ppxscal/embedding_network huggingface dataset:
A Genetic Based Approach to the Type I Structure Identification Problem
Authors: Stelios E. Papadakis, Panagiotis Tzionas, Vassilis G. Kaburlasos, John B. Theocharis
Venue: Informatica (2005)

The problem of system input selection, dubbed in the literature as Type I Structure Identification problem, is addressed in this paper using an effective novel method. More specifically, the fuzzy curve technique, introduced by Lin and Cunningham (1995), is extended to an advantageous fuzzy surface technique; the latter is used for fast building a coarse model of the system from a subset of the initial candidate inputs. A simple genetic algorithm, enhanced with a local search operator, is used for finding an optimal subset of necessary and sufficient inputs by considering jointly more than one inputs. Extensive simulation results on both artificial data and real world data have demonstrated comparatively the advantages of the proposed method.
A Fault Prediction Model with Limited Fault Data to Improve Test Process
Authors: Cagatay Catal, Banu Diri
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Software fault prediction models are used to identify the fault-prone software modules and produce reliable software. Performance of a software fault prediction model is correlated with available software metrics and fault data. In some occasions, there may be few software modules having fault data and therefore, prediction models using only labeled data can not provide accurate results. Semi-supervised learning approaches which benefit from unlabeled and labeled data may be applied in this case. In this paper, we propose an artificial immune system based semi-supervised learning approach. Proposed approach uses a recent semi-supervised algorithm called YATSI (Yet Another Two Stage Idea) and in the first stage of YATSI, AIRS (Artificial Immune Recognition Systems) is applied. In addition, AIRS, RF (Random Forests) classifier, AIRS based YATSI, and RF based YATSI are benchmarked. Experimental results showed that while YATSI algorithm improved the performance of AIRS, it diminished the performance of RF for unbalanced datasets. Furthermore, performance of AIRS based YATSI is comparable with RF which is the best machine learning classifier according to some researches.
Researching on Multi-net Systems Based on Stacked Generalization
Authors: Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

Among the approaches to build a Multi-Net system, Stacked Generalization is a well-known model. The classification system is divided into two steps. Firstly, the level-0 generalizers are built using the original input data and the class label. Secondly, the level-1 generalizers networks are built using the outputs of the level-0 generalizers and the class label. Then, the model is ready for pattern recognition. We have found two important adaptations of Stacked Generalization that can be applyied to artificial neural networks. Moreover, two combination methods, Stacked and Stacked+, based on the Stacked Generalization idea were successfully introduced by our research group. In this paper, we want to empirically compare the version of the original Stacked Generalization along with other traditional methodologies to build Multi-Net systems. Moreover, we have also compared the combiners we proposed. The best results are provided by the combiners Stacked and Stacked+ when they are applied to ensembles previously trained with Simple Ensemble.
Histogram PCA
Authors: P. Nagabhushan, R. Pradeep Kumar
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Histograms are data objects that are commonly used to characterize media objects like image, video, audio etc. Symbolic Data Analysis (SDA) is a field which deals with extracting knowledge and relationship from such complex data objects. The current research scenario of SDA has contributions related to dimensionality reduction of interval kind data. This paper makes an important attempt to analyze a symbolic data set for dimensionality reduction when the features are of histogram type. The result of an in-depth analysis of such a histogram data set has lead to proposing basic arithmetic and definitions related to histogram data. The basic arithmetic has been used for dimensionality reduction modeling of histogram data set through Histogram PCA. The modeling procedure is demonstrated by experiments with 700x3 data, iris data and 80X data. The utility/applicability of Histogram PCA is validated by clustering the above data.
Fuzzy Information Fusion Algorithm of Fault Diagnosis Based on Similarity Measure of Evidence
Authors: Chenglin Wen, Yingchang Wang, Xiaobin Xu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In this paper, a fuzzy information fusion method of fault diagnosis based on evidence similarity measure is presented. First, because of the fuzziness of information received by sensors, membership functions are introduced to describe the fault template mode in model database and features extracted from sensor observations; then the degrees of matching between them are obtained using random set model of fuzzy information, which can be transformed into BPAs. Second, cosine similarity measure of evidence is introduced to compute confidence degree of evidence. Finally, original evidences are modified according to the confidence degree. The diagnosis results of rotor system show that the proposed method can improve the accuracy of decision-making.
A Comparison of Two Approaches to Classify with Guaranteed Performance
Authors: Stijn Vanderlooy, Ida G. Sprinkhuizen-Kuyper
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

The recently introduced transductive confidence machine approach and the ROC isometrics approach provide a framework to extend classifiers such that their performance can be set by the user prior to classification. In this paper we use the k-nearest neighbour classifier in order to provide an extensive empirical evaluation and comparison of the approaches. From our results we may conclude that the approaches are competing and promising generally applicable machine learning tools.
Approximation methods for the solution of quantum evolution equations at the zero fluctuation limit
Authors: Buket Benek, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

This paper is focused on the solution of a univariate quantum dynamical system that can be treated through the dynamics of expectation values of the position and momentum operators. This goal is realised by using the fluctuationlessness theorem. The concerned equations are matrix equations and derived using the wave function of the Schrödinger equation. The quality of the obtained approximated solution is tested by comparing it with the real solution for different n values.
DINDOW: Towards an Interaction Based on Spatio-temporal Memory
Authors: Jesús Ibáñez, Oscar Serrano, David García
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

This paper describes the design and development of a novel system which allows non experienced users to easily interact with digital information and other users. In particular, the system allows the user to receive, handle and send media elements (pictures, text messages, videos). Instead of employing the file system to interact with information, the user interface promotes a kind of interaction which relies on spatial and temporal memory, which we believe to be more adequate.
Resource Discovery Based on VIRGO P2P Distributed DNS Framework
Authors: Lican Huang
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

Resource discovery plays an important role on scientific workflows in large scalable network environment. This paper presents a resource discovery framework based on VIRGO P2P Distributed DNS. With the convention of resource name as the format--- functionscheme":" global-hier-part"/"local-name, this framework supports flexible queries using partial keywords and wildcards, and range queries by a SQL-like query statement. The global-hier-part is managed by registers the same as DNS servers except the extension of RRs. The DNS servers construct n-tuple overlay virtual hierarchical overlay network of VIRGO. With cached addresses of DNS servers, the overload of traffic in tree structure can be avoided. The time complexity, space complexity and message-cost of lookup with this framework is O(L), where L is the number of sub domains in Domain Name. 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
Analyzing Peer Interactions in Computer-Supported Collaborative Learning: Model, Method and Tool
Authors: Yanyan Li, Ronghuai Huang
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

One of the most important facets in CSCL research is the interaction between individual and collaborative learning activities. This paper proposes a holistic and complementary analysis model of the collaborative interactions base on three dimensions --- process pattern, social relationship and topic space. By making use of content analysis, social network analysis and text mining technologies, asynchronous discussion transcripts are semi-automatically processed to address the questions concerned with peer interactions in collaborative learning: what are they talking about, who are talking to whom, and how do they talking with others. An integrated tool with comprehensive functionalities is designed and implemented to support collaborative interaction analysis with intelligence and visualization features. With the assistance of the tool, a case study is conducted to analyze the discussion records of a class composed of 18 graduate students who enrolled in a course along with online discussion in knowledge forum platform.
An Observational Model for Transactional Calculus of Services Orchestration
Authors: Jing Li, Huibiao Zhu, Jifeng He
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

The notion of web services orchestration provides a mean to specify a process model governing business rules to provide a value-added service. The task of building orchestrations requires mechanisms to deal with business transactions so as to truly increase the consistency and reliability of services. Business transactions have distinguishable features from traditional transactions, such as autonomous and interactive, so that it is highly suggested to be constructed by compensable transactions. In this paper, we formally address the problem for orchestrating services, with particular attention to the transaction issue. We enhance our past work t-calculus by expanding the descriptions of basic actions which include data computations and communications. On the other hand, the enriched calculus is equipped with an observational semantics which is more suitable to characterize transactions with several behavioral aspects. Under this model, we are able to investigate the equivalence relation for justifying algebraic laws, as well as refinement relation for supporting stepwise service development.
Shyness and the internet: Social problem or panacea?
Authors: Peter Lee Saunders, Andrea Chester
Venue: Computers in Human Behavior (2008)

Shyness is a debilitating experience for a large proportion of the population. Shyness can be defined as a form of excessive self-focus, a preoccupation with one's thoughts, feelings, and physical reactions and may vary from mild social awkwardness to total social inhibition. This article explores shyness, its prevalence and effects and examines the role of the internet in the experience and expression of shyness. Compared to research on shyness in the offline world, empirical work on shyness online is relatively scarce. Nevertheless, the research that does exist can be categorized into two seemingly contradictory positions. The first position views the internet as an isolating medium, attractive to shy people and enhancing shyness. The second position describes the internet as an empowering medium, offering opportunities to experience disinhibition and social competence. This paper considers how the two positions might be reconciled. In addition, in order to reduce inconsistencies in the literature and to determine how shy people use the internet, it is suggested that more research, incorporating objective measures and experimental methodologies, is needed.
Relax or Study?: A Qualitative User Study on the Usage of Mobile TV and Video
Authors: Koji Miyauchi, Taro Sugahara, Hiromi Oda
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

The usage of mobile TV and video devices is now spreading in Japan as well as in other countries. We conducted a user study to know when, how and why people were using the devices through qualitative interviews. In this paper, we showed one of the findings from this user study, that is, different attitudes concerning the usage of live mobile TV compared with that of mobile video on commuter buses or trains.
COMET(s), A Software Architecture Style and an Interactors Toolkit for Plastic User Interfaces
Authors: Alexandre Demeure, Gaëlle Calvary, Karin Coninx
Venue: Interactive Systems. Design, Specification, and Verification: 15th International Workshop, DSV-IS 2008 Kingston, Canada, July 16-18, 2008 Revised Papers (2008)

Plasticity of User Interfaces (UIs) refers to the ability of UIs to withstand variations of context of use (<User, Platform, Environment>) while preserving usability. This paper presents COMET, a software architecture style for building task-based plastic interactors. COMET bridges the gap between two main approaches in plasticity: model-driven engineering and interactors toolkits. Interactors that are compliant to the COMET style are called COMETs. These COMETs are multi-rendering multi-technological interactors (WIMP and post-WIMP, Web and non Web as well as vocal). COMETs are extensible and controllable by the user (up until now the designer, in the future the end-user). The COMET architecture and the use of COMETs are illustrated on an executable prototype: a slide viewer called CamNote++.
Minimal Deductive Systems for RDF
Authors: Sergio Muñoz, Jorge Pérez, Claudio Gutierrez
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

This paper presents a minimalist program for RDF, by showing how one can do without several predicates and keywords of the RDF Schema vocabulary, obtaining a simpler language which preserves the original semantics. This approach is beneficial in at least two directions: (a) To have a simple abstract fragment of RDFS easy to formalize and to reason about, which captures the essence of RDFS; (b) To obtain algorithmic properties of deduction and optimizations that are relevant for particular fragments. Among our results are: the identification of a simple fragment of RDFS; the proof that it encompasses the main features of RDFS; a formal semantics and a deductive system for it; sound and complete deductive systems for their sub-fragments; and an ${\cal O}(n \log n)$ complexity bound for ground entailment in this fragment.
Modeling and Simulation of Continuous Time-Invariant Systems in Simulation Based Learning Environments
Authors: Gang Chen, Yi Li, Jinyang Shi
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

Simulation based learning environments are widely used in elementary and secondary science education. However, a large number of these learning environments are domain-dependent so that they are only useful in some special domains. In this paper, we put forward a new method of simulating continuous time-invariant systems by using frame based knowledge representation and interpretive structural modeling. This method is helpful to realize the separation of knowledge representation and simulation program, and promotes the reusability of a simulation based learning environment.
Recognition of facial expressions using Gabor wavelets and learning vector quantization
Authors: Shishir Bashyal, Ganesh K. Venayagamoorthy
Venue: Engineering Applications of Artificial Intelligence (2008)

Facial expression recognition has potential applications in different aspects of day-to-day life not yet realized due to absence of effective expression recognition techniques. This paper discusses the application of Gabor filter based feature extraction in combination with learning vector quantization (LVQ) for recognition of seven different facial expressions from still pictures of the human face. The results presented here are better in several aspects from earlier work in facial expression recognition. Firstly, it is observed that LVQ based feature classification technique proposed in this study performs better in recognizing fear expressions than multilayer perceptron (MLP) based classification technique used in earlier work. Secondly, this study indicates that the Japanese Female Facial Expression (JAFFE) database contains expressers that expressed expressions incorrectly and these incorrect images adversely affect the development of a reliable facial expression recognition system. By excluding the two expressers from the data set, an improvement in recognition rate from 87.51% to 90.22% has been achieved. The present study, therefore, proves the feasibility of computer vision based facial expression recognition for practical applications like surveillance and human computer interaction.
Covering Heterogeneous Educative Environments with Integrated Editions in the Electronic Work
Authors: Miguel A. Martínez-Prieto, Pablo Fuente, Jesús Vegas, Joaquín Adiego
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

Although e-books usage has a positive impact in educational environments, contents representation is a complex issue given their audience. In this paper, we show a flexible and functional appearance that allows a synchronized consultation of the literary editions integrated in an electronic work.
On the design and implementation of a RISC processor extension for the KASUMI encryption algorithm
Authors: Tomas Balderas-Contreras, Rene Cumplido, Claudia Feregrino-Uribe
Venue: Computers and Electrical Engineering (2008)

Modern cellular networks allow users to transmit information at high data rates, have access to IP-based networks deployed around the world, and access to sophisticated services. In this context, not only is it necessary to develop new radio interface technologies and improve existing core networks to reach success, but guaranteeing confidentiality and integrity during transmission is a must. The KASUMI block cipher lies at the core of both the f8 data confidentiality algorithm and the f9 data integrity algorithm for Universal Mobile Telecommunications System networks. KASUMI implementations must reach high performance and have low power consumption in order to be adequate for network components. This paper describes a specialized processor core designed to efficiently perform the KASUMI algorithm. Experimental results show two orders of magnitude performance improvement over software only based implementations. We describe the used design technique that can also be applied to implement other Feistel-like ciphering algorithms. The proposed architecture was implemented on a FPGA, results are presented and discussed.
Do You Know How I Feel? Evaluating Emotional Display of Primary and Secondary Emotions
Authors: Julia Tolksdorf, Christian Becker-Asano, Stefan Kopp
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

In this paper we report on an empirical study on how well different facial expressions of primary and secondary emotions [2] can be recognized from the face of our emotional virtual human Max [1]. Primary emotions like happiness are more primitive, onto-genetically earlier types of emotions, which are expressed by direct mapping on basic emotion display; secondary emotions like relief or gloating are considered cognitively more elaborated emotions and require a more subtle rendition. In order to validate the design of our virtual agent, which entails devising facial expressions for both kinds of emotion, we tried to find answers to the questions: How well can emotions be read from a virtual agent's face by human observers? Are there differences in the recognizability between more primitve primary and more cognitively elaborated secondary emotions?
Conjunctive Grammars and Alternating Pushdown Automata
Authors: Tamar Aizikowitz, Michael Kaminski
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

In this paper we introduce a variant of alternating pushdown automata, Synchronized Alternating Pushdown Automata, which accept the same class of languages as those generated by conjunctive grammars.
2D Image-based reconstruction of shape deformation of biological structures using a level-set representation
Authors: R. Fablet, S. Pujolle, A. Chessel, A. Benzinou, F. Cao
Venue: Computer Vision and Image Understanding (2008)

This paper copes with the reconstruction of accretionary growth sequence from images of biological structures depicting concentric ring patterns. Accretionary growth shapes are modeled as the level-sets of a potential function. Given an image of a biological structure, the reconstruction of the sequence of growth shapes is stated as a variational issue derived from geometric criteria. This variational setting exploits image-based information, in terms of the orientation field of relevant image structures, which leads to an original advection term. The resolution of this variational issue is discussed. Experiments on synthetic and real data are reported to validate the proposed approach.