Torsion and Nonmetricity in Scalar-Tensor Theories of Gravity
什么是宏平均(macro-average)和微平均(micro-average)

什么是宏平均(macro-average)和微平均(micro-average)什么是宏平均(macro-average)和微平均(micro-average)Fri, 05/14/2010 - 14:53 — Fuller宏平均(macro-average)和微平均(micro-average)是衡量文本分类器的指标。
根据Coping with theNews: the machine learning wayWhen dealing with multiple classes there are two possible ways of averaging thesemeasures(i.e. recall, precision, F1-measure) , namely, macro-average andmicro-average. The macro-average weights equally all the classes, regardless of how manydocuments belong to it. The micro-average weights equally all the documents, thus favouringthe performance on common classes. Different classifiers will perform different in commonand rare categories. Learning algorithms are trained more often on more populated classesthus risking local over-fitting.宏平均指标相对微平均指标而言受小类别的影响更大文章《一种快速高效的文本分类方法》给出了几个文本分类性能评估的公式。
对于给定的某个类别,a 表示被正确分到该类的实例的个数,b 表示被误分到该类的实例的个数,c 表示属于该类但被误分到其它类别的实例的个数,则准确率(p)和召回率(r)和F-指标分别被定义为:r = a / (a + c), if a + c > 0; otherwise r = 1p = a / (a + b), if a + b > 0; otherwise p = 1其中参数β 用来为准确率(p)和召回率(r)赋予不同的权重,当β 取1 时,准确率和召回率被赋予相同的权重。
Distributed interactive simulation for group-distance exercise on the web

DISTRIBUTED INTERACTIVE SIMULATION FOR GROUP-DISTANCEEXERCISES ON THE WEBErik Berglund and Henrik ErikssonDepartment of Computer and Information ScienceLinköping UniversityS-581 83 Linköping, SwedenE-mail: {eribe, her}@ida.liu.seKEYWORDS: Distributed Interactive Simulation, Distance Education, Network, Internet, Personal ComputerABSTRACTIn distributed-interactive simulation (DIS), simulators act as elements of a bigger distributed simulation. A group-distance exercise (GDE) based on the DIS approach can therefore enable group training for group members participating from different locations. Our GDE approach, unlike full-scale DIS systems, uses affordable simulators designed for standard hardware available in homes and offices.ERCIS (group distance exERCISe) is a prototype GDE system that we have implemented. It takes advantage of Internet and Java to provide distributed simulation at a fraction of the cost of full-scale DIS systems.ERCIS illustrates that distributed simulation can bring advanced training to office and home computers in the form of GDE systems.The focus of this paper is to discuss the possibilities and the problems of GDE and of web-based distributed simulation as a means to provide GDE. INTRODUCTIONSimulators can be valuable tools in education. Simulators can reduce the cost of training and can allow training in hazardous situations (Berkum & Jong 1991). Distributed-interactive simulation (DIS) originated in military applications, where simulators from different types of forces were connected to form full battle situations. In DIS, individual simulators act as elements of a bigger distributed simulation (Loper & Seidensticker 1993).Thus, DIS could be used to create a group-distance exercise (GDE), where the participants perform a group exercise from different locations. Even though DIS systems based on complex special-hardware simulators provide impressive training tools, the cost and immobility of these systems prohibit mass training.ERCIS (group distance exERCISe) is a prototype GDE system that uses Internet technologies to provide affordable DIS support. Internet (or Intranet) technologies form a solid platform for GDE systems because they are readily available, and because they provide high level of support for network communication and for graphical simulation. ERCIS, therefore, takes advantage of the programming language Java, to combine group training, distance education and real-time interaction at a fraction of the cost of full-scale DIS systems.In this paper we discuss the possibilities and the problems of GDE and of web-based distributed simulation as a means to provide GDE. We do this by discussing and drawing conclusions from the ERCIS project.BACKGROUNDLet us first provide some background on GDE, DIS, distributed objects, ERCIS’s military application, and related work.Group-Distance Exercise (GDE)The purpose of GDE is to enable group training in distance education through the use of DIS. Unlike full-scale DIS systems, our GDE approach assumes simulators designed for standard hardware available in homes and offices. This approach calls for software-based simulators which are less expensive to use, can be multiplied virtually limitlessly, and can enable training with expensive, dangerous and/or non-existing equipment.A thorough background on the GDE concept can be found in Computer-Based Group-Distance Exercise (Berglund 1997).Distributed Interactive Simulation (DIS)DIS originated as a means to utilize military simulators in full battle situations by connecting them (Loper & Seidensticker 1993). As a result it becomes possible tocombine the use of advanced simulators and group training.The different parts of DIS systems communicate according to predefined data packets (IEEE 1995) that describe all necessary data on the bit level. The implementation of the communication is, therefore, built into DIS systems.Distributed ObjectsDistributed objects (Orfali et al. 1996) can be characterized as network transient objects, objects that can bridge networks. Two issues must be addressed when dealing with distributed objects: to locate them over the network and to transform them from abstract data to a transportation format and vice versa.The common object request broker architecture (CORBA) is a standard protocol for distributed objects, developed by the object management group (OMG). CORBA is used to cross both networks and programming languages. In CORBA, all objects are distributed via the object request broker (ORB). Objects requesting service of CORBA object have no knowledge about the location or the implementation of the CORBA objects (Vinoski 1997).Remote method invocation (RMI) is Java’s support for distributed objects among Java programs. RMI only provides the protocol to locate and distribute abstract data, unlike CORBA. In the ERCIS project we chose RMI because ERCIS is an all Java application. It also provided us with an opportunity to assess Java’s support for distributed objects.RBS-70 Missile UnitERCIS supports training of the RBS-70 missile unit of the Swedish anti-aircraft defense. The RBS-70 missile unit’s main purpose is to defend objects, for instance bridges, against enemy aircraft attacks, see Figure 1. The RBS-70 missile unit is composed of sub units: two intelligence units and nine combat units. The intelligence units use radar to discover and calculate flight data of hostile aircraft. Guided by the intelligence unit, the combat units engage the aircraft with RBS-70 missiles. (Personal Communication).Intelligence unitCombat unitData transferFigure 1. The RBS-70 missile unit. Its main purpose is to defend ground targets.During training, the RBS-70 unit uses simulators, for instance, to simulate radar images. All or part of the RBS-70 unit’s actual equipment is still used (Personal Communication).Related WorkIn military applications, there are several examples of group training conducted using distributed simulation. For instance, MIND (Jenvald 1996), Janus, Eagle, the Brigade/Battalion Simulation (Loper & Seidensticker 1993), and ABS 2000.C3Fire (Granlund 1997) is an example of a tool for group training, in the area of emergency management, that uses distributed simulation.A common high-level architecture for modeling and simulation, that will focus on a broader range of simulators than DIS, is being developed (Duncan 1996). There are several educational applets on the web that use simulation; see for instance the Gamelan applet repository. These applets are, however, generally small and there are few, if any, distributed simulations. ERCISERCIS is a prototype GDE system implemented in Java for Internet (or Intranets). It supports education of the RBS-70 missile unit by creating a DIS of that group’s environment. We have used RMI to implement the distribution of the system.ERCIS has two principal components: the equipment simulators and the simulator server, see Figure 2. A maximum of 11 group members can participate in a single ERCIS session, representing the 11 sub-unit leaders, see Figure 3. The group members join by loading an HTML document with an embedded equipment-simulator applet.Simulator serverIntelligence unit equipmentsimulatorCombat unit equipmentsimulatorFigure 2. The principal parts of ERCIS. The equipment simulators are connected to one another through the simulator server.Figure 3. A full ERCIS session. 11 equipment simulators can be active in one ERCIS session at a time. The equipment simulators communicate via the simulator server.Simulator ServerThe simulator server controls a microworld of the group’s environment, including simulated aircraft, exercise scenario and geographical information.The simulator server also distributes network communication among the equipment simulators. The reason for this client-server type of communication is that Java applets are generally only allowed to connect to the computer they were loaded from (Flanagan 1997).Finally, the simulator server functions as a point of reference by which the distributed parts locate one another. The simulator-server computer is therefore the only computer specified prior to an ERCIS session.Equipment SimulatorsThe equipment simulators simulate equipment used by the RBS-70 sub units and also function as user interfaces for the group members. There are two types of equipment simulators: the intelligence-unit equipment simulator and combat-unit equipment simulator.Intelligence Unit Equipment SimulatorThe intelligence-unit’s equipment simulator, see Figure 4,contains a radar simulator and a target-tracking simulator . The radar simulator monitors the air space. The target-tracking simulator performs part of the work of three intelligence-unit personnel to approximate position,speed and course of three aircraft simultaneously.The intelligence-unit leader’s task is to distribute the hostile aircraft among the combat units and to send approximated information to them.Panel used to send information to the combat unit equipment simulator.Target-tracking symbol used to initate target tracking.Simulated radarFigure 4. The user interface of the intelligence unit equipment simulator, running on a Sun Solaris Applet Viewer.Combat Unit Equipment SimulatorThe combat unit equipment simulator, see Figure 5,contains simulators of the target-data receiver and the RBS-70 missile launcher and operator .The target-data receiver presents information sent from the intelligence unit. The information is recalculated relative to the combat unit’s position and shows information such as: the distance and direction to the target. The RBS-70 missile launcher and operator represents the missile launcher and its crew. Based on the intelligence unit’s information it can locate, track and fire upon the target.The combat-unit leader’s task is to assess the situation and to grant permission to fire if all criteria are met.Switch used to grant fire permissionFigure 5. The user interface of the combat unit equipment simulator, running on a Windows 95 Applet Viewer.DISCUSSIONLet us then, with experience from the ERCIS project, discuss problems and possibilities of GDE though DIS and of the support Internet and Java provide for GDE. Pedagogical valueEducators can use GDE to introduce group training at an early stage by, for instance, simplifying equipment and thereby abstracting from technical details. Thus, GDE can focus the training on group performance.GDE could also be used to support knowledge recapitulation for expert practitioners. To relive the group’s tasks and environment can provide a more vivid experience than notes and books.GDE systems can automate collection and evaluation of performance statistics. It is possible to log sessions and replay them to visualize comments on performance in after-action reviews (Jenvald 1996).To fully assess the values of GDE, however, real-world testing is required.SecurityAccess control, software authentication, and communication encryption are examples of security issues that concern GDE and distributed simulators. Java 1.1 provides basic security, which includes fine-grained access control, and signed applets. The use of dedicated GDE Intranets would increase security, especially access control. It would, however, reduce the ability to chose location from where to participate.Security restrictions, motivated or not, limit applications. ERCIS was designed with a client-server type of communication because web browsers enforce security restrictions on applets (Flanagan 1997). Peer-to-peer communication would have been more suitable, from the perspective of both implementation and scalability. We are not saying that web browsers should give applets total freedom. In ERCIS, it would have sufficed if applets were allowed to make remote calls to RMI objects regardless of their location.Performance characteristicsOur initial concerns about the speed of RMI calls and of data transfer over Internet proved to be unfounded. The speed of communication is not a limiting factor for ERCIS. For instance, a modem link (28.8 kilobits per second) is sufficient to participate in exercises.Instead the speed of animation limits ERCIS. To provide smooth animation, ERCIS, therefore, requires more than the standard hardware of today, for instance a Pentium Pro machine or better.ScalabilityIn response to increased network load, ERCIS scales relatively well, because the volume of the data that is transmitted among the distributed parts is very small, for instance, 1 Kbytes.Incorporating new and better simulators in ERCIS requires considerable programming effort. In a full-scale GDE system it could be beneficial to modularize the simulators in a plug-and-play fashion, to allow variable simulator complexity.Download timeThe download time for applets the size of ERCIS’s equipment simulator can be very long. One way to overcome this problem is to create Java archive files (JAR files). JAR files aggregate many files into one and also compress them to decrease the download time considerably. Push technology such as Marimba’s Castanet could also be used to provide automatic distribution of the equipment-simulator software. Distributed objectsDistributed objects, such as RMI, provide a high level of abstraction in network communication compared to the DIS protocol. There are several examples of typical distributed applications that do not utilize distributed objects but that would benefit greatly from this approach. Two examples are the Nuclear Power Plant applet (Eriksson 1997), and NASA’s distributed control of the Sojourner.CONCLUSIONERCIS is a GDE prototype that can be used in training under teacher supervision or as part of a web site where web pages provide additional information. The system illustrates that the GDE approach can provide equipment-free mass training, which is beneficial, especially in military applications where training can be extremely expensive.Java proved to be a valuable tool for the implementation of ERCIS. Java’s level of abstraction is high in the two areas that concern ERCIS: animation and distributed objects. Java’s speed of animation is, however, too slow to enable acceptable performance for highly graphic-oriented simulators. Apart from this Java has supplied the support that can be expected from a programming language, for instance C++.Using RMI to implement distribution was straightforward. Compared to the DIS protocol, RMI provides a flexible and dynamic communication protocol. In conclusion, ERCIS illustrates that it is possible to use Internet technologies to develop affordable DIS systems. It also shows that distributed simulations can bring advanced training to office and home computers in the form of GDE systems.AcknowledgmentsWe would like to thank Major Per Bergström at the Center for Anti-Aircraft Defense in Norrtälje, Sweden for supplying domain knowledge of the RBS-70 missile unit. This work has been supported in part by the Swedish National Board for Industrial and Technical Development(Nutek) grant no. 93-3233, and by the Swedish Research Council for Engineering Science (TFR) grant no. 95-186. REFERENCESBerglund E. (1997) Computer-Based Group Distance Exercise, M.Sc. thesis no. 97/36, Department of Computer and Information Science, Linköping University (http://www.ida.liu.se/~eribe/publication/ GDE.zip: compressed postscript file).van Berkum J, de Jong T. (1991) Instructional environments for simulations Education & Computing vol. 6: 305-358.Duncan C. (1996) The DoD High Level Architecture and the Next Generation of DIS, Proceedings of the Fourteenth Workshop on Interoperability of Distributed Simulation, Orlando, Florida.Eriksson H. (1996) Expert Systems as Knowledge Servers, IEEE Expert vol. 11 no. 3: 14 -19. Flanagan, D. (1997) Java in a Nutshell 2nd Edition, O’Reilly, Sebastopol, CA.Granlund R. (1997) C3Fire A Microworld Supporting Emergency Management Training, licentiate thesis no.598, Department of Computer and Information Science 598, Department of Computer and Information Science Linköping University.IEEE (1995) IEEE Standard for Distributed Interactive Simulation--Application Protocols, IEEE 1278.1-1995 (Standard): IEEE.Jenvald J. (1996) Simulation and Data Collection in Battle Training, licentiate thesis no. 567, Department of Computer and Information Science, Linköping University.Loper M, Seidensticker S. (1994) The DIS Vision: A Map to the Future of Distributed Simulation, Orlando, Florida: Institute for Simulation & Training (/SISO/dis/library/vision.doc) Orfali R, Harkey D, Edwards J. (1996) The Essential Distributed Objects Survival Guide John Wiley, New York.Vinoski S. (1997) CORBA: Integrating Diverse Applications Within Distributed Heterogeneous Environments, IEEE Communications, vol. 14, no. 2.RESOURCES AT THE WEBThe OMG home page: /CORBA JavaSoft’s Java 1.1 documentation: /-products/jdk/1.1/docs/index.htmlThe Gamelan applet repository: / Marimba’s Castanet home page: http://www.marimba.-com/products/castanet.htmlThe Nuclear Power Plant Applet (Eriksson 1995): http://-www.ida.liu.se/∼her/npp/demo.htmlNASAS Soujourner, The techical details on the control distribution of NASAS Soujourner: /features/1997/july/juicy.wits.details.html AuthorsErik Berglund is a doctoral student of computer science at Linköping University. His research interests include knowledge acquisition, program understanding, software engineering, and computer supported education. He received his M.Sc. at Linköping University in 1997. Henrik Eriksson is an assistant professor of computer science at Linköping University. His research interests include expert systems, knowledge acquisition, reusable problem-solving methods and medical Informatics. He received his M.Sc. and Ph.D. at Linköping University in 1987 and 1991. He was a postdoctoral fellow and research scientist at Stanford University between 1991 and 1994. Since 1996, he is a guest researcher at the Swedish Institute for Computer Science (SICS).。
俱乐部趋同

Applied Economics Letters,2006,13,569–574Club convergence inEuropean regionsRita De Siano a and Marcella D’Uva b,*a Department of Economic Studies,University of Naples‘Parthenope’,Via Medina40,80133Naples,Italyb Department of Social Sciences,University of Naples L’Orientale,Largo S.Giovanni Maggiore30,80134Naples,ItalyThis study investigates the‘club convergence’hypothesis applying the stochastic notion of convergence to groups of European regions.In order to avoid the group selection bias problem,the innovative regression tree technique was applied to select endogenously the most important variables in achieving the best identification of groups on the base of per capita income and productive specialization.Tests on stochastic convergence in each group evidences a strong convergence among the wealthiest regions of the European Union and a trend of weak convergence among the remaining groups,confirming Baumol’s hypothesis of convergence.I.IntroductionOver the past decade many authors have explored the evolution of output discrepancies,at both national and regional levels.In particular,starting with Baumol(1986)it has been widely hypothesized that convergence may hold not for all economies but within groups of them showing similar characteristics (Azariadis and Drazen,1990).This evidence is referred to as the‘club convergence’hypothesis which implies that a set of economies may converge with each other,in the sense that in the long run they tend towards a common steady state position, but there is no convergence across different sets. In seeking to test the club convergence hypothesis (Qing Li,1999;Feve and Le Pen,2000;Su,2003,for example)two main questions arise:(a)which frame-work of convergence to use,and(b)how to identify the economies belonging to each club.Initially,a cross-section notion of convergence was used in order to verify the existence of a negative relationship between initial per capita income and its growth rate. In contrast with this notion a stochastic definition of convergence(Carlino and Mills,1993)was proposed and explored by using time series analyses. According to this framework there is stochastic convergence if per capita income disparities between economies follow a stationary process.Bernard and Durlauf(1996)found that when economies show multiple long run equilibria,cross-sectional tests tend to spuriously reject the null hypothesis of no convergence and,as a consequence,represent a weaker notion of convergence than that of the time series.As regards the second point,two methods can be used in order to create different groups of economies.The first sorts of economies follows some a priori criteria(initial level of GDP,education, technology,capital accumulation,etc.)while the second follows an endogenous selection method (Durlauf and Johnson,1995).Finally,the switching regression with the contribution of additional infor-mation on the sample separation followed by Feve and Le Pen(2000)can be mentioned as an intermediate method in modelling convergence clubs. This study investigates the‘club convergence’hypothesis applying the stochastic notion of conver-gence to groups of European regions sorted accord-ing to their initial levels of per capita income and*Corresponding author.E-mail:mduva@unior.itApplied Economics Letters ISSN1350–4851print/ISSN1466–4291onlineß2006Taylor&Francis569/journalsDOI:10.1080/13504850600733473productive specialization(De Siano and D’Uva, 2004,2005)through the application of an innovative methodology known as Classification and Regression Tree Analysis(CART).Unlike other partitioning methods,CART allows a regression to be performed together with a classification analysis on the same ‘learning’dataset,without requiring particular speci-fication of the functional form for the predictor variables which are selected endogenously.The importance of similarities in the initial productive specialization has been highlighted by several theore-tical contributions(Jacobs,1969;Marshall,1980; Romer,1986;Lucas,1988;Helg et al.,1995;Bru lhart, 1998;Ottaviano and Puga,1998)which found that it can be crucial in determining both the nature and size of responses to external shocks.The paper is organized as follows:Section II introduces the methodology of the empirical analysis, Section III displays the dataset,Section IV shows the results of econometric analysis and Section V concludes.II.MethodologyThe empirical analysis is carried out in two parts:first regions are grouped through the classification and regression tree analyses(CART),then convergence is tested within‘clubs’using the time series analysis. CART methodology(Breiman et al.,1984)provides binary recursive partitioning using non-parametric approaches in order to construct homogeneous groups of regions using splitting variables which minimize the intra-group‘impurity’as predictors. The final outcome is a tree with branches and ‘terminal nodes’,as homogeneous as possible,where the average value of the node represents the predicted value of the dependent variable.In this analysis the regression is carried out through the least squares method using the regional GDP growth rate as dependent variable and initial GDP and specializa-tion indexes as explicative variables.In the second part of the study Carlino and Mills(1993)notion of stochastic convergence is applied in each group identified by CART methodology.It follows that if the logarithm of a region’s per capita income relative to the group’s average does not contain a unit root,the region converges.The model(Ben-David, 1994;Qing Li,1999)is the following:y j i,t ¼ iþ i tþ’y i,tÀ1þ"i,tð1Þwhere y j i,t is the log of region i per capita income inyear t,j is the region’s group and"is white noise errorwith0mean.Summing Equation1over j for eachgroup and dividing the outcome by the number ofregions within the group,the following equation isobtained:"y t¼" þ" tþ’"y tÀ1þ"tð2Þwhere"y t is the group’s average per capita incomein year t(the group superscript is suppressed).Subtracting Equation2from Equation1one has:RI i,t¼AþBtþ’RI i,tÀ1þ"tð3Þwhere RI i,t is the logarithm of region i per capitaincome relative to the group’s average at time t(y j i,tÀ"y t).For each region of the sample we apply theAugmented Dickey–Fuller(ADF)test(Dickey andFuller,1979)using the ADF regression ofEquation3:ÁRI t¼ þ tþ RI tÀ1þX kj¼1c jÁRI tÀjþ"tð4ÞAt this point,considering the low power of the ADFtest in the case of short time series,we run alsothe Kwiatkowski et al.(1992)test(KPSS)for trendstationarity.The null hypothesis of the KPSS test isthe trend stationarity against the unit root alter-native.If the KPSS statistic is larger than the criticalvalues the null hypothesis is rejected.The combinedanalysis of KPSS and ADF tests results leads on thefollowing possibilities(Qing Li,1999):.rejection by ADF tests and failure to reject byKPSS!strong convergence;.failure to reject by both ADF and KPSS!weakconvergence;.rejection by KPSS test and failure to rejectADF!no convergence;.rejection by both ADF and KPSS tests invitesto perform further analyses.III.Data DescriptionThis section presents the dataset used both to groupthe sample regions and to run the econometricanalysis.Data for GDP and employment are fromthe Eurostat New Cronos Regio database at NUTS2level.1Annual values for GDP per inhabitant in termsof Purchasing Power Parity(PPP)and the number of1According to EC Regulation No.1059/2003.570R.De Siano and M.D’Uvaemployees in the NACE92productive branches from1981to 2000are used.The sample consists of 123regions belonging to nine countries:11Belgian,8Dutch,29German,222French,20Italian,18Spanish,5Portuguese,2Greek,38British.4For each region (i )the following initial productivespecialization indexes (SP)were built for all theconsidered branches 5(j ):SP ij ¼E ij P n j ¼1ij P m i ¼1E ij P n j ¼1P mi ¼1ijð5Þwhere E indicates the number of employees.IV.Empirical ResultsThe main purpose of the study is to test the ‘clubconvergence’hypothesis across the European regions.In particular,the study aims to investigate whethera region’s per capita income converges to the averageof the group to which it belongs.In order to avoidthe group selection bias problem,the regressiontree technique was applied to select endogenouslythe most important variables in achieving thebest identification of groups (De Siano and D’Uva,2005).If the majority of regions in a groupconverges,the group may be considered a conver-gence ‘club’.The CART method allowed a tree to be built withfour terminal nodes including regions showing a morehomogeneous behaviour of per capita GDP growthrate and productive specialization.Results of CARTanalysis together with the stochastic convergence tests for each group are presented in what follows.The first group consists of 11regions (from Spain,Greece and Portugal)characterized by:the highest estimated mean value of GDP growth rate (126.08%)despite the lowest initial income level (average equal to 4144.3);strong specialization in the agriculture sector (the highest and equal to 3.75),construction branch (2.09)and food and beverages compartment (1.93);the minimum specialization in chemical,energy,and machinery branches and the highest in food-beverages-tobacco,mineral and construction.More than 80%of these regions display ‘weak’convergence while remaining regions show ‘strong’convergence (Table 1).The second group includes 23regions (mainly from Belgium,Spain,Italy and the United Kingdom)characterized by:an average GDP growth rate equal to 111.36%and the second highest initial income level (5788.78);strong specialization in agriculture (2.68)sector,food and beverage (1.26),construction (1.52)and energy (1.20)compartments;the highest specialization in chemical products (0.98);the second highest level of specialization in agricul-ture construction and energy.Almost all these regions present ‘weak’convergence (Table 2).The third group is formed by 21regions from Belgium,France,Germany,the Netherlands,Spain,the UK and Italy (only Abruzzo)characterized by:an estimate for the GDP growth rate of 106%and an average initial level of income equal to 6920.6;main specializations in manufacturing (1.03),mineral products (1.13),construction (1.22),food and beverage (1.45)and energy (1.21);the highest 2The analysis starts from 1984due to the lack of data in the respective regional labour statistics.3During the period 1983–1987there has been a different aggregation of Greek regions at NUTS2level.Kriti and Thessalia are the only regions which presents data for the period 1984–2000.4The geographic units for UK are at NUTS1level of Eurostat classification because of the lack of data for NUTS2units.5Agricultural-forestry and fishery,manufacturing,fuel and power products,non-metallic minerals and minerals,food-beverages-tobacco,textiles-clothing-leather and footwear,chemical products,metal products,machinery-equipment and electrical goods,various industries,building and construction,transport and communication,credit and insurance services.Table 1.Convergence test results of group 1Regions group 1ADF statistics KPSS statistics l ¼4Regions group 1ADF statistics KPSS statistics l ¼4Castilla-la ManchaÀ2.9780.099gr 43Kriti À4.05ÃÃ0.080ExtremaduraÀ3.320.097Pt11Norte À4.03ÃÃ0.126AndaluciaÀ2.630.094Pt12Centro (P)À2.290.123Ceuta y MelillaÀ1.770.123Pt14Alentejo À2.770.104CanariasÀ1.940.121Pt15Algarve À2.010.086ThessaliaÀ1.760.137Notes :ÃÃdenote statistical significance using unit root critical values at the 5%(À3.645).Club convergence in European regions571specialization in energy and manufacturing branches.Except for Abruzzo and Noord Brabant,which donot converge,all the other regions ‘weakly’convergeto the group’s average (Table 3).The fourth group contains 68regions (almost allGerman,French and Italian (North-Centre)andsome Belgian and Dutch)characterized by thelowest estimation of the GDP growth rate (97.8%),despite their highest initial GDP level (8893.9);thehighest specialization in the branches of the servicessector (1.16and 1.07,respectively)and in machinery(1.01);the lowest specialization in agriculture,foodand beverages,textile and construction activities.These regions present the highest percentage of‘strong’convergence to the group’s average (morethan 60%,Table 4).Table 5presents the summary of convergence testsresults (percentage are in parentheses).The main outcome of this study is the evidence of strong convergence among the wealthiest regions of the European Union.Besides,it appears that there is a trend of weak convergence also among the remaining groups (percentages are considerably over 80%).Therefore,Baumol’s hypothesis of conver-gence within clubs showing similar characteristics is confirmed.V.Conclusion This study tests the ‘club convergence’hypothesis applying the stochastic notion of convergence to groups of European regions.In order to avoid the group selection bias problem,the innovative regression tree technique was applied to selectTable 3.Convergence test results of group 3Regions group 3ADF statistics KPSS statistics l ¼4Regions group 3ADF statistics KPSS statistics l ¼4LimburgÀ1.680.116Abruzzo 2.600.153ÃÃHainautÀ0.800.091Friesland À3.620.142NamurÀ1.840.094Noord-Brabant À2.590.148ÃÃNiederbayernÀ1.270.104Limburg (NL)À2.980.128OberpfalzÀ1.400.097Yorkshire and The Humber À1.610.085TrierÀ1.430.119East Midlands À2.190.091Comunidad Foral de NavarraÀ2.750.071West Midlands À1.920.080La RiojaÀ1.770.119East Anglia À2.150.134BalearesÀ2.960.108South West À1.950.091LimousinÀ2.410.083Scotland 2.220.093Languedoc-RoussillonÀ3.390.105Notes :ÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146).Table 2.Convergence test results of group 2Regions group 2ADF statistics KPSS statistics l ¼4Regions group 2ADF statistics KPSS statistics l ¼4Vlaams BrabantÀ1.220.100Murcia À1.530.124Brabant WallonÀ1.600.111Molise À2.170.078Luxembourg1.190.122Campania À3.220.078Lu neburgÀ0.280.114Puglia À2.820.115GaliciaÀ1.690.140Basilicata À2.100.140Principado de AsturiasÀ1.550.146ÃÃCalabria À5.07ÃÃÃ0.106CantabriaÀ1.080.133Sicilia À2.980.142Aragon À1.580.142Sardegna À2.210.141Comunidad de MadridÀ1.380.091Lisboa e Vale do Tejo À2.620.141Castilla y Leon À2.580.138Wales À2.120.098Cataluna À1.550.097Northern Ireland À1.790.120Comunidad Valenciana À1.420.105Notes :ÃÃand ÃÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146)and 1%level (0.216)respectively,using unit root critical values at the 5%(À3.645)and 1%(À4.469).572R.De Siano and M.D’Uvaendogenously the most important variables inachieving the best identification of groups.Testson stochastic convergence in each group identifiedby CART evidence strong convergence among thewealthiest regions of the European Union and atrend of weak convergence among the remaininggroups.References Azariadis,C.and Drazen,A.(1990)Threshold externalities in economic development,Quarterly Journal of Economics ,105,501–26.Baumol,W.J.(1986)Productivity growth,convergence and welfare:what the long run data show,AmericanEconomic Review ,76,1072–85.Table 5.Convergence test resultsGroupsNo.of regions Strong convergence Weak convergence No convergence 1112(18,19)9(81,81)2231(4.35)21(91.3)1(4.35)32119(90.48)2(9.52)46843(63.23)20(29.41)4(5.88)Table 4.Convergence test results of group 4Regions group 4ADF statistics KPSS statistics l ¼4Regions group 4ADF statistics KPSS statistics l ¼4RegionBruxelles capitale À2.650.112Haute-Normandie À4.11ÃÃ0.102AntwerpenÀ2.770.102Centre (FR)À5.13ÃÃÃ0.099Oost-VlaanderenÀ3.150.078Basse-Normandie À3.86ÃÃ0.101West-VlaanderenÀ3.030.097Bourgogne À5.03ÃÃÃ0.113Licge À3.060.089Nord-Pas-de-Calais À4.37ÃÃ0.130StuttgartÀ4.22ÃÃ0.123Lorraine À4.41ÃÃ0.139KarlsruheÀ4.51ÃÃÃ0.088Alsace À4.13ÃÃ0.094FreiburgÀ5.11ÃÃÃ0.092Franche-Comte À5.20ÃÃÃ0.145Tu bingenÀ4.94ÃÃÃ0.104Pays de la Loire À4.34ÃÃ0.116OberbayernÀ4.17ÃÃ0.094Bretagne À4.41ÃÃ0.124MittelfrankenÀ3.79ÃÃ0.089Poitou-Charentes À4.74ÃÃÃ0.102UnterfrankenÀ0.420.140Aquitaine À3.290.104SchwabenÀ4.11ÃÃ0.084Midi-Pyre ne es À5.48ÃÃÃ0.103BremenÀ3.76ÃÃ0.121Rho ne-Alpes À4.93ÃÃÃ0.104HamburgÀ3.350.097Auvergne À4.43ÃÃ0.135DarmstadtÀ3.150.125Provence-Alpes-Co te d’Azur À5.10ÃÃÃ0.109GießenÀ3.020.088Corse À2.560.166ÃÃKasselÀ3.0120.094Piemonte À3.460.112BraunschweigÀ3.82ÃÃ0.116Valle d’Aosta À4.36ÃÃ0.080HannoverÀ3.96ÃÃ0.083Liguria À4.26ÃÃ0.117Weser-EmsÀ3.400.084Lombardia À4.04ÃÃ0.101Du sseldorfÀ3.94ÃÃ0.097Trentino-Alto Adige À3.84ÃÃ0.109Ko lnÀ3.96ÃÃ0.084Veneto À3.68ÃÃ0.106Mu nsterÀ4.04ÃÃ0.087Friuli-Venezia Giulia À4.20ÃÃ0.116DetmoldÀ4.06ÃÃ0.099Emilia-Romagna À3.120.136ArnsbergÀ3.98ÃÃ0.096Toscana À3.190.121KoblenzÀ3.88ÃÃ0.113Umbria À3.560.146ÃÃRheinhessen-PfalzÀ4.18ÃÃ0.107Marche À3.250.136SaarlandÀ4.35ÃÃ0.090Lazio À3.96ÃÃ0.098Schleswig-HolsteinÀ3.360.089Drenthe À1.850.134Pais VascoÀ3.630.159ÃÃUtrecht À2.400.155ÃÃI le de FranceÀ4.61ÃÃÃ0.110Noord-Holland À1.990.137Champagne ArdenneÀ3.79ÃÃ0.157ÃÃZuid-Holland À2.200.138Picardie À4.44ÃÃ0.142Zeeland À3.78ÃÃ0.093Notes :ÃÃand ÃÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146)and 1%level (0.216)respectively,using unit root critical values at the 5%(À3.645)and 1%(‘4.469).Club convergence in European regions573Ben-David, D.(1994)Convergence clubs and diverging economies,unpublished manuscript,University of Houston,Ben-Gurion University and CEPR. Bernard, A. B.and Durlauf,S.N.(1996)Interpreting tests of the convergence hypothesis,Journal of Econometrics,71,161–73.Breiman,L.,Friedman,J.L.,Olshen,R.A.and Stone,C.J.,(1984)Classification and Regression Trees,Wadsworth,Belmont,CA.Bru lhart,M.(1998)Economic geography,industrial location and trade:the evidence,World Economy,21, 775–801.Carlino,G.A.and Mills,L.O.(1993)Are US regional incomes converging?A time series analysis,Journal of Monetary Economics,32,335–46.De Siano,R.and D’Uva,M.(2004)Specializzazione e crescita:un’applicazione alle regioni dell’Unione Monetaria Europea,Rivista Internazionale di Scienze Sociali,4,381–98.De Siano,R.and D’Uva,M.(2005)Regional growth in Europe:an analysis through CART methodology, Studi Economici,87,115–28.Dickey,D.A.and Fuller,W.A.(1979)Distribution of the estimators for autoregressive time series with a unit root,Journal of The American Statistical Association, 74,427–31.Durlauf,S.N.and Johnson,P.A.(1995)Multiple regimes and cross-country growth behaviour,Journal of Applied Econometrics,10,365–84.Feve,P.and Le Pen,Y.(2000)On modelling convergence clubs,Applied Economic Letters,7,311–14.Helg,R.,Manasse,P.,Monacelli,T.and Rovelli,R.(1995) How much(a)symmetry in Europe?Evidence from industrial sectors,European Economic Review,39, 1017–41.Jacobs,J.(1969)The Economy of Cities,Jonathen Cape, London.Kwiatkowski, D.,Phillips,P. C. B.,Schmidt,P.and Shin,Y.(1992)Testing the null hypothesis of stationarity against the alternative of a unit root:how sure are we that economic time series have a unit root?,Journal of Econometrics,54, 159–78.Lucas,R. E.(1988)On the mechanics of economic development,Journal of Monetary Economics,22, 3–42.Marshall,A.(1980)Principles of Economics,Macmillan, London.Ottaviano,I.and Puga,D.(1998)Agglomeration in the global economy:a survey of the‘new economic geography’,World Economy,21,707–31.Qing,L.(1999)Convergence clubs:some further evidence, Review of International Economics,7,59–67. Romer,P.M.(1986)Increasing returns and long run growth,Journal of Political Economy,94, 1002–37.Su,J.J.(2003)Convergence clubs among15OECD countries,Applied Economic Letters,10,113–18.574R.De Siano and M.D’Uva。
PRESENT An Ultra-Lightweight Block Cipher

mode (say) we get a stream cipher. But second, and perhaps more importantly, the art of block cipher design seems to be a little better understood than that of stream ciphers. For instance, while there is a rich theory under-pinning the use of linear feedback shift registers [29] it is not easy to combine these building blocks to give a secure proposal. We suspect that a carefully designed block cipher could be a less risky undertaking than a newly designed stream cipher. Thus, we feel that a block cipher that requires similar hardware resources as a compact stream cipher could be of considerable interest.
PRESENT: An Ultra-Lightweight Block Cipher
A. Bogdanov1, L.R. Knudsen2, G. Leander1, C. Paar1, A. Poschmann1, M.J.B. Robshaw3, Y. Seurin3, and C. Vikkelsoe2
The Versatile Method to Control the Orientation of

J. Chem. Chem. Eng. 6 (2012) 769-773The Versatile Method to Control the Orientation of BN Particles in Thermoset MatrixKarnthidaporn Wattanakul*a nd Sittisak SatasitCollege of Industrial Technology, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand Received: June 30, 2012 / Accepted: July 27, 2012 / Published: September 25, 2012.Abstract: A new thermally conductive thermoset composite has been developed. A hybrid organic-inorganic material composed of an epoxy resin crosslinked with a flexible diamine hardener, and a BN, was prepared by incorporating epoxy structure units covalently into a BN via the sol-gel approach. The precursor was obtained by the reaction of DGEBA (diglycidyl ether of bisphenol A) with TEOS (tetraethyl orthosilicate). The precursor was then hydrolyzed and co-condensated with tetraethyl orthosilicate which is covalently bond with the hydroxyl groups on the BN surface at room temperature to yield epoxy-BN hybrid sol-gel material. FTIR spectroscopy confirmed the formation of organic and inorganic network. The thermal conductivity as measured by thermal conductive analyzer showed an increase up to 0.4048 W/m·K, for a mixture containing 0.4 wt% of BN fillers in the epoxy matrix. Moreover, the optimum conditions for surface modification of BN particle were also investigated.Key words: BN filled-epoxy composite, particle orientation, chemical modification of epoxy, sol-gel method, inorganic-organic hybrid.1. IntroductionWith the increasing needs for heat dissipation from microelectronic devices, thermal management has become an increasingly important element in the design of electronic products. It has been observed that a reduction in the operation temperature of a device can correspond to an exponential increase in the reliability and life expectancy of the device [1, 2]. In addition, the device speeds continue to increase, leading to the generation of more heat within the smaller chip volume. These factors limit high power dissipation or high “clock” frequency of semiconductor chips because of the low thermal conductivity of presently available encapsulants. Epoxy resin systems are used for encapsulating a variety of electronic components because of their high thermal stability, high moisture resistance, and low*Corresponding author: Karnthidaporn Wattanakul, Ph.D., research fields: thermal conductive polymer composite, thermal insulator polymer composite, electrical conductive polymer composite.E-mail:**********************************.cost. Unfortunately, the cured epoxy resin has poor thermal properties, which are the high CTE (coefficient of thermal expansion) (90 × 10-6o C-1) and low thermal conductivity (0.2 W/m·K) [3]. Therefore, the conductive filler loading greatly exceed percolation threshold concentrations, and approach or even surpass critical pigment volume concentrations of 50%-70% in volume [4, 5]. At the percolation threshold concentration, an interconnecting path of conductive particles forms and extends throughout the entire sample thickness, thus enabling electrons to percolate. However, many more percolation pathways form for enhanced conductivity, but the materials become to be brittle because the material has insufficient carrier polymer and behaves like a solid. Consequently, the filler loading of the composites should be at levels well beyond these percolation levels for conductivity but slightly below the critical pigment volume concentration to achieve adequatestrength.All Rights Reserved.The Versatile Method to Control the Orientation of BN Particles in Thermoset Matrix 770The sol-gel process involving a change of the distribution of small particles (sol) into the frame gauze in three dimensions has a solid (gel) and is also an important process that can be applied preparation of the composite material of inorganic and organic substance. The reaction conditions are mild and the temperature is not high [6].Thus, this research is study and application of sol-gel process to control the distribution arrangement of the particles, boron nitride, to enhance thermal conductivity and improve mechanical properties of epoxy. High performance thermal conductive thermoset composites are fabricated via sol-gel method which is a versatile approach to control particle aggregation in polymer matrix. The incorporation of BN particles can influence the thermal conductivity of composite. The effects of chemical bonding between aggregation and thermal conductivity of the BN-epoxy composite are investigated to optimize the conditions that will give composite having both good thermal conductivity and mechanical properties. The microstructures of particles in gel and also in composite are observed by scanning electron microscopy. The improvement in thermal conductivity of composites is measured by thermal conductivity analyzer.2. Experimental Section2.1 ChemicalsEpoxy resin (diglycidyl ether of bisphenol A; DGEBA (YD-128)), W eq = 196, and curing agent (TH 7301) were generously provided by Aditya Birla Chemicals (Thailand) Ltd.. TEOS (tetraethyl orthosilicate) as a coupling agent between epoxy resin and BN and precursor for sol-gel preparation was purchased from Fluka. BN particles were purchased from Saint-Gobain Ceramics. Anhydrous ethanol (purity 99.9%) and tetrahydrofuran (THF reagent grade) were supplied by Aldrich, USA. Concentrated HNO3 (nitric acid) and liquid ammonium were obtained from Fluka, USA. 2.2 Preparation of TEOS-BNThe TEOS coating on BN (boron nitride) was achieved via the sol-gel approach. The BN slurry was prepared by adding an hydrous ethanol to obtain 5 wt% solid loading and then ultra-sonicated to break down agglomerates. A 20 wt% of TEOS ethanol solution was carefully added to the suspension step by step. The appropriate pH value of the suspension was adjusted using ammonia (30%; Fluka) or nitrate (65%; MERCK) to pH = 11. Afterward, the suspension was stirred at 50-75 o C for 2 h to control the thickness of the coating layer through the hydrolysis and condensation of TEOS on the surface of BN particle as shown in Fig. 1. Core-shell composite coated powders were then collected by filtration, washed with anhydrous ethanol and completely dried in an oven at 80 o C.2.3 Preparation of TEOS-BN/Epoxy CompositesThe modified epoxy resin was synthesized as follows: 4 g TEOS (equivalent weight 247 g) was added to 10 g epoxy resin (equivalent weight 196 g) at 60 o C, and was then stirred for 4 h. TEOS reacted with epoxy to form TEOS-epoxy and the final solution was stirred mechanically at room temperature for 20 min. The adequate amount of curing agent was added to the mixture and then homogeneously stirred using mechanical stirrer. The products were cast into petri-dishes to form gel resulting in the formation of organic network at room temperature as shown in Fig. 2. The wet gels were aged at room temperature for few minutes. Consequently, the mixture was cured and dried at 70 C for 2 h.2.4 CharacterizationFT-IR (Fourier-transform infrared) spectroscope (Nicolet, Magna IR 560) was used to study the surface modification of BN. The modified BN was dried at 100 o C for 3 h and then mixed with KBr powder to obtain the KBr pellet.The thermal conductivity was evaluated by Hot DiskAll Rights Reserved.The Versatile Method to Control the Orientation of BN Particles in Thermoset Matrix771Fig. 1 Formation of inorganic network by the sol-gel reaction.Fig. 2 Interphase bonding by the coupling reaction and consequently formation of organic network by the sol-gel reaction.Thermal Analyzer (TPS 2500) equipped with a 2.011 mm diameter of Kapton sensor disk. Samples were cut into 3 mm × 3 mm square with the thickness of 3 mm. The values of the thermal conductivity (k) were calculated from the following equation:k = αρC p(1) where, α is thermal diffusivity;ρis density;C p is specific heat capacity.3. Results and Discussion3.1 Preparation and Characterization of Modified BN ParticlesThe preparation route of TEOS-BN was shown in Fig. 1, in which the hydroxyl group on the BN surface was reacted with TEOS molecules. The first and simplest qualitative test to determine whether the functionalization procedure has been successfully involves checking the dispersion of the product in epoxy resin. It is found that TEOS-BN indeed exhibits good dispersion in epoxy resin as illustrated in Fig. 3. The result shows two vials containing equal volume of epoxy resin and equal masses of unmodified BN (vial a) and TEOS-BN (vial b). Clearly, unmodified BN has low stability and poor dispersion in epoxy resin, however, TEOS-BN forms a homogeneous suspension and it remains stable for a period of at least a month.FTIR spectroscopic analysis provides additional evidence that the BN surface modification proceeded according to the route shown in Figs. 1 and 2, respectively. Fig. 4 shows the FTIR spectra of unmodified BN and TEOS-BN. The FTIR spectrum of TEOS-BN shows the peak of Si-O at 1,073 cm-1. According to relevant literatures [7-9], the board absorption peak for Si-O-Si asymmetric stretching varies in the range of 1,200-1,000 cm-1 depending upon the density of silica. The FTIR results verify that the TEOS molecules are covalently attached to the surface of BN.Fig. 3 Effect of surface modification on the dispersion of 0.1 %wt BN in epoxy resin: (a) unmodified BN and (b) TEOS modified BN.Fig. 4 The FTIR spectra of unmodified BN and TEOS modified BN.All Rights Reserved.The Versatile Method to Control the Orientation of BN Particles in Thermoset Matrix 7723.2 Thermal Conductivity of Epoxy CompositesAs mentioned at the beginning of this paper, the goal of making polymer/BN composites is to develop lightweight highly thermal conductive materials using mild condition. The results are shown in Fig. 5.For the neat resin, the thermal conductivity is approximately 0.18 W/m·K at room temperature whichis same as Wang et al. [10]. The dispersion of 0.4 wt% sonicated BN into epoxy resin did slightly increase the thermal conductivity. Furthermore, the thermal conductivity of TEOS-BN/epoxy composite and TEOS-BN/TEOS-epoxy composite increased about 60% in comparison to the neat resin. This result shows that the conductive network can be easily formed because the reaction between TEOS molecules and epoxy resin helps to induce the appropriate gel formation resulting to the improvement in filler orientation. Therefore, TEOS modified BN to form sol-gel network considerably improved the BN dispersion in the composite and also retain the thermal conductivity. The improvement of thermal conductivity in the modified BN composites may stem from the improved percolation because of better dispersion and conductive network formation.Fig. 6 shows that the fracture surface of TEOS-BN/TEOS-epoxy composite is more roughness than unmodified BN/epoxy composite. There were no craters on the fractured surface. According to Spanoudakis et al. [11], in the case of good bondingFig. 5 Thermal conductivity of 0.4 wt% BN/epoxy composites.Fig. 6 SEM micrograph of fracture surface: (a) BN/epoxy composite and (b) TEOS-BN/TEOS-epoxy composite.between fillers and matrix in the composite, maximum stress will be in the matrix. The improvement in an interfacial bonding between fillers and polymer matrix can influence on the reduction of phonon scattering leading to an increase in thermal conductivity of composite [12-14].4. ConclusionsThe TEOS modification of BN with epoxy was successfully carried out via sol-gel method. FTIR analysis indicated that TEOS molecule was successfully covalently grafted on the surface of the BN. The TEOS modified BN exhibited relatively good dispersion and remained stable in epoxy resin. Therefore, the modified BN was found to be effectively improved percolation, which led to an obvious improvement of thermal conductivity. Moreover, the appropriate conductive network can be obtained by increasing the gel formation from the reaction between TEOS molecules and epoxy resin.All Rights Reserved.The Versatile Method to Control the Orientation of BN Particles in Thermoset Matrix 773AcknowledgementsThis research was financially supported by the TRF (Thailand Research Fund), OHEC (Office of the Higher Education Commission), STRI (Science and Technology Research Institute) and KMUTNB (King Mongkut’s University of Technology North Bangkok). The Thermal Conductive Analyzer was kindly supported by the MTEC (National Metal and Materials Technology Center).References[1]Kapur, P.; McVitie, J. P.; Saraswat, K. C. Technologyand Reliability Constrained Future Copper Interconnects-Part I: Resistance Modeling. IEEETransactions on Electron Devices2002,49, 590-597.[2]Obreja, V. V. N. In Advance in the Assembling andPackaging of Supercapacitor Modules for HigherPerformance, Proceeding of the 2nd ElectronicsSystem-Intergration Technology Conference, 2008, pp771-774.[3]Kim, W.; Bae, J. W.; Choi, I. D.; Kim, Y. S. ThermallyConductive EMD (Epoxy Molding Compound) forMicroelectronic Encapsulation. Polym. Eng. Sci.1999,39,756-766.[4]Mighri, F.; Huneault, M. A.; Champagne, M. F.Conductive Polymer Blends for Injection-Molded BipolarPlates. Polym. Eng. Sci.2004,44, 1755-1765.[5]Blunk, R.; Zhong, F.; Owen, J. Automotive CompositeFuel Cell Bipolar Plates: Hydrogen Permeation Concerns.J. Power Source2006,159, 533-542. [6]Wang, S. F.; Hsu, Y. F.; Yang, T.; Chang, C. M.; Yuhen,Y. C.; Huang, C.Y.; et al. Mater. Sci. Eng.2005,395,148-152.[7]Wang, J.; Deng, Z. S.; Shen, J.; Chen, L. Y. Silylation ofPolydiethoxysiloxane Derived Silica Aerogels. J.Non-Crystalline Solid2000,271, 100-105.[8]Farhadyar, N.; Rahimi, A.; Langroudi, A. E. Preparationand Characterization of Aromatic Amice CuredEpoxy-Silica Hybrid Inorganic-Organic Coating via inSitu Sol-Gel Process. Iranian Polym. J.2005,14,155-162.[9]Singh, L. P.; Agarwal, S. K.; Bhattacharyya, S. K.;Sharma, U.; Ahalawat, S. Preparation of SilicaNanoparticles and Its Benefitcial Role in CementitiousMaterials. Nanomater. Nanotechnol.2011,1, 44-51. [10]Wang, S.; Liang, R.; Wang, B.; Zhang, C. Dispersion andThermal Conductivity of Carbon Nanotube Composites.Carbon2009,47, 53-57.[11]Spanoudakis, J.; Young, R. J. Crack Propagation in GlassParticle-Filled Epoxy Resin. J. Mater. Sci.1984,19,473-486.[12] Hong, J. P.; Yoon, S. W.; Hwang, T. S.; Lee, Y. K.; Won,S. H.; Nam, J. D. Interphase Control of BoronNitride/Epoxy Composites for High Thermal Conductivity. Korea-Australia Rheo. J.2010,22,259-264.[13] Tian, W.; Yang, R. Phonon Transport and ThermalConductivity Percolation in Random NanoparticleComposites. Tech. Science 2008,24, 123-141.[14] Wattanakul, K.; Manuspiya, H.; Yanumet, N. EffectiveSurface Treatments for Enhancing the ThermalConductivity of BN-Filled Epoxy Composite. J. Appl.Polym. Sci.2011,119, 3234-3243.All Rights Reserved.。
Perfect nizk with adaptive soundness

Perfect NIZK with Adaptive SoundnessMasayuki Abe1Serge Fehr2November17,20061Information Sharing Platform Laboratories,NTT Corporation,Japanabe.masayuki@lab.ntt.co.jp2CWI Amsterdam,The Netherlandsfehr@cwi.nlAbstractThe notion of non-interactive zero-knowledge(NIZK)is of fundamental importance in cryptography.Despite the vast attention the concept of NIZK has attracted since its intro-duction,one question has remained very resistant:Is it possible to construct NIZK schemesfor any NP-language with statistical or even perfect ZK?Groth,Ostrovsky and Sahai recentlypositively answers to the question by presenting a couple of elegant constructions.However,their schemes pose a limitation on the length of the proof statement to achieve adaptivesoundness against dishonest provers who may choose the target statement depending on thecommon reference string(CRS).In this work,wefirst present a very simple and efficient adaptively-sound perfect NIZK argument system for any NP-language.Besides being thefirst adaptively-sound statisticalNIZK argument for all NP that does not pose any restriction on the statements to be proven,it enjoys a number of additional desirable properties:it allows to re-use the CRS,it canhandle arithmetic circuits,and the CRS can be set-up very efficiently without the need foran honest party.We then show an application of our techniques in constructing efficientNIZK schemes for proving arithmetic relations among committed secrets,whereas previousmethods required expensive generic NP-reductions.The security of the proposed schemes is based on a strong non-standard assumption, an extended version of the so-called Knowledge-of-Exponent Assumption(KEA)over bilin-ear groups.We give some justification for using such an assumption by showing that thecommonly-used approach for proving NIZK arguments sound does not allow for adaptively-sound statistical NIZK arguments(unless NP⊂P/poly).Furthermore,we show that theassumption used in our construction holds with respect to generic adversaries that do notexploit the specific representation of the group elements.We also discuss how to avoid thenon-standard assumption in a pre-processing model.1Introduction1.1BackgroundNon-Interactive Zero-Knowledge.The notion of non-interactive zero-knowledge(NIZK) captures the problem of proving that a statement is true by just sending one message and without revealing any additional information besides the validity of the statement,provided that a common reference string(CRS)has been properly set up.Since its introduction by Blum,Feldman and Micali in1988[6],NIZK has been a fundamental cryptographic primitive used throughout modern cryptography in essential ways.There is a considerable amount of literature dedicated to NIZK,in particular to the study of which languages allow for whatflavor of NIZK proof.As in case of interactive ZK it is well known that there cannot be statistical NIZK proofs(i.e.,both ZK and soundness are unconditional) for NP-complete languages unless the polynomial hierarchy collapses[22,2,30].Hence,when considering general NP-languages,this only leaves room for a NIZK proof with computational ZK or computational soundness(where the proof is also called an argument),or both.However, in contrast to interactive ZK where it has long been known that bothflavors can exist[8,7,23], all proposed NIZK proofs or arguments for general NP-languages have computational ZK(see e.g.[6,20,5,27,15]).Hence the construction of a statistically NIZK(NISZK)argument has remained an open problem(until very recently,see below).The question of the existence of NISZK arguments is in particular interesting in combination with a result by De Santis et al.[15],where they observe that for a strong notion of NIZK,called same-string NIZK,soundness can only be computational when considering NP-complete languages(assuming that one-way functions exist).Statistical NIZK Arguments.Recently,Groth,Ostrovsky and Sahai proposed an elegantconstruction for a perfect NIZK(NIPZK)argument for circuit-SAT[24]by using bilinear groups. This shows NIZK can come with perfect ZK for any NP-language.However,the scheme only provides security against a non-adaptive dishonest prover who chooses the target instance x∗∈L (for which it wants to fake a proof)independent of the CRS.In an application though,it is likely that the adversaryfirst sees the CRS and then chooses the false statement on which he wants to ing a counting argument,they argue that under some strengthened assumption their scheme is secure against an adaptive dishonest prover if the size of the circuit to be proven is a-priori limited.However,the bound on the size of the circuit is so restrictive that the circuit must be smaller than sublinear in the bit size of the CRS(as discussed in Section1.3).Groth et al.also proposed a perfect NIZK argument for SAT which is provably secure in Canetti’s Universal Composability(UC)framework[9].However,besides being much less efficient than theirfirst construction,the scheme still does not guarantee unrestricted security against an adaptive dishonest prover who chooses the target instance x∗∈L depending on the CRS.For instance,the UC security does not exclude the possibility that a dishonest prover comes up with an accepting proof for the statement“the CRS is invalid or S is true”for an arbitrary false statement S.Since in a real-life execution the CRS is assumed to be valid,this is a convincing argument of the false statement S.Accordingly,the existence of an unrestricted statistical or perfect NIZK argument,which does not pose any restriction on the instances to be proven,is still an open problem.The Knowledge-of-Exponent rmally,the Knowledge-of-Exponent As-sumption(kea)says that for certain groups,given a pair g andˆg=g x of group elements with unknown discrete-log x,the only way to efficiently come up with another pair A andˆA such that ˆA=A x(for the same x)is by raising g andˆg to some power a:A=g a andˆA=ˆg a.kea wasfirst introduced and used by Damg˚ard in1991[12],and later,together with an extended version (kea2),by Hada and Tanaka[25].Recently,Bellare and Palacio[4]showed that kea2does not hold,and proposed a new extended version called kea3in order to save Hada and Tanaka’s results.kea3,which we call xkea for eXtended kea,says that given two pairs(g,ˆg)and(h,ˆh) with the same unknown discrete-log x,the only way to efficiently come up with another pair A andˆA such thatˆA=A x is by computing A=g a hαandˆA=ˆg aˆhα.Assumptions like kea and xkea are widely criticized in particular because they do not appear to be“efficiently falsifiable”, as Naor put it[28],though Bellare and Palacio showed that this is not necessarily the case.1.2Our ResultBased on xkea over bilinear groups,we construct an adaptively-sound NIPZK argument for circuit-SAT without any restrictions on the instances to be proven.Besides being thefirst un-restricted adaptively-sound NISZK argument for any NP-language,the proposed scheme enjoys a number of additional desirable properties:It is same-string NIZK,which allows to re-use the CRS.It is very efficient:the CRS essentially consists of a few group elements,and a proof consists of a few group elements per multiplication gate;this is comparable(if not better)to the first scheme by Groth et al.,which is the most efficient general-purpose NIZK scheme known up to date(see the comparison in[24]).Furthermore,our scheme can also be applied to arithmetic circuits over Z q for a large prime q whereas known schemes are tailored to binary circuits;this often allows a more compact representation of the statement to be proven.Finally,the CRS does not need to be set-up by a trusted party.It can efficiently be set-up jointly by the prover and the verifier.Furthermore,it can even be provided solely from a(possibly dishonest)verifier without any correctness proof if we view the proof system as a zap[19]rather than a NIZK.We are not aware of any other NIZK arguments or proofs that enjoy all these desirable properties.Based on the techniques developed for the perfect NIZK argument for SAT,we also construct an efficient NIPZK argument for arithmetic relations among committed secrets over Z q with large prime q.To the best of our knowledge,all known schemes only work for secrets from restricted domains such as Z[2]and have to rely on generic inefficient reductions to NP-complete problems to handle larger secrets.Our approach in particular allows for additive and multiplicative relations among secrets committed to by standard Pedersen commitments.We give two justifications for using such a strong non-standard assumption like xkea.First, we give some indication that a non-standard assumption is unavoidable for adaptively-sound NISZK arguments.We prove that using the common approach for proving computational soundness,which has been used for all NIZK arguments(we are aware of),a non-standard assumption is necessary unless NP⊂P/poly(i.e.unless any NP-problem can be solved by an efficient non-uniform algorithm).And,second,we prove that kea and xkea hold in the generic group model(even over bilinear groups).This suggests that if there exists an algorithm that breaks,say,kea in a certain group,then this algorithm must use the specific representation of the elements of that group,and it is likely to fail when some other group(representation)is used.A similar result was independently developed by Dent[18]for non-bilinear groups.Finally,we discuss how to avoid xkea in our NIZK arguments by allowing a pre-processing phase.Our scheme allows very efficient pre-processing where the prover only need to make random commitments and prove its knowledge about the witness by using efficient off-the-shelf zero-knoweldge schemes.1.3Related WorkIn order to make it easier for the reader to position our results,we would like to give a brief discussion about recently proposed NIPZK arguments.In[24]Groth et al.presented two schemes for proving circuit satisfiability,where thefirst one comes in twoflavors.Let us name the resulting three schemes by the non-adaptive,the adaptive and the UC GOS scheme.These are thefirst(and so far only)NISZK arguments proposed in the literature.The non-adaptive GOS scheme is admitted by the authors to be not adaptively sound.The adaptive GOS scheme is adaptively sound,but it only allows for circuits that are limited in size,and the underlying computational assumption is somewhat non-standard in that it requires that some problem can only be solved with“sub-negligible”probability,like2−ǫκǫlogκnegl(κ)whereκis the bit size of the problem instance.The more one relaxes the bound on the size of the circuits,the strongerthe underlying assumption gets in terms of the assumed bound on the success probability of solving the problem;but in any case the size of the circuits are doomed to be sub-linear in the size of the CRS.Concerning the UC GOS scheme,wefirst would like to point out that it is of theoretical interest,but it is very inefficient(though poly-time).Furthermore,it has some tricky weak soundness property in that if a dishonest prover should succeed in proving a false statement, then the statement cannot be distinguished from a true one.It is therefore claimed in[24]that the scheme“achieves a weaker,but sufficient,form of adaptive security.”This is true but only if some care is taken with the kind of statements that the(dishonest)prover is allowed to prove; in particular,soundness is only guaranteed if the statement to be proven does not incorporate the CRS.Indeed,the same example that the authors use to reason that theirfirst scheme is not adaptively sound can also be applied to the UC secure scheme:Consider a dishonest prover that comes up with an accepting proof for the statement“the CRS is invalid”,or for a statement like“the CRS is invalid or S is true”where S is an arbitrary false statement.In real-life, where the CRS is guaranteed to be correct,this convinces the verifier of the truth of the false statement S.However,such a prover is not ruled out by the UC security:the simulator given in[24]does generate an invalid CRS so that the statement in fact becomes true;and thus the proof can obviously be simulated in the ideal-world(when given a corresponding witness,which the simulator has in case of the UC GOS scheme).We stress that this is not aflaw in the UC GOS scheme but it is the UC security definition that does not provide any security guarantees for statements that incorporate the CRS,essentially because in the ideal-life model there is no (guaranteed-to-be-correct)CRS.1In conclusion,UC NIZK security provides good enough security under the condition that the statements to be proven do not incorporate the CRS.This is automatically guaranteed in a UC setting,where the statements to be proven must make sense in the ideal-world model,but not necessarily in other settings.2Preliminaries2.1NotationWe consider uniform probabilistic algorithms(i.e.Turing machines)which take as input(the unary encoding of)a security parameterκ∈N and possibly other inputs and run in deterministic poly-time inκ.We thus always implicitly require the size of the input to be bounded by some polynomial inκ.Adversarial behavior is modeled by non-uniform poly-time probabilistic algorithms,i.e.,by algorithms which together with the security parameterκalso get some(poly-size)auxiliary input order to simplify notation,we usually leave the dependency onκ(and on auxκ)implicit.By y←A(x),we mean that algorithm A is executed(with a randomly sampled random tape)on input x(and the security parameterκand,in the non-uniform case,auxκ) and the output is assigned to y.We may also denote it as y←A(x;r)when the randomness r is to be explicitly noted.Similarly,for anyfinite set S,we use the notation y←S to denote that y is sampled uniformly from S,and y←x means that the value x is assigned to y.For two algorithms A and B,we write B◦A for the composed execution of A and B,where A’s output is given to B as input.Similarly,A B denotes the joint execution A and B on the same input and the same random tape,and we write(x;y)←(A B)(w)to express that in the joint execution on input w(and the same random tape)A’s output is assigned to x and B’s to y.Furthermore,P y=A(x) denotes the probability(taken over the uniformly distributed random tape)that A outputs y on input x,and we write P x←B:A(x)=y for the(average) probability that A outputs y on input x when x is output by B:P x←B:A(x)=y = x P y=A(x) P x=B .We also use natural self-explanatory extensions of this notion.An oracle algorithm A is an algorithm in the above sense connected to an oracle in that it can write on its own tape an input for the oracle and tell the oracle to execute,and then,in a single step,the oracle processes its input in a prescribed way,and writes its output to the tape. We write A O when we consider A to be connected to the particular oracle O.A valueν(κ)∈R,which depends on the security parameterκ,is called negligible,denoted by ν(κ)≤negl(κ)orν≤negl,if∀c>0∃κ◦∈N∀κ≥κ◦:ν(κ)<1/κc.Furthermore,ν(κ)∈R is called noticeable if∃c>0,κ◦∈N∀κ≥κ◦:ν(κ)≥1/κc.2.2DefinitionLet L⊆{0,1}∗be an NP-language.Definition1.Consider poly-time algorithms G,P and V of the following form:G takes the security parameterκ(implicitly treated hereafter)and outputs a common reference string(CRS)Σtogether with a trapdoorτ.P takes as input a CRSΣand an instance x∈L together with an NP-witness w and outputs a proofπ.V takes as input a CRSΣ,an instance x and a proof πand outputs1or0.The triple(G,P,V)is a statistical/perfect NIZK argument for L if the following properties hold.Completeness:For any x∈L with corresponding NP-witness wP (Σ,τ)←G,π←P(Σ,x,w):V(Σ,x,π)=0 ≤negl. Soundness:For any non-uniform poly-time adversary P∗P (Σ,τ)←G,(x∗,π∗)←P∗(Σ):x∗∈L∧V(Σ,x∗,π∗)=1 ≤negl.Statistical/Perfect Zero-Knowledge(ZK):There exists a poly-time simulator S such that for any x∈L with NP-witness w,and for(Σ,τ)←G,π←P(Σ,x,w)andπsim←S(Σ,τ,x), the joint distributions of(Σ,π)and(Σ,πsim)are statistically/perfectly close.Remark2.The notion of soundness we use here guarantees security against an adaptive at-tacker,which may choose the instance x∗depending on the CRS.We sometimes emphasize this issue by using the term adaptively-sound.Note that this is a strictly stronger notion than when the adversary must choose x∗independent of the CRS.Remark3.In the notion of ZK we use here,P and S use the same CRS string.In[15],this is called same-string ZK.In the context of statistical ZK,this notion is equivalent(and not only sufficient)to unbounded ZK,2which captures that the same CRS can be used an unboundednumber of times.This is obviously much more desirable compared to the original notion of NIZK, where every proof requires a fresh CRS.In[15],it is shown that there cannot be a same-string NIZK proof with statistical soundness for a NP-complete language unless there exist no one-way functions.This makes it even more interesting tofind out whether there exists a same-string NIZK argument with statistical security on at least one side,namely the ZK side.2.3Bilinear Groups and the Hardness AssumptionsWe use the standard setting of bilinear groups.Let BGG be a bilinear-group generator that(takes as input the security parameterκand)outputs(G,H,q,g,e)where G and H is a pair of groups of prime order q,g is a generator of G,and e is a non-degenerate bilinear map e:G×G→H, meaning that e(g a,g b)=e(g,g)ab for any a,b∈Z q and e(g,g)=1H.We assume the Discrete-Log Assumption,dla,that for a random h∈G it is hard to compute w∈Z q with h=g w.In some cases,we also assume the Diffie-Hellman Inversion Assumption, dhia,which states that,for a random h=g w∈G,it is hard to compute g1/w.Formally, these assumptions for a bilinear-group generator BGG are stated as follows.In order to simplify notation,we abbreviate the output(G,H,q,g,e)of BGG by pub(for“public parameters”).Assumption4(dla).For every non-uniform poly-time algorithm AP pub←BGG,h←G,w←A(pub,h):g w=h ≤negl.Assumption5(dhia).For every non-uniform poly-time algorithm AP pub←BGG,h←G,g1/w←A(pub,h):g w=h ≤negl.Furthermore,we assume xkea,a variant of the Knowledge-of-Exponent Assumption kea, (referred to as kea3respectively kea1in[4]).kea informally states that givenˆg=g x∈G with unknown discrete-log x,the only way to efficiently come up with a pair A,ˆA∈G such thatˆA=A x for the same x is by choosing some a∈Z q and computing A=g a andˆA=ˆg a. xkea states that givenˆg=g x∈G as well as another pair h andˆh=h x with the same unknown discrete-log x,the only way to efficiently come up with a pair A,ˆA such thatˆA=A x is by choosing a,α∈Z q and computing A=g a hαandˆA=ˆg aˆhα.Formally,kea and xkea are phrased by assuming that for every algorithm which outputs A andˆA as required,there exists an extractor which outputs a(andαin case of xkea)when given the same input and randomness.Assumption6(kea).For every non-uniform poly-time algorithm A there exists a non-uniform poly-time algorithm X A,the extractor,such thatP pub←BGG,x←Z q,(A,ˆA;a)←(A X A)(pub,g x):ˆA=A x∧A=g a ≤negl. Recall that(A,ˆA;a)←(A X A)(pub,g x)means that A and X A are executed on the same input (pub,g x)and the same random tape,and A outputs(A,ˆA)whereas X A outputs a. Assumption7(xkea).For every non-uniform poly-time algorithm A there exists a non-uniform poly-time algorithm X A,the extractor,such that:ˆA=A x∧A=g a hα ≤negl.P pub←BGG,x←Z q,h←G,(A,ˆA;a,α)←(A X A)(pub,g x,h,h x)It is well known that dla holds provably with respect to generic algorithms(see e.g.[32]), which operate on the group elements only by applying the group operations(multiplication and inversion),but do not make use of the specific representation of the group elements.It is not so hard to see that this result extends to groups G that come with a bilinear pairing e:G×G→H,i.e.,to generic algorithms that are additionally allowed to apply the pairing and the group operations in H.We prove in Section6that also kea and xkea hold with respect to generic algorithms.We would also like to point out that we only depend on xkea for“proof-technical”reasons: our perfect NIZK argument still appears to be secure even if xkea should turn out to be false (for the particular generator BGG used),but we cannot prove it anymore formally.This is in contrast to how kea and xkea are used in[25]respectively[4]for3-round ZK,where there seems to be no simulator anymore as soon as kea is false.3A Perfect NIZK Argument for SAT3.1Handling Multiplication GatesLet(G,H,q,g,e)be generated by BGG,as described in Section2.3above.Furthermore,let h=g w for a random w∈Z q which is unknown to anybody.Consider a prover who announces an arithmetic circuit over Z q and who wants to prove in NIZK that there is a satisfying input for it.Following a standard design principle,where the prover commits to every input value using Pedersen’s commitment scheme with“basis”g and h as well as to every intermediate value of the circuit when evaluating it on the considered input,the problem reduces to proving the consistency of the multiplication gates in NIZK(the addition gates come for free due to the homomorphic property of Pedersen’s commitment scheme).Concretely,though slightly informally,given commitments A=g a hα,B=g b hβand C= g c hγfor values a,b and c∈Z q,respectively,the prover needs to prove in NIZK that c=a·b. Note thate(A,B)=e(g a hα,g b hβ)=e(g,g)ab e(g,h)aβ+αb e(h,h)αβande(C,g)=e(g c hγ,g)=e(g,g)c e(g,h)γand hence,if indeed c=a·b,thene(A,B)/e(C,g)=e(g,h)aβ+αb−γe(h,h)αβ=e(g aβ+αb−γhαβ,h).(1) Say that,in order to prove that c=a·b,the prover announces P=g aβ+αb−γhαβand the verifier accepts if and only if P is satisfying in thate(A,B)/e(C,g)=e(P,h).Then,by the above observations it is immediate that an honest verifier accepts the correct proof of an honest prover.Also,it is quite obvious that a simulator which knows w can“enforce”c=a·b by“cheating”with the commitments,and thus perfectly simulate a satisfying P for the multiplication gate.Note that the simulator needs to know some opening of the commitments in order to simulate P;this though is good enough for our purpose.For completeness,though,we address this issue again in Section4and show a version which allows a full-fledged simulation. Finally,it appears to be hard to come up with a satisfying P unless one can indeed open A,B and C to a,b and c such that c=a·b.Concretely,the following holds.Lemma8.Given openings of A,B and C to a,b and c,respectively,with c=a·b,and given an opening of a satisfying P,one can efficiently compute w.Proof.Let P=gρh̟be the given opening of P.Then,inheriting the notation from above, e(A,B)/e(C,g)=e(g a hα,g b hβ)/e(g c hγ,g)=e(g,g)ab−c e(g,h)aβ+αb−γe(h,h)αβ.ande(A,B)/e(C,g)=e(P,h)=e(gρh̟,h)=e(g,h)ρe(h,h)̟are two different representations of the same element in H with respect to the“basis”e(g,g), e(g,h)=e(g,g)w,e(h,h)=e(g,g)w2.This allows to compute w by solving a quadratic equation in Z q.The need for an opening of P can be circumvented by basing security on dhia rather than dla as stated in the following lemma.Lemma9.Given openings of A,B and C to a,b and c,respectively,with c=a·b,and given a satisfying P,one can efficiently compute g1/w.Proof.For a satisfying P it holds thate(P,h)=e(A,B)/e(C,g)=e(g,g)ab−c e(g,h)aβ+bα−γe(h,h)αβand thus,when c=a·b as assumed,the following equalities follow one after the other.e(g,g)=e (P g−aβ−bα+γh−αβ)1/(ab−c),he(g1/w,g)=e (P g−aβ−bα+γh−αβ)1/(ab−c),gg1/w=(P g−aβ−bα+γh−αβ)1/(ab−c)It remains to argue that a(successful)prover can indeed open all the necessary commitments. This can be enforced as follows.Instead of committing to every value s by S=g s hσ,the prover has to commit to s by S=g s hσandˆS=ˆg sˆhσ,whereˆg=g x for a random x∈Z q andˆh=h x (with the same x).Note that the same randomnessσis used for computing S andˆS,such that ˆS=S x;this can be verified using the bilinear map:e(ˆS,g)=e(S,ˆg).xkea now guarantees that for every correct double commitment(S,ˆS)produced by the prover,he knows(respectively there exists an algorithm that outputs)s andσsuch that S=g s hσ.Based on the above observations,we construct and prove secure an adaptively-sound perfect NIZK argument for circuit-SAT in the next section.3.2The Perfect NIZK SchemeThe NIZK scheme for circuit-SAT is given in Figure1.Note that we assume an arithmetic circuit C over Z q(rather than a binary circuit),but of course it is standard to“emulate”a binary circuit by an arithmetic one.Theorem10.(G,P,V)from Fig.1is an adaptively-sound perfect NIZK argument for circuit-SAT,assuming xkea and dla.CRS Generator G`1κ´:G-1.(G,H,q,g,e)←BGG(1κ),w←Z q,ˆg←G,h←g w,ˆh←ˆg w,G-2.outputΣ←(G,H,q,g,h,ˆg,ˆh,e)andτ←w.Prover P`Σ,C,x=(x1,...,x n)´:pute commitments for every input value x i by X i=g x i hξi andˆX i=ˆg x iˆhξi.P-2.Inductively,for every multiplication gate in C for which the two input values a and b are committed upon(either directly or indirectly via the homomorphic property)by A=g a hαandˆA=ˆg aˆhαrespectively B=g b hβandˆB=ˆg bˆhβ,do the pute a(double)commitment C=g c hγandˆC=ˆg cˆhγfor the corresponding output value c=a·b,and compute the(double)commitment P=g aβ+αb−γhαβandˆP=ˆg aβ+αb−γˆhαβ.P-3.As proofπoutput all the commitments as well as the randomnessηfor the commitment Y=g C(x)hηfor the output value C(x)=1.Verifier V`Σ,C,π´:Output1(i.e.“accept”)if all of the following holds,otherwise output0.V-1.Every double commitment(S;ˆS)satisfies e(ˆS,g)=e(S,ˆg).V-2.Every multiplication gate in C,with associated(double)commitments(A,ˆA),(B,ˆB),(C,ˆC)and(P,ˆP) for the two input values,the output value and the“multiplication proof”,satisfies e(A,B)/e(C,g)= e(P,h).V-3.The commitment Y for the output value satisfies Y=g1hη.Figure1:Perfect NIZK argument for circuit-SATpleteness is straightforward using observation(1).Also,perfect ZK is easy to see. Indeed,the simulator S can run P with a default input for x,say o=(0,...,0),and then simply open the commitment Y for the output value y=C(o)(which is likely to be different from1) to1using the trapdoor w.Since Pedersen’s commitment scheme is perfectly hiding,and since P andˆP computed in step P-2.for every multiplication gate are uniquely determined by A,B, and C,it is clear that this simulation is perfectly indistinguishable from a real execution of P.It remains to argue soundness.Assume there exists a dishonest poly-time prover P∗,which on input the CRSΣoutputs a circuit C∗together with a proofπ∗such that with non-negligible probability,C∗is not satisfiable but V(Σ,C∗,π∗)outputs1.By xkea,there exists a poly-time extractor X P∗such that when run on the same CRS and the same random tape as P∗,the extrac-tor X P∗outputs the opening information for all commitments in the proof with non-negligible probability.Concretely,for every multiplication gate and the corresponding commitments A, B,C and P,the extractor X P∗outputs a,α,b,β,c,γ,ρ,̟such that A=g a hα,B=g b hβ, C=g c hγand P=gρh̟.3If P∗succeeds in forging a proof for an unsatisfiable circuit,then there obviously must be an inconsistent multiplication gate with inputs a and b and output c=a·b.(Note that since addition gates are processed using the homomorphic property,there cannot be an inconsistency in an addition gate.)But this contradicts dla by Lemma8.Remark11.The NIZK argument from Fig.1actually provides adaptive ZK,which is a stronger flavor of ZK than guaranteed by Definition1.It guarantees that S cannot only perfectly simulate a proofπfor any circuit C,but when later given a satisfying input x for C,it can also provide。
Graph Regularized Nonnegative Matrix

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1 INTRODUCTION
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techniques for matrix factorization have become popular in recent years for data representation. In many problems in information retrieval, computer vision, and pattern recognition, the input data matrix is of very high dimension. This makes learning from example infeasible [15]. One then hopes to find two or more lower dimensional matrices whose product provides a good approximation to the original one. The canonical matrix factorization techniques include LU decomposition, QR decomposition, vector quantization, and Singular Value Decomposition (SVD). SVD is one of the most frequently used matrix factorization techniques. A singular value decomposition of an M Â N matrix X has the following form: X ¼ UÆVT ; where U is an M Â M orthogonal matrix, V is an N Â N orthogonal matrix, and Æ is an M Â N diagonal matrix with Æij ¼ 0 if i 6¼ j and Æii ! 0. The quantities Æii are called the singular values of X, and the columns of U and V are called
Character of geoelectric intermediate term precursory anomaly and judgment for intermediate term ten

Key words: earth resistivity
diffusion speed
dynamic distribution
Introduction
Earthquake monitoring and prediction is still at the stage of exploration and empirical prediction. The basis is the anomaly variation consisting of seismometry index and the observed resuits using the precursory approaches. Although these variation shows variety and complexity and its relation with earthquakes is not certain, through carefully studying on Ms>7 earthquakes we can find that the anomaly variation before earthquake still shows steady reappearance and has regularity. They are all relative to the seismogenic process. In this paper we focus on strong earthquakes with magnitude over 7, such as Tangshan and Songpan earthquakes, studying their geoelectric intermediate term tendency anomaly variation character and the correlation with seismogenie process, which provide some obvious criterion for the judgment of strong earthquake tendency background and intermediate term prediction.
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a r X i v :g r -q c /9303013v 1 9 M a r 1993TORSION AND NONMETRICITY IN SCALAR-TENSOR THEORIES OF GRAVITYBYJean-Paul Berthias and Bahman Shahid-Saless Jet Propulsion Laboratory 301-150California Institute of Technology Pasadena,CA 91109ABSTRACTWe show that the gravitational field equations derived from an action composed of i)an arbitrary function of the scalar curvature and other scalar fields plus ii)connection-independent kinetic and source terms,are identical whether one chooses nonmetricity to vanish and have non-zero torsion or vice versa.Scalar-Tensor theories of gravitation have been around for decades.These the-ories,commonly based on actions representing coupling between the gravitational metric tensor and other scalarfields have been of interest for various reasons since the birth of General Relativity(GR).1The most well know example is the Brans-Dicke theory2which was proposed to incorporate Mach’s principle in gravitational interactions.Dirac3based his large-number hypothesis on a scalar-tensor theory of gravity.Other theorists favored such theories simply because of the presence of a scalarfield which seems to be an inevitable bi-product of modern physics.More recent examples of such models include conformal-invariant theories of gravity,low-energy limit of superstring theories,Einstein-Cartan type theories coupled to scalar fields and many modern inflationary models based on scalar-tensor theories.In deriving thefield equations of a theory of gravity from an action functional one is faced with choices.The most common approach is to consider the metric tensor as the only independentfield describing the geometry of space-time and to restrict the affine connections to be the well known Christoffel symbols.This guar-antees the metricity of the theory.Thus Riemannian structure and local Lorentz structure are preserved and the metric is the solution to the ten metricfield equa-tions derived from the variation of the action.Another choice is to follow the Palatini formalism which is to consider the metric and the connections as indepen-dentfields.This choice allows the geometry to have a general affine structure.The space-time associated with this type of theory is usually called(L4,g).Here there are in general10equations for the metric tensor and64for the connections.In many cases this increase in the number of equations is compensated by the reduction in order of the metricfield equations.For example in quadratic gravity the Palatini variation yields two sets offirst order equations for the metric and the connections whereas the usual metric formalism yields fourth order equations for the metric.In the case of general relativity the two formalisms produce identicalfield equations.The advantage of deriving thefield equations using the Palatini method is that the geometry of space-time is less restrictive.In general the Palatini variation al-lows for the existence of torsion and non-metricity.The possible importance of suchexoticfields was not realized until the construction of a gauge theory of gravitation was attempted.In the more recent years the inclusion of suchfields in gravita-tional interactions and the study of their properties have become more common as attempts to unify all fundamental interactions with standard GR have failed in one way or another.The simplest theory incorporating torsion and nonmetricity is the Einstein-Cartan-Sciama-Kibble(ECSK)theory4in which torsion is coupled to the canonical spin tensor via the matter part of the lagrangian.In this theory torsion does not propagate and also vanishes in vacuum.The Brans-Dicke version of the ECSK theory(ECSK minimally coupled to a scalarfield),with non-zero torsion and vanishing non-metricity,which we denote by BDT,was discussed by Rauch5,German6,Kim7and others.It was shown that the scalarfield can act as a source of propagating torsion even in vacuum.Furthermore Smalley8showed that the simplest non-metric version of the Brans-Dicke model,with vanishing torsion, which we denote by BDN here,is equivalent to the BDT theory via a conformal transformation.In this paper we generalize Smalley’s result to include a much larger class of scalar-tensor theories.Furthermore,we do this by considering the so-called pro-jective transformation of the connections rather than by extended conformal trans-formations.This can be done because we allow nonmetricity to exist.We prove that given any scalar-tensor action composed of any arbitrary function of the scalar curvature and other scalarfields plus any kinetic and/or matter terms,which are independent of the connections,thefield equations are independent of whether the torsion is set to zero and non-metricity is nonzero or non-metricity is set to zero and the torsion is non-zero.We show that this equivalence is a result of the projective gauge invariance of the action.We prove our results by showing that:a)two dis-tinct choices of the projective gauge vector correspond to the two cases mentioned above,and b)the two cases considered in a)result in identicalfield equations.Our results then imply that the equivalence between the BDT and BDN theories is a consequence of this gauge freedom.As a further example we apply our results to the case of another simple action which involves a quadratic term in the scalarcurvature.Our index conventions are the same as those of Held et.al.9The connections are defined such that when a vector Aλis parallel transported,it undergoes an infinitesimal change given by:dAλ=−Γλµν(x)Aνdxµ.THE FIELD EQUATIONSLet us consider the action:A= [f(φ,R)√2(Γβαγ−Γβγα)(3)is the torsion tensor andQαγβ=∇αgγβ,(4)is the non-metricity tensor.The square brackets denote anti-symmetrization as in Eq.(3)and the prime on f denotes partial differentiation with respect to R.Also in Eq.(2)Qγ≡12Qαβγ=Pαβγ+12∂ηgλτ−Sηλτ+1Γσαβ= σαβ−g σµ[P βαµ+P αµβ−P µβα]−g σµ − 32g βµV α−32δγ[α∂β]ln f ′−12δσβV α.(10)The non-metricity is found by taking the covariant derivative of the metric using the full connections Eq.(10).After some algebra we get:∇αg βγ=Q αβγ=V αg βγ.(11)Note that Eq.(10)is not an explicit solution for the connections but rather an implicit equation since the connections are present in the function f itself.The Ricci tensor can now be calculated using the standard definition.We have:R βγ≡R σβγσ=Γσβγ,σ−Γσσγ,β+ΓσσλΓλβγ−ΓσβλΓλσγ=R βγ({})+12g βγ(∂σln f ′)(∂σln f ′)+1Vαis the projective gauge vector.Furthermore we note that if Vαis the derivative of a scalar one can show that the Riemann-Cartan tensor,the Ricci tensor itself and therefore the metricfield equations are also independent of Vα.Two cases are of interest here:Case A:Vα=0;Here non-metricity vanishes via Eq.(9).and the torsion field is given by:Sαβγ=12gβγDσ∂σln f′+Dβ∂γln f′−12(∂βln f′)(∂γln f′).(14)Case B:Vα=∂αln f′;In this case torsion vanishes via Eq.(10)and non-metricity is given by:Qαµν=gµν∂αln f′,(15)and Rµνremains the same as in Eq.(14)because Vαis a derivative of a scalar. Therefore thefield equations in the two cases are the same.For the action corresponding to the Brans-Dicke theory,f(φ,R)=φR.Case A corresponds to the BDT theory discussed by Refs.(5-7).Case B corresponds to the BDN theory discussed by Smalley.8It is clear that the two theories are equivalent. It is interesting to note that an extended conformal transformation which would gauge away the torsionfield for the BDT theory was found by German6which corresponds to the choice of Vαmade in case B.However,the freedom of having nonmetricity here makes it unnecessary to rescale the metric,or even the scalar field,to make the action invariant.EXAMPLEAs a further example we consider another class of actions,which has regained its popularity in recent years,because of its emergence in the low energy limit of superstrings.11The simplest such action is given in terms of the Hilbert-Einstein term plus a quadratic scalar term,f(R)=R+αR2.Recently the non-metric version of this theory has been discussed by Shahid-Saless.12−14It was shown that,assuming no torsion,the Palatini variation of this action yields a non-metric theory.A more general version of this type of theory which assumes vanishing non-metricity but includes torsion was discussed by many authors.In particular Minkevich15derived and examined the cosmologicalfield equations based on an action which included all the possible quadratic combinations of curvature.Given the formalism developed here it is clear that the two theories yield the samefield equations in the limit that the action considered by Minkevich corresponds to that examined by Shahid-Saless; that is f(R)=R+αR2.In the case of vanishing torsion Eqs.(10)and(9)imply:2αR,βQβµν=gµν(δσβR,α+δσαR,β−gσµgαβR,µ),(16)1+2αRwhich agree with the results given by Shahid-Saless.However since Vαis a total derivative,it does not contribute to the the Ricci tensor.Thus Eq.(12)will agree with the expression for the Ricci tensor used by Ref.(11).Therefore even if we had set Vα=0,we would have the same expression for the Ricci tensor.This case would however correspond to the theory considered by Minkevich which is a metric theory with torsion.The equivalence of his theory with that considered by Shahid-Saless can be inspected easily by setting Minkevich’s f6by−α.The cosmological equations discussed by these authors13,15have also been checked for their equivalence.CONCLUSIONWe have proven that for all actions composed of i)an arbitrary function of the scalar curvature and other scalarfields,plus ii)any other kinetic and matter terms which are independent of the connections,thefield equations are the same whether the torsion is set to zero and the theory is non-metric or non-metricity is set to zero but torsion is non-vanishing.Traditionally non-metricity has been viewed as an unwanted bi-product of some extensions of GR because of its volume non-preserving property.On the other hand it is generally argued that the existence of torsion in nature does not pose a problem for fundamental physics.Our results show that within the class of scalar-tensor theories considered here the twofields result in identicalfield equations and therefore imply the same physics.One conclusion that could be made is that perhaps one needs a deeper understanding of the meaning of thesefields and their inter-relationships in all aspects of measurement before discarding them as physically unreasonable mathematical artifacts.ACKNOWLEDGEMENTThis work was performed at the Jet Propulsion Laboratory which is under con-tract with the National Aeronautics and Space Adiministration.BSS was supported by a resident research associateship award from the National Research Council of the National Academy of Science.REFERENCES1.A.Einstein,Sitz.Pruess.Akad.Wiss.Berlin,47,pp.778,799,844(1915).2.C.Brans and R.H.Dicke,Phys.Rev.124,925(1961).3.P.A.M.Dirac,Proc.Roy.Soc.Lon.A333,403(1973).4.D.W.Sciama,Rev.Mod.Phys.36,463and1103(1964).5.R.T.Rauch,Phys.Rev.Lett.52,1843(1984).6.G.German,Phys.Rev.D32,3307(1985).7.Sung-Won Kim,Phys.Rev.D34,1011(1986).8.L.L.Smalley,Phys.Rev.D33,3590(1986).9.F.Hehl,P.von der Heyde and G.D.Kerlick,Rev.Mod.Phys.48,393(1976).10.See for example V.D.Sandberg,Phys.Rev.D12,3013(1975)and referencestherein.11.M.B.Green and J.H.Schwarz,Phys.Lett.B149,117(1984);M.B.Greenand J.H.Schwarz,Nucl.Phys.B255,93(1985).12.B.Shahid-Saless,Phys.Rev.D35,467(1987).13.B.Shahid-Saless,J.Math.Phys.31,2429(1990).14.B.Shahid-Saless,J.Math.Phys.32(3),694(1991).15.A.V.Minkevich,Phys.Lett.A80,232(1980).。