ppxscal/embedding_network huggingface dataset:
Interactive Aggregation/Disaggregation Dichotomic Sorting Procedure for Group Decision Analysis Based on the Threshold Model
Authors: Andrej Bregar, József Györkös, Matjaž B. Jurič
Venue: Informatica (2008)

In this paper, a new multi-criteria decision-making procedure is presented, which captures preferential information in the form of the threshold model. It is based on the ELECTRE-like sorting analysis restricted by the localization principle, which enables high adaptability of the decision model and reduces the cognitive load imposed on the decision-makers. It lays the foundation for the introduction of three concepts that have been previously insufficiently supported by outranking methods - semiautomatic derivation of criteria weights according to the selective effects of discordance and veto thresholds, convergent group consensus seeking, and autonomous multi-agent negotiation. The interdependent principles are justified, and the methodological solutions underlying their implementation are provided.
Doubling: The Semantic Driving Force Behind Functional Categories
Authors: Hedde Zeijlstra
Venue: Logic, Language, and Computation: 6th International Tbilisi Symposium on Logic, Language, and Computation,TbiLLC 2005 Batumi, Georgia, September 12-16, 2005. Revised Selected Papers (2007)

In this paper I argue that the set of formal features that can head a functional projection is not predetermined by UG but derived through L1 acquisition. I formulate a hypothesis that says that every functional category F is realised as a semantic feature [F] unless there are overt doubling effects in the L1 input with respect to F; this feature is then analysed as a formal feature [i/uF]. In the first part of the paper I provide a theoretical motivation for this hypothesis, in the second part I test this proposal with a case study, namely the cross-linguistic distribution of Negative Concord (NC). I demonstrate that in NC languages negation must be analysed as a formal feature [i/uNEG], whereas in Double Negation languages this feature remains a semantic feature [NEG] (always interpreted as a negative operator), thus paving the way for an explanation of NC in terms of syntactic agreement. In the third part I argue that the application of the hypothesis to the phenomenon of negation yields two predictions that can be tested empirically. First I demonstrate how this hypothesis predicts negative markers Neg° can be available only in NC languages; second, independent change of the syntactic status of negative markers, can invoke a change with respect to the exhibition of NC in a particular language. Both predictions are proven to be correct. I finally argue what the consequences of the proposal presented in this paper are for both the syntactic structure of the clause and second for the way parameters are associated to lexical items.
High Quality Surface Mesh Generation for Multi-physics Bio-medical Simulations
Authors: Dominik Szczerba, Robert Mcgregor, Gábor Székely
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Manual surface reconstruction is still an everyday practice in applications involving complex irregular domains, necessary for modeling biological systems. Rapid development of biomedical imaging and simulation, however, requires automatic computations involving frequent re-meshing of (r)evolving domains that human-driven generation can simply no longer deliver. This bottleneck hinders the development of many applications of high social importance, like computational physiology or computer aided medicine. While many commercial packages offer mesh generation options, these depend on high quality input, which is rarely available when depending on image segmentation results. We propose a simple approach to automatically recover a high quality surface mesh from low-quality, oversampled and possibly non-consistent inputs that are often obtained via 3-D acquisition systems. As opposed to the majority of the established meshing techniques, our procedure is easy to implement and very robust against damaged or partially incomplete, inconsistent or discontinuous inputs.
Interval Subroutine Library Mission
Authors: George F. Corliss, R. Baker Kearfott, Ned Nedialkov, John D. Pryce, Spencer Smith
Venue: Reliable Implementation of Real Number Algorithms: Theory and Practice: International Seminar Dagstuhl Castle, Germany, January 8-13, 2006 Revised Papers (2008)

We propose the collection, standardization, and distribution of a full-featured, production quality library for reliable scientific computing with routines using interval techniques for use by the wide community of applications developers.
A Control-Theoretic Modeling Approach for Service Differentiation in Multi-hop Ad-hoc Networks
Authors: Yimeng Yang, Boudewijn R. Haverkort, Geert J. Heijenk
Venue: Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems (2008)

This paper proposes a control-theoretic modeling approach for service differentiation in multi-hop ad-hoc networks, in which a new priority scheme is applied by considering variable control gains and so-called Transmission Opportunity (TXOP) limits. The model is studied and evaluated based on an IEEE 802.11 DCF WLAN system using the well-known 20-sim dynamic system simulator. The use of the control-theoretical framework, as opposed to an ns-2 simulation, has as advantage that results are obtained much more quickly, and that the model remains much more structured and formalized. By means of the implemented model, the average queue length, queuing delay and network throughput can be evaluated. Simulation results show that our approach is able to satisfy QoS requirements of high-priority stations in both single-hop and multi-hop ad-hoc networks.
Inducing Regular Languages Using Grammar-Based Classifier System
Authors: Olgierd Unold
Venue: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications (2008)

This paper takes up the topic of a task of training Grammar-based Classifier System (GCS) to regular grammars from data. GCS is a new model of Learning Classifier Systems in which the population of classifiers has a form of a context-free grammar rule set in a Chomsky Normal Form. Near-optimal solutions or better than reported in the literature were obtained.
Business Process Modelling and Purpose Analysis for Requirements Analysis of Information Systems
Authors: Jose Luis Vara, Juan Sánchez, Óscar Pastor
Venue: Proceedings of the 20th international conference on Advanced Information Systems Engineering (2008)

Although requirements analysis is acknowledged as a critical success factor of information system development for organizations, problems related to the requirements stage are frequent. Some of these problems are lack of understanding of the business by system analysts, lack of focus on the purpose of the system, and miscommunication between business people and system analysts. As a result, an information system may not fulfil organizational needs. To try to prevent these problems, this paper describes an approach based on business process modelling and purpose analysis through BPMN and the goal/strategy Map approach. The business environment is modelled in the form of business process diagrams. The diagrams are validated by end-users, and the purpose of the system is then analyzed in order to agree on the effect that the information system should have on the business processes. Finally, requirements are specified by means of the description of the business process tasks to be supported by the system.
Designing for privacy and self-presentation in social awareness
Authors: Mika Raento, Antti Oulasvirta
Venue: Personal and Ubiquitous Computing (2008)

Social awareness applications are based on the idea of a group sharing real-time context information via personal and ubiquitous terminals. Studies of such applications have shown that users are not only concerned with the preservation privacy through non-disclosure. Instead, disclosure is manipulated for the constant presentation of self to the group in everyday social situations. Basing on 3 years of research with the mobile social awareness system ContextContacts, established findings in social psychology and ubiquitous computing, we propose a number of design principles to support users in this management of privacy and presentation. These principles are to apply even if disclosure is automated, and include support for lightweight permissions, assuming reciprocity, appearing differently to different audiences, providing for feedback on presentation and allowing lying. These principles are applied in interaction design and protocol engineering for the next version of a mobile awareness system called ContextContacts.
Multilingual Plagiarism Detection
Authors: Zdenek Ceska, Michal Toman, Karel Jezek
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

Multilingual text processing has been gaining more and more attention in recent years. This trend has been accentuated by the global integration of European states and the vanishing cultural and social boundaries. Multilingual text processing has become an important field bringing a lot of new and interesting problems. This paper describes a novel approach to multilingual plagiarism detection. We propose a new method called MLPlag for plagiarism detection in multilingual environment. This method is based on analysis of word positions. It utilizes the EuroWordNet thesaurus which transforms words into language independent form. This allows to identify documents plagiarized from sources written in other languages. Special techniques, such as semantic-based word normalization, were incorporated to refine our method. It identifies the replacement of synonyms used by plagiarists to hide the document match. We performed and evaluated our experiments on monolingual and multilingual corpora and results are presented in this paper.
Improved Multilabel Classification with Neural Networks
Authors: Rafał Grodzicki, Jacek Mańdziuk, Lipo Wang
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

This paper considers the multilabel classification problem, which is a generalization of traditional two-class or multi-class classification problem. In multilabel classification a set of labels (categories) is given and each training instance is associated with a subset of this label-set. The task is to output the appropriate subset of labels (generally of unknown size) for a given, unknown testing instance. Some improvements to the existing neural network multilabel classification algorithm, named BP-MLL, are proposed here. The modifications concern the form of the global error function used in BP-MLL. The modified classification system is tested in the domain of functional genomics, on the yeast genome data set. Experimental results show that proposed modifications visibly improve the performance of the neural network based multilabel classifier. The results are statistically significant.
Selecting Features and Objects for Mixed and Incomplete Data
Authors: Yenny Villuendas-Rey, Milton García-Borroto, José Ruiz-Shulcloper
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Selecting objects and features before classifying is a very important task, and can lead to big improvements in classifier accuracy and speed. There are many papers about this topic, but few of them consider the simultaneous or combined approach. In this paper, we present a new method for combined object and feature selection for databases with features not purely numeric or non-numeric. The experiments performed show that it attains the best tradeoff between object and feature reduction in 12 of 15 tested databases, without a significant impact in 1-NN accuracy.
N-rationality of a certain class of formal series
Authors: Sylvain Lavallée
Venue: Information Processing Letters (2008)

A series of the form (1-ax+bx^k)^-^1, where a@?N, b@?Z and k>=2@?N is N-rational if and only if (k-1)^k^-^1a^k-k^kb>=0.
Brief Announcement: Local-Spin Algorithms for Abortable Mutual Exclusion and Related Problems
Authors: Robert Danek, Hyonho Lee
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

A mutual exclusion (ME) algorithm consists of a trying protocol (TP) and exit protocol (EP) that surround a critical section (CS) and satisfy the following properties: mutual exclusion: at most one process is allowed to use the CS at a given time; lockout freedom: any process that enters the TP eventually enters the CS; and bounded exit: a process can complete the EP in a bounded number of its own steps. A First-Come-First-Served (FCFS) ME algorithm [1] additionally requires processes to enter the CS in roughly the order in which they start the TP. Once a process has started executing the TP of a ME algorithm, it has committed itself to entering the CS, since the correctness of the algorithm may depend on every process properly completing its TP and EP.
Quantifier Elimination for Approximate Factorization of Linear Partial Differential Operators
Authors: Elena Kartashova, Scott Mccallum
Venue: Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference (2007)

This paper looks at the feasibility of applying the quantifier elimination program QEPCAD-B to obtain quantifier-free conditions for the approximate factorization of a simple hyperbolic linear partial differential operator (LPDO) of order 2 over some given bounded rectangular domain in the plane. A condition for approximate factorization of such an operator to within some given tolerance over some given bounded rectangular domain is first stated as a quantified formula of elementary real algebra. Then QEPCAD-B is applied to try to eliminate the quantifiers from the formula. While QEPCAD-B required too much space and time to finish its task, it was able to find a partial solution to the problem. That is, it was able to find a nontrivial quantifier-free sufficient condition for the original quantified formula.
Risk Based Authorisation for Mobile Ad Hoc Networks
Authors: Nilufer Tuptuk, Emil Lupu
Venue: Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management (2007)

Mobile ad hoc networks (MANETs) do not share the properties of traditional wired networks, as mobile nodes are more vulnerable to security attacks. Detection of selfish, malicious or faulty nodes presents security challenges that are not encountered traditionally in wired networks. The nodes in the network need to identify, and take the necessary security measures to protect their resources against these malicious nodes. We propose a risk-based authorisation model to help build ad-hoc trust relationships, capturing the dynamic behaviour of the entities with time, and ensuring the sharing of trust information through recommendations.
Informational Technologies for Further Education of Latvian Province Teachers of Informatics
Authors: Jurijs Lavendels, Vjaceslavs Sitikovs, Kaspars Krauklis
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

This is a review of the procedure, technologies and process of further educational courses within the framework of the ESF project "Informational Technologies for Further Education of Latvian Province Teachers of Informatics". The objective of these courses is to clarify the method of teaching of algorithmization and basic programming in secondary schools. The technological realization of the courses was based on online e-teaching using costless VoIP Skype network based software. Summarizing results of e-teaching courses imperfection considerations regarding unsolved problems of virtual communication as a new way of cooperation were made.
Clonal Selection-Based Neural Classifier
Authors: A. Lanaridis, V. Karakasis, A. Stafylopatis
Venue: Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems (2008)

Artificial Immune Systems (AIS) constitute an emerging and promising field, and have been applied to pattern recognition and classification tasks to a limited extent so far. This work is a first attempt of applying the clonal selection principle to the training of Multi-Layer Perceptrons (MLPs). The Clonal Selection based Neural Classifier (CSNC) uses the basic concepts of clonal selection to evolve MLPs, which are represented as real-valued linear antibodies. The proposed system is actually a multi-classifier, consisting of multiple sets of MLPs, each one devoted to the recognition of a different class of the input data. The final trained classifier is comprised of the best MLPs from each set. The proposed classifier is tested against a set of benchmark problems and yields promising results.
Towards automatic generation of AXML web services for dynamic data integration
Authors: Vânia Vidal, Fernando Lemos, Fábio Porto
Venue: Proceedings of the 2008 EDBT workshop on Database technologies for handling XML information on the web (2008)

Active XML (AXML, in short) provides a declarative framework for data and service integration over the Web. In this paper, we present a framework for generation of AXML Web services for materializing the dynamic content of Web pages in data intensive Web sites. In our framework, the dynamic content of a Web page is defined as a (virtual) view, and the view is specified with the help of a set of correspondence assertions, which specifies the semantic mapping between the XML view schema and the base sources schemas. This paper focuses on an algorithm that automatically generates, based on the view's correspondence assertions, the Web service that materializes the view's content.
Guided Test Generation from CSP Models
Authors: Sidney Nogueira, Augusto Sampaio, Alexandre Mota
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

We introduce an approach for the construction of feature test models expressed in the CSP process algebra, from use cases described in a controlled natural language. From these models, our strategy automatically generates test cases for both individual features and feature interactions, in the context of an industrial cooperation with Motorola Inc., where each feature represents a mobile device functionality. The test case generation can be guided by test purposes, which allow selection based on particular traces of interest. More generally, we characterise a testing theory in terms of CSP: test models, test purposes, test cases, test execution, test verdicts and soundness are entirely defined in terms of CSP processes and refinement notions. We have also developed a tool, ATG, which mechanises the entire generation process.
Optimization of Feature Processing Chain in Music Classification by Evolution Strategies
Authors: Igor Vatolkin, Wolfgang Theimer
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

In this paper a new method based on evolution strategies (ES) is presented to optimize a classifier for personal music categories. The user assigns songs to multiple personal music categories: Examples from each category are selected in order to train a category-specific classifier using musical features as input. The classifier then ranks all songs according to their similarity to the category examples. Since an exhaustive search for parameters maximizing the classifier performance is not feasible an ES is applied. The experiments show a significant performance increase for various music categories due to the ES optimization.
Proceedings of the 9th ACM SIGITE conference on Information technology education
Venue: Conference On Information Technology Education (formerly CITC) (2008)

With great pleasure, we welcome you to the 9th ACM SIG-Information Technology Education Conference -- SIGITE 2008. This year's conference continues its tradition of being the premier forum for presentation of research results and classroom experience regarding the pillars of information technology education: programming, networking, web technologies, resource management and human-computer interaction. Our mission is to share novel, practical and generally applicable pedagogical approaches to all topics in IT education, demonstrate effective bridges between academia and industry, and provide an environment conducive to peer discussion, student engagement and institutional cooperation. The call for papers attracted 76 full-paper submissions from all over the world. The program committee accepted 39 papers and 9 posters that cover a variety of topics, including general IT Education as well as online education issues, IT Curriculum Development in Programming and System Design, and Accreditation issues. Panels include a session devoted to exploring concerns around the involvement of women in IT and IT education, the formalization of an IT research agenda and standardizing network diagrams. We have a very full conference and look forward to your participation.
Verification of the Document Components from Dual Extraction of MRTD Information
Authors: Young-Bin Kwon, Jeong-Hoon Kim
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

This paper proposes a method for character region extraction and picture separation in a passport by adopting a preprocessing phase for the passport recognition system. Character regions required for the recognition make black pixel and remainder of the passport regions makes white pixel in the detected character spaces. This method uses the MRZ sub-region in order to automatically calculate the threshold value of the binary image which is also applied to the other character regions. This method also applies horizontal/ vertical histogram projection in order to remove the picture region from the binary image. After region detection of picture area, the image part of the passport is stored in the database of face images. The remainder of the passport is composed of character part. Recognition on the extracted character is performed on the various different passports. From the obtained information, auto-correlation of extracted characters within a given passport are accomplished after character recognition. A cross-check process of MRZ information and field information of passport on similarity is implemented. For this purpose, this paper uses the auto-correlation between the binarization method based on the color information and an extracted image from a passport to propose a characteristic extraction method to prevent passport forgery.