ppxscal/embedding_network huggingface dataset:
Towards an Adaptive Grid Scheduling: Architecture and Protocols Specification
Authors: Inès Thabet, Chihab Hanachi, Khaled Ghédira
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

Grid is known to be a heterogeneous, distributed and dynamic environment. In order to take fully advantages from grid power, Grid scheduling must take into consideration the environment's constraints and be adaptive. In this work, Grid architecture is fully rethought in terms of agents in order to implement a cooperative and adaptive scheduling. At a macro level, our architecture enables flexible cooperation among its components using high level interaction protocols. At the micro level, agents in charge of scheduling perform an adaptive behaviour since they are able to perceive their environment and its disturbances, to reason and to deliberate about the actions to undertake in order to adapt. This is made possible by the use of Belief-Desire-Intention mechanisms. For that purpose, we propose a conceptual model useful for the perception function. Also, a typology of adaptive rules useful for the deliberation step is given. Component's behaviour are specified and simulated with Petri-Nets.
Students' Understandings and Attitudes toward Group learning: An Empirical Study
Authors: Jianhua Zhao, David McConnell
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Group learning is a fundamental method to organise learners participating in a learning process, traditionally in the classroom-based environments, and recently in the web-based environments or the blended e-learning environments. The purpose of this study is to examine students' understandings and attitudes toward group learning in the blended e-learning environments in Chinese Higher Education Institutions (CHEIs). 20 students were involved in a course-“Computer in Education (I)” --and group learning was used to organise the relevant learning and teaching process in a blended e-learning environment. The methodology of this study is action research and the data were collected through questionnaire survey, group interview, and personal blogs. Students' understandings of group learning were examined and the results reveal big change from absence to familiarity between the beginning and the end of the course. This result also demonstrated that students' attitudes to group learning were positive.
Three extensional models of type theory
Authors: Benno Van den berg
Venue: Mathematical Structures in Computer Science (2009)

We compare three categorical models of type theory with extensional constructs: setoids over extensional type theory; setoids over intensional type theory and a certain free exact category (the free ‘ΠW-pretopos’). By studying the amount of choice available in these categories, we are able show that they are distinct.
The efficiency of real time sequences FFT computing
Authors: Costin Cepisca, Mircea Covrig, Sorin Dan Grigorescu, Nicolae Jula, Cornelia Cepisca
Venue: Proceedings of the 2nd conference on European computing conference (2008)

Fast Fourier Transform (FFT) computing may be improved using two ways: the first way consists in packing two separate real functions into the complex input array in such a way that their individual transforms can be separated from the result; the second method used to improve the FFT computation consists in packing the real input of length N array cleverly, without extra zeros, into a complex array having half of its length. In this paper an analysis of a combination of these two methods is performed and also a numerical simulation in order to detect the right conditions in which this method is applicable.
Component-Based Grid Programming Using the HOC-Service Architecture
Authors: Jan Dünnweber, Sergei Gorlatch
Venue: Proceeding of the 2005 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fourth SoMeT_W05 (2005)

Grids are a novel class of distributed systems that allow to seamlessly combine multiple resources of heterogeneous servers on the Internet for demanding applications. We deal with the challenging task of programming grid applications which have to meet the requirements of abstraction and interoperability. We present our concept of customizable Higher-Order Components (HOCs) whose parameters may be not only data but also mobile code units. We demonstrate how applications are built by customizing HOCs using code parameters and describe the HOC-SA --a service-oriented architecture for developing grid applications by composing HOCs. We show where HOC-SA ranges in the variety of currently available software component architectures. In presenting our implementation, we explain how HOC-SA exploits modern grid middleware such as the WSRF implementation in the latest Globus Toolkit while hiding its complexity from the user.
Collective revelation: a mechanism for self-verified, weighted, and truthful predictions
Authors: Sharad Goel, Daniel M. Reeves, David M. Pennock
Venue: Proceedings of the tenth ACM conference on Electronic commerce (2009)

Decision makers can benefit from the subjective judgment of experts. For example, estimates of disease prevalence are quite valuable, yet can be difficult to measure objectively. Useful features of mechanisms for aggregating expert opinions include the ability to: (1) incentivize participants to be truthful; (2) adjust for the fact that some experts are better informed than others; and (3) circumvent the need for objective, "ground truth" observations. Subsets of these properties are attainable by previous elicitation methods, including proper scoring rules, prediction markets, and the Bayesian truth serum. Our mechanism of collective revelation, however, is the first to simultaneously achieve all three. Furthermore, we introduce a general technique for constructing budget-balanced mechanisms-where no net payments are made to participants--that applies both to collective revelation and to past peer-prediction methods.
A multilevel additive Schwarz method for a hypersingular integral equation on an open curve with graded meshes
Authors: Matthias Maischak
Venue: Applied Numerical Mathematics (2009)

In this paper we present the additive Schwarz method for the hypersingular integral equation of the first kind in two dimensions for the h version of the Galerkin method on algebraically graded meshes. We prove that the condition number of the preconditioned system grows only polylogarithmically with respect to the number of unknowns. Our theoretical results are underlined by numerical experiments.
Constructing a new communication system by integrating the GSM to the satellites infrastructure
Authors: Muzhir Sh. Al-Ani, Basil M. Al-Kasasbeh, Rafa E. Al-Qutaish, Mohammad I. Muhairat
Venue: WSEAS TRANSACTIONS on COMMUNICATIONS (2009)

The current researches and industries are looking forward to integrate different technologies to get a global technology that offers all of the intended services in a simple way. In this paper, a new communications system is proposed to integrate the use of GSM over the available satellites infrastructures. The proposed communications system could be used to facilitates and get benefits of both systems (the GSM and Satellites) to achieve competitive services over the world. The proposed system is concentrated on a global communications system that served all over the world and gives some specialization and privacy for each country. Furthermore, this paper shows an algorithm on how to implement the GSM over satellite systems in an efficient, flexible, and cost-effective manner.
Asymptotic behavior of generalized processor sharing queues under subexponential assumptions
Authors: Marc Lelarge
Venue: Queueing Systems: Theory and Applications (2009)

We analyze the behavior of Generalized Processor Sharing (GPS) queues with heavy-tailed service times. We compute the exact tail asymptotics of the stationary workload of an individual class and give new conditions for reduced-load equivalence and induced burstiness to hold. We also show that both phenomena can occur simultaneously. Our proofs rely on the single big event theorem and new fluid limits obtained for the GPS system that can be of interest by themselves.
Three-State Financial Distress Prediction Based on Support Vector Machine
Authors: Hongshan Yao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

This paper examines the three-state financial distress prediction using support vector machine (SVM) and compares the classification results with the one using multinominal logit analysis(MLA).The results show that SVM provides better three-state classification than MLA. The model using SVM has better generalization than the model using MLA.
Posterior approximation by interpolation for bayesian inference in computationally expensive statistical models
Authors: Nikolay Bliznyuk
Venue:  (2008)

Markov Chain Monte Carlo (MCMC) is nowadays a standard approach to numerical computation of integrals of the posterior density it of the parameter vector &eta;. Unfortunately, Bayesian inference using MCMC is computationally intractable when it is expensive to evaluate. In this work, we develop practical methods that approximate it with radial basis functions (RBFs) and Gaussian processes (GPs) interpolants and use the resulting cheap-to-evaluate surfaces in MCMC. In Chapter 1, &pi; arises from a nonlinear regression model with transformation and dependence. To build the RBF approximation, we limit evaluation of the computationally expensive regression function to points chosen on a high posterior density (HPD) region found using a local quadratic approximation of log(&pi;) at its mode. We illustrate our approach on simulated data for a pollutant diffusion problem and study the frequentist coverage properties of credible intervals. In Chapter 2, we relax the assumptions about it made in Chapter 1 and develop a derivative-free procedure GRIMA to approximate the logarithm of &pi; using RBF interpolation over a HPD region of it estimated using the RBF surface. We use GRIMA for Bayesian inference in a computationally intensive nonlinear regression model for real measured streamflow data in the Town Brook watershed. In Chapter 3, we study statistical models where it is possible to identify a minimal subvector &beta; of &eta; responsible for the expensive computation in the evaluation of &pi;. We propose two approaches to approximate &pi; by interpolation that exploit this computational structure. Our primary contribution is derivation of a GP interpolant that provably improves over some of the existing approaches by reducing the effective dimension of the interpolation problem from dim(&eta;) to dim(&beta;). When dim(&eta;) is high but dim(&beta;) is low, this allows one to dramatically reduce the number of expensive evaluations necessary to construct an accurate approximation of &pi;. Our experiments indicate that our methods produce results similar to those when the true expensive posterior density is sampled by MCMC while reducing computational costs by well over an order of magnitude. 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
Compiling possibilistic knowledge bases
Authors: Salem Benferhat, Henri Prade
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

Possibilistic knowledge bases gather propositional formulas associated with degrees belonging to a linearly ordered scale. These degrees reflect certainty or priority, depending if the formulas encode pieces of beliefs or goals to be pursued. Possibilistic logic provides a simple format that turns to be useful for handling qualitative uncertainty, exceptions or preferences. The main result of the paper provides a way for compiling a possibilistic knowledge base in order to be able to process inference from it in polynomial time. The procedure is based on a symbolic treatment of the degrees under the form of sorted literals and on the idea of forgetting variables. The number of sorted literals that are added corresponds exactly to the number of priority levels existing in the base, and the number of binary clauses added in the compilation is also equal to this number of levels. The resulting extra compilation cost is very low.
Isomorphism classes of the hypergroups of type U on the right of size five
Authors: Mario De Salvo, Dario Fasino, Domenico Freni, Giovanni Lo Faro
Venue: Computers Mathematics with Applications (2009)

By means of a blend of theoretical arguments and computer algebra techniques, we prove that the number of isomorphism classes of hypergroups of type U on the right of order five, having a scalar (bilateral) identity, is 14751. In this way, we complete the classification of hypergroups of type U on the right of order five, started in our preceding papers [M. De Salvo, D. Freni, G. Lo Faro, A new family of hypergroups and hypergroups of type U on the right of size five, Far East J. Math. Sci. 26(2) (2007) 393-418; M. De Salvo, D. Freni, G. Lo Faro, A new family of hypergroups and hypergroups of type U on the right of size five Part two, Mathematicki Vesnik 60 (2008) 23-45; M. De Salvo, D. Freni, G. Lo Faro, On the hypergroups of type U on the right of size five, with scalar identity (submitted for publication)]. In particular, we obtain that the number of isomorphism classes of such hypergroups is 14865.
In-game help in the Tactical Language Training System
Authors: Prasan Samtani, W. Lewis Johnson
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Game-based learning software shows tremendous potential in its ability to motivate and engage learners. However, when giving pedagogical feedback in a game context, it is important to do so in a way that does not break a student's engagement and is not prone to abuse. This paper describes in-game help in the Tactical Language and Culture Training System, a tool designed to help learners rapidly acquire basic communicative skills in a foreign language and culture.
Overcoming the J-shaped distribution of product reviews
Authors: Nan Hu, Jie Zhang, Paul A. Pavlou
Venue: Communications of the ACM (2009)

Introduction While product review systems that collect and disseminate opinions about products from recent buyers (Table 1) are valuable forms of word-of-mouth communication, evidence suggests that they are overwhelmingly positive. Kadet notes that most products receive almost five stars. Chevalier and Mayzlin also show that book reviews on Amazon and Barnes & Noble are overwhelmingly positive. Is this because all products are simply outstanding? However, a graphical representation of product reviews reveals a J-shaped distribution (Figure 1) with mostly 5-star ratings, some 1-star ratings, and hardly any ratings in between. What explains this J-shaped distribution? If products are indeed outstanding, why do we also see many 1-star ratings? Why aren't there any product ratings in between? Is it because there are no "average" products? Or, is it because there are biases in product review systems? If so, how can we overcome them? The J-shaped distribution also creates some fundamental statistical problems. Conventional wisdom assumes that the average of the product ratings is a sufficient proxy of product quality and product sales. Many studies used the average of product ratings to predict sales. However, these studies showed inconsistent results: some found product reviews to influence product sales, while others did not. The average is statistically meaningful only when it is based on a unimodal distribution, or when it is based on a symmetric bimodal distribution. However, since product review systems have an asymmetric bimodal (J-shaped) distribution, the average is a poor proxy of product quality. This report aims to first demonstrate the existence of a J-shaped distribution, second to identify the sources of bias that cause the J-shaped distribution, third to propose ways to overcome these biases, and finally to show that overcoming these biases helps product review systems better predict future product sales. We tested the distribution of product ratings for three product categories (books, DVDs, videos) with data from Amazon collected between February--July 2005: 78%, 73%, and 72% of the product ratings for books, DVDs, and videos are greater or equal to four stars (Figure 1), confirming our proposition that product reviews are overwhelmingly positive. Figure 1 (left graph) shows a J-shaped distribution of all products. This contradicts the law of "large numbers" that would imply a normal distribution. Figure 1 (middle graph) shows the distribution of three randomly-selected products in each category with over 2,000 reviews. The results show that these reviews still have a J-shaped distribution, implying that the J-shaped distribution is not due to a "small number" problem. Figure 1 (right graph) shows that even products with a median average review (around 3-stars) follow the same pattern.
Exploiting Semantic Association To Answer 'Vague Queries'
Authors: Jianhan Zhu, Marc Eisenstadt, Dawei Song, Chris Denham
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

Although today's web search engines are very powerful, they still fail to provide intuitively relevant results for many types of queries, especially ones that are vaguely-formed in the user's own mind. We argue that associations between terms in a search query can reveal the underlying information needs in the users' mind and should be taken into account in search. We propose a multi-faceted approach to detect and exploit such associations. The CORDER method measures the association strength between query terms, and queries consisting of terms having low association strength with each other are seen as 'vague queries'. For a vague query, we use WordNet to find related terms of the query terms to compose extended queries, relying especially on the role of least common subsumers (LCS). We use relation strength between terms calculated by the CORDER method to refine these extended queries. Finally, we use the Hyperspace Analogue to Language (HAL) model and information flow (IF) method to expand these refined queries. Our initial experimental results on a corpus of 500 books from Amazon shows that our approach can find the right books for users given authentic vague queries, even in those cases where Google and Amazon's own book search fail.
Preliminary Analysis of the Effects of Pair Programming and Test-Driven Development on the External Code Quality
Authors: Lech Madeyski
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

Test-driven development (TDD) and pair programming (PP) are the key practices of eXtreme Programming methodology that have caught the attention of software engineers and researchers worldwide. One of the aims of the large experiment performed at Wroclaw University of Technology was to investigate the difference between test-driven development and the traditional, test-last develop-ment as well as pair programming and solo programming with respect to the external code quality. It appeared that the external code quality was lower when test-driven development was used instead of the classic, test-last software development approach in case of solo programmers (p=0.028) and pairs (p=0.013). There was no difference in the external code quality when pair programming was used instead of solo programming.
Visual programming language for bit-level concurrent programming: APECbits
Authors: Takashi Ajiro, Kensei Tsuchida
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

We designed and developed a visual programming language (VPL) APECbits that is based on the APEC (Asynchronous Program Elements Connection) model. The APEC model is a base model of computation for bit-level concurrent programming, which composes a network of operation elements called primitives connected by data carriers called carriers. The model can express bit-level concurrent computation briefly and diagrammatically. In particular, the model is suitable to express fine-grain concurrent programs such as virtual-machine emulators and multimedia applications. Programs are represented clearly by a new notion (function) called wireless edge, which reduces the number of crossed connection lines.
Numerical solution for Stokes' first problem for a heated generalized second grade fluid with fractional derivative
Authors: Chunhong Wu
Venue: Applied Numerical Mathematics (2009)

In this paper, we consider Stokes' first problem for a heated generalized second grade fluid with fractional derivative (SFP-HGSGF). An effective implicit numerical approximation scheme (INAS) for solving the SFP-HGSGF is presented. The stability and convergence of the numerical scheme are analyzed by the energy method. Some numerical examples are presented to show the application of the present technique. The numerical results exhibit the good performance of our theoretical analysis.
ABC-boost: adaptive base class boost for multi-class classification
Authors: Ping Li
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We propose abc-boost (adaptive base class boost) for multi-class classification and present abc-mart, an implementation of abc-boost, based on the multinomial logit model. The key idea is that, at each boosting iteration, we adaptively and greedily choose a base class. Our experiments on public datasets demonstrate the improvement of abc-mart over the original mart algorithm.
Semantic Modularity and Module Extraction in Description Logics
Authors: Boris Konev, Carsten Lutz, Dirk Walther, Frank Wolter
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

The aim of this paper is to study semantic notions of modularity in description logic (DL) terminologies and reasoning problems that are relevant for modularity. We define two notions of a module whose independence is formalised in a model-theoretic way. Focusing mainly on the DLs EL and ALC, we then develop algorithms for module extraction, for checking whether a part of a terminology is a module, and for a number of related problems. We also analyse the complexity of these problems, which ranges from tractable to undecidable. Finally, we provide an experimental evaluation of our module extraction algorithms based on the large-scale terminology SNOMED CT.
by chance enhancing interaction with large data sets through statistical sampling
Authors: Alan Dix, Geoff Ellis
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

The use of random algorithms in many areas of computer science has enabled the solution of otherwise intractable problems. In this paper we propose that random sampling can make the visualisation of large datasets both more computationally efficient and more perceptually effective. We review the explicit uses of randomness and the related deterministic techniques in the visualisation literature. We then discuss how sampling can augment existing systems. Furthermore, we demonstrate a novel 2D zooming interface - the Astral Telescope Visualiser, a visualisation suggested and enabled by sampling. We conclude by considering some general usability and technical issues raised by sampling-based visualisation.