KIM PHILBY,THE AMERICAN INTELLIGENCE COMMUNITY,AND OP-20-G: THE FOX BUILT THE HEN-HOUSE AND TOOK THE KEYS

Abstract

Lester S. Hill, who is known for the polygraphic cipher that he published in 1929, published three papers about error-detecting codes in 1926 and 1927, and he and Louis Weisner submitted a patent application for an error-detection machine in 1929. Hill's error-detection schemes of the 1920s were based upon number theory and matrix multiplication, and one of Hill's error-detecting codes essentially includes the encoding method for linear error-correcting codes, which was developed two decades later by Richard Hamming.     

CRYPTANALYSTS' CORNER

Abstract

The Hill cipher, also known as matrix encryption, is a polygraphic substitution cipher, developed by the mathematician Lester S. Hill in 1929. While various attacks had been known on the Hill cipher, the ciphertext-only attack without assumptions about the encryption matrix or probable plaintext words was introduced only recently by Bauer and Millward. They obtained high efficiency of attack by recovering the decryption matrix row by row rather than all rows at once. In this paper, we extend their ciphertext-only attack in two ways. First, we present a better scoring system for cryptanalysis based on the goodness-of-fit statistics. Specifically, we reduce the average number of candidate rows from 24.83 to 7.00 for 3 × 3 matrix and from 4027.78 to 1220.38 for 4 × 4 matrix. Second, we show how to apply our attacks to the Hill cipher without knowing the numeric equivalents of the letters of the plaintexts.     

A POLYGRAPHIC SUBSTITUTION CIPHER BASED ON MULTIPLE INTERLOCKING APPLICATIONS OF PLAYFAIR

This paper presents a non-numerical polygraphic substitution cipher which appears more efficient than Hill's algebraic system. For instance, by using the same number of “operations” per message as a 6-graphic algebraic substitution cipher, the present cipher can achieve 4096-graphic substitution. Less dramatically, a 16-graphic application of the present cipher requires only one-eighth as many operations as a 16-graphic algebraic cipher. The source of the greater efficiency of the proposed cipher is that the number of letters which can be jointly enciphered is exponential, rather than linear, with respect to the number of operations performed.     

FORTY ONE AND STRONG: ARLINGTON HALL STATION

Abstract

Dr. Donald H. Menzel is well known for his work in astronomy, but his cryptologic work has never received a thorough review. The present article describes how his interest in this area was first sparked and provides the details of the secret class he led in “Naval Communications” (really cryptanalysis) at Radcliffe College during World War II. This class served as a prototype and was copied elsewhere. A sketch of some of the classified work he carried out during the war, and after, as a consultant, is also included, along with a brief overview of Menzel's personality and other interests.     

THE MEMORIA TECHNICA CIPHER

A comprehensive analysis of the ciphers invented by Charles L. Dodgson (Lewis Carroll) and how he used them indicate that his Memoria Technica (1875), a variant of a mnemonic scheme first proposed by Richard Grey in 1730, is properly viewed as Dodgson's fifth cipher system. He used his Memoria Technica cipher as a tool in work that was never published, a projected book whose working title was “Logarithms by Lightning: A Mathematical Curiosity.” The logarithms project, a joint work with his colleague, Robert Edward Baynes, is examined in detail.     

Commentary on Alan M. Turing: The Applications of Probability to Cryptography

Abstract

In April 2012, two papers written by Alan Turing during the Second World War on the use of probability in cryptanalysis were released by GCHQ. The longer of these presented an overall framework for the use of Bayes's theorem and prior probabilities, including four examples worked out in detail: the Vigenère cipher, a letter subtractor cipher, the use of repeats to find depths, and simple columnar transposition. (The other paper was an alternative version of the section on repeats.) Turing stressed the importance in practical cryptanalysis of sometimes using only part of the evidence or making simplifying assumptions and presents in each case computational shortcuts to make burdensome calculations manageable. The four examples increase roughly in their difficulty and cryptanalytic demands. After the war, Turing's approach to statistical inference was championed by his assistant in Hut 8, Jack Good, which played a role in the later resurgence of Bayesian statistics.     

Cryptanalysis of Chaocipher and solution of Exhibit 6

Chaocipher is a manual encryption method designed by John F. Byrne in 1918. Until he passed away in 1960, Byrne fervently believed that his cipher system was unbreakable, regardless of the amount of material available to a cryptanalyst. For several decades, he tried (unsuccessfully), to propose the Chaocipher to government agencies. In 1953, he exposed his Chaocipher in his autobiography, Silent Years, providing several examples of texts encrypted with Chaocipher as challenges, but without divulging the inner workings of the cipher. Those were made public only in 2010, when Byrne’s family donated the entire corpus of Chaocipher papers to the National Cryptologic Museum (NCM) in Fort Meade.

A known-plaintext method for recovering the key settings, given sufficient matching plaintext and ciphertext, was published in 2010. However, to date, no method for the cryptanalysis of a single ciphertext-only Chaocipher message has been proposed, nor for the cryptanalysis of short messages “in-depth,” i.e., multiple messages generated with the same initial key settings.

In this article, the authors present a new hillclimbing algorithm for a ciphertext-only cryptanalysis of Chaocipher in-depth messages. This algorithm is based on a “divide-and-conquer” approach and the use of the Index of Coincidence. It takes advantage of a major weakness in the design of the cipher. This previously unknown weakness may have been the reason why William F. Friedman, the inventor of the Index of Coincidence, rejected Byrne’s offer for the use of Chaocipher by the U.S. government. Additionally, the authors present a known-plaintext attack for short in-depth messages, as well as the solution for Lou Kruh’s and Cipher Deavours’s alternate Exhibit 5, also known as “Exhibit 6.” Finally, the authors reevaluate the security of the Chaocipher in view of those findings, with the conclusion that in its classic form, as designed by Byrne, the Chaocipher was a relatively weak cipher, despite Byrne’s rather strong assertions to the contrary.     

A TENSOR-THEORETIC ENHANCEMENT TO THE HILL CIPHER SYSTEM

The Hill matrix algorithm[3], published in 1929, is known for being the first purely algebraic cryptographic system and for starting the entire field of algebraic cryptology. In this paper, an operator derived from ring isomorphism theory is adapted for use in the Hill system which greatly increases the block size that a matrix can encrypt; specifically, a k×k invertible matrix over Z _n represents an invertible matrix of order k ³, which produces ciphertext blocks k ²-times as long as the original matrix could. This enhancement increases the Hill system's security considerably.     

HOW TO MAKE THE HILL CIPHER SECURE

ABSTRACT

This paper presents a symmetric cipher that is actually a variation of the Hill cipher. The new scheme makes use of “random” permutations of columns and rows of a matrix to form a “different” key for each data encryption. The cipher has matrix products and permutations as the only operations which may be performed “efficiently” by primitive operators, when the system parameters are carefully chosen.     

Preface

I am extremely pleased to have been able to organize the assembly of the set of papers contained in this special issue of the International Journal of Software and Informatics, honoring the career of Prof. Barry W. Boehm. The papers contained in this special issue were all contributed by friends, colleagues, and admirers of Prof. Boehm, and were presented during a special Symposium held in Beijing, China on April 26 and 27, 2011, under the sponsorship of the Institute of Software, Chinese Academy of Sciences and the International Journal of Software and Informatics. The range of the subjects of these papers matches the extraordinary breadth of interests and influences of Prof. Boehm and his work. The natures of the papers range from those that make very specific technical contributions to those that are conceptual and analytical, to those that are visionary. The subject matter of the papers addresses software measurement, software management, specific software development phases, and software processes, among other topics. All cite the specific influences, inspirations, and contributions of Prof. Boehm to the work, thereby serving as documented testimony to the far ranging influence that Prof. Boehm has had upon software engineering thought and software development practice. In "Measuring Agility and Architectural Integrity", a paper that focuses on measurement, a longstanding interest of Prof. Boehm''s, Walker Royce tackles the difficult issue of how to quantify agility that nevertheless does not jeopardize the structural integrity of software. Ross Jeffery''s paper, "Software Development Cost Modeling and Estimation Through a UNSW Lens", focuses on the measurement and estimation of a different software issue, namely cost, an area in which Prof. Boehm has made some of his most fundamental and long-lasting contributions (e.g. with his COCOMO models). Neil G. Siegel''s paper, "Organizing Projects Around the Mitigation of Risks Arising from System Dynamic Behavior", shows how appropriate use of software measurement can help to mitigate risk. Risk mitigation is another issue that has been a strong and central focus of Prof. Boehm and his work, as it is a core issue behind his famous Spiral Model of software development. Another set of papers addresses the ways in which Prof. Boehm and his ideas have been broadly inspirational. In my own paper, "A Process Programmer Looks at the Spiral Model: A Tribute To the Deep Insights of Barry W. Boehm", I demonstrate how Prof. Boehm, through the Spiral Model, elucidates some profound insights about the fundamental nature of software and its development. The paper suggests that the community may have only scratched the surface of the important implications that could be drawn from the ideas behind the Spiral Model. Lori A. Clarke, in her paper, "Environment Support for Improving Software Development Processes: A Vision Influenced by the Work of Barry W. Boehm", similarly indicates how papers and ideas presented by Prof. Boehm have provided inspiration and foundations for her own work in the development and integration of software analysis tools. The application of these tools to new software domains, such as process software, is further evidence of the far-reaching impact of Prof. Boehm''s work. Two papers provide further development of Prof. Boehm''s long-held interest in the importance of software and system requirements and the difficulty of eliciting them. In "Attentiveness: Design for Reactivity at Scale", Gregory S. Hartman and William L. Scherlis explore these themes. Their paper suggests that better, more complete requirements specifications might result from focusing on attentiveness, a type of requirement whose importance has been overlooked. In "On ''The Right'' Software", Dines Bjorner presents a rigorous approach to developing software and system requirements tied directly to a correspondingly rigorous approach to domain specification. Bjorner draws a strong and important parallel to Prof. Boehm''s own insights about requirements, thereby strengthening both views, and attesting to the profundity of Prof. Boehm''s views on this crucial area of software engineering. Finally, two papers take philosophical and visionary views of software engineering, each in its own way, indicating how Prof. Boehm''s ideas and work stimulated and nourished the visionary thinking. Dieter Rombach''s paper, Empirical Software Engineering Models: Can They Become the Equivalent of Physical Laws in Traditional Engineering?" suggests the possibility of developing a solid conceptual foundation for software engineering. He suggests that this more solid conceptual foundation could derive from a focus on empirical software models, an area pioneered by Prof. Boehm. In "Polyphonic Aspects of Software Process: Looking for Philosophical Foundation of Software Engineering", Kouichi Kishida''s thoughts range broadly across Western and Eastern literature and philosophy in search of the proper philosophical foundation for software engineering. Along the way Kishida touches often upon how Prof. Boehm''s ideas helped to provide guidance for his search. This paper is an eloquent treatise on how effectively grappling with deep and difficult problems, as Prof. Boehm has done, can lead to improvements in practice, the discovery of deeper issues and truths, and to stimulating the imaginations and visions of others. Ultimately, this volume can only hint and suggest at the breadth and depth of the ideas and work of our colleague, Prof. Barry W. Boehm. It is offered in the hope that the papers themselves will educate and stimulate, but also in the hope that they will also encourage the reader to follow the many references in these papers to explore in more depth the work of Prof. Boehm. I would like to thank the authors of these papers for their excellent contributions to this Special Issue of the International Journal of Software and Informatics. In addition I would like to express my sincere thanks to Prof. Ruqian Lu, the Editor-in-Chief of the International Journal of Software and Informatics, for giving me the great honor of serving as the Editor of this Special Issue. I would also like to express my very sincere thanks to Ms. Mei Fang for her outstanding leadership of the editorial work needed to prepare these papers for publication, which has allowed the publication of this volume on a very demanding schedule. Finally, on behalf of a very grateful software engineering community, I would like to thank our friend, colleague, and leader, Prof. Barry W. Boehm, for his tireless work and amazing contributions to the formation, nurturing, and maturation of our community. This Special Issue is a small, but very earnest measure of our esteem for Prof. Boehm and his work. Leon J. Osterweil     

Biography of Alexandre Dikovsky

Alexandre Dikovsky is born in Leningrad (St. Petersburg), Russia on August 9, 1945. He died in Nantes, France in the beginning of 2014. He is well known for his significant contributions to the fields of Mathematics, Linguistics, and Informatics. In the course of his career, he published over 100 research papers, 12 book chapters, and participated in numerous national and international projects.     

Geometric Analysis of Particle Motion in a Vector Image Field

This paper proposes a geometrical model for the Particle Motion in a Vector Image Field (PMVIF) method. The model introduces a c-evolute to approximate the edge curve in the gray-level image. The c-evolute concept has three major novelties: (1) The locus of Particle Motion in a Vector Image Field (PMVIF) is a c-evolute of image edge curve; (2) A geometrical interpretation is given to the setting of the parameters for the method based on the PMVIF; (3) The gap between the image edge’s critical property and the particle motion equations appeared in PMVIF is padded. Our experimental simulation based on the image gradient field is simple in computing and robust, and can perform well even in situations where high curvature exists. Chenggang Lu received his Bachelor of Science and PhD degrees from Zhejiang University in 1996 and 2003, respectively. Since 2003, he has been with VIA Software (Hang Zhou), Inc. and Huawei Technology, Inc. His research interests include image processing, acoustic signaling processing, and communication engineering. Zheru Chi received his BEng and MEng degrees from Zhejiang University in 1982 and 1985 respectively, and his PhD degree from the University of Sydney in March 1994, all in electrical engineering. Between 1985 and 1989, he was on the Faculty of the Department of Scientific Instruments at Zhejiang University. He worked as a Senior Research Assistant/Research Fellow in the Laboratory for Imaging Science and Engineering at the University of Sydney from April 1993 to January 1995. Since February 1995, he has been with the Hong Kong Polytechnic University, where he is now an Associate Professor in the Department of Electronic and Information Engineering. Since 1997, he has served on the organization or program committees for a number of international conferences. His research interests include image processing, pattern recognition, and computational intelligence. Dr. Chi has authored/co-authored one book and nine book chapters, and published more than 140 technical papers. Gang Chen received his Bachelor of Science degree from Anqing Teachers College in 1983 and his PhD degree in the Department of Applied Mathematics at Zhejiang University in 1994. Between 1994 and 1996, he was a postdoctoral researcher in electrical engineering at Zhejiang University. From 1997 to 1999, he was a visiting researcher in the Institute of Mathematics at the Chinese University of Hong Kong and the Department of Electronic and Information Engineering at The Hong Kong Polytechnic University. Since 2001, he has been a Professor at Zhejiang University. He has been the Director of the Institute of DSP and Software Techniques at Ningbo University since 2002. His research interests include applied mathematics, image processing, fractal geometry, wavelet analysis and computer graphics. Prof. Chen has co-authored one book, co-edited five technical proceedings and published more than 80 technical papers. (David) Dagan Feng received his ME in Electrical Engineering & Computing Science (EECS) from Shanghai JiaoTong University in 1982, MSc in Biocybernetics and Ph.D in Computer Science from the University of California, Los Angeles (UCLA) in 1985 and 1988 respectively. After briefly working as Assistant Professor at the University of California, Riverside, he joined the University of Sydney at the end of 1988, as Lecturer, Senior Lecturer, Reader, Professor and Head of Department of Computer Science/School of Information Technologies, and Associate Dean of Faculty of Science. He is Chair-Professor of Information Technology, Hong Kong Polytechnic University; Honorary Research Consultant, Royal Prince Alfred Hospital, the largest hospital in Australia; Advisory Professor, Shanghai JiaoTong University; Guest Professor, Northwestern Polytechnic University, Northeastern University and Tsinghua University. His research area is Biomedical & Multimedia Information Technology (BMIT). He is the Founder and Director of the BMIT Research Group. He has published over 400 scholarly research papers, pioneered several new research directions, made a number of landmark contributions in his field with significant scientific impact and social benefit, and received the Crump Prize for Excellence in Medical Engineering from USA. More importantly, however, is that many of his research results have been translated into solutions to real-life problems and have made tremendous improvements to the quality of life worldwide. He is a Fellow of ACS, HKIE, IEE, IEEE, and ATSE, Special Area Editor of IEEE Transactions on Information Technology in Biomedicine, and is the current Chairman of IFAC-TC-BIOMED.     

Parallel algorithms for a hypercomplex discrete fourier transform

Methods for the parallel computation of a multidimensional hypercomplex discrete Fourier transform (HDFT) are considered. The basic idea consists in the application of the properties of the hypercomplex algebra in which this transform is performed. Additional possibilities for increasing the efficiency of the algorithm are provided by the natural parallelism of the multidimensional Cooley-Tukey scheme. Marat Vyacheslavovich Aliev. Born 1978. Graduated from the Adygeya State University in 2000. Received candidate’s degree in physics and mathematics in 2004. Presently he is a senior lecturer at the Department of Applied Mathematics and Information Technologies, Adygeya State University. Scientific interests: image processing, fractals, fast algorithms of discrete transforms, and finite-dimensional algebras. Author of 14 publications, including 7 papers. Member of the Russian Association of Pattern Recognition and Image Analysis. Aleksandr Mikhailovich Belov. Born 1980. Graduated from the Samara State Aerospace University in 2002. In the same year, he entered postgraduate courses with the specialty 05.13.18: mathematical modeling, numerical methods, and program complexes. Presently he is a postgraduate student at the Department of Geoinformatics, Samara State Aerospace University, and a trainee at the Laboratory of Mathematical Methods of Image Processing, Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: discrete orthogonal transforms, fast algorithms of discrete orthogonal transforms, and theory of canonical systems of calculus. Author of 13 publications, including 5 papers. Member of the Russian Association of Pattern Recognition and Image Analysis. Aleksei Vladimirovich Ershov. Born 1983. In 2000, he graduated from the Samara Lyceum of Economics and entered the Faculty of Mechanics and Mathematics, Samara State University, to specialize in the field of Organization and Technology of Information Security. In 2001, he started his training within an additional educational program and was qualified as a translator in the field of professional communication. Presently he is a fifth-year student at Samara State University. The title of his diploma work is “Control of the Flows of Confidential Information.” He is an active participant in the translation of the monograph Principia Mathematica, Cambridge University Press, 1927, by A. Whitehead and B. Russell. Author of four publications, including two papers. Marina Aleksandrovna Chicheva. Born 1964. Graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1987. Received candidate’s degree in Engineering in 1998. Presently she is a senior researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: image processing, compression, and fast algorithms of discrete transforms. Author of more than 50 publications, including 18 papers and 1 monograph. Member of the Russian Association of Pattern Recognition and Image Analysis.     

Constructive negation and constraint logic programming with sets

The aim of this paper is to extend theConstructive Negation technique to the case ofCLP(SεT), a Constraint Logic Programming (CLP) language based on hereditarily (and hybrid) finite sets. The challenging aspects of the problem originate from the fact that the structure on whichCLP(SεT) is based is notadmissible closed, and this does not allow to reuse the results presented in the literature concerning the relationships betweenCLP and constructive negation. We propose a new constraint satisfaction algorithm, capable of correctly handling constructive negation for large classes ofCLP(SεT) programs; we also provide a syntactic characterization of such classes of programs. The resulting algorithm provides a novel constraint simplification procedure to handle constructive negation, suitable to theories where unification admits multiple most general unifiers. We also show, using a general result, that it is impossible to construct an interpreter forCLP(SεT) with constructive negation which is guaranteed to work for any arbitrary program; we identify classes of programs for which the implementation of the constructive negation technique is feasible. Agostino Dovier, Ph.D.: He is a researcher in the Department of Science and Technology at the University of Verona, Italy. He obtained his master degree in Computer Science from the University of Udine, Italy, in 1991 and his Ph.D. in Computer Science from the University of Pisa, Italy, in 1996. His research interests are in Programming Languages and Constraints over complex domains, such as Sets and Multisets. He has published over 20 research papers in International Journals and Conferences. He is teaching a course entitled “Special Languages and Techniques for Programming” at the University of Verona. Enrico Pontelli, Ph.D.: He is an Assistant Professor in the Department of Computer Science at the New Mexico State University. He obtained his Laurea degree from the University of Udine (Italy) in 1991, his Master degree from the University of Houston in 1992, and his Ph.D. degree from New Mexico State University in 1997. His research interests are in Programming Languages, Parallel Processing, and Constraint Programming. He has published over 50 papers and served on the program committees of different conferences. He is presently the Associate Director of the Laboratory for Logic, Databases, and Advanced Programming. Gianfranco Rossi, Ph.D.: He received his degree in Computer Science from the University of Pisa in 1979. From 1981 to 1983 he was employed at Intecs Co. System House in Pisa. From November 1983 to February 1989 he was a researcher at the Dipartimento di Informatica of the University of Turin. Since March 1989 he is an Associate Professor of Computer Science, currently with the University of Parma. He is the author of several papers dealing mainly with programming languages, in particular logic programming languages and Prolog, and extended unification algorithms. His current research interests are (logic) programming languages with sets and set unification algorithms.     

InfoFilter: Supporting quality of service for fresh information delivery

With the explosive growth of the Internet and World Wide Web comes a dramatic increase in the number of users that compete for the shared resources of distributed system environments. Most implementations of application servers and distributed search software do not distinguish among requests to different web pages. This has the implication that the behavior of application servers is quite unpredictable. Applications that require timely delivery of fresh information consequently suffer the most in such competitive environments. This paper presents a model of quality of service (QoS) and the design of a QoS-enabled information delivery system that implements such a QoS model. The goal of this development is two-fold. On one hand, we want to enable users or applications to specify the desired quality of service requirements for their requests so that application-aware QoS adaptation is supported throughout the Web query and search processing. On the other hand, we want to enable an application server to customize how it should respond to external requests by setting priorities among query requests and allocating server resources using adaptive QoS control mechanisms. We introduce the Infopipe approach as the systems support architecture and underlying technology for building a QoS-enabled distributed system for fresh information delivery. Ling Liu, Ph.D.: She is an associate professor at the College of Computing, Georgia Institute of Technology. She received her Ph.D. from Tilburg University, The Netherlands in 1993. Her research interests are in the area of large-scale data intensive systems and its applications in distributed, mobile, multimedia, and Internet computing environments. Her work has focused on systems support for creating, searching, manipulating, and monitoring streams of information in wide area networked information systems. She has published more than 70 papers in internal journals or international conferences, and has served on more than 20 program committees in the area of data engineering, databases, and knowledge and information management. Calton Pu, Ph. D.: He is a Professor and John P. Imlay, Jr. Chair in Software at the College of Computing, Georgia Institute of Technology. Calton received his Ph.D. from University of Washington in 1986. He leads the Infosphere expedition project, which is building the system software to support the next generation information flow applications. Infosphere research includes adaptive operating system kernels, communications middleware, and distributed information flow applications. His past research included operating system projects such as Synthetix and Microfeedback, extended transaction projects such as Epsilon Serializability, and Internet data management. He has published more than 125 journal and conference papers, and served on more than 40 program committees. Karsten Schwan, Ph.D.: He is a professor in the College of Computing at the Georgia Institute of Technology. He received the M.Sc. and Ph.D. degrees from Carnegie-Mellon University in Pittsburgh, Pennsylvania. He directs the IHPC project for high performance cluster computing at Georgia Tech. His current research addresses the interactive nature of modern high performance applications (i.e., online monitoring and computational steering), the development of efficient and object-based middleware, the operating system support for distributed and parallel programs, and the online configuration of applications for distributed real-time applications and for communication protocols. Jonathan Walpole, Ph.D.: He is a Professor in the Computer Science and Engineering Department at oregon Graduate Institute of Science and Technology. He received his Ph.D. in Computer Science from Lancaster University, U.K. in 1987. His research interests are in the area of adaptive systems software and its application in distributed, mobile, multimedia computing environments. His work has focused on quality of service specification, adaptive resource management and dynamic specialization for enhanced performance, survivability and evolvability of large software systems, and he has published extensively in these areas.     

The National Security Agency and the William F. Friedman Collection

In addition to being one of the founders of modern American cryptology, William Friedman was a noted cryptologic historian who amassed a major collection of cryptologic literature and artifacts in both his personal and official files. Drawing on over 50,000 pages of documents newly released by the National Security Agency and other sources, this article places the man, his career, and his collections in the context of the government's changing secrecy policies of the early Cold War to offer new insights into Friedman's sometimes fraught relationship with that agency, its efforts to influence the amount and nature of cryptologic information in the public domain, and a series of confrontations over his personal and private papers.     

Multiple labels associative classification

Building fast and accurate classifiers for large-scale databases is an important task in data mining. There is growing evidence that integrating classification and association rule mining can produce more efficient and accurate classifiers than traditional techniques. In this paper, the problem of producing rules with multiple labels is investigated, and we propose a multi-class, multi-label associative classification approach (MMAC). In addition, four measures are presented in this paper for evaluating the accuracy of classification approaches to a wide range of traditional and multi-label classification problems. Results for 19 different data sets from the UCI data collection and nine hyperheuristic scheduling runs show that the proposed approach is an accurate and effective classification technique, highly competitive and scalable if compared with other traditional and associative classification approaches. Fadi Abdeljaber Thabtah received a B.S. degree in Computer Science from Philadelphia University, Jordan, in 1997 and an M.S. degree in Computer Science from California State University, USA in 2001. From 1996 to 2001, he worked as professional in database programming and administration in United Insurance Ltd. in Amman. In 2002, he started his academic career and joined the Philadelphia University as a lecturer. He is currently a final graduate student at the Department of Computer Science, Bradford University, UK. He has published about seven scientific papers in the areas of data mining and machine learning. His research interests include machine learning, data mining, artificial intelligence and object-oriented databases. Peter Cowling is a Professor of Computing at the University of Bradford. He obtained M.A. and D.Phil. degrees from the University of Oxford. He leads the Modelling Optimisation Scheduling And Intelligent Control (MOSAIC) research centre (http://mosaic.ac), whose main research interests lie in the investigation and development of new modelling, optimisation, control and decision support technologies, which bridge the gap between theory and practice. Applications include production and personnel scheduling, intelligent game agents and data mining. He has published over 40 scientific papers in these areas and is active as a consultant to industry. Yonghong Peng's research areas include machine learning and data mining, and bioinformatics. He has published more than 35 scientific papers in related areas. Dr. Peng is a member of the IEEE and Computer Society, and has been a member of the programme committee of several conferences and workshops. Dr. Peng referees papers for several journals including the IEEE Trans. on Systems, Man and Cybernetics (part C), IEEE Trans. on Evolutionary Computation, Journal of Fuzzy Sets and Systems, Journal of Bioinformatics, and Journal of Data Mining and Knowledge Discovery, and is refereeing papers for several conferences.     

On Semismooth Newton’s Methods for Total Variation Minimization

In [2], Chambolle proposed an algorithm for minimizing the total variation of an image. In this short note, based on the theory on semismooth operators, we study semismooth Newton’s methods for total variation minimization. The convergence and numerical results are also presented to show the effectiveness of the proposed algorithms. The research of this author is supported in part by Hong Kong Research Grants Council Grant Nos. 7035/04P and 7035/05P, and HKBU FRGs. The research of this author is supported in part by the Research Grant Council of Hong Kong. This work was started while the author was visiting Department of Applied Mathematics, The Hong Kong Polytechnic University. The research of this author is supported in part by The Hong Kong Polytechnic University Postdoctoral Fellowship Scheme and the National Science Foundation of China (No. 60572114). Michael Ng is a Professor in the Department of Mathematics at the Hong Kong Baptist University. As an applied mathematician, Michael’s main research areas include Bioinformatics, Data Mining, Operations Research and Scientific Computing. Michael has published and edited 5 books, published more than 140 journal papers. He is the principal editor of the Journal of Computational and Applied Mathematics, and the associate editor of SIAM Journal on Scientific Computing. Liqun Qi received his B.S. in Computational Mathematics at Tsinghua University in 1968, his M.S, and Ph.D. degree in Computer Sciences at University of Wisconsin-Madison in 1981 and 1984, respectively. Professor Qi has taught in Tsinghua University, China, University of Wisconsin-Madison, USA, University of New South Wales, Australia, and The Hong Kong Polytechnic University. He is now Chair Professor of Applied Mathematics at The Hong Kong Polytechnic University. Professor Qi has published more than 140 research papers in international journals. He established the superlinear and quadratic convergence theory of the generalized Newton method, and played a principal role in the development of reformulation methods in optimization. Professor Qi’s research work has been cited by the researchers around the world. According to the authoritative citation database ISIHighlyCited.com, he is one of the world’s most highly cited 300 mathematicians during the period from 1981 to 1999. Yu-Fei Yang received the B.Sc., M.S. and Ph.D. degrees in mathematics from Hunan University, P. R. China, in 1987, 1994 and 1999, respectively. From 1999 to 2001, he stayed at the University of New South Wales, Australia as visiting fellow. From 2002 to 2005, he held research associate and postdoctoral fellowship positions at the Hong Kong Polytechnic University. He is currently professor in the College of Mathematics and Econometrics, at Hunan University, P. R. China. His research interests includes optimization theory and methods, and partial differential equations with applications to image analysis. Yu-Mei Huang received her M.Sc. in Computer science from Lanzhou University in 2000. She is now pursuing her doctoral studies in computational mathematics in Hong Kong Baptist University. Her research interests are in image processing and numerical linear algebra.