ppxscal/embedding_network huggingface dataset:
Version Control with Subversion, 2 edition
Authors: C Pilato, Ben Collins-Sussman, Brian Fitzpatrick
Venue:  (2008)

Written by members of the development team that maintains Subversion, this is the official guide and reference manual for the popular open source revision control technology. The new edition covers Subversion 1.5 with a complete introduction and guided tour of its capabilities, along with best practice recommendations. Version Control with Subversion is useful for people from a wide variety of backgrounds, from those with no previous version control experience to experienced system administrators. Subversion is the perfect tool to track individual changes when several people collaborate on documentation or, particularly, software development projects. As a more powerful and flexible successor to the CVS revision control system, Subversion makes life so much simpler, allowing each team member to work separately and then merge source code changes into a single repository that keeps a record of each separate version. Inside the updated edition Version Control with Subversion, you'll find: An introduction to Subversion and basic concepts behind version control A guided tour of the capabilities and structure of Subversion 1.5 Guidelines for installing and configuring Subversion to manage programming, documentation, or any other team-based project Detailed coverage of complex topics such as branching and repository administration Advanced features such as properties, externals, and access control A guide to best practices Complete Subversion reference and troubleshooting guide If you've never used version control, you'll find everything you need to get started. And if you're a seasoned CVS pro, this book will help you make a painless leap into Subversion.
Topological and Variational Properties of a Model for the Reconstruction of Three-Dimensional Transparent Images with Self-Occlusions
Authors: Giovanni Bellettini, Valentina Beorchia, Maurizio Paolini
Venue: Journal of Mathematical Imaging and Vision (2008)

We introduce and study a two-dimensional variational model for the reconstruction of a smooth generic solid shape E, which may handle the self-occlusions and that can be considered as an improvement of the 2.1D sketch of Nitzberg and Mumford (Proceedings of the Third International Conference on Computer Vision, Osaka, 1990). We characterize from the topological viewpoint the apparent contour of E, namely, we characterize those planar graphs that are apparent contours of some shape E. This is the classical problem of recovering a three-dimensional layered shape from its apparent contour, which is of interest in theoretical computer vision. We make use of the so-called Huffman labeling (Machine Intelligence, vol. 6, Am. Elsevier, New York, 1971), see also the papers of Williams (Ph.D. Dissertation, 1994 and Int. J. Comput. Vis. 23:93---108, 1997) and the paper of Karpenko and Hughes (Preprint, 2006) for related results. Moreover, we show that if E and F are two shapes having the same apparent contour, then E and F differ by a global homeomorphism which is strictly increasing on each fiber along the direction of the eye of the observer. These two topological theorems allow to find the domain of the functional ¿ describing the model. Compactness, semicontinuity and relaxation properties of ¿ are then studied, as well as connections of our model with the problem of completion of hidden contours.
Learning unions of ω(1)-dimensional rectangles
Authors: Alp Atc, Rocco A. Servedio
Venue: Theoretical Computer Science (2008)

We consider the problem of learning unions of rectangles over the domain [b]^n, in the uniform distribution membership query learning setting, where both b and n are ''large''. We obtain poly(n,logb)-time algorithms for the following classes: *poly(nlogb)-way Majority of O(log(nlogb)loglog(nlogb))-dimensional rectangles. *Union of poly(log(nlogb)) many O(log^2(nlogb)(loglog(nlogb)logloglog(nlogb))^2)-dimensional rectangles. *poly(nlogb)-way Majority of poly(nlogb)-Or of disjoint O(log(nlogb)loglog(nlogb)) dimensional rectangles. Our main algorithmic tool is an extension of Jackson's boosting- and Fourier-based Harmonic Sieve algorithm [J.C. Jackson, An efficient membership-query algorithm for learning DNF with respect to the uniform distribution, Journal of Computer and System Sciences 55 (3) (1997) 414-440] to the domain [b]^n, building on work of Akavia et al. [A. Akavia, S. Goldwasser, S. Safra, Proving hard core predicates using list decoding, in: Proc. of the 44th Annual IEEE Symposium on Foundations of Computer Science, FOCS '03, 2003, pp. 146-156]. Other ingredients used to obtain the results stated above are techniques from exact learning [A. Beimel, E. Kushilevitz, Learning boxes in high dimension, Algorithmica 22 (1/2) (1998) 76-90] and ideas from recent work on learning augmented AC^0 circuits [J.C. Jackson, A.R. Klivans, R.A. Servedio, Learnability beyond AC^0, in: Proc. of the 34th Annual ACM Symposium on Theory of Computing, STOC '02, 2002, pp. 776-784] and on representing Boolean functions as thresholds of parities [A.R. Klivans, R.A. Servedio, Learning DNF in time 2^O^@?^(^n^^^1^^^/^^^3^), Journal of Computer and System Sciences 68 (2) (2004) 303-318].
Similarity-Guided Clause Generalization
Authors: S. Ferilli, T. M. Basile, N. Mauro, M. Biba, F. Esposito
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

Few works are available in the literature to define similarity criteria between First-Order Logic formulæ, where the presence of relations causes various portions of one description to be possibly mapped in different ways onto another description, which poses serious computational problems. Hence, the need for a set of general criteria that are able to support the comparison between formulæ. This could have many applications; this paper tackles the case of two descriptions (e.g., a definition and an observation) to be generalized, where the similarity criteria could help in focussing on the subparts of the descriptions that are more similar and hence more likely to correspond to each other, based only on their syntactic structure. Experiments on real-world datasets prove the effectiveness of the proposal, and the efficiency of the corresponding implementation in a generalization procedure.
Influence-Based Autonomy Levels in Agent Decision-Making
Authors: Bob Vecht, André P. Meyer, Martijn Neef, Frank Dignum, John-Jules Ch. Meyer
Venue: Coordination, Organizations, Institutions, and Norms in Agent Systems II: AAMAS 2006 and ECAI 2006 International Workshops, COIN 2006 Hakodate, Japan, May 9, 2006 Riva del Garda, Italy, August 28, 2006. Revised Selected Papers (2007)

Autonomy is a crucial and powerful feature of agents and it is the subject of much research in the agent field. Controlling the autonomy of agents is a way to coordinate the behavior of groups of agents. Our approach is to look at it as a design problem for agents. We analyze the autonomy of an agent as a gradual property that is related to the degree of intervention of other agents in the decision process. We define different levels of autonomy in terms of inter-agent influences and we present a BDI-based deliberation process in which different levels of autonomy can be implemented.
Analyzing Behavior of Objective Rule Evaluation Indices Based on a Correlation Coefficient
Authors: Hidenao Abe, Shusaku Tsumoto
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

In this paper, we present an analysis of behavior of objective rule evaluation indices on classification rule sets using Pearson productmoment correlation coefficients. To support data mining post-processing, which is one of important procedures in a data mining process, at least 40 indices are proposed to find out valuable knowledge. However, their behavior have never been clearly articulated. Therefore, we carried out a correlation analysis between each objective rule evaluation index. In this analysis, we calculated average values of each index using bootstrap method on 32 classification rule sets learned with information gain ratio. Then, we found the following relationships based on the correlation coefficient values: similar pairs, discrepant pairs, and independent indices. With regarding to this result, we discuss about relative functional relationships between each group of objective indices.
Optic Disc Segmentation by Means of GA-Optimized Topological Active Nets
Authors: J. Novo, M. G. Penedo, J. Santos
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

In this paper we propose a new approach to the optic disc segmentation process in digital retinal images by means of Topological Active Nets (TAN). This is a deformable model used for image segmentation that integrates features of region-based and edge-based segmentation techniques, being able to fit the edges of the objects and model their inner topology. The optimization of the Active Nets is performed by a genetic algorithm, with adapted or new ad hoc genetic operators to the problem. The active nets incorporate new energy terms for the optic disc segmentations, without the need of any pre-processing of the images. We present results of optic disc segmentations showing the advantages of the approach.
Rough Sets and Approximation Schemes
Authors: Victor W. Marek, Mirosław Truszczynski
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

Approximate reasoning is used in a variety of reasoning tasks in Logic-based Artificial Intelligence. In this abstract we compare a number of such reasoning schemes and show how they relate and differ from the approach of Pawlak's Rough Sets.
MODIS Image Compression with Optimal Waveband Prediction Tree
Authors: Wei-hua Ai, Xing-wang Zhou, Yi-ming Guo
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Proposed a practical compression method using optimal waveband prediction tree, integer wavelet and SPIHT algorithm for MODIS multispectral images effectively. First, an optimal waveband prediction tree is designed for de-correlating the spectral redundancy. Then, spatial redundancy in the image is reduced by using IWT and SPIHT algorithm. Finally the arithmetic algorithm is used to improve the compression performance. We demonstrate the compression performance with different compression schemes in details. The experimental results show that the method is efficient and practical for MODIS images.
Using Charts to Present International Trade Data
Authors: Irwin Jarett
Venue: IEEE Computer Graphics and Applications (1983)

A set of graphic icons based on international accounting principles can serve as a common language for comparison of commercial operations conducted in different currencies. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Chaotic Hybrid Cultural Algorithm for Constrained Optimization
Authors: Xiaohui Yuan, Anjun Su, Yanbin Yuan, Xiaopan Zhang, Bo Cao, Bo Yang
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

This paper proposes a new chaotic hybrid cultural algorithm to solve constrained optimization problems. In the proposed method, differential evolution is embedded into cultural algorithm as its population space and applies situational and normative knowledge sources in belief space to influence the variationoperator of differential evolution. We apply chaos theory to obtain self-adaptive parameter settings for differential evolution and then simple feasibility-based selection comparison techniques are devised to handle constraints effectively. The performance of the proposed method has been examined by its application to eleven test cases. The results are competitive with respect to three state-of-the-art evolutionary optimization algorithms.
Model Driven Engineering for Designing Adaptive Multi-Agents Systems
Authors: Sylvain Rougemaille, Frédéric Migeon, Christine Maurel, Marie-Pierre Gleizes
Venue: Engineering Societies in the Agents World VIII: 8th International Workshop, ESAW 2007, Athens, Greece, October 22-24, 2007, Revised Selected Papers (2008)

A challenge for our days is to provide new efficient CASE (Computer Aided Software Engineering) tools enabling MAS designers towards Model Driven Engineering (MDE) approaches. The goal of MDE is to improve the development process and the quality of the software produced. Our work focuses on two different aspects of MAS. The functional one, which is application dependent and close to the decision process of agents, and the operational one related to elementary capabilities of agents. For each point of view, we have defined specific meta-models. Our goal in this paper is to provide a mapping from the functional meta-model to the operational that constitutes a specific platform model. As we are interested in adaptive systems, we have to deal with adaptation both at the agent and the system level. We address this problem by respectively using the JavAct flexible architecture and the Adaptive MAS principles.
Query Translation through Dictionary Adaptation
Authors: Stephane Clinchant, Jean-Michel Renders
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

Our participation to CLEF07 (Domain-specific Track) was motivated this year by assessing several query translation and expansion strategies that we recently designed and developed. One line of research and development was to use our own Statistical Machine Translation system (called Matrax) and its intermediate outputs to perform query translation and disambiguation. Our idea was to benefit from Matrax' flexibility to output more than one plausible translations and to train its Language Model component on the CLEF07 target corpora. The second line of research consisted in designing algorithms to adapt an initial, general probabilistic dictionary to a particular pair (query, target corpus); this constitutes some extreme viewpoint on the "bilingual lexicon extraction and adaptation" topic. For this strategy, our main contributions lie in a pseudo-feedback algorithm and an EM-like optimisation algorithm that realize this adaptation. A third axis was to evaluate the potential impact of "Lexical Entailment" models in a cross-lingual framework, as they were only used in a monolingual setting up to now. Experimental results on CLEF-2007 corpora (domain-specific track) show that the dictionary adaptation mechanisms appear quite effective in the CLIR framework, exceeding in certain cases the performance of much more complex Machine Translation systems and even the performance of the monolingual baseline. In most cases also, Lexical Entailment models, used as query expansion mechanisms, turned out to be beneficial.
Multi-objective Optimization Algorithm Based on Clonal Selection
Authors: Yubo Hu, Tiejun Chen
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

In this paper, we propose a new multi-objective optimization approach based the clonal selection principle which is from an artificial immune system. Our approach uses the cluster method in the memory cell set of the clonal selection principle to renew and eliminate antibody; the non-uniform mutation operator is employed to the multiplicity of population. This algorithm cannot promote to individual competition and universality of populations by using antibody-antibody affinity but restrain excessive competition by using antigen-antigen affinity. In our study, a test function and some metrics commonly adopted in multi-objective optimization are used. Our results indicate that the proposed approach has its performances better than those produced by NSGA, and closer to Pareto-curve which is a set of the uniform and widespread solutions.
Development of a Web Type DVD Viewer Synchronized with Multilingual Captions for Existing DVDs
Authors: Takaaki Okura, Yoko Hirose
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

We have developed the Web type DVD Viewer by which you can watch existing DVDs synchronized with additional captions. We have applied it to our released Japanese DVD about the supporting system in U.S.A. for the students with difficulties. The results of questionnaires shows 1) it is effective for watching a DVD which dose not have a subtitle of user's own language. 2) ease of using is improved by removing setup of security options.
Rethinking traffic management: design of optimizable networks
Authors: Mung Chiang, Jennifer Rexford
Venue:  (2008)

Traffic management refers to controlling how much traffic traverses each path in a network. On the Internet today, end hosts run congestion control to adapt sending rates, routers route traffic on shortest paths based on link weights, and operators tune link weights to direct traffic away from heavily-loaded links. This dissertation performs a top-down redesign of traffic management to support diverse application requirements, leveraging emerging technology trends in network virtualization and multipath routing. We begin by analyzing, then redesigning today&rsquo;s traffic-management system. In the &lsquo;bottom-up&rsquo; approach, we study the interaction of congestion control and traffic engineering using established optimization models. We find congestion control and traffic-engineering interact in a stable, though not always efficient manner. Efficiency can be improved by tuning the operator&rsquo;s traffic-engineering function, but at the cost of robustness. In the &lsquo;top-down&rsquo; approach, we propose a new objective function that captures the goals of both end users and network operators. Next, using various optimization decomposition techniques, we generate four distributed algorithms that divide traffic over multiple paths based on feedback from the network links. These distributed algorithms are provably stable and optimal, but can converge slowly and are sensitive to tuning parameters. Finally, combining the best features of these distributed algorithms, we construct TRUMP: TRaffic-management Using Multipath Protocol. TRUMP converges quickly and contains a single easy to tune parameter. Packet-level simulations show TRUMP behaves well with realistic topologies, feedback delays, capacities, and traffic loads. Since applications today may have different performance objectives, we next redesign traffic management to handle multiple traffic classes. A natural objective for an ISP is to maximize aggregate performance objectives across multiple traffic classes. Decomposing the ISP&rsquo;s problem leads to a stable and optimal solution where each traffic class optimizes according to its own performance objective, with an algorithm to dynamically allocate bandwidth shares. The distributed protocols can be implemented using DaVinci: Dynamically Adaptive VIrtual Networks for a Customized Internet. In DaVinci, each virtual network runs traffic-management protocols optimized for a traffic class, and link bandwidth is dynamically allocated between virtual networks through separate queues. Overall, we show that using optimization theory as a foundation, simulations as a building block, and engineering intuition as a guide can be a principled approach to architecture and protocol design.
Computer-Aided Vision System for Surface Blemish Detection of LED Chips
Authors: Hong-Dar Lin, Chung-Yu Chung, Singa Wang Chiu
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

This research explores the automated detection of surface blemishes in light-emitting diode (LED) chips. An LED is a semiconductor device that emits visible light when an electric current passes through the semiconductor chip. Water-drop blemishes, commonly appearing on the surfaces of chips, impair the appearance of LEDs as well as their functionality and security. Consequently, detecting water-drop blemishes becomes crucial for the quality control of LED products. We first use the one-level Haar wavelet transform to decompose a chip image and extract four wavelet characteristics. Then, the T 2 statistic of multivariate statistical analysis is applied to integrate the multiple wavelet characteristics. Finally, the wavelet based multivariate statistical approach judges the existence of water-drop blemishes. Experimental results show that the proposed method achieves an above 95% detection rate and a below 1.5% false alarm rate in inspecting water-drop blemishes of LED chips.
OMIE: Ontology Mapping within an Interactive and Extensible Environment
Authors: Amel Bouzeghoub, Abdeltif Elbyed, Fariza Tahi
Venue: Proceedings of the 5th international workshop on Data Integration in the Life Sciences (2008)

The increasing number of on-line accessible biological data sources has involved a growth of the number and the size of ontologies. This makes it increasingly valuable to map ontologies each other to determine which of their concepts are semantically related. Nowadays, developed tools are often semi-automatic and require the help of experts. Determining semantic relations between concepts is a difficult task, and the problem is still open. Several methods have been proposed in the literature. Existing tools for mapping concepts usually combine several methods, called matchers. In this paper, we propose a tool called OMIE (Ontology Mapping within an Interactive and Extensible environment) which uses and combines several matchers. OMIE is extensible, i.e. matchers could be added or inhibited, and is interactive, i.e. experts could validate or invalidate mappings as well as choose between mapping specific concepts or mapping the entire ontologies.
Local variable access behavior of a hardware-translation based Java virtual machine
Authors: Hitoshi Oi
Venue: Journal of Systems and Software (2008)

Hardware bytecode translation is a technique to improve the performance of the Java virtual machine (JVM), especially on the portable devices for which the overhead of dynamic compilation is significant. However, since the translation is done on a single bytecode basis, a naive implementation of the JVM generates frequent memory accesses for local variables which can be not only a performance bottleneck but also an obstacle for instruction folding. A solution to this problem is to add a small register file to the data path of the microprocessor which is dedicated for storing local variables. However, the effectiveness of such a local variable register file depends on the size and the local variable access behavior of the applications. In this paper, we analyze the local variable access behavior of various Java applications. In particular, we will investigate the fraction of local variable accesses that are covered by the register file of a varying size, which determines the chip area overhead and the operation speed. We also evaluate the effectiveness of the sliding register window for parameter passing in context of JVM and on-the-fly optimization of local variable to register file mapping. With two types of exceptions, a 16-entry register file achieves coverages of up to 98%. The first type of exception is represented by the SAXON XSLT processor for which the effect of cold miss is significant. Adding the sliding window feature to the register file for parameter passing turns 6.2-13.3% of total accesses from miss to hit to the register file for the SAXON with XSLTMark. The second type of exception is represented by the FFT, which accesses more than 16 local variables for most of method invocations. In this case, on-the-fly profiling is effective. The hit ratio of a 16-entry register file for the FFT is increased from 44% to 83% by an array of 8-bit counters.