ppxscal/embedding_network huggingface dataset:
EDNA: Estimation of Dependency Networks Algorithm
Authors: José A. Gámez, Juan L. Mateo, José M. Puerta
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

In this work we present a new proposal in order to model the probability distribution in the estimation of distribution algorithms. This approach is based on using dependency networks [1] instead of Bayesian networks or simpler models in which structure is limited. Dependency networks are probabilistic graphical models similar to Bayesian networks, but with a significant difference: they allow directed cycles in the graph. This difference can be an important advantage because of two main reasons. First, in some real problems cyclic relationships appear between variables an this fact cannot be represented in a Bayesian network. Secondly, dependency networks can be built easily due to the fact that there is no need to check the existence of cycles as in a Bayesian network.In this paper we propose to use a general (multivariate) model in order to deal with a richer representation, however, in this initial approach to the problem we also propose to constraint the construction phase in order to use only bivariate statistics. The algorithm is compared with classical approaches with the same complexity order, i.e. bivariate models as chains and trees.
Information architecture using asymmetric in spreading activation
Authors: Se Eung Oh, Jong Soon Park, Rohae Myung
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

As products are getting more diverse and new products are entering the market faster, customers have trouble learning how to use them. User-oriented menu structures may solve this problem. Therefore, to design user-oriented information architectures, we studied menus structures with asymmetric transitions and label analysis methods. As the spreading activation test shows a relationship between words is closer if the shorter response time is, the stronger association is, we can establish a hypothesis that in a well-designed menu structure, association between upper-low menu pairs is not affected by an activation direction. So, in this study the menu of a cellular phone (Model: SPH-w2900) was extracted, and underwent 1st spreading activation tests. Then, on each menu pair, response time differences (asymmetric transition) by accuracy and directions were analyzed to find out problems in labels and improve menu structures and vocabulary. 2nd spreading activation tests were conducted to check whether asymmetric transitions decreased. And it was found that response time differences (asymmetric transition) for activation directions dropped significantly. Asymmetric transitions in spreading activation presented in this study will be helpful to define user-oriented menu labels.
On the Effectiveness of Techniques to Detect Phishing Sites
Authors: Christian Ludl, Sean Mcallister, Engin Kirda, Christopher Kruegel
Venue: Proceedings of the 4th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment (2007)

Phishing is an electronic online identity theft in which the attackers use a combination of social engineering and web site spoofing techniques to trick a user into revealing confidential information. This information is typically used to make an illegal economic profit (e.g., by online banking transactions, purchase of goods using stolen credentials, etc.). Although simple, phishing attacks are remarkably effective. As a result, the numbers of successful phishing attacks have been continuously increasing and many anti-phishing solutions have been proposed. One popular and widely-deployed solution is the integration of blacklist-based anti-phishing techniques into browsers. However, it is currently unclear how effective such blacklisting approaches are in mitigating phishing attacks in real-life. In this paper, we report our findings on analyzing the effectiveness of two popular anti-phishing solutions. Over a period of three weeks, we automatically tested the effectiveness of the blacklists maintained by Google and Microsoft with 10,000 phishing URLs. Furthermore, by analyzing a large number of phishing pages, we explored the existence of page properties that can be used to identify phishing pages.
On a Special Co-cycle Basis of Graphs
Authors: Telikepalli Kavitha
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

In this paper we consider the problems of computing a minimum co-cycle basis and a minimum weakly fundamental co-cycle basis of a directed graph G. A co-cycle in G corresponds to a vertex partition (S,V ¿ S) and a { ¿ 1,0,1} edge incidence vector is associated with each co-cycle. The vector space over ¿ generated by these vectors is the co-cycle space of G. Alternately, the co-cycle space is the orthogonal complement of the cycle space of G. The minimum co-cycle basis problem asks for a set of co-cycles that span the co-cycle space of G and whose sum of weights is minimum. Weakly fundamental co-cycle bases are a special class of co-cycle bases, these form a natural superclass of strictly fundamental co-cycle bases and it is known that computing a minimum weight strictly fundamental co-cycle basis is NP-hard. We show that the co-cycle basis corresponding to the cuts of a Gomory-Hu tree of the underlying undirected graph of G is a minimum co-cycle basis of G and it is also weakly fundamental.
Mining Context-Specific Web Knowledge: An Experimental Dictionary-Based Approach
Authors: Vincenzo Lecce, Marco Calabrese, Domenico Soldo
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This work presents an experimental semantic approach for mining knowledge from the World Wide Web (WWW). The main goal is to build a context-specific knowledge base from web documents. The basic idea is to use a reference knowledge provided by a dictionary as the indexing structure of domain-specific computed knowledge instances organised in the form of interlinked text words. The WordNet lexical database has been used as reference knowledge for the English web documents. Both the reference and the computed knowledge are actually conceived as word graphs. Graph is considered here as a powerful way to represent structured knowledge. This assumption has many consequences on the way knowledge can be explored and similar knowledge patterns can be identified. In order to identify context-specific elements in knowledge graphs, the novel semantic concept of "minutia" has been introduced. A preliminary evaluation of the efficacy of the proposed approach has been carried out. A fair comparison strategy with other non-semantic competing approaches is currently under investigation.
Portable execution of legacy binaries on the Java virtual machine
Authors: Alexander Yermolovich, Andreas Gal, Michael Franz
Venue: Proceedings of the 6th international symposium on Principles and practice of programming in Java (2008)

The move toward pure managed-code environments is held back by the vast amount of legacy software available only as statically compiled binaries for some legacy instruction set architecture (ISA). Catering to this legacy software requires all sorts of compromises, from the necessity of providing backward compatibility with dated instruction sets to the need for unsatisfactory mixed-mode environments, in which the legacy code runs "besides" (rather than on top of) the managed code platform. We have been investigating strategies for running legacy binaries on top of, rather than "besides", a managed code platform, by virtualizing the legacy ISA. Our system "upcompiles" low-level machine code to high-level Java code, which can then be executed on any Java Virtual Machine (JVM). On JVMs that have a just-in-time compiler, our generated JVM bytecode is subsequently "downcompiled" again into the native code of the host machine (which may be identical or different from the starting ISA). Despite executing on top of the Java Virtual Machine, our system delivers performance comparable to commercial-strength dynamic translators such as QEMU that directly generate platform-dependant machine code.
Induction and Evaluation of Affects for Facial Motion Capture
Authors: Gaspard Breton, Florence Février, Eric Jamet, Géraldine Rouxel
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

In this study, we are interested in capturing the facial configuration of Affects in order to use them for Embodied Conversational Agents. In order to create a believable eca, it is necessary to capture natural Affects that can be learnt and replayed. However, until now, animation data are extracted from videos and their description is far from being sufficient to generate realistic facial expressions. It seems that believable results cannot be obtained without using 3D motion capture. This is why in this study we tried to set up a protocol for Affects induction in a motion capture situation with manipulated subjects who are unaware of the real goals. Similarly from [1], we induce natural Affects in order to capture the related facial expressions.
Ideal Multipartite Secret Sharing Schemes
Authors: Oriol Farràs, Jaume Martí-Farré, Carles Padró
Venue: Proceedings of the 26th annual international conference on Advances in Cryptology (2007)

Multipartite secret sharing schemes are those having a multipartite access structure, in which the set of participants is divided into several parts and all participants in the same part play an equivalent role. Several particular families of multipartite schemes, such as the weighted threshold schemes, the hierarchical and the compartmented schemes, and the ones with bipartite or tripartite access structure have been considered in the literature. The characterization of the access structures of ideal secret sharing schemes is one of the main open problems in secret sharing. In this work, the characterization of ideal multipartite access structures is studied with all generality. Our results are based on the well-known connections between ideal secret sharing schemes and matroids. One of the main contributions of this paper is the application of discrete polymatroids to secret sharing. They are proved to be a powerful tool to study the properties of multipartite matroids. In this way, we obtain some necessary conditions and some sufficient conditions for a multipartite access structure to be ideal.Our results can be summarized as follows. First, we present a characterization of matroid-related multipartite access structures in terms of discrete polymatroids. As a consequence of this characterization, a necessary condition for a multipartite access structure to be ideal is obtained. Second, we use linear representations of discrete polymatroids to characterize the linearly representable multipartite matroids. In this way we obtain a sufficient condition for a multipartite access structure to be ideal. Finally, we apply our general results to obtain a complete characterization of ideal tripartite access structures, which was until now an open problem.
LMI-Based Approach for Global Asymptotic Stability Analysis of Discrete-Time Cohen-Grossberg Neural Networks
Authors: Sida Lin, Meiqin Liu, Yanhui Shi, Jianhai Zhang, Yaoyao Zhang, Gangfeng Yan
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

The global asymptotic stability of discrete-time Cohen---Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions of asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The obtained conditions are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by resorting to the MATLAB LMI Control Toolbox.
A Proof of Concept Attack against Norwegian Internet Banking Systems
Authors: Yngve Espelid, Lars---Helge Netland, André N. Klingsheim, Kjell J. Hole
Venue: Financial Cryptography and Data Security: 12th International Conference, FC 2008, Cozumel, Mexico, January 28-31, 2008. Revised Selected Papers (2008)

The banking industry in Norway has developed a new security infrastructure for conducting commerce on the Internet. The initiative, called BankID, aims to become a national ID infrastructure supporting services such as authentication and digital signatures for the entire Norwegian population. This paper describes a practical man-in the- middle attack against online banking applications using BankID. The attack gives an adversary access to customer bank accounts in two different online banking systems. Proof of concept code has been developed and executed to demonstrate the seriousness of the problem.
The International Conference on Advanced Optical Diagnostics in Fluids, Solids and Combustion (VSJ-SPIE04)
Authors: M. Kawahashi
Venue: Journal of Visualization (2005)

The International Conference on Advanced Optical Diagnostics in Fluids, Solids and Combustion (VSJ-SPIE04) was successfully held in Tokyo from December 4th to 7th in 2004 under the co-sponsorship of Visualization Society of Japan (VSJ) and The International Society for Optical Engineering (SPIE). Total 66 papers on forefront optical diagnostics and those applications were presented at the conference and the active and enthusiastic discussions were made. The results of the conference surely contribute to the future developments of optical diagnostics in the wide engineering fields.
Constructing High Dimensional Feature Space for Time Series Classification
Authors: Victor Eruhimov, Vladimir Martyanov, Eugene Tuv
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

The paper investigates a generic method of time series classification that is invariant to transformations of time axis. The state-of-art methods widely use Dynamic Time Warping (DTW) with One-Nearest-Neighbor (1NN). We use DTW to transform time axis of each signal in order to decrease the Euclidean distance between signals from the same class. The predictive accuracy of an algorithm that learns from a heterogeneous set of features extracted from signals is analyzed. Feature selection is used to filter out irrelevant predictors and a serial ensemble of decision trees is used for classification. We simulate a dataset for providing a better insight into the algorithm. We also compare our method to DTW+1NN on several publicly available datasets.
Universal Accumulators with Efficient Nonmembership Proofs
Authors: Jiangtao Li, Ninghui Li, Rui Xue
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

Based on the notion of accumulators, we propose a new cryptographic scheme called universal accumulators. This scheme enables one to commit to a set of values using a short accumulator and to efficiently compute a membership witness of any value that has been accumulated. Unlike traditional accumulators, this scheme also enables one to efficiently compute a nonmembership witness of any value that has not been accumulated. We give a construction for universal accumulators and prove its security based on the strong RSA assumption. We further present a construction for dynamic universal accumulators; this construction allows one to dynamically add and delete inputs with constant computational cost. Our construction directly builds upon Camenisch and Lysyanskaya's dynamic accumulator scheme. Universal accumulators can be seen as an extension to dynamic accumulators with support of nonmembership witness. We also give an efficient zero-knowledge proof protocol for proving that a committed value is not in the accumulator. Our dynamic universal accumulator construction enables efficient membership revocation in an anonymous fashion.
Using a multi-dimensional model to predict software quality
Authors: Tim Chamillard
Venue:  (2008)

Due to the pervasive nature of software, software engineering practitioners have continuously expressed their concern over the industry's inability to accurately predict the quality of a software product as it is developed. To begin to meet this need to accurately predict the quality of a software product, the industry has attempted to build models that can begin to analyze different elements of quality that go into a software product. Using a conglomeration of these models, it may be possible to create a model that can accurately predict quality within a certain level of uncertainty. In this dissertation, the existing techniques that are used for building software prediction models are discussed along with the respective models that currently exist for analyzing software quality. A software quality model is constructed that analyzes the quality dimensions of people, process, product, environment and technology in performing its predictions and providing a level of uncertainty in its predictions based on the phase of the software lifecycle the project is currently in. The software quality model is applied to three software applications to examine how well the predictions and uncertainty values work on real world applications. Using the data from the three software applications, the software quality model is recalibrated to determine whether the model can be enhanced to improve its predictions. The results of this research along with future work for this research is provided.
Sampling-Based Resolution-Complete Algorithms for Safety Falsification of Linear Systems
Authors: Amit Bhatia, Emilio Frazzoli
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

In this paper, we describe a novel approach for checking safety specifications of a dynamical system with exogenous inputs over infinite time horizon. We introduce the notion of resolution completeness for analysis of safety falsification algorithms and present sampling-based resolution-complete algorithms for safety falsification of discrete-time linear time-invariant systems. Given a target resolution of inputs, the algorithms terminate either with a reachable state that violates the safety specification, or prove that the system does not violate the specification at the given resolution of inputs.
A constrained argumentation system for practical reasoning
Authors: Leila Amgoud, Caroline Devred, Marie-Christine Lagasquie-Schiex
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

Practical reasoning (PR), which is concerned with the generic question of what to do, is generally seen as a two steps process: (1) deliberation, in which an agent decides what state of affairs it wants to reach -- that is, its desires; and (2) means-ends reasoning, in which the agent looks for plans for achieving these desires. A desire is justified if it holds in the current state of the world, and feasible if there is a plan for achieving it. The agent's intentions are thus a consistent subset of desires that are both justified and feasible. This paper proposes the first argumentation system for PR that computes in one step the intentions of an agent, allowing thus to avoid the drawbacks of the existing systems. The proposed system is grounded on a recent work on constrained argumentation systems, and satisfies the rationality postulates identified in argumentation literature, namely the consistency and the completeness of the results.
Expand-and-Reduce Algorithm of Particle Swarm Optimization
Authors: Eiji Miyagawa, Toshimichi Saito
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper presents an optimization algorithm: particle swarm optimization with expand-and-reduce ability. When particles are trapped into a local optimal solution, a new particle is added and the trapped particle(s) can escape from the trap. The deletion of the particle is also used in order to suppress excessive network grows. The algorithm efficiency is verified through basic numerical experiments.
A tree-based approach to matchmaking algorithms for resource discovery
Authors: Md. Rafiqul Islam, Md. Zahidul Islam, Nazia Leyla
Venue: International Journal of Network Management (2008)

One of the essential operations in a distributed computing is resource discovery. A resource discovery service provides mechanisms to identify the set of resources capable of satisfying the requirements of a job from a large collection of resources. The matchmaking framework provides a reasonable solution to resource management in a distributed environment; it is composed of four important components as classified advertisement (classad), matchmaker protocol, matchmaking algorithm and claiming protocols. Most of the time required to find a resource depends on the performance of the matchmaking algorithms. A distributed environment introduces a large set of heterogeneous resources which is always changing. The matchmaking algorithms should incorporate with this highly changing environment. In this paper we proposed a fast and efficient searching method for matchmaking algorithms which also deals with resource heterogeneity. The proposed approach reduces the searching time to a linear function from a cubic function proposed by R. Raman, M. Livny, and M. Solomon. We discuss briefly the working principles of the method and compare the experimental results of the proposed matchmaking algorithm with those of the existing algorithm.
Concepts and Models for the Future Generation of Emotional and Intelligent Systems
Authors: José Antonio Martín H., Javier Lope
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

In this work, we first present a view of the philosophic study of Intelligent Behavior in a wide sense. We expose some key ideas to understand Intelligence and Rationality in an operational way based on the notions of Prediction and Randomness. In particular, we hypothesize that unpredictability is the key concept of Intelligence while not randomness is the key concept of Rationality. Next we undertake the study of Emotional Behavior discussing the basic principle of emotional attachment which is modeled by means of an operational definition of the Self. We hypothesize that the most basic principles of the Emotional Behavior emerges from a sort of ego-centric mechanism.
On a New Isothermal Quantum Euler Model: Derivation, Asymptotic Analysis and Simulation
Authors: Pierre Degond, Samy Gallego, Florian Méhats
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

In the first part of this article, we derive a New Isothermal Quantum Euler model. Starting from the quantum Liouville equation, the system of moments is closed by a density operator which minimizes the quantum free energy. Several simplifications of the model are then written for the special case of irrotational flows. The second part of the paper is devoted to a formal analysis of the asymptotic behavior of the quantum Euler system in two situations: at the semiclassical limit and at the zero-temperature limit. The remarkable fact is that in each case we recover a known model: respectively the isothermal Euler system and the Madelung equations. Finally, we give in the third part some preliminary numerical simulations.