ppxscal/embedding_network huggingface dataset:
How an "incoherent behavior" inside generic hardware component characterizes functional errors
Authors: Bruno Monsuez, Franck Védrine, Micaela Mayero, Nicolas Vallé
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Detecting functional errors on generic hardware components is often a complex task. This task becomes more complex in a componentwise approach when analyzing components without their embedded context that is the entire system description. In this paper, we propose a methodology that successfully detects just from the component's description a pure functional error that neither extensive tests nor formal methods could find.
Extending parameterized problem-tracing questions for Java with personalized guidance
Authors: I-Han Hsiao, Sergey Sosnovsky, Peter Brusilovsky
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

Problem-tracing questions are popular among teachers of various programming languages. In an assessment mode these questions allows to evaluate student knowledge of language semantics. In a self-assessment mode, they provide an excellent learning tool. A 2004 ITiCSE working group report [4] stressed the importance of this type of questions to build foundation of higher-level knowledge. Yet the use of problem-tracing questions is still limited due to a large authoring overhead. To resolve this bottleneck, we explored the idea of parameterized question generation [2]. We developed QuizPACK [1], a system which can generate parameterized problem-tracing questions for C programming language. We also developed QuizGuide [1], a personalized guidance system for QuizPACK, which models student knowledge and guides students individually to most appropriate questions to try. The results of our studies demonstrated that QuizPACK strongly benefits student knowledge and that QuizGuide personalized guidance technology increased student ability to answer questions correctly and encouraged them to use the system more extensively (which, in turn, positively impacted their knowledge) [1]. However, parameterized questions in area of C programming were not as diverse from the complexity point of view as parameterized questions explored in other areas such as physics [2]. As a result, it was left unclear whether personalized guidance technology can successfully guide students to a broader range of questions from relatively simple to very difficult. The work reported in this poster expands our work on parameterized questions to a more sophisticated domain of object-oriented Java programming, which allowed us to introduce questions of much broader. Capitalizing on our experience with QuizPACK, we developed QuizJET (Java Evaluation Toolkit), which supports authoring, delivery, and evaluation of parameterized questions for Java [3]. We also implemented JavaGuide system (Figure 1), which provides personalized guidance for QuizJET questions. We assessed the impact of adaptive navigation support to student work with questions of different complexity as well as the impact of this technology on weaker and stronger students. The results of two classroom studies indicate that personalized guidance encouraged students to use parameterized questions more extensively and also helped them to access right questions at the right time. Students were 2.5 times more likely to answer a quiz correctly with personalized guidance than without such it. In addition, we found that personalized guidance especially benefited weak students to achieve scores comparable with the scores of strong students on each complexity level of questions.
Three-Dimensional Polyhedra Can Be Described by&#x00a0;Three Polynomial Inequalities
Authors: Gennadiy Averkov, Martin Henk
Venue: Discrete Computational Geometry (2009)

Bosse et al. conjectured that for every natural number d&#x2265;2 and every d-dimensional polytope P in &#x211d; d , there exist d polynomials p 1(x),&#x2026;,p d (x) satisfying P={x&#x2208;&#x211d;d :p 1(x)&#x2265;0,&#x2026;,p d (x)&#x2265;0}. We show that every three-dimensional polyhedron can be described by three polynomial inequalities, which confirms the conjecture for the case d=3 but also provides an analogous statement for the case of unbounded polyhedra. The proof of our result is constructive.
An optimized B-spline method for solving singularly perturbed differential difference equations with delay as well as advance
Authors: Vivek Kumar, Kapil K. Sharma
Venue: Neural, Parallel Scientific Computations (2008)

The aim of this work is to present a numerical technique to approximate the solution of boundary value problems for singularly perturbed differential difference equations with delay as well as advance. Such type of problems are the ubiquitous in the mathematical modeling of various practical phenomena in biology and physics, such as in variational problems in control theory and first exit time problems in the modeling of the determination of expected time for the generation of action potential in nerve cells by random synaptic inputs in dendrites. Here, we present a second order convergent numerical scheme based on B-spline collocation. Analysis has also been carried out to establish the error estimate which shows that the method converges quadraticly. Finally, to support the predicted theory and to demonstrate the efficiency of the proposed method several numerical experiments are carried out and a comparison is made with existence method.
Stretchable fingernail sensors for measurement of fingertip force
Authors: Jumana M. Abu-Khalaf, Jung Woo Park, Debra J. Mascaro, Stephen A. Mascaro
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

This paper describes a novel stretchable fingernail sensor for measuring fingertip forces for human-computer interaction. The fingernail sensor uses photoplethysmography to measure the change in blood perfusion in the fingernail bed when the fingerpad touches a surface with various forces. The original fingernail sensor was rigidly attached to the human fingernail, necessitating a customized fabrication for each individual user. Using novel fabrication techniques, a new stretchable sensor has been developed, where optoelectronic components are embedded within a soft rubber substrate, connected by stretchable conductors. This stretchable sensor can conform to the two-dimensional curvature of any human finger, eliminating the need for individual customization. In this paper, we demonstrate the successful fabrication of a prototype sensor with two LEDs and two photodetectors
Incorporating Agent Negotiation to Promote Learning Effectiveness in an Adaptive Learning Environment
Authors: K. Robert Lai, Chung Hsien Lan
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This study proposes a constraint-based agent negotiation mechanism to enhance the learner-to-instructor interaction in order to promote learning effectiveness. Through the negotiation process, the instructor can reflect on the appropriateness of the learning sequences and adjust instructional goals, approaches and schemes by gradually perceiving the learners' feedback. The instructor can thus provide more adaptive teaching based on learners' specific needs. An illustrative example expresses that the proposed methodology can adjust the learning sequences according to learners' preferences and instructors' cognition. The experimental results indicated that the methodology could improve learning performance, enhance their learning motivation and increase the flexibility in learning.
An agent-based approach to component management
Authors: David Lillis, Rem Collier, Mauro Dragone, G. M. P. O'Hare
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

This paper details the implementation of a software framework that aids the development of distributed and self-configurable software systems. This framework is an instance of a novel integration strategy called SoSAA (SOcially Situated Agent Architecture), which combines Component-Based Software Engineering [15] and Agent-Oriented Software Engineering, drawing its inspiration from hybrid agent control architectures. The framework defines a complete construction process by enhancing a simple component-based framework with reasoning and self-awareness capabilities through a standardized interface. The capabilities of the resulting framework are demonstrated through its application to a non-trivial Multi Agent System (MAS). The system in question is a pre-existing Information Retrieval (IR) system that has not previously taken advantage of CBSE principles. In this paper we contrast these two systems so as to highlight the benefits of using this new hybrid approach. We also outline how component-based elements may be integrated into the Agent Factory agent-oriented application framework.
Modelo integral de evaluaci&oacute;n del gobierno electr&oacute;nico: un propuesta preliminar
Authors: Luis F. Luna-Reyes, J. Ramon Gil-Garcia, Georgina Romero
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

El uso de tecnolog&iacute;as de informaci&oacute;n y comunicaci&oacute;n se ha considerado como una importante estrategia de reforma gubernamental. Se plantean diversos beneficios que van desde la eficiencia y la eficacia hasta la transparencia y la mayor participaci&oacute;n democr&aacute;tica. Gobiernos en muchas partes del mundo han invertido grandes cantidades de recursos en proyectos de gobierno electr&oacute;nico, con la expectativa de obtener estos y otros resultados. Sin embargo, en muchos de los casos los resultados son limitados e incluso inexistentes. Es necesario tener un m&eacute;todo de medici&oacute;n y evaluaci&oacute;n que permita identificar los avances y problemas relacionados con el gobierno electr&oacute;nico. Basado en una revisi&oacute;n de la literatura existente y en el an&aacute;lisis de las mejores pr&aacute;cticas usadas hasta el momento, este art&iacute;culo propone un modelo multidimensional de medici&oacute;n del gobierno electr&oacute;nico, incluyendo ejemplos y propuestas para su operacionalizaci&oacute;n y usos pr&aacute;cticos.
CMO --An Ontological Framework for Academic Programs and Examination Regulations
Authors: Richard Hackelbusch
Venue: Proceeding of the 2008 conference on Information Modelling and Knowledge Bases XIX (2008)

Academic institutions release teaching and examination regulations in order to form the statutory framework of academic programs. Because of the fact that these regulations are worded using legal terminology and are often very complicated, students often do not know how to satisfy these laid down program requirements. This can lead to needlessly long study times. In addition, academic boards have to supply an amount of courses that fits the students' actual demand that is a difficult task because there is often only little information available. Frequent changes of those regulations and the existing of parallel valid different regulations of programs leading to the same degrees may aggravate these problems. In order to be able to offer software support to handle these problems, a computer-understandable representation of academic programs and their examination regulations is needed. In this paper, we present and explain our approach, based upon ontologies. It defines a meta-model that allows such semantic representations. Instantiations of the ontology can be used within a framework, e.g., to implement decision support systems that can help students to decide how they can satisfy the corresponding program requirements, or that can help academic boards to forecast the students' demand on certain courses, or examinations.
Multispectral Image Segmentation for Fruit Quality Estimation
Authors: Adolfo Martínez-Usó, Filiberto Pla, Pedro García-Sevilla
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

An unsupervised segmentation algorithm based on a multiresolution method is presented. This method uses variational functions as a segmentation criterion. The algorithm has been applied to multispectral images of fruits as a quality assessment application. In addition, due to the unsupervised nature of the procedure, it can be applied to real images in order to test the quality of these results.
Paper Annotation with Learner Models
Authors: Tiffany Y. Tang, Gordon McCalla
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

In this paper, we study some learner modelling issues underlying the construction of an e-learning system that recommends research papers to graduate students wanting to learn a new research area. In particular, we are interested in learner-centric and paper-centric attributes that can be extracted from learner profiles and learner ratings of papers and then used to inform the recommender system. We have carried out a study of students in a large graduate course in software engineering, looking for patterns in such “pedagogical attributes”. Using mean-variance and correlation analysis of the data collected in the study, four types of attributes have been found that could be usefully annotated to a paper. This is one step towards the ultimate goal of annotating learning content with full instances of learner models that can then be mined for various pedagogical purposes.
Multiscale basis optimization for darcy flow
Authors: Todd J. Arborgast
Venue:  (2007)

Simulation of flow through a heterogeneous porous medium with fine-scale features can be computationally expensive if the flow is fully resolved. Coarsening the problem gives a faster approximation of the flow but loses some detail. We propose an algorithm that obtains the fully resolved approximation but only iterates on a sequence of coarsened problems. The sequence is chosen by optimizing the shapes of the coarse finite element basis functions. As a stand-alone method, the algorithm converges globally and monotonically with a quadratic asymptotic rate. Computational experience indicates the number of iterations needed is independent of the resolution and heterogeneity of the medium. However, an externally provided error estimate is required; the algorithm could be combined as an accelerator with another iterative algorithm. A single &ldquo;inner&rdquo; iteration of the other algorithm would yield an error estimate; following it with an &ldquo;outer&rdquo; iteration of our algorithm would give a viable method.
A discriminant analysis of perceived attitudes toward statistics and profiles identification of statistics learners
Authors: Zamalia Mahmud
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

This study attempts to construct the profiles of two types of statistics learners: namely those with a positive and a negative attitude towards statistics. The contribution of this work lies in its attempt to characterize each profile of learner by relating to his/her perceived attitudes toward statistics, types of learners, mode of study, programme structure, age, gender and learners' evaluation towards the statistics course. Learners' attitudes toward statistics were measured using Attitudes Toward Statistics (ATS) instrument which comprised four dimensions, that is, Affect, Cognitive Competence, Value and Difficulty. These variables are examined as predictors that discriminate learners with positive and negative attitudes toward statistics. The results indicate that learners with positive attitudes can be reliably distinguished from learners with negative attitudes toward statistics across the four dimensions of ATS, types of learners, mode of study and learner's evaluation towards the course. This then can assist instructors to fine-tune their teaching methodologies to optimize the teaching and learning of statistics in the classroom.
Some Computational Problems Related to Pseudo-intents
Authors: Barış Sertkaya
Venue: Proceedings of the 7th International Conference on Formal Concept Analysis (2009)

We investigate the computational complexity of several decision, enumeration and counting problems related to pseudo-intents. We show that given a formal context and a subset of its set of pseudo-intents, checking whether this context has an additional pseudo-intent is in conp, and it is at least as hard as checking whether a given simple hypergraph is not saturated. We also show that recognizing the set of pseudo-intents is also in conp, and it is at least as hard as identifying the minimal transversals of a given hypergraph. Moreover, we show that if any of these two problems turns out to be conp-hard, then unless p = np, pseudo-intents cannot be enumerated in output polynomial time. We also investigate the complexity of finding subsets of a given Duquenne-Guigues Base from which a given implication follows. We show that checking the existence of such a subset within a specified cardinality bound is np-complete, and counting all such minimal subsets is #p-complete.
Evolving Computer Game Playing via Human-Computer Interaction: Machine Learning Tools in the Knowledge Engineering Life-Cycle
Authors: Dimitris Kalles, Christos Kalantzis
Venue: Proceeding of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (2008)

In this paper we review our work on the acquisition of game-playing capabilities by a computer, when the only source of knowledge comes from extended self-play and sparsely dispersed human (expert) play. We summarily present experiments that show how a reinforcement learning backbone coupled with neural networks for approximation can indeed serve as a mechanism of the acquisition of game playing skill and we derive game interestingness measures that are inexpensive and straightforward to compute, yet also capture the relative quality of the game playing engine. We draw direct analogues to classical genetic algorithms and we stress that evolutionary development should be coupled with more traditional, expert-designed paths. That way the learning computer is exposed to tutorial games without having to revert to domain knowledge, thus facilitating the knowledge engineering life-cycle.
Layered upward embedding of acyclic digraphs
Authors: Nassim Sohaee
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

A layered upward drawing of a directed acyclic graph is a plane drawing of the digraph in which nodes are embedded in parallel horizontal lines, called layers, and each directed edge is represented as a line segments increasing in the vertical direction. In this papers, first we prove that the minimum number of layers for layered upward embedding of a st-graph is one more than the length of longest path from source node s to sink node t. Then, we will discuss about the edge insertion process to find a super st-graph of any upward embeddable graph. Finally we will prove that minimum number of layers in layered upward embedding of any upward embeddable graph is one less than the length of longest path from s to t in its super st-graph.
Looking for Planning Problems Solvable in Polynomial Time via Investigation of Structures of Action Dependencies
Authors: Lukáš Chrpa, Roman Barták
Venue: Proceeding of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008 (2008)

There are a lot of planning techniques for solving planning problems and many of them solve the planning problems by 'brute force' even though some problems (or parts of them) are easy. An easy planning problem typically has a plan with a specific structure. The structure described in this paper is based on action dependencies that appear in plans. We are looking for such constraints that are in the plan structures that provide algorithms running in polynomial time.
Lung area extraction from X-ray CT images for computer-aided diagnosis of pulmonary nodules by using active contour model
Authors: Noriyasu Homma, Satoshi Shimoyama, Tadashi Ishibashi, Makoto Yoshizawa
Venue: WSEAS Transactions on Information Science and Applications (2009)

In this paper, we develop a lung area extraction technique from X-ray computed tomography (CT) images for computer-aided diagnosis (CAD) systems. In lung cancer cases, pulmonary nodules are typical pathological changes and thus they are the target to be detected by CAD systems. The isolated nodules can be detected more easily by CAD systems developed previously, while previous CAD systems are often hard to detect nonisolated nodules. The extraction technique can then be used for transforming the non-isolated pulmonary nodules connected to the walls of the chest into isolated ones. The technique proposed here is based on an active contour model, but such model is often trapped into a local optimum solution. To avoid the local optimum solutions, an essential core of the proposed technique is to select an appropriate initial contour by using an anatomical feature of the lung shape in X-ray CT slices. Some experimental results demonstrate the usefulness of the proposed technique for assisting the CAD systems to detect non-isolated nodules more accurately.
BioKI:Enzymes: an adaptable system to locate low-frequency information in full-text proteomics articles
Authors: Sabine Bergler, Jonathan Schuman, Julien Dubuc, Alexandr Lebedev
Venue: Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis (2006)

BioKI:Enzymes is a literature navigation system that uses a two-step process. First, full-text articles are retrieved from PubMed Central (PMC). Then, for each article, the most relevant passages are identified according to a set of user selected keywords, and the articles are ranked according to the pertinence of the representative passages.
An optimized sequential pattern matching methodology for sequence classification
Authors: Themis P. Exarchos, Markos G. Tsipouras, Costas Papaloukas, Dimitrios I. Fotiadis
Venue: Knowledge and Information Systems (2009)

In this paper we present a novel methodology for sequence classification, based on sequential pattern mining and optimization algorithms. The proposed methodology automatically generates a sequence classification model, based on a two stage process. In the first stage, a sequential pattern mining algorithm is applied to a set of sequences and the sequential patterns are extracted. Then, the score of every pattern with respect to each sequence is calculated using a scoring function and the score of each class under consideration is estimated by summing the specific pattern scores. Each score is updated, multiplied by a weight and the output of the first stage is the classification confusion matrix of the sequences. In the second stage an optimization technique, aims to finding a set of weights which minimize an objective function, defined using the classification confusion matrix. The set of the extracted sequential patterns and the optimal weights of the classes comprise the sequence classification model. Extensive evaluation of the methodology was carried out in the protein classification domain, by varying the number of training and test sequences, the number of patterns and the number of classes. The methodology is compared with other similar sequence classification approaches. The proposed methodology exhibits several advantages, such as automated weight assignment to classes using optimization techniques and knowledge discovery in the domain of application.