习（真·170）两部分。
上课讲过的精选 200 题。
2
目录
第一章.
精选 200 题 ...................................................................................................................................... 4
Mobile ad hoc network
CHALMERSWireless Networks ProjectReportMobile Ad-hoc Network (MANET)Group 5Azadeh Hosseinzadeh 810911-6742Molood Noori Alavijeh 850913-5789Wenjing Li 860323-T120Yang Wang 850426-5110Table of contentsTable of contents (2)Review Question (3)Introduction (4)MANET (4)MANET Features (5)Mobile IP (6)Problems and issues concerning combination of MANET andMobile IP (6)Mobile IP for ad hoc network (8)Features of the suggested method (8)Adapting Mobile IP to MANET (9)1.Advertisements broadcasting by Foreign Agents: (9)2.Detecting nodes movement: (9)Summary of Study of Simulation (11)Results (12)Conclusion (12)Future work (13)Reference: (13)Review QuestionHow Mobile IP for ad hoc network method does works in short?IntroductionIn today’s communication world, wireless technique and mobility computing are gaining more and more popularity. Wireless devices are widely accepted and used by movable devices such as cell phones, laptops, and PDAs.A recent very hot research area concerning IP mobility is mobile ad hoc network (MANET). It is a self-configuring network of mobile devices which are connected by wireless links. Outstanding features of MANET compared to normal wireless network are that no fixed infrastructure is needed, it is easy to set up and it can transmit beyond the range of normal fixed access point. In recent years, there have been tremendous researches in developing MANET routing in order to achieve mobility feature. Many routing protocols have been proposed including several using on-demand routing ones. [1] In our study of simulation session, an on-demand routing protocol named AODV will be applied to the emulation environment.On the other hand, in wireless internet environment Mobile IP is a standard protocol to support IP mobility which has been wildly accepted. Mobile IP allows a host to roam from one subnet to another while retaining the same IP-address. Within MANET, IP mobility is restricted to the ad hoc network area and because nodes in ad hoc network are mobile, roaming of nodes between different ad hoc networks cannot be avoided.Therefore there is a need to make use of Mobile IP and MANET together.In this project we have looked at how ad hoc networks in which on-demand routing is used can be connected to the Internet and how to provide nodes in the ad hoc network with the roaming services that Mobile IP enables.Mobile IP for Mobile Ad Hoc Networks is a solution to use Mobile IP to provide nodes within MANET with internet. From a technical point of view, there can be a simulation environment for testing the suggested solution for combining MANET and MIP. Since the expenses of the simulation is too high for a university term paper,in this project the results of the simulation that has been performed in Carnegie Mellon University about this issue is also going to be studied. MANETMANET is a self-configuring network and it is a type of wireless ad hoc networks that became popular due to the increasing application of laptops and 802.11/Wi-Fiwireless networking since 1990s. In a MANET, mobile devices are connected by any number of wireless links, every device is free to move independently in any arbitrary direction and thus its links to other devices will be changed on a regular basis. Therefore, each device is also a router to forward traffic to other devices. A MANET may operate in isolation, or may be connected to a fixed network. MANET FeaturesMANETs have several important characteristics different from the higher-speed, semi-static topology of the fixed Internet. These characteristics create some basic assumptions and performance concerns for MANET’s protocol design.(1)Dynamic topologies: Devices are mobile and free to move arbitrarily andthe change of the connectivity among the devices and network topology may be unpredictable.(2)Multi-hop routing: a MANET uses multi-hop routing instead of staticnetwork infrastructure to provide network connectivity. Multi-hop is more complex than single-hop in terms of structure and implementation, but even more in functionality and applicability.(3)Bandwidth-constrained, variable capacity links: Wireless links will havelower capacity than their hardwired counterparts. In addition to the effects of multiple access, fading, noise, and interference conditions.(4)Energy-constrained: Some or all of the devices in a MANET may rely onbatteries.(5)Limited physical security: The increased possibility of security threatsshould be carefully considered. Mobile wireless networks are usually easier to threats than are fixed cable nets. Existing link security techniques are often applied within wireless networks.MANET routing protocol AODV is an on-demand distance vector protocol. Therefore periodic routing table exchanges do not exist. As soon as a node requires communicating with another node, the routes are set up. When a node does not have any information about the route to the node it wants to communicate with, a rout discovery starts in order to set up a path from the source to the destination and vice versa.[6]Mobile IPThe Mobile IP is a standard defined by IETF to support IP mobility for mobile device users when they are moving from one network to another.[3]Transparent to higher level protocols like TCP and UDP and applications it allows users with mobile devices to stay connected without changing IP address when roaming between networks with a different IP addresses.In order to keep existing transport layer connections, like TCP, during roaming every mobile node get a home address which is connected with the endpoint of a tunnel to mobile node home agent,.With this home address the mobile devices become able to receive data in such a way that it was on its home network ignoring its current location on the Internet.[4]When a user leaves its home network and enters a foreign network it uses an IP address valid on foreign network called care-of address which recognize its current location. The care of address must be changed whenever a mobile node moves from one network to another. A mobile node in a foreign network is named a visiting node.A visiting node has to register its current care of address with its home agent while visiting a foreign network to represent it within its home network and makes it able to receive data. It will be done by registering through a foreign agent that is located in foreign network.Problems and issues concerning combination of MANET and Mobile IPSince an ad hoc network has special characteristics and it is substantially different from those of the fixed internet, connecting an ad hoc network to the internet raise several issues concerning routing and providing nodes with IP addresses with possibility to route from fix internet. Also, Mobile IP for MANET solution brings up some problems because it has been based on using foreign care-of address.In this part, some of these routing and addressing issues are going to be argued and also problems of using Mobile IP within a multi-hop ad hoc network are going to be discussed.On the other hand, since ad hoc network (MANET) is a self-configuring network of mobile devices which can come and go as they want the two aspects of fix network which are the capability to use one route to entire network instead of having one route per host and the capability to use default routes have not been required. Moreover, mobile ad hoc network must be able to perform without any centralized control and it should be formed by any number of nodes without necessity to use any special network ID and unconcerned of addresses they use.It indicates that it is not possible to understand if a node is a part of special network by looking at the network ID. Also default routes are not useful since ad hoc network doesn`t have hierarchy and it is totally autonomous. Consequently, routing in MANET is usually accomplished using just host specific routes.IP multi-hop communication within ad hoc network is another characteristic of MANET that differentiates it from a fixed network. IP layer routing must be used by nodes to attain a gateway between fixed internet and ad hoc network since they do not have link-layer connectivity with all other nodes in the ad hoc network. Another problem that has to be concern is, it is impossible for nodes to find out the location of the destination by looking at the destination`s network ID due to do not having any assumptions about their network ID`s. Moreover, since on-demand routing has been used in ad hoc network and routs are only set up when they are needed, nodes are not able to expect to have routes to all obtainable hosts within the ad hoc network.The route discovery mechanism of MANET protocol has to look for the destination inside the ad hoc network before making decision about if the destination is in the ad hoc network or not because do not having a host route does not necessarily mean that it is impossible for nodes to reach it inside the ad hoc network.Furthermore, using Mobile IP for internet access in a multi-hop ad hoc network also brings several problems since IP mobile is designed generally for fixed internet and wireless leaf networks. It has been designed to have the foreign agent and the visiting node on the same link. Packets to the visiting node are forwarded by the foreign agent during link layer connectivity .On the other hand, in ad hoc network, the foreign agent and a visiting node might not have link-layer connectivity and it use multi-hop communication instead. So Mobile IP has to rely on the network routing protocol that has been used in ad hoc network for routing packets between the foreign agent and mobile node when it applied to MANET. Multi-hop communication has also influence on the movement detectionmechanism supported by Mobile IP.A visiting node has to count on the routing protocol to decide if there is a root to the foreign agent or not since it doesn`t have access to foreign agent by using link-layer feedback .[2][8]Mobile IP for ad hoc networkIn our project we studied a method to enable MANET nodes to access Internet and obtain mobility services of Mobile IP which is called Mobile IP for ad hoc network. This method uses Mobile IP foreign agents as access points to the Internet.The way this method works as follows in short:1) Any node within an ad hoc network that wants to access Internet always uses their home address for any interactions and communications. When the node roams from the home network to a new network it registers with a foreign agent.2) For any node to send a packet to a host on the Internet, tunnel the packet to the currently registered foreign agent.3) For any node to receive packets from hosts on the Internet. The packets will be delivered to foreign agent through ordinary Mobile IP mechanisms. The foreign agent will then send the packet to the node using ad hoc routing protocol. Features of the suggested methodThis method allows a host to move from one subnet to another while retaining the same IP-address. Since the host retains the same address all the time it can be used to contact the host without knowing its physical location. A session between two hosts can continue even if one of them moves. Each host has a router called its home agent. The home agent is the router for the subnet belonging to the host’s home address. When a host moves, it registers with a foreign agent who is willing to serve and informs its home agent of its new address, called it's care of address. When a host B wants to send a packet to another host A the packet is routed to the home agent of A. The agent knows the care of address of A and forwards the packet there. When host A sends packets to host B it uses its home address as the source address. The pattern of the routing is that of a triangle, from host B to the home agent of A, and finally back to host B.Tunneling mechanism makes it possible that this method can incorporate the default route concept into AODV without big modifications, when a node tries to send a packet, the packet is firstly delivered within the ad hoc network, if the destination cannot be found, it will be tunneled to the foreign agent preserving that it has already registered with the foreign agent.When a packet is tunneled to the foreign agent, the IP address of that foreign agent is required to be encapsulated into the packet outer IP header. The ad hoc routing protocols will tunnel the packet by looking at the source address and destination address. If no route to the foreign agent can be found, a searching mechanism directed by ad hoc routing protocols will be activated. If the node does not have any connection with any foreign agent, it considers the destination as unreachable.A feature called reverse tunneling is used by having the Foreign Agent tunnel packets back to the Home Agent when it receives them from the Mobile Node. Adapting Mobile IP to MANETWhen a visiting node roams from one subnet to another using Mobile IP foreign agent, this node must have link-layer connectivity with the foreign agent. At the meanwhile, link-layer connecting cannot be obtained in a mobile ad-hoc network. In order to identify the connection an upper layer-network layer is used, i.e. IP addresses.In the following sections the different Mobile IP mechanisms that are affected by mobile IP for ad hoc network will be discussed further.1.Advertisements broadcasting by Foreign Agents:Broadcasting advertisements is a very important feature in wireless communication which enables all related units keeps information updated. In Mobile IP the minimal time interval between two advertisements is 1 second.This can lead to a message over flooding problem in Mobile ad hoc network considering MANET uses multi-hop mechanism. Though the most suitable time interval has not been derived, a period of 5 seconds will be used in the study of simulation section later on.2.Detecting nodes movement:Mobile IP provides several algorithms on detecting nodes movement i.e., Lazy Cell Switching (LCS), Eager Cell Switching (ECS). However, none of themcould meet the requirement of MANET since MANET uses multi-hop mechanism in which several hops may occur between the foreign agent and the visiting node. For example, LCS principle suggests that a node should use the same foreign agent for as long time as possible. However as MANET uses multi-hop, this creates time delay problems, if a new foreign agent is discovered to be much closer (for example 3 hops less) than the one that the node is currently registered, the node can still not switch to it. Problems when applying ECS to MANET emerges as that it assumes movement along a straight line. [8] ECS does not allow a visiting node switch freely between different agents which may cause the same time delay problems as described in LCS.Mobile IP for ad hoc network provides a new method using hop counts to decide which agent should be chosen. The mobile IP for MANET Cell Switching (MMCS) algorithm suggests that a registered visiting node should register with another foreign agent if it is at least two hops closer to this foreign agent than the foreign agent that it is currently registered through, for two consecutive agent advertisements.(a)All nodes are currently registered with Foreign Agent 1. Node D is moving towards Foreign Agent 2.(b) Node D has registered to Foreign Agent 2 now since there exist two more hops than to connect to Foreign Agent 1Figure.1 Mobile IP for MANET Cell Switching Algorithm ExampleMMCS is an extension of ECS. It helps visiting nodes easier to connect them to a more efficient foreign agent and also helps prevent frequent switching and minimize the chances that the visiting node will connect to a temporary seemingly stable agent. Figure.1 shows how MMCS works.Summary of Study of SimulationIn order to study the different mechanisms of Mobile IP for MANET the Carnegie Mellon University has set up the Monarch project in Network Simulator 2which actually simulates this mechanism. The routing protocol they have used is AODV. The periodic agent advertisement is the main mechanism that is studied in the simulations.The mechanisms for adapting Mobile IP to an on-demand ad hoc network include broadcast and unicast approaches. Switching between foreign agents is impossible in the unicast approach.The study of simulation presented in this section intends to evaluate the differences between the two approaches of broadcast and unicast.This experience includes 15 mobile nodes that move randomly over a rectangular (1000m x 500m) flat space for 900 seconds and two foreign agents, one on each side of the rectangle and there are a number of wired nodes as well i.e. home agents and their corresponding nodes but our focus will be on the wireless part only. The total number of visiting nodes in the network is the core parameter in the simulations which demonstrates the relative movement between nodes.ResultsFor both the broadcast and unicast approaches, the number of visiting nodes that reply to the request for registration is supposed to be almost linear.In the broadcast approach the two foreign agents flood the network with their agent advertisements periodically. In the unicast approach foreign agents only send agent advertisements to those nodes which are registered with them.Since unicast generates more control packets the AODV overhead is higher. Therefore when the percentage of visiting nodes is low the unicast approach is better than the broadcast approach. But this statement is only true when more than half of the nodes are visiting nodes and so the broadcast approach generates less overhead than the unicast approach. So when there are no visiting nodes the broadcast approach generates more traffic than the unicast approach.Because the overhead of the protocol is larger in the unicast approach,the total number of transmissions is higher.A lost packet might be a result of a broken link and therefore the overhead of routing is larger in the unicast approach.In the broadcast approach typically the nodes switch about 2 times but in the unicast approach they are not able to reregister with a closer foreign agent. Although in the unicast approach, a node might switch a foreign agent can continue to send agent advertisements to it which is why sometimes a visiting node is reregistered with two foreign agents at the same time. Switching to the closest foreign agent is good because the delay of traverse will be kept at minimum. ConclusionIn this project, we have studied on the theory of MANET, Mobile IP and make our focus on the solution of integrating these two techniques which enables IP mobility of mobile nodes in MANET between networks. Regarding to the issues when applying Mobile IP to mobile ad hoc networks, this method uses Mobile IP foreign agents as access points to the Internet and ad hoc routing protocol when information sent between the foreign agent and the visiting node. Also a scheme of movement detection and the use of reverse tunneling to Internet access points are included. The simulation study has evaluated from the two different approaches, namely, unicast and broadcast. Broadcasting is better than unicasting at all times in sending agent advertisements periodically except when no visiting nodes are in MANET.The outcomes of the simulation illustrate that being close to a foreign agent leads to reduction of traffic load and delay of packets. Therefore spreadingthe information about the existence of foreign agents is valuable even though it has some disadvantages.Future workBecause of the lack of experiences and time in the study of MANET area, we didn’t implement the simulation ourselves. This might be some future work for us. At the same time, there are some related areas we didn’t work through but are still very interested in. For instance, Optimized Link State Routing Protocol (OLSR), Study of Node Mobility, Multicast and Dynamic address allocation. Reference:[1]David B. Johnson and David A. Maltz, Mobile computing,chapter 5, pp. 153-181, Kluwer Academic Publishers,1996[2]Yu-Chee Tseng, Chia-Ching Shen, and Wen-Tsuen Chen," Mobile IP and Ad Hoc Networks: An Integration and Implementation Experience", Computer, 2003[3] Charles E. Perkins, “Mobile IP,” IEEE Communications Magazine, May 1997.[4] Hui Lei and Charles E. Perkins, “Ad hoc networking with Mobile IP,” in Proceedings of 2nd European Personal Mobile Communication Conference, 1997[5] “The Internet Engineering Task Force (IETF),” Webpage, /.[6] David A. Maltz, Josh Broth, a d David B. Johnson, “The effects of on-demand behaviour in routing protocols for ad hoc networks,” IEEE Journal on Selected Areas of Communications, 1999[7] Charles E. Perkins and Elizabeth M. Royer, “Ad-hoc on-demand distance vector routing,” in Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, Feb. 1999.[8] Ulf Jonsson, Fredrik Alriksson, “MIPMANET -Mobile IP for Mobile Ad Hoc Networks”, IEEE, 2000.。
英语作文,写关于互联网的发明1971年
英语作文,写关于互联网的发明1971年全文共6篇示例，供读者参考篇1The Amazing Story of How the Internet Was BornHi there! My name is Jamie and I'm going to tell you all about how the internet was invented way back in 1971. It's a pretty wild story involving lots of really smart people and some huge computers. Get ready, because this is going to blow your mind!It all started in the 1960s when computers were these massive machines that took up entire rooms. Scientists and researchers used them to do lots of heavy duty calculations and store information. However, each computer could only work on its own. There was no way for the different computers to share data and talk to each other over long distances.Some super geniuses at places like MIT and the University of California had a brilliant idea - what if they could connect all these mighty computers together into one giant network? That way, researchers across the country could easily share information and work together on projects. A scientist inCalifornia could send data straight to a computer in Massachusetts! Revolutionary, right?The guy who really got the ball rolling on this "computer network" concept was a mathematician named Leonard Kleinrock. In 1961, he wrote the first paper about something called "packet switching" which is a fancy way to transmit data between computers. Kleinrock's theories became the basis for how information would travel through this future network.A few years later in 1965, an MIT computer expert named Lawrence G. Roberts took Kleinrock's ideas and proposed an actual technological plan to build this network. He called it the "ARPANET" which stood for the "Advanced Research Projects Agency Network." The special agency in charge of developing new technology for the military loved Roberts' networked computer concept and gave him a bunch of funding to make it happen.After years of tireless work engineering both the software and hardware, the first two nodes of the ARPANET were established in 1969 at UCLA and Stanford. A "node" is just a single computer connected to the network. By the end of 1969 there was a tiny ARPANET made up of four nodes located atUCLA, Stanford, UC Santa Barbara, and the University of Utah. Baby steps, but it was the birth of the internet!Over the next couple years, the ARPANET kept adding more nodes at universities and research centers across the United States. By 1971, there was a fully operational network of 15 nodes all sharing resources and data across the country. It was slow, clunky, and certainly not user-friendly. But it was officially the first working model of the internet as we know it today!One of the key breakthroughs that really expanded the ARPANET's capabilities came in 1971 when a computer programmer named Ray Tomlinson invented a way for network messages to be sent between different computers. Up until that point, the messaging capabilities of the ARPANET were pretty limited. But Tomlinson figured out how to send messages from one node to another by putting the recipient's address and the sender's address separated by an @ sign.Forexample:raymailbox@************************** format for email addresses to this day! Tomlinson's invention of network email kicked the ARPANET into overdrive and totally transformed how researchers could collaborate together over the network. No more having to mail documents or transfer datausing physical storage media. You could just type out a message and instantly send it through the network!By the mid 1970s, the ARPANET had proven that a functional computer network for sharing data was not only possible, but incredibly useful. However, it was still pretty exclusive and limited to the military, universities, and research labs working on defense-funded projects. That all changed in the late 1970s and into the 1980s when protocol standards like TCP/IP were developed, allowing different networks to join together and form an "internet."More user-friendly tools like the World Wide Web, web browsers, search engines and graphical user interfaces were also created in the 1980s and 90s. This transformed the internet into a global network open to the public, not just restricted to the military or academics. Ordinary people could now access this wealth of information and communicate across the world!So while the roots of the internet trace back to 1971 and the ARPANET, it really took about 20 years of continuous innovation, engineering and improvement by thousands of people before the modern internet emerged. And now here we are today where the internet impacts just about every aspect of our lives - how we work, study, shop, get entertainment, socialize with friends, andso much more! All because a bunch of big brains decades ago had a vision for an interconnected world of shared knowledge.It still blows my mind just how far the internet has come in my lifetime. From those first few clunky nodes sending basic messages and data over old school modems and phone lines. To today's high speed fiber optic networks beaming all of human knowledge to your smartphones and laptops with just a few taps. The story of the internet's invention and evolution is one of remarkable teamwork, perseverance and human ingenuity. And I'm excited to see what incredible new internet technologies get invented next!篇2The Awesome Invention of the InternetDid you know that the internet was invented way back in 1971? That was over 50 years ago! It's hard to imagine life without being able to go online, watch videos, play games, and chat with friends any time we want. But there was a time when the internet didn't exist at all!It all started with a computer scientist named Leonard Kleinrock. He was one of the first people to have the crazy idea that computers should be able to talk to each other and shareinformation over long distances. Up until then, computers just worked alone without being connected.In 1969, a team led by Kleinrock set up the first computer network called ARPANET. It connected computers at universities and research labs across the United States. ARPANET sent its first message in 1969, but it had some issues at first. The first message they tried to send was "LOGIN" but the system crashed after the first two letters "LO"! They had to reboot everything and try again.Two years later in 1971, a computer programmer named Ray Tomlinson invented a way for people to send messages between computers on ARPANET. He came up with the idea of the @ symbol for email addresses. So the first email in history might have looked something like "************************." Pretty cool, right?At first, ARPANET was mostly used by scientists, researchers, and universities to share data and research. But more people started joining the network and by the 1980s, there were thousands of computers connected! This eventually led to the internet we know today.In 1990, a computer scientist in Switzerland named Tim Berners-Lee took ARPANET to the next level and invented the World Wide Web. He came up with rules for formatting pages with text, images, and links using HTML and HTTP protocols. This made it much easier to view and navigate between pages on the internet.Berners-Lee's boss didn't think the World Wide Web was a good idea at first! He wrote in his notebook "Vague, but exciting..." Luckily, he let Berners-Lee keep working on it, and the World Wide Web has grown into the amazing resource we use every day.From those early days of connecting just a few university computers, the internet has expanded all around the world. Now there are over 4.5 billion people using the internet! We can go online from computers, phones, tablets, gaming systems, and even watches.The internet connects people for communication, education, entertainment, business, and so much more. We can learn about any topic, watch movies and shows, play multiplayer games with friends across the world, read news from any country, take classes online, and discover amazing things 24/7.Just think how different your life would be without the internet! You couldn't video chat with your cousins, watch unboxing videos of the latest toys, or download new games and apps. Your parents and teachers wouldn't be able to quickly look up information or do online research.Basically, the world has been completely transformed because of the invention of the internet back in 1971. What started as a small network called ARPANET to connect a few university computers has grown into a global phenomenon used by billions every single day.The internet opens up a world of knowledge, connections and opportunities that didn't exist before the 1970s. We owe a lot to the computer scientists, programmers and inventors who pioneered things like ARPANET, email, and the World Wide Web. Their important work shaped the modern internet age we live in today.I can't even imagine trying to write a report or do homework without being able to go online and access information from anywhere in the world. The internet brings the world to our fingertips! It has made learning, communicating, and being entertained so much easier.While the internet can have some downsides if it's not used properly, overall it has been an amazing advancement for the world. The next time you go online to watch a video, chat with friends, or look something up, remember that it all started with an idea over 50 years ago to connect computers together. Thank you Leonard Kleinrock, Ray Tomlinson, Tim Berners-Lee and the other internet pioneers!篇3The Amazing Story of the InternetHi friends! Today I'm going to tell you all about one of the most incredible inventions of the 20th century - the internet! The internet has changed our lives in so many ways. We use it for school projects, playing games, watching videos, and keeping in touch with friends and family. But where did this awesome technology come from?It all started way back in 1971 at a research lab in California. There was a computer scientist named Ray Tomlinson who sent the very first email! Can you believe people used to communicate without email? It must have been so slow having to wait for letters to arrive in the mail.Ray's email was just a simple test message to himself, but it proved that computers could talk to each other over a network. This was huge news! Up until then, computers could only do calculations on their own. Connecting them together opened up a whole new world of possibilities.After Ray's successful test, other scientists quickly realized how useful this computer network could be. They started connecting more and more computers located at different universities and research centers. By 1973, this early version of the internet linked almost 40 different machine language computer systems!As the network grew bigger, scientists had to find better ways to organize and route all the data being sent across the connections. They created protocols, which are kind of like the internet's language and traffic rules. These protocols help all the computers communicate properly.One of the most important protocols was called TCP/IP, created in 1978. It's kind of like the internet's address system that lets data find its way to the right destination. Another key part of the internet was created in 1991 - the World Wide Web. This allowed words, pictures, sounds and videos to be shared easily between computers, not just plain data.Once the World Wide Web arrived, the internet really started taking off. More and more people began connecting their home computers and using the web to find information on almost any topic imaginable. Businesses also rushed to create websites to attract customers.The web was made even awesomer in 1993 with the release of Mosaic, one of the first easy-to-use web browsers with menus and clickable links. Up until then, using the web had been a lot more complicated with just text and codes. But Mosaic helped open up the internet to everyone, not just experts.As the 90s rolled along, the internet grew like crazy! More homes got online, email became a daily thing, and Google launched in 1998 to help people search the massive new ocean of info on the world wide web.And this incredible resource all started with one simple test email sent by a scientist named Ray Tomlinson. If he could see how the internet has transformed our lives, education, business, entertainment and more, I bet he'd be totally blown away!I'm sure the internet will keep evolving and getting even smarter as new technologies are invented. Maybebrain-computer links or something crazy like that! For now, I'mjust grateful we have this awesome tool to learn, create, and connect with others near and far. Thanks, internet!篇4The Amazing Internet: How It All BeganHave you ever wondered how the Internet started? It's hard to imagine a world without it, isn't it? Well, get ready to be amazed because the story of how the Internet was invented is like something straight out of a sci-fi movie!It all began a long, long time ago, way back in 1971. That's like, a gazillion years ago in grown-up years! Back then, computers were these massive, room-filling machines that looked like they came from outer space. They were nothing like the sleek laptops and smartphones we have today.In those days, scientists and researchers were trying to figure out how to connect these giant computers so they could share information. You see, each computer had its own little world of data, and they couldn't talk to each other. It was like having a bunch of kids at a playground, but they all spoke different languages and couldn't understand each other.That's when a brilliant scientist named Ray Tomlinson came up with a mind-blowing idea. He invented something called "email," which allowed people to send messages from one computer to another. It was like having a secret code that every computer could understand!But Ray wasn't done yet. He realized that if computers could send messages to each other, they could probably share all kinds of information too. That's when the idea for the Internet was born!Now, you might be thinking, "But how did they actually build this Internet thingy?" Well, it was a team effort by some of the smartest people on the planet. They were like a group of superheroes, each with their own special power.There was Vint Cerf, who helped create the rules and protocols that allowed computers to communicate with each other. Then there was Bob Kahn, who figured out how to break up information into tiny packets that could be sent across the network. And let's not forget Leonard Kleinrock, who did a bunch of mathematical calculations to make sure the whole system would work smoothly.Together, these brilliant minds (and many others) worked tirelessly to make the Internet a reality. They had to overcome allsorts of challenges, like figuring out how to route information across different networks and making sure everything was secure.Finally, after years of hard work, the Internet was born! It was like a brand new world, where information could travel at the speed of light and people could connect with each other from anywhere on the planet.At first, the Internet was just a small network used by scientists and researchers. But as more and more people discovered its awesomeness, it started to grow and grow. Pretty soon, universities, businesses, and even regular folks like you and me were getting connected.Nowadays, the Internet is everywhere. We use it to do our homework, watch funny videos, play online games, and so much more. It's like having a magical portal to all the knowledge and entertainment in the entire universe, right at our fingertips.But we can't forget the pioneers who made it all possible. People like Ray Tomlinson, Vint Cerf, Bob Kahn, and Leonard Kleinrock are the real superheroes of the Internet age. Without their brilliant ideas and hard work, we might still be living in a world where computers couldn't talk to each other.So, the next time you're surfing the web, playing an online game, or video chatting with your friends, take a moment to appreciate the amazing invention that is the Internet. It all started with a dream, a bunch of really smart people, and a whole lot of hard work. Who knows what other mind-blowing inventions are waiting to be discovered in the future?篇5The Awesome Invention of the InternetHi everyone! Today I want to tell you all about one of the most awesome inventions ever - the internet! The internet is this really cool thing that lets computers all around the world connect and share information. Isn't that just mind-blowing?It all started way back in 1971. That was over 50 years ago, even before my parents were born! Back then, computers were these huge, room-sized machines. They took up so much space and weren't very powerful compared to our phones and laptops today. Pretty crazy, right?There was this guy named Ray Tomlinson who helped create the first email program. Email is where you can send messages to people over the internet. Ray sent the first email ever to himselfin 1971! I can't even imagine a world without email. How did people communicate before that?Another really important person was Vint Cerf. He's known as one of the "fathers of the internet." In 1973, he helped develop something called the Transmission Control Protocol (TCP). This protocol defined how data could be transmitted between multiple networks. Basically, it's what allowed computers on different networks to connect and share data with each other over the internet.Things really started taking off in the 1980s and 1990s. More and more people started getting personal computers and hooking them up to the internet. Websites started popping up left and right. You could suddenly access all this information from anywhere with an internet connection!One of the earliest websites was the CERN website launched in 1991. CERN is this big science lab in Switzerland. Their website gave instructions on how to access other websites and even let people make their own web pages. It helped spread website creation tools to the public.Then in 1993, things got even crazier when a student created a web browser called Mosaic. A web browser is like a window that lets you view and navigate different websites. Mosaic madethe internet way more user-friendly with its point-and-click interface. More and more people started "surfing" the web after that.Nowadays, the internet is absolutely everywhere! We use it for school projects, playing games, watching videos, listening to music, and so much more. Internet companies like Google, Facebook, and Amazon have become some of the biggest companies in the world.We can video chat with our friends and family across the world with just a few clicks. We can learn about any topic imaginable by looking it up online. Heck, I'm even writing this essay about the internet's history while connected to the internet! How meta is that?The internet has changed our lives in so many amazing ways. And to think it all started with those early computer scientists just trying to connect a few machines together. Just imagine how it will keep evolving over the next 50 years! Who knows what awesome new internet inventions are coming our way?I don't know about you, but I'm super grateful for the internet. Giving us the ability to access infinite information and connect with others globally is one of the greatest inventions of all time in my book. Three cheers for the internet!篇6The Awesome Invention of the InternetHave you ever thought about how the internet started? It's such a big part of our lives now - we use it for school, games, watching videos, and keeping in touch with friends and family. But it wasn't always around! The internet as we know it today was invented way back in 1971. That's over 50 years ago! Can you imagine life without it?It all began with a computer scientist named Leonard Kleinrock. He was one of the first people to start thinking about how to connect computers together so they could share information. In 1969, he helped develop the first computer network called ARPANET. This allowed computers at different universities to send messages to each other.Two years later in 1971, another very smart man named Ray Tomlinson invented a way for people to send messages between these connected computers. He came up with the idea of an "@" symbol to separate the username from the computer name. This became the first email system! Pretty cool, right?With email, ARPANET grew quickly as more computers joined the network. Scientists used it to share research and data.But back then, you couldn't just sign up for an email account like Gmail or Outlook. Only certain universities, companies, and government organizations had access.In the 1980s, some researchers wanted to make the network more open and user-friendly. They created new protocols and systems for linking computers around the world. One of the key people was a computer scientist named Vint Cerf. Some even call him one of the "Fathers of the Internet!"By the 1990s, this globally connected network of computers had become known as the "internet." More regular people started to use it, not just scientists. Can you believe that in 1992 there were only about 1 million internet users worldwide? That's a tiny fraction of the billions today!One of the biggest changes came in 1994 when the World Wide Web became popular. This is the internet system of websites, hyperlinks, and browsers that we're all familiar with now. A computer programmer in Switzerland named Tim Berners-Lee is credited with inventing the World Wide Web.Once the web took off, the internet grew at an absolutely mind-blowing rate. More and more people wanted to use it for communication, information, entertainment, shopping, you name it. Companies raced to set up websites. Schools startedteaching students computer skills. The internet changed everything!Nowadays, the internet connects nearly every computer and mobile device on the planet. Billions of people use it every single day. We can instantly access any information, communicate with anyone, watch or listen to anything, play games with friends across the world, and so much more. It's hard to imagine modern life without it.The birth of the internet was a really remarkable point in human history. What started as a small computer network for researchers transformed into a global system that puts the world's knowledge at our fingertips. Whenever I'm watching a video, playing an online game, or video chatting with my cousins overseas, I'm amazed at how far the internet has come in just the last 50 years or so.Who knows what amazing new internet technologies will be invented in our lifetimes? The possibilities seem endless as more of the world comes online. The internet has already opened up so many opportunities for learning, connecting people across distances, and exploring our world in ways our grandparents could have never imagined. I can't wait to see what future innovations will change our lives next!。
vldb论文
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INTRODUCTION
Categories andຫໍສະໝຸດ Subject Descriptors
H.2.4 [Database Management]: Systems—Query processing
Keywords
Graph analytics; Cloud computing; Ego-centric analysis; Subgraph extraction; Graph Partitioning; Data Placement; Social networks
NScale: Neighborhood-centric Analytics on Large Graphs
Abdul Quamar University of Maryland abdul@ Amol Deshpande University of Maryland amol@ Jimmy Lin University of Maryland jimmylin@
Friends in CS dept
High school friends
Office Work place friends Colleagues
Friends in database lab in CS dept
College friends Friends
Family members
Figure 1: An example of neighborhood-centric analysis: identify users’ social circles in a social network, i.e., cluster each user’s friends into different (possibly overlapping) groups using the network structure and the node and edge contents. Figure shows a small subset of such circles that may be present.
mathworks
The Value of the Fourth Year of Mathematics Too many students and educators view the senior year and graduation from high school as an end point, rather than one vital step along the education pipeline. Students who engage in a fourth year of math tap into and build upon their advanced analytic skills and are more likely to have better success in postsec-ondary course work, as they have maintained their momentum and continued to practice mathematics throughout their high school experience.Math is a continuum of learning.n R esearchers who study learning and cognition describemathematical learning as a progression in which conceptualunderstanding builds logically, and expertise is developedgradually.1n W hen students are not directly engaged in instruction, they suffer a learning loss. Just over an average summer, students lose approximately 2.6 months of grade-level equivalency in mathematics.2 The learning loss during a student’s senior year similarly has the potential to be very significant.n A dditionally, 67 percent of middle school teachers rank math as the single most difficult subject for students to re-engage in when returning to school after the summer break and 50 percent claimed that students’ math skills regress the most, compared to other subjects, during that time off.3n A ll students gain more advanced math skills later in high school, but the most significant gains are found among students who take rigorous math during their junior and senior years. The largest learning gains made in advanced skill proficiency—such as complex multi-step analysis—were among students who took pre-calculus and another course during 11th and 12th grade.The largest gains in intermediate math skills–such as simpleoperations and problem solving—were made by students who took Geometry and Algebra II during the last two years of high school.4 n U nsurprisingly, the smallest gains at all proficiency levels were made were among students who took no math or only one math course during 11th and 12th grade.5math works1775 Eye Street NW n Suite 410 n Washington, DC 20006 n Phone (202) 419-1540 n /mathworksFOURTH YEAR MATH ALTERNATIVES Many students who complete a three-course sequence, such as Algebra I, Geometry, and Algebra II, go on to take Pre-Calculus and Calculus. Yet, for those students who choose not to follow that track, there need to be options for fourth year courses that include rich and meaningful mathematics. Students not intending to pursue math-intensive majors should be able to select from a number of fourth year “capstone” courses to maintain and extend their prior mathematical knowledge and connect mathematics instruction with other interests. Effective capstone courses can keep students engaged in learning and ensure a smoother transition into postsecondary education and the workplace.10A fourth year of math improves students’ college readiness.n A recent report from ACT finds that a fourth year of math is associated positively with students’ college readiness. While only 16 percent of students taking three years of math met the readiness benchmarks on the ACT in math, 62 percent of students taking four years, and 75 percent of students taking four and a half years of math met that benchmark.6n S imilarly, on average, students with four years of high school math score 63 points higher on the SAT-I quantitative section than students with only three years of math. Students who take more than four years of math, such as students who complete Algebra I in middle school, score 52 points higher on the SAT-I quantitative section than students with exactly four years of math.7n I n one study of students from three states who had taken the ACT, 26 percent of students who took three years of math in high school (including Algebra, Geometry and Algebra II) required remediation upon entering college, while taking a fourth year of advanced math reduced the remediation rate to 17 percent.8n 74 percent of recent high school graduates surveyed believe that requiring four years of math and science would have better prepared them for life after high school. Additionally, about 80 percent of graduates say they would have worked harder had their high schools demanded more of them.9ENDNOTES1 NRC, 2005 /openbook.php?record_id=11101&page=432 Cooper, Harris et al (1996). The Effects of Summer Vacation on Achievement Test Scores: A Narrative and Meta-Analytic Review. Review of Educational Research, v66 n3 p227-68 Fall 1996.3 The Raytheon MathMovesU Back-to-School Survey, Nov 2006.4 Bozick, R., and Ingels, S.J. (2008). Mathematics Coursetaking and Achievement at the End of High School: Evidence from the Education Longitudinal Study of 2002. (NCES 2008-319). Washington, DC: U.S. Department of Education, National Center for Education Statistics.5 Bozick, R., and Ingels, S.J. (2008). Mathematics Coursetaking and Achievement at the End of High School: Evidence from the Education Longitudinal Study of 2002. (NCES 2008-319). Washington, DC: U.S. Department of Education, National Center for Education Statistics.6 ACT, Inc. (2007). Rigor At Risk: Reaffirming Quality in the High School Core Curriculum. /research/policymakers/pdf/rigor_ report.pdf7 College Board. (2006). 2006 College-Bound Seniors Total Group Profile Report. /prod_downloads/about/news_ info/cbsenior/yr2006/national-report.pdf.8 ACT, Inc. (2007). Rigor At Risk: Reaffirming Quality in the High School Core Curriculum. /path/policy/pdf/rigor_report.pdf9 Peter D. Hart Research Associates/Public Opinion Strategies. (2005). Rising to the Challenge: Are High School Graduates Prepared for College and Work? Washington, DC: Achieve.10 To see examples of fourth year capstone courses, see /k12mathbenchmarks/resources/capstone.php1775 Eye Street NW n Suite 410n Washington, DC 20006n Phone (202) 419-1540n /mathworks© November 2008。
Chapter6-Arithmatic and Logical operation
CHAPTER6ARITHMETIC AND LOGIC OPERA TIONSWHAT WILL WE LEARN?•Which arithmetic and logic operations can be applied to digital images?•How are they performed in MATLAB?•What are they used for?6.1ARITHMETIC OPERATIONS:FUNDAMENTALS AND APPLICATIONSArithmetic operations involving images are typically performed on a pixel-by-pixel basis;that is,the operation is independently applied to each pixel in the image.Given a2D array(X)and another2D array of the same size or a scalar(Y),the resulting array,Z,is obtained by calculatingX opn Y=Z(6.1) where opn is a binary arithmetic(+,−,×,/)operator.This section describes each arithmetic operation in more detail,focusing on how they can be performed and what are their typical applications.Practical Image and Video Processing Using MATLAB®.By Oge Marques.©2011John Wiley&Sons,Inc.Published2011by John Wiley&Sons,Inc.103104ARITHMETIC AND LOGIC OPERATIONSFIGURE6.1Adding two images:(a)first image(X);(b)second image(Y);(c)result(Z= X+Y).6.1.1AdditionAddition is used to blend the pixel contents from two images or add a constant value to pixel values of an image.Adding the contents of two monochrome images causes their contents to blend(Figure6.1).Adding a constant value(scalar)to an image causes an increase(or decrease if the value is less than zero)in its overall brightness, a process sometimes referred to as additive image offset(Figure6.2).Adding random amounts to each pixel value is a common way to simulate additive noise(Figure6.3). The resulting(noisy)image is typically used as a test image for restoration algorithms such as those described in Chapter12.FIGURE6.2Additive image offset:(a)original image(X);(b)brighter version(Z=X+ 75).ARITHMETIC OPERATIONS:FUNDAMENT ALS AND APPLICA TIONS105FIGURE 6.3Adding noise to an image:(a)original image (X );(b)zero-mean Gaussian white noise (variance =0.01)(N );(c)result (Z =X +N ).In MATLABMATLAB’s Image Processing Toolbox (IPT)has a built-in function to add two images or add a constant (scalar)to an image:imadd .In Tutorial 6.1(page 113),you will have a chance to experiment with this function.When adding two images,you must be careful with values that exceed the maxi-mum pixel value for the data type being used.There are two ways of dealing with this overflow issue:normalization and truncation .Normalization consists in storing the intermediate result in a temporary variable (W )and calculating each resulting pixel value in Z using equation (6.2).g =L maxf max min(f −f min )(6.2)where f is the current pixel in W ,L max is the maximum possible intensity value (e.g.,255for uint8or 1.0for double ),g is the corresponding pixel in Z ,f max is the maximum pixel value in W ,and f min is the minimum pixel value in W .Truncation consists in simply limiting the results to the maximum positive number that can be represented with the adopted data type. EXAMPLE 6.1For the two 3×3monochrome images below (X and Y ),each of which represented as an array of unsigned integers,8-bit (uint8),calculate Z =X +Y ,using (a)normalization and (b)truncation.X =⎡⎢⎣2001001000105050250120⎤⎥⎦106ARITHMETIC AND LOGIC OPERATIONSY=⎡⎢⎣100220230 4595120 2051000⎤⎥⎦SolutionThe intermediate array W(an array of unsigned integers,16-bit,uint16)is obtained by simply adding the values of X and Y on a pixel-by-pixel basis:W=⎡⎢⎣300320330 45105170 255350120⎤⎥⎦(a)Normalizing the[45,350]range to the[0,255]interval using equation(6.2), we obtainZ a=⎡⎢⎣213230238050105 17525563⎤⎥⎦(b)Truncating all values above255in W,we obtainZ b=⎡⎢⎣255255255 45105170 255255120⎤⎥⎦MATLAB code:X=uint8([200100100;01050;50250120])Y=uint8([100220230;4595120;2051000])W=uint16(X)+uint16(Y)fmax=max(W(:))fmin=min(W(:))Za=uint8(255.0*double((W-fmin))/double((fmax-fmin))) Zb=imadd(X,Y)6.1.2SubtractionSubtraction is often used to detect differences between two images.Such differences may be due to several factors,such as artificial addition to or removal of relevant contents from the image(e.g.,using an image manipulation program),relative object motion between two frames of a video sequence,and many others.Subtracting aARITHMETIC OPERATIONS:FUNDAMENT ALS AND APPLICA TIONS107FIGURE6.4Subtractive image offset:(a)original image(X);(b)darker version(Z= X−75).constant value(scalar)from an image causes a decrease in its overall brightness,a process sometimes referred to as subtractive image offset(Figure6.4).When subtracting one image from another or a constant(scalar)from an image, you must be careful with the possibility of obtaining negative pixel values as a result. There are two ways of dealing with this underflow issue:treating subtraction as absolute difference(which will always result in positive values proportional to the difference between the two original images without indicating,however,which pixel was brighter or darker)and truncating the result,so that negative intermediate values become zero.In MATLABThe IPT has a built-in function to subtract one image from another,or subtract a constant from an image:imsubtract.The IPT also has a built-in function to cal-culate the absolute difference of two images:imabsdiff.The IPT also includes a function for calculating the negative(complement)of an image,imcomplement.In Tutorial6.1(page113),you will have a chance to experiment with these functions. EXAMPLE6.2For the two3×3monochrome images below(X and Y),each of which represented as an array of unsigned integers,8-bit(uint8),calculate(a)Z=X−Y,(b)Z= Y−X,and(c)Z=|Y−X|.For parts(a)and(b),use truncation to deal with possible negative values.X=⎡⎢⎣20010010001050 50250120⎤⎥⎦108ARITHMETIC AND LOGIC OPERATIONSY=⎡⎢⎣100220230 4595120 2051000⎤⎥⎦SolutionMATLAB’s imsubtract will take care of parts(a)and(b),while imabsdiff will be used for part(c).(a)Z a=⎡⎢⎣100000000150120⎤⎥⎦(b)Z b=⎡⎢⎣0120130 458570 15500⎤⎥⎦(c)Z c=⎡⎢⎣100120130 458570 155150120⎤⎥⎦MATLAB code:X=uint8([200100100;01050;50250120])Y=uint8([100220230;4595120;2051000])Za=imsubtract(X,Y)Zb=imsubtract(Y,X)Zc=imabsdiff(Y,X)Image subtraction can also be used to obtain the negative of an image(Figure6.5):g=−f+L max(6.3) where L max is the maximum possible intensity value(e.g.,255for uint8or1.0for double),f is the pixel value in X,g is the corresponding pixel in Z.ARITHMETIC OPERATIONS:FUNDAMENT ALS AND APPLICA TIONS109FIGURE6.5Example of an image negative:(a)original image;(b)negative image.6.1.3Multiplication and DivisionMultiplication and division by a scalar are often used to perform brightness adjust-ments on an image.This process—sometimes referred to as multiplicative image scaling—makes each pixel value brighter(or darker)by multiplying its original value by a scalar factor:if the value of the scalar multiplication factor is greater than one,the result is a brighter image;if it is greater than zero and less than one,it results in a darker image(Figure6.6).Multiplicative image scaling usually produces better subjective results than the additive image offset process described previously.In MATLABThe IPT has a built-in function to multiply two images or multiply an image by a constant:immultiply.The IPT also has a built-in function to divide one imageFIGURE6.6Multiplication and division by a constant:(a)original image(X);(b)multipli-cation result(X×0.7);(c)division result(X/0.7).110ARITHMETIC AND LOGIC OPERATIONS into another or divide an image by a constant:imdivide.In Tutorial6.1(page113), you will have a chance to experiment with these functions.6.1.4Combining Several Arithmetic OperationsIt is sometimes necessary to combine several arithmetic operations applied to one or more images,which may compound the problems of overflow and underflow discussed previously.To achieve more accurate results without having to explicitly handle truncations and round-offs,the IPT offers a built-in function to perform a linear combination of two or more images:imlincomb.This function computes each element of the output individually,in double-precisionfloating point.If the output is an integer array,imlincomb truncates elements that exceed the range of the integer type and rounds off fractional values.EXAMPLE6.3Calculate the average of the three3×3monochrome images below(X,Y,and Z), each of which represented as an array of unsigned integers,8-bit(uint8),using(a) imadd and imdivide without explicitly handling truncation and round-offs;(b) imadd and imdivide,but this time handling truncation and round-offs;and(c) imlincomb.X=⎡⎢⎣20010010001050 50250120⎤⎥⎦Y=⎡⎢⎣100220230 4595120 2051000⎤⎥⎦Z=⎡⎢⎣200160130 145195120 105240150⎤⎥⎦Solution (a)S a=⎡⎢⎣858585 638585 858585⎤⎥⎦LOGIC OPERA TIONS:FUNDAMENTALS AND APPLICA TIONS111(b)S b=⎡⎢⎣167160153 6310097 12019790⎤⎥⎦(c)S c=⎡⎢⎣167160153 6310097 12019790⎤⎥⎦MATLAB code:X=uint8([200100100;01050;50250120])Y=uint8([100220230;4595120;2051000])Z=uint8([200160130;145195120;105240150])Sa=imdivide(imadd(X,imadd(Y,Z)),3)a=uint16(X)+uint16(Y)b=a+uint16(Z)Sb=uint8(b/3)Sc=imlincomb(1/3,X,1/3,Y,1/3,Z,’uint8’)The result in(a)is incorrect due to truncation of intermediate results.Both(b)and (c)produce correct results,but the solution using imlincomb is much more elegant and concise.6.2LOGIC OPERATIONS:FUNDAMENTALS AND APPLICATIONS Logic operations are performed in a bit-wise fashion on the binary contents of each pixel value.The AND,XOR,and OR operators require two or more arguments, whereas the NOT operator requires only one argument.Figure6.7shows the most common logic operations applied to binary images,using the following convention: 1(true)for white pixels and0(false)for black pixels.Figures6.8–6.11show examples of AND,OR,XOR,and NOT operations on monochrome images.The AND and OR operations can be used to combine images for special effects purposes.They are also used in masking operations,whose goal is to extract a region of interest(ROI)from an image(see Tutorial6.2).The XOR operation is often used to highlight differences between two monochrome images.It is,therefore,equivalent to calculating the absolute difference between two images. The NOT operation extracts the binary complement of each pixel value,which is equivalent to applying the“negative”effect on an image.112ARITHMETIC AND LOGIC OPERATIONSFIGURE6.7Logic operations on binary images.FIGURE6.8The AND operation applied to monochrome images:(a)X;(b)Y;(c)X AND Y.FIGURE6.9The OR operation applied to monochrome images:(a)X;(b)Y;(c)X OR Y.In MATLABMATLAB has built-in functions to perform logic operations on arrays:bitand, bitor,bitxor,and bitcmp.In Tutorial6.2(page118),you will have a chance to experiment with these functions.TUTORIAL6.1:ARITHMETIC OPERA TIONS113FIGURE6.10The XOR operation applied to monochrome images:(a)X;(b)Y;(c)X XOR Y.FIGURE6.11The NOT operation applied to a monochrome image:(a)X;(b)NOT X.6.3TUTORIAL6.1:ARITHMETIC OPERATIONSGoalThe goal of this tutorial is to learn how to perform arithmetic operations on images.Objectives•Learn how to perform image addition using the imadd function.•Explore image subtraction using the imsubtract function.•Explore image multiplication using the immultiply function.•Learn how to use the imdivide function for image division.What You Will Need•cameraman2.tif•earth1.tif•earth2.tif•gradient.tif•gradient_with_text.tif114ARITHMETIC AND LOGIC OPERATIONSProcedureThe IPT offers four functions to aid in image arithmetic:imadd,imsubtract, immultiply,and imdivide.You could use MATLAB’s arithmetic functions (+,−,*,/)to perform image arithmetic,but it would probably require additional coding to ensure that the operations are performed in double precision,as well as setting cutoff values to be sure that the result is within grayscale range.The functions provided by the IPT do this for you automatically.Image addition can be used to brighten(or darken)an image by adding(subtracting) a constant value to(from)each pixel value.It can also be used to blend two images into one.e the imadd function to brighten an image by adding a constant(scalar)value to all its pixel values.I=imread(’tire.tif’);I2=imadd(I,75);figuresubplot(1,2,1),imshow(I),title(’Original Image’); subplot(1,2,2),imshow(I2),title(’Brighter Image’);Question1What are the maximum and minimum values of the original and the adjusted image?Explain your results.Question2How many pixels had a value of255in the original image and how many have a value of255in the resulting image?e the imadd function to blend two images.Ia=imread(’rice.png’);Ib=imread(’cameraman.tif’);Ic=imadd(Ia,Ib);figureimshow(Ic);Image subtraction is useful when determining whether two images are the same. By subtracting one image from another,we can highlight the differences between the two.3.Close all openfigures and clear all workspace variables.4.Load two images and display them.I=imread(’cameraman.tif’);J=imread(’cameraman2.tif’);TUTORIAL6.1:ARITHMETIC OPERA TIONS115 figuresubplot(1,2,1),imshow(I),title(’Original Image’); subplot(1,2,2),imshow(J),title(’Altered Image’);While it may not be obvious atfirst how the altered image differs from the orig-inal image,we should be able to see where the difference is located after using the imsubtract function.5.Subtract both images and display the result.diffim=imsubtract(I,J);figuresubplot(2,2,1),imshow(diffim),title(’Subtracted Image’);e the zoom tool to zoom into the right area of the difference image abouthalfway down the image.You will notice that a small region of pixels is faintly white.7.To zoom back out,double-click anywhere on the image.Now that you know where the difference is located,you can look at the original images to see the change.The difference image above does not quite seem to display all the details of the missing building.This is because when we performed image subtraction,some of the pixels resulted in negative values,but were then set to0by the imsubtract function(the function does this on purpose to keep the data within grayscale range).What we really want to do is calculate the absolute value of the difference between two images.8.Calculate the absolute difference.Make sure Figure2is selected before exe-cuting this code.diffim2=imabsdiff(I,J);subplot(2,2,2),imshow(diffim2),title(’Abs Diff Image’);e the zoom-in tool to inspect the new difference image.Even though the new image may look the same as the previous one,it represents both positive and negative differences between the two images.To see this difference better,we will scale both difference images for display purposes,so their values occupy the full range of the gray scale.10.Show scaled versions of both difference images.subplot(2,2,3),imshow(diffim,[]),...title(’Subtracted Image Scaled’);116ARITHMETIC AND LOGIC OPERATIONS subplot(2,2,4),imshow(diffim2,[]),...title(’Abs Diff Image Scaled’);e the zoom tool to see the differences between all four difference images. Question3How did we scale the image output?Question4What happened when we scaled the difference images?Question5Why does the last image show more detail than the others?Multiplication is the process of multiplying the values of each pixel of same coor-dinates in two images.This can be used for a brightening process known as dynamic scaling,which results in a more naturally brighter image compared to directly addinga constant to each pixel.12.Close all openfigures and clear all workspace variables.e immultiply to dynamically scale the moon image.I=imread(’moon.tif’);I2=imadd(I,50);I3=immultiply(I,1.2);figuresubplot(1,3,1),imshow(I),title(’Original Image’); subplot(1,3,2),imshow(I2),title(’Normal Brightening’); subplot(1,3,3),imshow(I3),title(’Dynamic Scaling’); Question6When dynamically scaling the moon image,why did the dark regions around the moon not become brighter as in the normally adjusted image?Image multiplication can also be used for special effects such as an artificial3D look.By multiplying aflat image with a gradient,we create the illusion of a3D textured surface.14.Close all openfigures and clear all workspace variables.15.Create an artificial3D planet by using the immultiply function to multiplythe earth1and earth2images.I=im2double(imread(’earth1.tif’));J=im2double(imread(’earth2.tif’));K=immultiply(I,J);figuresubplot(1,3,1),imshow(I),title(’Planet Image’);subplot(1,3,2),imshow(J),title(’Gradient’);subplot(1,3,3),imshow(K,[]),title(’3D Planet’);TUTORIAL6.1:ARITHMETIC OPERA TIONS117Image division can be used as the inverse operation to dynamic scaling.Image division is accomplished with the imdivide function.When using image division for this purpose,we can achieve the same effect using the immultiply function.16.Close all openfigures and clear all workspace variables.e image division to dynamically darken the moon image.I=imread(’moon.tif’);I2=imdivide(I,2);figuresubplot(1,3,1),imshow(I),title(’Original Image’);subplot(1,3,2),imshow(I2),title(’Darker Image w/Division’) 18.Display the equivalent darker image using image multiplication.I3=immultiply(I,0.5);subplot(1,3,3),imshow(I3),...title(’Darker Image w/Multiplication’);Question7Why did the multiplication procedure produce the same result as division?Question8Write a small script that will verify that the images produced from division and multiplication are equivalent.Another use of the image division process is to extract the background from an image.This is usually done during a preprocessing stage of a larger,more complex operation.19.Close all openfigures and clear all workspace variables.20.Load the images that will be used for background subtraction.notext=imread(’gradient.tif’);text=imread(’gradient_with_text.tif’);figure,imshow(text),title(’Original Image’);This image could represent a document that was scanned under inconsistent light-ing conditions.Because of the background,the text in this image cannot be processed directly—we must preprocess the image before we can do anything with the text.If the background were homogeneous,we could use image thresholding to extract the text pixels from the background.Thresholding is a simple process of converting an image to its binary equivalent by defining a threshold to be used as a cutoff value: anything below the threshold will be discarded(set to0)and anything above it will be kept(set to1or255,depending on the data class we choose).118ARITHMETIC AND LOGIC OPERATIONS 21.Show how thresholding fails in this case.level=graythresh(text);BW=im2bw(text,level);figure,imshow(BW)Although the specifics of the thresholding operation(using built-in functions graythresh and im2bw)are not important at this time,we can see that even though we attempted to segregate the image into dark and light pixels,it produced only part of the text we need(on the upper right portion of the image).If an image of the background with no text on it is available,we can use the imdivide function to extract the letters.To obtain such background image in a real scenario,such as scan-ning documents,a blank page that would show only the inconsistently lit background could be scanned.22.Divide the background from the image to get rid of the background.fixed=imdivide(text,notext);figuresubplot(1,3,1),imshow(text),title(’Original Image’); subplot(1,3,2),imshow(notext),title(’Background Only’); subplot(1,3,3),imshow(fixed,[]),title(’Divided Image’) Question9Would this technique still work if we were unable to obtain the back-ground image?6.4TUTORIAL6.2:LOGIC OPERATIONS AND REGION OF INTEREST PROCESSINGGoalThe goal of this tutorial is to learn how to perform logic operations on images.Objectives•Explore the roipoly function to generate image masks.•Learn how to logically AND two images using the bitand function.•Learn how to logically OR two images using the bitor function.•Learn how to obtain the negative of an image using the bitcmp function.•Learn how to logically XOR two images using the bitxor function.What You Will Need•lindsay.tif•cameraman2.tifTUTORIAL6.2:LOGIC OPERA TIONS AND REGION OF INTEREST PROCESSING119 ProcedureLogic operators are often used for image masking.We will use the roipoly function to create the image mask.Once we have a mask,we will use it to perform logic operations on the selected image.e the MATLAB help system to learn how to use the roipoly function whenonly an image is supplied as a parameter.Question1How do we add points to the polygon?Question2How do we delete points from the polygon?Question3How do we end the process of creating a polygon?e the roipoly function to generate a mask for the pout image.I=imread(’pout.tif’);bw=roipoly(I);Question4What class is the variable bw?Question5What does the variable bw represent?Logic functions operate at the bit level;that is,the bits of each image pixel are compared individually,and the new bit is calculated based on the operator we are using(AND,OR,or XOR).This means that we can compare only two images that have the same number of bits per pixel as well as equivalent dimensions.In order for us to use the bw image in any logical calculation,we must ensure that it consists of the same number of bits as the original image.Because the bw image already has the correct number of rows and columns,we need to convert only the image to uint8, so that each pixel is represented by8bits.3.Convert the mask image to class uint8.bw2=uint8(bw);Question6In the above conversion step,what would happen if we used the im2uint8function to convert the bw image as opposed to just using uint8(bw)? (Hint:after conversion,check what is the maximum value of the image bw2.)e the bitand function to compute the logic AND between the originalimage and the new mask image.I2=bitand(I,bw2);imshow(I2);120ARITHMETIC AND LOGIC OPERATIONS Question7What happens when we logically AND the two images?To see how to OR two images,we mustfirst visit the bitcmp function,which is used for complementing image bits(NOT).e the bitcmp function to generate a complemented version of the bw2mask.bw_cmp=bitcmp(bw2);figuresubplot(1,2,1),imshow(bw2),title(’Original Mask’);subplot(1,2,2),imshow(bw_cmp),title(’Complemented Mask’); Question8What happened when we complemented the bw2image?We can now use the complemented mask in conjunction with bitor.e bitor to compute the logic OR between the original image and the com-plemented mask.I3=bitor(I,bw_cmp);figure,imshow(I3)Question9Why did we need to complement the mask?What would have hap-pened if we used the original mask to perform the OR operation?The IPT also includes function imcomplement,which performs the same operation as the bitcmp function,complementing the image.The function imcomplement allows input images to be binary,grayscale,or RGB,whereas bitcmp requires that the image be an array of unsigned integers.plement an image using the imcomplement function.bw_cmp2=imcomplement(bw2);Question10How can we check to see that the bw_cmp2image is the same as the bw_cmp image?The XOR operation is commonly used forfinding differences between two images.8.Close all openfigures and clear all workspace variables.e the bitxor function tofind the difference between two images.I=imread(’cameraman.tif’);I2=imread(’cameraman2.tif’);I_xor=bitxor(I,I2);figuresubplot(1,3,1),imshow(I),title(’Image1’);TUTORIAL6.2:LOGIC OPERA TIONS AND REGION OF INTEREST PROCESSING121 subplot(1,3,2),imshow(I2),title(’Image2’);subplot(1,3,3),imshow(I_xor,[]),title(’XOR Image’);Logic operators are often combined to achieve a particular task.In next steps,we will use all the logic operators discussed previously to darken an image only withina region of interest.10.Close all openfigures and clear all workspace variables.11.Read in image and calculate an adjusted image that is darker using theimdivide function.I=imread(’lindsay.tif’);I_adj=imdivide(I,1.5);12.Generate a mask by creating a region of interest polygon.bw=im2uint8(roipoly(I));e logic operators to show the darker image only within the region of interest,while displaying the original image elsewhere.bw_cmp=bitcmp(bw);%mask complementroi=bitor(I_adj,bw_cmp);%roi imagenot_roi=bitor(I,bw);%non_roi imagenew_img=bitand(roi,not_roi);%generate new image imshow(new_img)%display new image Question11How could we modify the above code to display the original image within the region of interest and the darker image elsewhere?WHAT HAVE WE LEARNED?•Arithmetic operations can be used to blend two images(addition),detect differ-ences between two images or video frames(subtraction),increase an image’s average brightness(multiplication/division by a constant),among other things.•When performing any arithmetic image processing operation,pay special attention to the data types involved,their ranges,and the desired way to handle overflow and underflow situations.•MATLAB’s IPT has built-in functions for image addition(imadd),subtraction (imsubtract and imabsdiff),multiplication(immultiply),and divi-sion(imdivide).It also has a function(imlincomb)that can be used to perform several arithmetic operations without having to worry about underflow or overflow of intermediate results.122ARITHMETIC AND LOGIC OPERATIONS •Logic operations are performed on a bit-by-bit basis and are often used to maskout a portion of an image(the region of interest)for further processing.•MATLAB’s IPT has built-in functions for performing basic logic operations on digital images:AND(bitand),OR(bitor),NOT(bitcmp),and XOR (bitxor).6.5PROBLEMS6.1What would be the result of adding a positive constant(scalar)to a monochrome image?6.2What would be the result of subtracting a positive constant(scalar)from a monochrome image?6.3What would be the result of multiplying a monochrome image by a positive constant greater than1.0?6.4What would be the result of multiplying a monochrome image by a positive constant less than1.0?6.5Given the3×3images X and Y below,obtain(a)X AND Y;(b)X OR Y;(c) X XOR Y.X=⎡⎢⎣20010010001050 50250120⎤⎥⎦Y=⎡⎢⎣100220230 4595120 2051000⎤⎥⎦6.6What happens when you add a uint8[0,255]monochrome image to itself?6.7What happens when you multiply a uint8[0,255]monochrome image by itself?6.8What happens when you multiply a double[0,1.0]monochrome image by itself?6.9What happens when you divide a double[0,1.0]monochrome image by itself?6.10Would pixel-by-pixel division be a better way tofind the differences between two monochrome images than subtraction,absolute difference,or XOR?Explain.PROBLEMS123 6.11Write a MATLAB function to perform brightness correction on monochrome images.It should take as arguments a monochrome image,a number between0and 100(amount of brightness correction,expressed in percentage terms),and a third parameter indicating whether the correction is intended to brighten or darken the image.6.12Write a MATLAB script that reads an image,performs brightness correction using the function written for Problem6.11,and displays a window with the image and its histogram,1before and after the brightness correction operation.What do the histograms tell you?Would you be able to tell from the histograms alone what type of brightness correction was performed?Would you be able to estimate from the histogram information how much brightening or darkening the image experienced? 1Histograms will be introduced in Chapter9,so you may try this problem after reading that chapter.。
chapter10post-secondary
Chapter 10 Postsecondary Education: AdmissionsIn this lecture, I’m going to talk to you about postsecondary education in the United States. Today I’ll give you some facts and figures about colleges and universities in the United States and some general information about admission policies. I will also make a few remarks about community colleges and finish up by giving you an idea of what kinds of students make up the student body on a typical U.S. campus.Let’s begin with some facts and figures. The most recent figures I have reveal there are 4,182 public and private four-year and two-year colleges in the United States. These range from full universities with diverse programs to smaller four-year colleges to two-year community colleges. Most of them are accredited, which means the schools meet certain standards set by institutional and private evaluators. When applying to a school, you would probably want to make sure it was accredited. Even though there are more private colleges than public ones, over three-quarters of students, precisely 78 percent, are enrolled at public colleges and universities. Some of the small private schools may have fewer than 100 students, whereas some of the large state university systems may have 50,000 or more students. Most of these schools are coeducational although some of them are primarily for women and others are primarily for men. Some schools may offer only one program of study and others have a great variety of programs. The total cost for attending one of these schools may be less than $5,000 a year or as much as 30 or 40 thousand dollars a year for one of the prestigious private schools. These schools are located all over—in industrial areas, agricultural areas, large cities, and small towns in a wide variety of climates.With such a wide variety of sizes, kinds, and locations of schools, it probably won’t surprise you to find out that admissions requirements at these colleges anduniversities vary greatly also. Some are relatively easy to be admitted to whereas others are highly competitive. However, most schools will ask undergraduate applicants to submit their high school transcripts with a record of their grades and test results from one of the standardized tests regularly offered to high school students. The most common of these standardized exams is the Scholastic Aptitude Test, commonly known as the SAT. Students who are applying to graduate school are usually asked to take other, more specific standardized exams depending on which college they are applying to. For example, some students are required to take the Graduate Record Exam, or the GRE. Students applying to a business college will probably have to take the GMAT, and students applying to law college will have to take the LSAT. You probably know about the TOEFL exam, which most foreign students have to take before being admitted to American colleges or universities. These exams, including the TOEFL, are all prepared by a company that is independent of the school system. These exams have come under a lot of criticism lately, but they are still widely used as one way to determine who will be admitted to various schools. However, most schools try to look at the whole student and consider factors other than simply grades and test scores. Some of these factors may be extracurricular activities in school, ethnic background, work experience, and so on. Some schools will have personal interviews with students they are considering for admission. Many schools, private as well as public, try very hard to have a student population with a wide variety of backgrounds and ages. Even the most prestigious and most highly competitive colleges and universities will not take only those students with the highest grades and standardized test scores but will consider these other factors. Nevertheless, schools of this type, such as Stanford and Harvard, have so many more people applying than they can possibly accept that students who want to get into such schools take grades and SAT exams very seriously. In general, medical and law colleges, both private and public, are very difficult to get into, and, once again,test scores on standardized exams can be extremely important to those applying to these schools.However, for students who want to attend a state college or university in their own state, it may be enough to graduate from high school in the upper third or even upper half of their high school class. This may surprise those of you who come from an educational system that is highly competitive, a system in which only a small percentage of students who pass a very difficult nationwide standardized high school examination can enter a university. You may be even more surprised by what I have to tell you about community colleges.An interesting feature of education in the United States is the two-year community college. Community colleges that are publicly supported offer somewhat different educational opportunities than those offered by a senior college or a university. First, admissions requirements at public community colleges are usually much more lenient than those at a four-year college or university. It’s usually enough to have graduated from an American high school to be admitted. Second, it is also cheaper to attend a community college. The tuition and fees are usually quite a bit lower. Students often live at home because this type of school does not have dormitories. For these two reasons, many people who are unable to go to a four-year college or university can have an opportunity to take classes for college credit. Finally, community colleges offer two-year programs that can lead to an Associate of Arts degree. Many of these programs, but not all of them, are vocational in nature. People attend community colleges for many different purposes. Some people may be taking on a course or two in some field that particularly interests them and may not be planning on getting a degree. Other people may be going to community college full-time and planning to transfer to a four-year college or university upon successful completion of two years at a community college. Well, so much for community colleges.I promised to tell you a little about the actual student body on a typical U.S. campus. Let’s start with some statistics, and then we’ll discuss two items that surprise many foreign students. Among the million high school graduates in 2002, percent were enrolled in college the following October. More than 90 percent of those attended full time. Young men represented half of the high school graduates, but more women than men went on to college. The exact statistics are: percent of female high school graduates and percent of male high school graduates. If we break down the statistics racially, we find that white students enrolled in college in greater proportions than black or Hispanic students. The figures are percent for white graduates, percent of black graduates, and percent of Hispanic students. My next statistic may be surprising. p ercent of full-time students in 2002 were either employed or looking for work. That number jumps to percent for part-time students. That last statistic makes more sense when we consider that besides the students who are from eighteen to twenty-two years old that one expects to find on a college campus, there are also many older married students. They may be people who attend part-time to upgrade their skills, people who are changing careers, or retired people who still have a desire to learn. Also, foreign students are often surprised at how poorly prepare American students are when they enter a university. Actually, at very select schools the students are usually very well prepared, but at less selective schools, they may not be as well prepared as students in your country are. If you will remember the educational philosophy we discussed in the last lecture, you will understand why. Schools in the States simply admit a lot more students than is usual in most other countries.Also, most young American university students have not traveled in other countries and are not very well versed in international matters and do not know a lot about people from other countries. Foreign students usually find them friendly but not very well informed about their countries or cultures.In brief, you can see that educational opportunities and admissions standardsvary greatly in the United States. While it may be quite difficult to gain admission to some colleges and universities because of the very large number of applicants, probably any student graduating from high school with reasonable grades can find some accredited university or college to attend. Those students hoping to enter graduate school will often face very stiff competition, whether at private or public schools. Many students who start at a college or university will not finish in four years. Some will drop out to work or travel and may never finish. Others will return to school a few months or a few years later. Some will go to school full-time and others part-time. Some will not work while going to school, but most will work at some time or other during their school years.We’re out of time, I see. In my next lecture, I’ll talk to you about a relatively new development in education, distance learning. It should be of interest to those of you who want to attend college but can’t because of living far from a colle ge, busy schedules, or for other reasons.。
HCM 2010 - Chapter 10 - Freeway Facilities
NCHRP Project 3-92Production of the 2010 Highway Capacity ManualTRB Delivery Draft Chapter 10Freeway FacilitiesPrepared for:National Cooperative Highway Research ProgramTransportation Research BoardNational Research CouncilTransportation Research BoardNAS‐NRCLIMITED USE DOCUMENTThis draft material, not released for publication, is furnished only for review tomembers of, or participants in the work of, the National Cooperative HighwayResearch Program and the Transportation Research Board. It is to be regarded asfully privileged, and dissemination of the information included herein must beapproved by the NCHRP.This is an uncorrected draft as submitted by the research agency. The opinionsand conclusions expressed or implied are those of the research agency. They arenot necessarily those of the Transportation Research Board, the NationalAcademies, or the program sponsors. The information, data, and procedurescontained herein have not been incorporated into the published HighwayCapacity Manual and are not recommended for the analysis of transportationfacilities.February 8, 2010Kittelson & Associates, Inc.Polytechnic Institute of NYUTexas Transportation InstituteUniversity of Florida2010 Highway Capacity Manual CHAPTER 10FREEWAY FACILITIESCONTENTS1.INTRODUCTION..................................................................................................10‐1Segments and Influence Areas..........................................................................10‐2Free‐Flow Speed.................................................................................................10‐3Capacity of Freeway Facilities..........................................................................10‐4Level of Service: Component Segments and the Freeway Facility..............10‐8Service Flow Rates, Service Volumes, and Daily Service Volumes for aFreeway Facility.........................................................................................10‐10Generalized Daily Service Volumes for Freeway Facilities........................10‐11Active Traffic Management and Other Measures to ImprovePerformance...............................................................................................10‐142.METHODOLOGY...............................................................................................10‐16Scope of the Methodology...............................................................................10‐16Limitations of the Methodology.....................................................................10‐17Computational Steps........................................................................................10‐183.APPLICATIONS..................................................................................................10‐40Operational Analysis........................................................................................10‐40Traffic Management Strategies.......................................................................10‐41Use of Alternative Tools..................................................................................10‐424.EXAMPLE PROBLEMS.......................................................................................10‐48Example Problem 1: Evaluation of an Undersaturated Facility.................10‐48Example Problem 2: Evaluation of an Oversaturated Facility...................10‐54Example Problem 3: Capacity Improvements to an OversaturatedFacility.........................................................................................................10‐585.REFERENCES.......................................................................................................10‐62Chapter 10/Freeway Facilities Page 10-i Contents DRAFT February 20102010 Highway Capacity ManualLIST OF EXHIBITSExhibit 10‐1 Influence Areas of Merge, Diverge, and Weaving Segments........10‐2Exhibit 10‐2 Basic Freeway Segments on an Urban Freeway..............................10‐3Exhibit 10‐3 Ramp Density Determination.............................................................10‐4Exhibit 10‐4 Example of the Effect of Segment Capacity on a FreewayFacility..................................................................................................................10‐5Exhibit 10‐5 Free‐Flow Speed vs. Base Capacity for Freeways............................10‐6Exhibit 10‐6 Base Capacity vs. Total Ramp Density..............................................10‐7Exhibit 10‐7 Level‐of‐Service Criteria for Freeway Facilities...............................10‐9Exhibit 10‐8 Generalized Daily Service Volumes for Urban Freeway Facilities(1,000 veh/day)..................................................................................................10‐13Exhibit 10‐9 Generalized Daily Service Volumes for Rural Freeway Facilities(1,000 veh/day)..................................................................................................10‐14Exhibit 10‐10 Freeway Facility Methodology.......................................................10‐18Exhibit 10‐11 Example Time‐Space Domain for Freeway Facility Analysis....10‐20Exhibit 10‐12 Defining Analysis Segments for a Ramp Configuration............10‐22Exhibit 10‐13 Defining Analysis Segments for a Weaving Configuration.......10‐23Exhibit 10‐14 Capacity of Long‐Term Construction Zones................................10‐28Exhibit 10‐15 Capacity Reductions Due to Weather and EnvironmentalConditions in Iowa...........................................................................................10‐29Exhibit 10‐16 Capacities on German Autobahns Under Varying Conditions(veh/h/ln)...........................................................................................................10‐29Exhibit 10‐17 Proportion of Freeway Segment Capacity Available Under IncidentConditions.........................................................................................................10‐30Exhibit 10‐18 Illustration of Speed‐Flow Curves for Different WeatherConditions.........................................................................................................10‐31Exhibit 10‐19 Illustration of Adjusted Speed‐Flow Curves for IndicatedCapacity Reductions........................................................................................10‐32Exhibit 10‐20 Node‐Segment Representation of a Freeway Facility.................10‐35Exhibit 10‐21 Mainline and Segment Flow at On‐ and Off‐Ramps...................10‐35Exhibit 10‐22 Required Input Data for Freeway Facility Analysis....................10‐40Exhibit 10‐23 Limitations of the HCM Freeway Facilities AnalysisProcedure..........................................................................................................10‐43Exhibit 10‐24 List of Example Problems...............................................................10‐48Exhibit 10‐25 Freeway Facility in Example Problem 1........................................10‐48Exhibit 10‐26 Geometry of Directional Freeway Facility for ExampleProblem 1...........................................................................................................10‐48Exhibit 10‐27 Demand Inputs for Example Problem 1.......................................10‐50Exhibit 10‐28 Segment Capacities for Example Problem 1.................................10‐50Contents Page 10-ii Chapter 10/Freeway FacilitiesDRAFT February 20102010 Highway Capacity ManualExhibit 10‐29 Segment Demand‐to‐Capacity Ratios for Example Problem 1..10‐51Exhibit 10‐30 Volume‐Served Matrix for Example Problem 1...........................10‐51Exhibit 10‐31 Speed Matrix for Example Problem 1...........................................10‐52Exhibit 10‐32 Density Matrix for Example Problem 1........................................10‐52Exhibit 10‐33 LOS Matrix for Example Problem 1..............................................10‐52Exhibit 10‐34 Facility Performance Measure Summary for ExampleProblem 1...........................................................................................................10‐53Exhibit 10‐35 Demand Inputs for Example Problem 2.......................................10‐55Exhibit 10‐36 Segment Capacities for Example Problem 2................................10‐55Exhibit 10‐37 Segment Demand‐to‐Capacity Ratios for Example Problem 2..10‐56Exhibit 10‐38 Volume‐Served Matrix for Example Problem 2...........................10‐57Exhibit 10‐39 Speed Matrix for Example Problem 2...........................................10‐57Exhibit 10‐40 Density Matrix for Example Problem 2........................................10‐57Exhibit 10‐41 Expanded LOS Matrix for Example Problem 2...........................10‐57Exhibit 10‐42 Facility Performance Measure Summary for ExampleProblem 2...........................................................................................................10‐58Exhibit 10‐43 Freeway Facility in Example Problem 3.......................................10‐58Exhibit 10‐44 Geometry of Directional Freeway Facility in ExampleProblem 3...........................................................................................................10‐58Exhibit 10‐45 Segment Capacities for Example Problem 3................................10‐60Exhibit 10‐46 Segment Demand‐to‐Capacity Ratios for Example Problem 3..10‐60Exhibit 10‐47 Speed Matrix for Example Problem 3...........................................10‐61Exhibit 10‐48 Density Matrix for Example Problem 3........................................10‐61Exhibit 10‐49 LOS Matrix for Example Problem 3..............................................10‐61Exhibit 10‐50 Facility Performance Measure Summary for ExampleProblem 3...........................................................................................................10‐61Chapter 10/Freeway Facilities Page 10-iii Contents DRAFT February 20102010 Highway Capacity ManualThis page intentionally left blank.Contents Page 10-iv Chapter 10/Freeway FacilitiesDRAFT February 20102010 Highway Capacity Manual1. INTRODUCTIONVOLUME 2: UNINTERRUPTED FLOW 10. Freeway Facilities 11. Basic Freeway Segments 12. Freeway Weaving Segments 13. Freeway Merge and Diverge Segments 14. Multilane Highways 15. Two-Lane HighwaysA freeway is a separated highway with full control of access and two or more lanes in each direction dedicated to the exclusive use of traffic. Freeways are comprised of various uniform segments that may be analyzed to determine capacity and level of service. There are three types of segments found on freeways:• Freeway Merge and Diverge Segments: Segments where two or more traffic streams combine to form a single traffic stream (merge), or where a single traffic stream divides to form two or more separate traffic streams(diverge).• Freeway Weaving Segments: S egments in which two or more traffic streams traveling in the same general direction cross paths along a significantlength of freeway without the aid of traffic control devices (except forguide signs). Weaving segments are formed when a diverge segmentclosely follows a merge segment, or when a one ‐lane off ‐ramp closelyfollows a one ‐lane on ‐ramp and the two are connected by a continuous auxiliary lane.• Basic Freeway Segments: All segments that are not merge, diverge, or weaving segments.Analysis methodologies are detailed for basic freeway segments in Chapter 11, for weaving segments in Chapter 12, and for merge and diverge segments in Chapter 13.Chapter 10, Freeway Facilities, provides a methodology for analyzingextended lengths of freeway comprised of continuously connected basic freeway, weaving, merge, and diverge segments. Such extended lengths are referred to as a freeway facility. Note that in this terminology, the term facility does not refer to an entire freeway from beginning to end; instead, it refers to a specific set of connected segments that have been identified for analysis. In addition, the term does not refer to a freeway system consisting of several interconnected freeways.The methodologies of Chapters 11, 12, and 13 all focus on a single time period of interest, generally the peak 15 min within a peak hour. This chapter’s methodology allows for the analysis of multiple and continuous 15‐min time periods, and is capable of identifying breakdowns and the impact of such breakdowns over space and time.The methodology is integral with the FREEVAL 2010 model, whichimplements the complex computations involved. This chapter discusses the basic principles of the methodology and its application. Chapter 25, Freeway Facilities: Supplemental, contains a complete and detailed description of all of the algorithms that define the methodology. The Technical Reference Library in Volume 4 contains a user’s guide to FREEVAL 2010, and an executable spreadsheet that implements the methodology. Chapter 10/Freeway Facilities Page 10-1 IntroductionDRAFT February 20102010 Highway Capacity ManualSEGMENTS AND INFLUENCE AREASIt is important that the definition of freeway segments and their influenceareas is clearly understood. The influence areas of merge, diverge, and weavingsegments are as follows:•Weaving Segment: The base length of the weaving segment itself plus 500 ftupstream of the entry point to the weaving segment and 500 ftdownstream of the exit point from the weaving segment; entry and exitpoints are defined as the points where the appropriate edges of themerging or diverging lanes meet.•Merge Segment: From the point at which the edges of the travel lanes of themerging roadways meet to a point 1,500 ft downstream of that point;•Diverge Segment: From the point at which the edges of the travel lanes ofthe merging roadways meet to a point 1,500 ft upstream of that point.Points at which the “edges of travel lanes” meet are most often defined bypavement markings.The influence areas of merge, diverge, and weaving segments are illustratedin Exhibit 10‐1.Exhibit 10-1Influence Areas of Merge,Diverge, and WeavingSegments(a) Merge Influence Area (b) Diverge Influence Area(c) Weaving Influence AreaBasic freeway segments are any other segments along the freeway that arenot within these defined influence areas. This is not to say that basic freewaysegments are not affected by the presence of adjacent and nearby merge, diverge,and weaving segments. Particularly when a segment breaks down, its effects willpropagate to both upstream and downstream segments, regardless of type.Furthermore, there is the general impact of the frequency of merge, diverge, andweaving segments on the general operation of all segments, which is taken intoaccount by the free‐flow speed (FFS) of the facility.Basic freeway segments, therefore, do exist even on urban freeways wheremerge and diverge points (most often ramps) are closely spaced. Exhibit 10‐2illustrates this point. It shows a 9,100‐ft (1.7‐mi) length of freeway with fourramp terminals, two of which form a weaving segment. Even with an averageramp spacing less than 0.5 mi, this length of freeway contains three basic freewaysegments. The lengths of these segments are relatively short, but in terms ofIntroduction Page 10-2 Chapter 10/Freeway FacilitiesDRAFT February 20102010 Highway Capacity Manualanalysis methodologies, these must be treated as basic freeway segments. Thus, while it is true that many urban freeways will be dominated by frequent merge, diverge, and weaving segments, there will still be segments classified and analyzed as basic freeway segments.Exhibit 10-2Basic Freeway Segments on an Urban Freeway1,500 ft 1,600 ft 2,000 ft 2,500 ft 1,500 ft1,000 ft Basic 2,600 ft Weaving 1,500 ft Basic 1,500 ft Merge 1,000 ft Basic 1,500 ftMergeFREE-FLOW SPEEDFree ‐flow speed is strictly defined as the theoretical speed when the density and flow rate on the study segment are both zero. Chapter 11, Basic Freeway Segments, presents speed ‐flow curves that indicate that the free ‐flow speed on freeways is expected to prevail at flow rates between 0 and 1,000 pc/h/ln. In this broad range of flows, speed is insensitive to flow rates. This characteristic simplifies and permits the measurement of free ‐flow speeds in the field.Chapter 11 also presents a methodology for estimating the free ‐flow speed of a basic freeway segment in cases in which it cannot be directly measured. Itindicates that the free ‐flow speed of a basic freeway segment is sensitive to three variables:• Lane widths,• Lateral clearances, and• Total ramp density.Of these, the most critical is total ramp density. Total ramp density is defined as the average number of on ‐ramp, off ‐ramp, major merge, and major diverge junctions per mile. It applies to a 6‐mi segment of freeway facility, 3 mi upstream and 3 mi downstream of the midpoint of the study segment.While the methodology for determining free ‐flow speed is provided in Chapter 11, Basic Freeway Segments, it is also applied in Chapter 12, Freeway Weaving Segments and Chapter 13, Freeway Merge and Diverge Segments. Thus, the free ‐flow speed affects the operation of all basic, weaving, merge, and diverge segments on a freeway facility.Chapter 10/Freeway Facilities Page 10-3 IntroductionDRAFT February 20102010 Highway Capacity ManualThe free‐flow speed is an important characteristic, as the capacity c, serviceflow rates SF, service volumes SV, and daily service volumes DSV all dependupon the free‐flow speed.Exhibit 10‐3 illustrates the determination of total ramp density on a 6‐milength of freeway facility.Exhibit 10-3Ramp Density DeterminationAs illustrated in Exhibit 10‐3, there are four ramp terminals and one majordiverge point in the 6‐mi segment illustrated. The total ramp density is,therefore, 5 / 6 = 0.83 ramps/mi.CAPACITY OF FREEWAY FACILITIESCapacity has been traditionally defined for segments of uniform roadway,traffic, and control conditions. When facilities consisting of a series of connectedsegments are considered, the concept of capacity is more complicated.The methodologies of Chapters 11, 12, and 13, allow the capacity of eachbasic freeway, freeway weaving, freeway merge, or freeway diverge segment tobe estimated. It is highly unlikely that every segment of a facility will have thesame roadway, traffic, and control conditions, and even less likely that they willhave the same capacity.Conceptual Approach to the Capacity of a Freeway FacilityConsider the example shown in Exhibit 10‐4. It illustrates five consecutivesegments that are to be analyzed as one “freeway facility.” Demand flow rates v d,capacities c, and actual flow rates v a are shown, as are the resulting v d /c and v a /cratios. A lane is added in segment 3 (even though this segment begins with anoff‐ramp), providing higher capacities for segments 3, 4, and 5 than in segments1 and 2. The example analyzes three scenarios.In Scenario 1, none of the demand flow rates exceed the capacities of thesegments comprising the facility. Thus, no breakdowns occur, and the actualflow rates are the same as the demand flow rates (i.e., v d = v a for this scenario).None of the v d /c or v a /c ratios exceed 1.00, although the highest ratios (0.978)occur in segment 5.Scenario 2 adds 200 veh/h of demand to each segment (essentially another200 veh/h of through freeway vehicles). In this case, segment 5 will experience abreakdown, i.e., the demand flow rate will exceed the capacity. In this segment,demand flow rate v d is different from the actual flow rate v a, as the actual flowrate v a can never exceed the capacity c.In Scenario 3, all demand flow rates are increased by 10%. This, in effect,keeps the relative values of the segment demand flow rates constant. In this case,Introduction Page 10-4 Chapter 10/Freeway FacilitiesDRAFT February 20102010 Highway Capacity Manualdemand flow rate will exceed capacity in both segments 4 and 5. Again, the demand flow rates and actual flow rates will be different in these segments.Exhibit 10-4 Example of the Effect of Segment Capacity on a Freeway Facility 12345 Freeway Segment ScenarioPerformance Measures 1 2 3 4 5 Scenario 1(Stable Flow) Demand v d , veh/h Capacity c , veh/h Volume v a , veh/h v d /c ratio v a /c ratio3,400 4,000 3,400 0.850 0.850 3,500 4,000 3,500 0.875 0.875 3,400 4,500 3,400 0.756 0.756 4,200 4,500 4,200 0.933 0.933 4,400 4,500 4,400 0.978 0.978 Scenario 2 (Add 200 veh/h to each segment) Demand v d , veh/hCapacity c , veh/hVolume v a , veh/h v d /c ratio v a /c ratio3,600 4,000 3,600 0.900 0.900 3,700 4,000 3,700 0.925 0.925 3,600 4,500 3,600 0.800 0.800 4,400 4,500 4,400 0.978 0.978 4,600 4,500 4,500 1.022 1.000 Scenario 3 (Increase demand by 10% in all segments)Demand v d , veh/hCapacity c , veh/hVolume v a , veh/h v d /c ratio v a /c ratio 3,740 4,000 3,740 0.935 0.935 3,850 4,000 3,850 0.963 0.963 3,740 4,500 3,740 0.831 0.831 4,840 4,500 4,500 1.078 1.000 5,060 4,500 4,500 1.120 1.000 Note: Shaded cells indicate segments where demand exceeds capacity.This example highlights a number of points that make the analysis of freeway facilities very complicated:1. It is critical to this methodology that the difference between demand flow rate v d and actual flow rate v a be highlighted, and that both values be clearly and appropriately labeled.2. In Scenarios 2 and 3, the analysis of Exhibit 10‐4 is inadequate andmisleading. In Scenario 2, when segment 5 breaks down, queues begin to form, and to propagate upstream. Thus, even though the demands in segments 1 through 4 are less than the capacity of those segments, the queues generated by segment 5 will, over time, propagate throughsegments 1 through 4 and significantly affect their operation. In Scenario 3, segments 4 and 5 fail, and queues are generated, which also propagate upstream over time.3. It might be argued that the analysis of Scenario 1 is sufficient to understand the facility operation as long as all segments areundersaturated (i.e., all segment v d /c ratios are less than or equal to 1.00). However, when any segment v d /c ratio exceeds 1.00, such a simpleanalysis ignores the spreading impact of breakdowns in both space and time.4. In Scenarios 2 and 3, the segments downstream of segment 5 will also be affected, as demand flow is prevented from reaching those segments by the segment 5 (and segment 4 in Scenario 3) breakdowns and queues.5. In this example, it is also important to note that the segment(s) that break down first do not have the lowest capacities. Segments 1 and 2, with Chapter 10/Freeway Facilities Page 10-5 Introduction DRAFT February 2010lower capacities, do not break down in any of the scenarios. Breakdown occurs first in Segment 5, which has one of the higher capacities.Considering all these complications, the capacity of a freeway facility is defined as:Freeway facility capacity is the capacity of the critical segment among thosesegments comprising the defined facility. This capacity must, for analysis purposes, be compared to the demand flow rate on the critical segment.The critical segment is defined as the segment that will break down first, given that all traffic, roadway, and control conditions do not change, including the spatial distribution of demands on each component segment. This is not a simple definition. It depends upon the relative demand characteristics, and can change over time as the demand pattern changes. Facility capacity may be more than the capacity of the component segment with the lowest capacity. Because of this, it is important that individual segment demands and capacities beevaluated. The fact that one of these will be the critical segment and will define the facility capacity does not diminish the importance of the capacities of other segments in the defined facility.Base Capacity of Freeway FacilitiesIn the methodologies of Chapters 11, 12, and 13, a base capacity is used. The base capacity represents the capacity of the facility, assuming that there are no heavy vehicles in the traffic stream and that all drivers are regular users of the segment. The base capacity for all freeway segments varies with the free ‐flow speed, as indicated in Exhibit 10‐5.Exhibit 10-5Free-Flow Speed vs. Base Capacity for Freeways Free-Flow Speed (mi/h) Base Capacity (pc/h/ln) 75706560 55 2,400 2,400 2,350 2,300 2,250The equation given in Chapter 11, Basic Freeway Segments, for estimating the free ‐flow speed of a segment is as shown in Equation 10‐1:Equation 10-1 84.022.34.75TRD f f FFS LC LW −−−=whereFFS = free ‐flow speed (mi/h),f LW = adjustment for lane width (mi/h), f LC = adjustment for lateral clearance (mi/h), andTRD = total ramp density (ramps/mi).The process for determining the value of adjustment factors is described in Chapter 11.Because the base capacity of a freeway segment is directly related to the free ‐flow speed, it is possible to construct a relationship between base capacity and the lane width, lateral clearance, and total ramp density of the segment. If thelane width and lateral clearance are taken to be their base values (12 ft and 6 ft, respectively), a relationship between base capacity and total ramp density emerges, as shown in Exhibit 10‐6.Base capacity is expressed as a flow rate for a 15‐min analysis period, not a full ‐hour volume. It also represents a flow rate in pc/h, with no heavy vehicles, and a driver population familiar with the characteristics of the analysis segment.Exhibit 10-6Base Capacity vs. Total Ramp DensitySegment Capacity vs. Facility CapacityFree ‐flow speed is a characteristic of a length of freeway extending three miles upstream and three miles downstream of the center point of an analysis segment. The segment may be a basic freeway segment, a weaving segment, a merge segment, or a diverge segment. In essence, it is a measure of the impact of overall facility characteristics on the operation of the individual analysis segment centered in the defined 6‐mi range.This concept can be somewhat generalized where freeway facility analysis is involved. If conditions (particularly ramp density) are similar along a longer length of freeway, it is acceptable to compute the total ramp density for the longer length, and apply it to all segments within the analysis length. Thisassumes that moving the “center” of a 6‐mi length for each component segment would not result in a significant change in the free ‐flow speed.The capacity of a nearly homogeneous freeway facility is, for all practical purposes, the same as the capacity of a basic freeway segment with the same roadway and traffic characteristics. Consider that:• Merge and diverge segments have the same capacity as a similar basic freeway segment. As discussed in Chapter 13, the presence of merge and diverge segments on a freeway may affect operating characteristics,generally reducing speeds and increasing densities, but does not reduce capacity.•Weaving segments often have per‐lane capacities that are less than the per‐lane capacities of the entering and leaving basic freeway segments. In almost all cases, however, weaving segments have more lanes than theentering and leaving basic freeway segments. Thus, the impact on thecapacity of the mainline freeway is most often negligible.This does not mean, however, that the capacity of each component segment of a facility is the same. Each segment has its own demand and demand characteristics. Demand flow rate can change at every entry or exit point along the freeway, and the percent of heavy vehicles can change too. Terrain can change at various points along the freeway.Changes in heavy vehicle presence can change the capacity of individual segments within a defined facility. Changes in the split of movements in a weaving segment can change its capacity. In the same way, changes in the relative demand flows at on‐ and off‐ramps can change the location of the critical segment within a defined facility, and its capacity.As noted previously, the capacity of a freeway facility is defined as the capacity of its critical segment.LEVEL OF SERVICE: COMPONENT SEGMENTS AND THE FREEWAY FACILITYLevel of Service of Component SegmentsChapters 11, 12, and 13 provide methodologies to determine the level of service (LOS) in basic, weaving, merge, and diverge segments. In all cases, LOS F is identified when v d /c is greater than 1.00. Such breakdowns are simply identified, and users are referred to this chapter.This chapter’s methodology provides an analysis of breakdown conditions, including the spatial and time impacts of a breakdown. Thus, when doing a facility‐level analysis, LOS F in a component segment can be identified (a) when the segment v d /c is greater than 1.00, and (b) when a queue from a downstream breakdown extends into an upstream segment. The latter cannot be done using the individual segment analysis procedures of Chapters 11–13.Thus, when facility‐level analysis is undertaken using the methodology of this chapter, LOS F for a component segment will be identified in two different ways:•When v/c is greater than 1.00, ord•When the density is greater than 45 pc/mi/ln for basic freeway segments or 43 pc/mi/ln for weaving, merge, or diverge segments.The latter identifies segments in which queues have formed as a result of downstream breakdowns.Level of Service for a Freeway FacilityBecause LOS for basic, weaving, merge, and diverge segments on a freeway is defined in terms of density, LOS for a freeway facility is also defined on the basis of density.。
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北阳电子内部技术资料
ቤተ መጻሕፍቲ ባይዱ7章
凌阳音频压缩算法
第10章 综合应用实例
前面我们介绍了 SPCE061A 的结构、C 语言的基本语法以及使用 C 语言开发一些 简单的单片机应用程序。本章将结合一个用 SPCE061A 实现简易录音笔的软硬件设计 实例，详细介绍开发单片机应用系统程序的过程。
10.1 开发背景
数码录音笔适用于外语学习、课堂记录、会议记录、谈判、研讨、访问、市场调 查、速记、采访、备忘的诸多领域。 目前，数码录音笔的功能种类百花齐放，百家争鸣。它们具有的功能一般有：闹 钟功能、定时录音功能、重复播放功能、播放速度控制功能、覆盖和附加录音功能， 资料的上传和下载功能。 此外，有些数码录音笔还具有其他特殊功能，如视像功能，MP3 功能，录音监听 功能，添加目录功能等，不一而足。 因为本章的目的是介绍开发单片机应用系统程序的过程，不是真正的开发一个产 品，所以，本章实现的录音笔的功能只有：录音、播放、循环播放、重复播放、选择 上一段播放、选择下一段播放、上传数据到 PC、从 PC 下载数据的功能。
第 10 章 综合应用实例 ................................................................................................. 129 10.1 开发背景............................................................................................................. 129 10.2 硬件设计............................................................................................................. 129 10.2.2 电源部分 ...................................................................................................... 130 10.2.3 音频录入部分 .............................................................................................. 130 10.2.4 键盘部分 ...................................................................................................... 131 10.2.5 外扩存储器部分 .......................................................................................... 132 10.2.6 通信接口部分 .............................................................................................. 133 10.2.7 音频输出部分 .............................................................................................. 134 10.3 软件设计............................................................................................................. 134 10.3.1 主程序 ......................................................................................................... 134 10.3.2 硬件系统初始化程序 .................................................................................. 142 10.3.3 内部 FLASH 的读写程序 ............................................................................. 143 10.3.4 串行 FLASH 的读写程序 ............................................................................. 146 10.3.5 UART 通讯程序 ............................................................................................ 151 10.3.6 键盘扫描程序 .............................................................................................. 152 10.4 小结 .................................................................................................................... 152
10.2 硬件设计
从硬件上来说，本系统涉及到电源管理、音频录入、键盘管理，外扩存储器、与 PC 通信的接口、音频输出几部分。结构框图见图 10.1。
Micphone 输 入 电 路 外 部 存 储 器