ppxscal/embedding_network huggingface dataset:
News
Authors: Greg Goth, Pam Frost Gorder, Scott L. Andresen
Venue: IEEE Security and Privacy (2004)

E-Voting Security: The Electoral Dialectic Gets Hot, Greg GothThe looming question is whether the activity surrounding e-voting signals a willingness to build consensus around a commonly accepted e-voting security apparatus, or is, instead, the preparation for a competing stakeholders' titanic clash in the billion-dollar-plus market of e-voting systems.Balancing Video-Game Piracy Issues, Pam Frost GorderThe Business Software Alliance (BSA), an international alliance of software publishers, placed the global software piracy rate at 39 percent in 2002, down from 40 percent the year before, and from a high of 49 percent in 1994. The game industry is working out an uneasy truce with pirates to do business, and new technologies to combat piracy are taking customer enjoyment into account.News Briefs, Scott L. Andresen
Non-synchronous Communications in Process Algebraic Architectural Description Languages
Authors: Marco Bernardo, Edoardo Bontà
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Architectural description languages are a useful tool for modeling complex software systems at a high level of abstraction and, if based on formal methods, for enabling the early verification of various properties among which correct component coordination. This is the case with process algebraic architectural description languages, as they have been equipped with several techniques for verifying the absence of coordination mismatches in the case of synchronous communications. The objective of this paper is twofold. On the modeling side, we show how to enhance the expressiveness of a typical process algebraic architectural description language by including the capability of representing non-synchronous communications, in such a way that the usability of the original language is preserved. On the analysis side, we show how to modify the compatibility check for acyclic topologies and the interoperability check for cyclic topologies, in such a way that both checks can still be applied in the presence of non-synchronous communications.
A Novel Improvement of Neural Network Classification Using Further Division of Partition Space
Authors: Lin Wang, Bo Yang, Zhenxiang Chen, Ajith Abraham, Lizhi Peng
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)

Further Division of Partition Space (FDPS) is a novel technique for neural network classification. Partition space is a space that is used to categorize data sample after sample, which are mapped by neural network learning. The data partition space, which are divided manually into few parts to categorize samples, can be considered as a line segment in the traditional neural network classification. It is proposed that the performance of neural network classification could be improved by using FDPS. In addition, the data partition space are to be divided into many partitions, which will attach to different classes automatically. Experiment results have shown that this method has favorable performance especially with respect to the optimization speed and the accuracy of classified samples.
A Copyright Protection using Watermarking Algorithm
Authors: Abou Ella Hassanien
Venue: Informatica (2006)

In this paper, a digital watermarking algorithm for copyright protection based on the concept of embed digital watermark and modifying frequency coefficients in discrete wavelet transform (DWT) domain is presented. We embed the watermark into the detail wavelet coefficients of the original image with the use of a key. This key is randomly generated and is used to select the exact locations in the wavelet domain in which to embed the watermark. The corresponding watermark detection algorithm is presented. A new metric that measure the objective quality of the image based on the detected watermark bit is introduced, which the original unmarked image is not required for watermark extraction. The performance of the proposed watermarking algorithm is robust to variety of signal distortions, such a JPEG, image cropping, geometric transformations and noises.
A Constructive Technique Based on Linear Programming for Training Switching Neural Networks
Authors: Enrico Ferrari, Marco Muselli
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

A general constructive approach for training neural networks in classification problems is presented. This approach is used to construct a particular connectionist model, named Switching Neural Network (SNN), based on the conversion of the original problem in a Boolean lattice domain. The training of an SNN can be performed through a constructive algorithm, called Switch Programming (SP), based on the solution of a proper linear programming problem. Simulation results obtained on the StatLog benchmark show the good quality of the SNNs trained with SP.
ASBO: Argumentation System Based on Ontologies
Authors: Andrés Muñoz, Juan A. Botía
Venue: Proceedings of the 12th international workshop on Cooperative Information Agents XII (2008)

Conflicts are unavoidable in open distributed systems. Belief or semantic conflicts are of special interest in multiagent systems, where agents need to communicate by exchanging knowledge. A common approach to deal with conflicts is the use of argumentation-based negotiation processes. There have been much work in the argumentation research arena. Amongst the outcomes of this research, some generic argumentation frameworks for handling inconsistences can be found, together with several persuasion dialogue systems. The goal of this paper is to contribute in advancing the state-of-art in argumentation by extending the basic mechanisms used in conventional argumentation frameworks. This contribution consists of a new and convenient style of attack to arguments and making explicit the argumentation process structure through an OWL-based ontology. Main benefits of this research are twofold. Firstly, the availability of a more realistic framework thanks to the definition of the new attack. Secondly, to enable automatic reasoning about the argumentation process itself. To illustrate this approach, we expose a persuasive argumentation scenario based on a real situation.
Evolve Individual Agent Strategies to Global Social Law by Hierarchical Immediate Diffusion
Authors: Yichuan Jiang, Toru Ishida
Venue: Massively Multi-Agent Technology: AAMAS Workshops, MMAS 2006, LSMAS 2006, and CCMMS 2007 Hakodate, Japan, May 9, 2006 Honolulu, HI, USA, May 15, 2007 Selected and Revised Papers (2008)

A social law is a restriction on the set of strategies available to agents [1]. Each agent can select some social strategies in the operation of the systems, however, the social strategies of different agents may collide with each other. Therefore, we need to endow the global social laws for the whole system. In this paper, the social strategy is defined as the living habits of agent, and the social law is the set of living habits which can be accepted by all agents. This paper initiates a study of evolving social strategies of individual agents to global social law of the whole system, which is based on the hierarchical immediate diffusion interaction from superior agents to junior ones. In the diffusion interactions, the agents with superior social position can influence the social strategies of junior agents, so as to reduce the social potential energy of the system. The set of social strategies with the minimum social potential energy can be regarded as the global social law.
A Sparse Sampling Method for Classification Based on Likelihood Factor
Authors: Linge Ding, Fuchun Sun, Hongqiao Wang, Ning Chen
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

The disadvantages of large computing and complex discriminant function involved in classical SVM emerged when the scale of training data was larger. In this paper, a method for classification based on sparse sampling is proposed. A likelihood factor which can indicate the importance of sample is defined. According to the likelihood factor, non-important samples are cliped and misjudged samples are revised, this is called sparse sampling. Sparse sampling can reduce the number of the training samples and the number of the support vectors. So the improved classification method has advantages in reducing computational complexity and simplifying discriminant function.
A Short Algebraic Proof of the Farkas Lemma
Authors: David Bartl
Venue: SIAM Journal on Optimization (2008)

The purpose of this paper is to present a generalization of the Farkas lemma with a short algebraic proof. The generalization lies in the fact that we formulate the Farkas lemma in the setting of two vector spaces over a common linearly ordered field where one of the vector spaces is also linearly ordered. At the end of the paper, we mention the key theorem and two theorems of the alternative, namely Motzkin's theorem and Tucker's theorem.
Application of q-Gram Distance in Digital Forensic Search
Authors: Slobodan Petrović, Sverre Bakke
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

In order to find evidence, digital forensic investigation often includes search procedures applied on large data sets. For such search procedures, appropriate fault tolerant distance measures are needed in order to detect evidence even if it has been previously distorted/partially erased from the search media. One of the appropriate fault-tolerant distance measures for this purpose is constrained edit distance, where the maximum numbers of consecutive insertions and deletions represent the constraints. However, the time complexity of its computation is too high. We propose a two-phase indexless search procedure for application in forensic evidence search that makes use of q-gram distance instead of the constrained edit distance. The q-gram distance is known to approximate well the unconstrained edit distance. We study how well q-gram distance approximates edit distance with special constraints needed in forensic search applications. We compare the performances of the search procedure with the two distances applied in it. Experimental results show that the procedure with the q-gram distance implemented achieves for some values of q almost the same accuracy as the one with the constrained edit distance, but the efficiency of the procedure that implements the q-gram distance is much better, for a much lower time complexity of computation of the q-gram distance.
Seam carving for media retargeting
Authors: Ariel Shamir, Shai Avidan
Venue: Communications of the ACM (2009)

Traditional image resizing techniques are oblivious to the content of the image when changing its width or height. In contrast, media (i.e., image and video) retargeting take s content into account. For example, one would like to change the aspect ratio of a video without making human figures look too fat or too skinny, or change the size of an image by automatically removing "unnecessary" portions while keeping the "important" features intact. We propose a simple operator; we term seam carving to support image and video retargeting. A seam is an optimal 1D path of pixels in an image, or a 2D manifold in a video cube, going from top to bottom, or left to right. Optimality is defined by minimizing an energy function that assigns costs to pixels. We show that computing a seam reduces to a dynamic programming problem for images and a graph min-cut search for video. We demonstrate that several image and video operations, such as aspect ratio correction, size change, and object removal, can be recast as a successive operation of the seam carving operator.
A Design for a Physical RNG with Robust Entropy Estimators
Authors: Wolfgang Killmann, Werner Schindler
Venue: Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems (2008)

We briefly address general aspects that reliable security evaluations of physical RNGs should consider. Then we discuss an efficient RNG design that is based on a pair of noisy diodes. The main contribution of this paper is the formulation and the analysis of the corresponding stochastic model which interestingly also fits to other RNG designs. We prove a theorem that provides tight lower bounds for the entropy per random bit, and we apply our results to a prototype of a particular physical RNG.
Cooperative Visualization of Privacy Risks
Authors: George O. Yee, Larry Korba, Ronggong Song
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

The growth of the Internet has been accompanied by the growth of e-services (e.g. e-commerce, e-health). This proliferation of e-services has put large quantities of customer private information in the hands of service providers, who in many cases have mishandled the information to the detriment of customer privacy. As a result, government bodies have put in place privacy legislation that spells out the privacy rights of customers and how their private information is to be handled. Service providers are required to comply with this privacy legislation. This paper proposes a cooperative visualization technique that can be employed by service providers to understand how private information flows within their organizations, as a way of identifying privacy risks or vulnerabilities that can lead to violations of privacy legislation. The description of the technique includes a model of how an e-service uses private information, a graphical notation for the visualization, and an application example.
Supporting Relational Processing in Complex Animated Diagrams
Authors: Richard Lowe, Jean-Michel Boucheix
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

The psychological utility of different approaches to cueing key information within complex animated diagrams remains relatively unexplored. Because of the varied processing demands required to comprehend such representations, it is likely that providing a range of different cue types would be best for supporting effective user information extraction. Traditional cueing approaches used with static diagrams may need to be reconsidered in order to meet the new design challenges associated with their animated counterparts.
ISL Person Identification Systems in the CLEAR 2007 Evaluations
Authors: Hazım Kemal Ekenel, Qin Jin, Mika Fischer, Rainer Stiefelhagen
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

In this paper, we present ISL person identification systems in the CLEAR 2007 evaluations.The identification systems consist of a face recognition system, a speaker identification system and a multi-modal identification system that combines the individual systems. The experimental results show that the face recognition system outperforms the speaker identification system significantly on the short duration test segments. They perform equally well on the longer duration test segments. Combination of the individual systems improves the performance further.
Modeling the Dynamic Nonlinear Nature of Emotional Phenomena
Authors: Luís Morgado, Graça Gaspar
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

The study of emotional phenomena, particularly the development of emotion models for intelligent agent implementation, has been mainly based on a perspective of emotion as a human phenomenon and on the assumption that emotions can be divided into discrete and independent categories. We propose an alternative model that emphasizes the continuous nonlinear nature of emotion processes, where emotional phenomena are rooted not on high level cognitive or even nervous structures, but on biophysical principles that are pervasive among biological organisms.
Grid and Taxation: The Server as Permanent Establishment in International Grids
Authors: Davide Maria Parrilli
Venue: Proceedings of the 5th international workshop on Grid Economics and Business Models (2008)

Tax issues can be a great barrier to the development of international Grids and can be perceived as an obstacle for ICT companies. Provided this fact, the scope of this paper is to analyse the concept of server (to the ends of income taxation) in case of international Grid infrastructures, in the light of the findings of the Organisation for Economic Cooperation and Development (Model Tax Convention and Commentaries) and of the practices so far developed in some countries and, in particular, to assess whether any server can be considered to be a permanent establishment of the company acting as Grid provider, with all its consequences in terms of tax liability.
Cross-validation and bootstrapping are unreliable in small sample classification
Authors: A. Isaksson, M. Wallman, H. Göransson, M. G. Gustafsson
Venue: Pattern Recognition Letters (2008)

The interest in statistical classification for critical applications such as diagnoses of patient samples based on supervised learning is rapidly growing. To gain acceptance in applications where the subsequent decisions have serious consequences, e.g. choice of cancer therapy, any such decision support system must come with a reliable performance estimate. Tailored for small sample problems, cross-validation (CV) and bootstrapping (BTS) have been the most commonly used methods to determine such estimates in virtually all branches of science for the last 20 years. Here, we address the often overlooked fact that the uncertainty in a point estimate obtained with CV and BTS is unknown and quite large for small sample classification problems encountered in biomedical applications and elsewhere. To avoid this fundamental problem of employing CV and BTS, until improved alternatives have been established, we suggest that the final classification performance always should be reported in the form of a Bayesian confidence interval obtained from a simple holdout test or using some other method that yields conservative measures of the uncertainty.
Rule-based dependency models for security protocol analysis
Authors: Qingfeng Chen, Shichao Zhang, Yi-Ping Phoebe Chen
Venue: Integrated Computer-Aided Engineering (2008)

Security protocol analysis has been discussed for quite some time in the past few years. Although formal methods have been widely used to identify various vulnerabilities, mainly susceptibility to freshness attacks and impersonation, the arisen inconsistent data between principals and collusion attacks held by a group of dishonest principals have been largely ignored. Moreover, the previous methods focus on reasoning about certain security-related properties and detecting known attacks against secure message, whereas there have been insufficient efforts to handle the above hidden but powerful attacks. In this paper, we address these critical issues and prove the efficiency and intuitiveness of rule-based dependency models in defending a protocol against the attacks. This is able to provide a numerical estimation to measure he occurrence of these attacks. It will be useful in enhancing the current protocol analysis.
Local Proofs for Linear-Time Properties of Concurrent Programs
Authors: Ariel Cohen, Kedar S. Namjoshi
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

This paper develops a local reasoning method to check linear-time temporal properties of concurrent programs. In practice, it is often infeasible to model check over the product state space of a concurrent program. The method developed in this paper replaces such global reasoning with checks of (abstracted) individual processes. An automatic refinement step gradually exposes local state if necessary, ensuring that the method is complete. Experiments show that local reasoning can hold a significant advantage over global reasoning.
Dependency Tree Semantics: Branching Quantification in Underspecification
Authors: Livio Robaldo
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

Dependency Tree Semantics (DTS) is a formalism that allows to underspecify quantifier scope ambiguities. This paper provides an introduction of DTS and highlights its linguistic and computational advantages. From a linguistics point of view, DTS is able to represent the so-called Branching Quantifier readings, i.e. those readings in which two or more quantifiers have to be evaluated in parallel. From a computational point of view, DTS features an easy syntax---semantics interface wrt a Dependency Grammar and allows for incremental disambiguations.
Proposal of an Artificial Emotion Expression System Based on External Stimulus and Emotional Elements
Authors: Seungwon Oh, Minsoo Hahn
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

Recently, for intelligent agents, the concept of emotion has become more and more important and many researchers think that emotion is one of the major factors for more natural and friendly interaction between human and agents [1]. There have been several researches to build more emotional creatures.
Classifying points for sweeping solids
Authors: Hüseyin Erdim, Horea T. Ilieş
Venue: Computer-Aided Design (2008)

Many diverse engineering problems can be modeled with solid sweeping in a conceptually simple and intuitive way, and sweeps are considered to be one of the basic representation schemes in solid modeling. However, many properties of sweeps as well as their ''informational completeness'' are not well understood, which is the primary reason why computational support for solid sweeping remains scarce. We propose a generic point membership classification (PMC) for sweeping solids of arbitrary complexity moving according to one parameter affine motions. The only restrictive assumption that we make in this paper is that the initial and final configurations of the moving object do not intersect during the sweep. Our PMC test is defined in terms of inverted trajectory tests against the original geometric representation of the generator object, which implies that this test can be implemented in any geometric representation that supports curve-solid intersections. Importantly, this PMC test provides complete geometric information about the set swept by 3-dimensional objects in general motions. At the same time, it establishes the foundations for developing a new generation of computational tools for sweep boundary evaluation and trimming, as well as a number of practical applications such as shape synthesis, contact analysis and path planning.
Modeling of Agents in Organizational Context
Authors: Alexei Sharpanskykh
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

At present the agent paradigm is often used for computational modeling of human behavior in an organizational setting. However, not many of the existing computational approaches make use of a rich theoretical basis developed in social science. Therefore, often mathematically sound models are invalid in practice. This paper proposes a formal approach for modeling of characteristics and behavior of agents in organizations, diverse aspects of which are represented using an expressive formal framework. The approach is based on the theoretical findings from social science and enables analysis of how different organizational and environmental factors influence the behavior and performance of agents. The approach is illustrated by a simulation case study.