ppxscal/embedding_network huggingface dataset:
Manifold Training Technique to Reconstruct High Dynamic Range Image
Authors: Cheng-Yuan Liou, Wei-Chen Cheng
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

This paper presents two manifold training techniques to reconstruct high dynamic range images from a set of low dynamic range images which have different exposure times. It provides the performance on noisy images.
Nonlinear dynamics analysis of electrocardiograms for detection of coronary artery disease
Authors: Karolis Antanavičius, Algirdas Bastys, Juozas Bluas, Liudas Gargasas, Svetlana Kaminskien, Graina Urbonavičien, Alfonsas Vainoras
Venue: Computer Methods and Programs in Biomedicine (2008)

A computerized approach of nonlinear dynamics analysis of electrocardiogram (ECG) signals was applied for the detection of coronary artery disease (CAD). The proposed nonlinear dynamics descriptors were derived from 12-lead rest ECG data, and evaluated by originally developed computer software. Fluctuations of potentials of ECG leads that occur during the period of 20ms with a magnitude of 5-20@mV were significantly less beat-to-beat predictable in ischemic versus non-ischemic patients. The well-known nonlinear dynamics descriptors, recurrences percentage, mutual information, fractal dimension, and a new descriptor, next embedding dimension error, were good quantitative descriptors of fluctuations. They were significantly different (
Dynamic photonic lightpaths in the StarPlane network
Authors: Paola Grosso, Damien Marchal, Jason Maassen, Eric Bernier, Li Xu, Cees de Laat
Venue: Future Generation Computer Systems (2009)

The StarPlane project enables users to dynamically control network photonic paths. Applications running on the Distributed ASCI Supercomputer (DAS-3) can manipulate wavelengths in the Dutch research and education network SURFnet6. The goal is to achieve fast switching times so that when the computational pattern in the computing clusters changes, the underlying network topology adapts rapidly to the new traffic flow. StarPlane develops: the software to perform optimal traffic engineering; the management plane to map the users' request into directives for the network control plane, as well as the integration to the DAS-3 Grid middleware. We present here some preliminary results obtained with few selected Grid applications that make use of StarPlane.
On the Positive--Negative Partial Set Cover problem
Authors: Pauli Miettinen
Venue: Information Processing Letters (2008)

The Positive-Negative Partial Set Cover problem is introduced and its complexity, especially the hardness-of-approximation, is studied. The problem generalizes the Set Cover problem, and it naturally arises in certain data mining applications.
Design of a Multiagent Solution for Demand-Responsive Transportation
Authors: Claudio Cubillos, Sandra Gaete, Franco Guidi-Polanco, Claudio Demartini
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

Mobility patterns in large cities has changed in the last decades making traditional fix-line public transportation no longer efficient to tackle the increasing complexity. Demand-responsive transportation leverages as an alternative where routes, departure times, vehicles and even operators, can be matched to the identified demand, allowing a more user-oriented and cost effective approach to service provision. In this context, the design of a multiagent system is presented following the agent-oriented software engineering methodology (AOSE) PASSI.
Integration of ACO in a Constraint Programming Language
Authors: Madjid Khichane, Patrick Albert, Christine Solnon
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

We propose to integrate ACO in a Constraint Programming (CP) language. Basically, we use the CP language to describe the problem to solve by means of constraints and we use the CP propagation engine to reduce the search space and check constraint satisfaction; however, the classical backtrack search of CP is replaced by an ACO search. We report first experimental results on the car sequencing problem and compare different pheromone strategies for this problem.
Conceptual Integration of Flow-Based and Packet-Based Network Intrusion Detection
Authors: Gregor Schaffrath, Burkhard Stiller
Venue: Proceedings of the 2nd international conference on Autonomous Infrastructure, Management and Security: Resilient Networks and Services (2008)

Network-based Intrusion Detection Systems aim at the detection of malicious activities by an inspection of network traffic. Since network link speeds and traffic volume grew over the last years, payload-based analysis became difficult, leading to the development of alternative approaches for flowbased analysis. Although each approach alone suffers a set of drawbacks, a few experiments with hybrid approaches show potential for synergies. This work analyses these drawbacks in order to develop a conceptual framework for hybrid approaches, integrating the two concepts in a fashion to compensate for their respective weaknesses proposed.
Gestural Interaction Using Feature Classification
Authors: Cornelius Malerczyk
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

This paper describes our ongoing research work on deviceless interaction using hand gesture recognition with a calibrated stereo system. Video-based interaction is one of the most intuitive kinds of Human-Computer-Interaction with Virtual-Reality applications due to the fact that users are not wired to a computer. If interaction with three-dimensional environments is considered, pointing, grabbing and releasing are the most intuitive gestures used by humans. This paper describes our video-based gesture recognition system that observes the user in front of a large displaying screen, identifying three different hand gestures in real time using 2D feature classification and determines 3D information like the 3D position of the user's hand or the pointing direction if performed. Different scenario applications like a virtual chess game against the computer or an industrial scenario have been developed and tested. To estimate the possible count of distinguishable gestures a sign language recognition application has been developed and tested using a single uncalibrated camera only. 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
An Environment to Support Multi-Party Communications in Multi-Agent Systems
Authors: Julien Saunier, Flavien Balbo
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

Two-party communication is the most-studied model to support interaction between two cognitive agents, whereas that is only one case of what an agent should be able to do. Multi-party communications enhance this model, by taking into account all the roles an agent can have in a communication. Nevertheless, there are no generic models and infrastructures that enable to apply multi-party communication in a standardized way. We emphasize that the environment, in the sense of a common medium for the agents, is a suitable paradigm to support multi-party communication. We propose a general and operational model called Environment as Active Support of Interaction (EASI), that enables each agent to actively modify the environment according to its communication needs. Algorithms are proposed and assessed with an example stemming from the ambient intelligence domain.
Coinductive Properties of Causal Maps
Authors: Jiho Kim
Venue: Proceedings of the 12th international conference on Algebraic Methodology and Software Technology (2008)

Variants of causal functions on streams are defined, and the interplay between them is studied from different perspectives with attention to coalgebraic considerations. We prove that the sets of causal and bicausal functions, respectively, are closed under a certain natural coinductive construction. This closure property paves the way to constructing new final stream coalgebras over finite alphabets. This result is used to show that the 2-adic version of the Collatz function yields a final bit-stream coalgebra. 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
Web Personalization: Is It Effective?
Authors: Kar Yan Tam, Shuk Ying Ho
Venue: IT Professional (2003)

This study shows that subjects who receive personalized information downloaded music files more frequently.
The Development of a Self-assessment System for the Learners Answers with the Use of GPNN
Authors: John Pavlopoulos, John Vrettaros, George Vouros, Athanasios S. Drigas
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

The goal of this study is the development of an assessment system with the support of a Neural Network approach optimized with the use of Genetic Programming. The data used as training data are real data derived from an educational project. The developed system is proved capable of assessing data from both single select and multiple choice questions in an e-learning environment. The final result is the assessment of the learners' answers through various criteria.
A Projection-Based Framework for Classifier Performance Evaluation
Authors: Nathalie Japkowicz, Pritika Sanghi, Peter Tischer
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

In this paper, we propose approaching the problem of classifier evaluation in terms of a projection from a high-dimensional space to a visualizable two-dimensional one. Rather than collapsing confusion matrices into a single measure the way traditional evaluation methods do, we consider the vector composed of the entries of the confusion matrix (or the confusion matrices in case several domains are considered simultaneously) as the performance evaluation vector, and project it into a two dimensional space using a recently proposed distance-preserving projection method. This approach is shown to be particularly useful in the case of comparison of several classifiers on many domains as well as in the case of multiclass classification. Furthermore, by providing simultaneous multiple views of the same evaluation data, it allows for a quick and accurate assessment of classifier performance.
Test Pattern Generator Design Optimization Based on Genetic Algorithm
Authors: Tomasz Garbolino, Gregor Papa
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

In this paper an approach for the generation of deterministic test pattern generator logic composed of D-type and T-type flip-flops is described. The approach employs a genetic algorithm to find an acceptable practical solution in a large space of possible implementations. In contrast to conventional approaches our genetic algorithm approach reduces the gate count of built-in self-test structure by concurrent optimization of multiple parameters that influence the final solution. Results of experiments with combinational benchmarks demonstrate the efficiency of the proposed evolutionary approach.
A Multi-Agent Model for Mine Detection --- MAMMD
Authors: Umar Manzoor, Samia Nefti, Haris Hasan, Majid Mehmood, Bassam Aslam, Osama Shaukat
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

From decades mines have taken thousands of innocent lives and a lot of research is going on mine detection problems. In this paper we have proposed a multi-agent based model for detecting (MAMMD) mines in unknown environment. Mine positions are unknown to the agents and they cannot predict there positions using any probability method. Agents have mine detector devices and they coordinate their actions/movements with each other. MAMMD architecture is implemented using layer based approach to make the system distributed and fault tolerant. We are using an algorithm which is quite similar to depth first search algorithm for movement of agents. Proposed architecture is evaluated on large number of test cases including use of different grids sizes from 10x10 to 100x100. Grids had mines randomly placed, occupying 0% to 30% of the search space. Experiments used 5 to 25 agents for each randomly generated grid with same mine ratio. Experimentally we have observed that MAMMD is effective in both time and solution quality.
Asymptotic results in segmented multiple regression
Authors: Jeankyung Kim, Hyune-Ju Kim
Venue: Journal of Multivariate Analysis (2008)

This paper studies the asymptotic behavior of the least squares estimators in segmented multiple regression. For a model with more than one partitioning variable, each of which has one or more change-points, we study the asymptotic properties of the estimated change-points and regression coefficients. Using techniques in empirical process theory, we prove the consistency of the least squares estimators and also establish the asymptotic normality of the estimated regression coefficients. For the estimated change-points, we obtain their consistency at the rates of 1/n or 1/n, with or without continuity constraints, respectively. The change-points estimated under the continuity constraints are also shown to asymptotically have a multivariate normal distribution. For the case where the regression mean functions are not assumed to be continuous at the change-points, the asymptotic distribution of the estimated change-points involves a step function process, whose distribution does not follow a well-known distribution.
Identifying psycho-social fingerprints in medical and engineering documents
Authors: Mateja Verlic, Gregor Stiglic, Peter Kokol
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Sentiment analysis enables new possibilities for classification of text documents by considering different aspects of sentiment, appraisal and other linguistic elements. Our psycho-social fingerprint approach to the text-classification is based on the General Inquirer dictionary of psycho-social categories and provides instant solution for text classification in quickly changing target domains, such as newsgroups.
A Note on the Relationship between Different Types of Correction Queries
Authors: Cristina Tîrnăucă
Venue: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications (2008)

The adult-child interaction which takes place during the child's language acquisition process has been the inspiration for Angluin's teacher-learner model [1], the forerunner of today's active learning field. But the initial types of queries have some drawbacks: equivalence queries are both unrealistic and computationally costly; membership queries, on the other hand, are not informative enough, not being able to capture the feedback received by the child when he or she makes mistakes. This is why a new type of query (called correction query), weaker than the first one and more informative than the second, appeared. While in the case of natural languages it is well understood what correcting means, in formal language theory different objects may require different types of corrections. Therefore, several types of correction queries have been introduced so far. In this paper we investigate the relations existing between different models of correction queries, as well as their connection to other well-known Gold-style and query learning models. The study comprises results obtained in the general case when time complexity issues are ignored, and in the restricted case when efficiency constraints are imposed.
Solving Dial-a-Ride Problems with a Low-Level Hybridization of Ants and Constraint Programming
Authors: Broderick Crawford, Carlos Castro, Eric Monfroy
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

This paper is about Set Partitioning formulation and resolution for a particular case of VRP, the Dial-a-ride Problem. Set Partitioning has demonstrated to be useful modeling this problem and others very visible and economically significant problems. But the main disadvantage of this model is the need to explicitly generate a large set of possibilities to obtain good solutions. Additionally, in many cases a prohibitive time is needed to find the exact solution. Nowadays, many efficient metaheuristic methods have been developed to make possible a good solution in a reasonable amount of time. In this work we try to solve it with Low-level Hybridizations of Ant Colony Optimization and Constraint Programming techniques helping the construction phase of the ants. Computational results solving some benchmark instances are presented showing the advantages of using this kind of hybridization.
Analysing Ontological Structures through Name Pattern Tracking
Authors: Ondřej Šváb-Zamazal, Vojtěch Svátek
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Concept naming over the taxonomic structure is a useful indicator of the quality of design as well as source of information exploitable for various tasks such as ontology refactoring and mapping. We analysed collections of OWL ontologies with the aim of determining the frequency of several combined name graph patterns potentially indicating underlying semantic structures. Such structures range from simple set-theoretic subsumption to more complex constructions such as parallel taxonomies of different entity types. The final goal is to help refactor legacy ontologies as well as to ease automatic alignment among different models. The results show that in most ontologies there is a significant number of occurrences of such patterns. Moreover, their detection even using very simple methods has precision sufficient for a semi-automated analysis scenario.
Numerical solution of ordinary differential equations via splines
Authors: Nejla Altay, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

In this work a numerical solution for a given first order linear Ordinary Differential Equation is obtained by High Dimensional Model Representation (HDMR). Although HDMR is commonly used for multivariate functions, univariate functions are considered through the work to trace everything more easily. The numerical solution is written in the form of a linear combination of first linear and then quadratic functions chosen in Hilbert Space. The unknown constants in that combination are determined in such a way that the constancy measurer becomes maximum.
Feature Extraction from the Mesh Model with Some Noise
Authors: Zhong Li, Lizhuang Ma, Zuoyong Zheng, Wuzheng Tan
Venue: Proceedings of the 8th international symposium on Smart Graphics (2007)

This paper presents a new feature extraction method on the mesh model with some noise. Firstly, we compute Mesh saliency value of every vertex on the mesh model. Then we set it as the weighted factor and employ the weighted bi-quadratic Bézier surface to fit the vertex and its neighborhood by the least square method. So we obtain the smoothed principal curvature and principal direction of every vertex, which can be used for detecting and extracting the feature point. The advantage of our method is that we can achieve the better feature extraction result from the mesh model with some noise.
Using Normal Bases for Compact Hardware Implementations of the AES S-Box
Authors: Svetla Nikova, Vincent Rijmen, Martin Schläffer
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

The substitution box (S-box) of the Advanced Encryption Standard (AES) is based on the multiplicative inversion s(x) = x ¿ 1 in GF(256) and followed by an affine transformation in GF(2). The S-box is the most expansive building block of any hardware implementation of the AES, and the multiplicative inversion is the most costly step of the S-box transformation. There exist many publications about hardware implementations of the S-box and the smallest known implementations are based on normal bases. In this paper, we introduce a new method to implement the multiplicative inversion over GF(256) based on normal bases that have not been considered before in the context of AES implementations.
A Hierarchical Approach to Object Comparison
Authors: Axel Hallez, Guy Tré
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

Comparing objects is a very general problem domain. The way objects are compared can differ a lot, in the way objects are related to each other as well as in the meaning that is attributed to the result of a comparison. In this paper we develop a theoretical framework for comparing objects. This framework can be tailored to the specific needs of an application through the choice of appropriate operators and evaluation domain (i.e. the domain in which the comparison results are expressed).
A Unique Microprcessor Instruction Set
Authors: Dennis Fairclough
Venue: IEEE Micro (1982)

New instruction sets have been based on traditather than on the application of scientific method. Here, the latter has yielded a simple, optimal, en-member instruction set.
Optimum Neural Network Construction Via Linear Programming Minimum Sphere Set Covering
Authors: Xun-Kai Wei, Ying-Hong Li, Yu-Fei Li
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

A novel optimum feedforward neural networks construction method was proposed. We first define a 0-1 covering matrix and propose an integer programming method for minimum sphere set covering problem. We then further define the extended covering matrix with smooth function, relax the objective and constraints to formulate a more general linear programming method for the minimum sphere set covering problem. We call this method Linear Programming Minimum Sphere set Covering (LPMSC). After that, we propose to apply the LPMSC method to neural network construction. With specific smooth functions, we can obtain optimum neural networks via LPMSC needless of prior knowledge, which is more objective and automatic like Support Vector Machines (SVM). Finally, we investigate the performances of the proposed method through UCI benchmark datasets compared with SVM. The parameters of SVM and our method are determined using 5-fold cross validation. Results shows that our method need less neurons than SVM while retain comparable even superior performances in the datasets studied.
Learning Coreference Resolution for Portuguese Texts
Authors: José Guilherme Souza, Patricia Nunes Gonçalves, Renata Vieira
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

This work presents the implementation of an automatic coreference resolution system based on supervised machine learning that is capable of processing any type of noun phrases for Portuguese. The system was trained and tested in a journalistic corpus formed by 50 texts with a total of 5047 markables. Both the induced classifier and the anaphoric clustering algorithm were evaluated using appropriate metrics. The clustering evalution was performed using the MUC and B 3 scorers.