ppxscal/embedding_network huggingface dataset:
Geosimulation in Education: A System for Teaching Police Resource Allocation
Authors: Vasco Furtado, Eurico Vasconcelos
Venue: International Journal of Artificial Intelligence in Education (2007)

This article describes the ExpertCop tutorial system. ExpertCop is a geosimulator of criminal dynamics in urban environments that aims to train police officers in the activity of preventive policing allocation. ExpertCop intends to i) help students comprehend the task of resources allocation and identify the variables involved; ii) induce students to reflect about their actions related to resources allocation; and iii) help students understand the relation between preventive policing and crime. In ExpertCop, the students (police officers) configure and allocate an available police force according to a selected geographic region, and then follow the simulation process. The students interpret the results with the aid of an intelligent tutor, the Pedagogical Agent, by observing how crime behaves in the presence of the allocated preventive policing. The interaction between domain agents representing social entities such as criminals and police teams allocated by the students drives the simulation. Assisting the user, the Pedagogical Agent aims to define interaction strategies between the student and the geosimulator in order to make simulated phenomena better understood. The innovative character of the work is in the strategy adopted by the Pedagogical Agent in order to assist the user in understanding the simulated model. It seeks to explain the model at the macro-level (global or emergent behavior) and micro-level (behavior of the agents individually). The evaluation of the system in training held with students of the domain has shown that the system attains its intended pedagogical goals.
Design and Implementation of the ScaLAPACK LU, QR, and Cholesky Factorization Routines
Authors: Jaeyoung Choi, Jack J. Dongarra, L. Susan Ostrouchov, Antoine P. Petitet, David W. Walker, R. Clint Whaley
Venue: Scientific Programming (1996)

This article discusses the core factorization routines included in the ScaLAPACK library. These routines allow the factorization and solution of a dense system of linear equations via LU, QR, and Cholesky. They are implemented using a block cyclic data distribution, and are built using de facto standard kernels for matrix and vector operations (BLAS and its parallel counterpart PBLAS) and message passing communication (BLACS). In implementing the ScaLAPACK routines, a major objective was to parallelize the corresponding sequential LAPACK using the BLAS, BLACS, and PBLAS as building blocks, leading to straightforward parallel implementations without a significant loss in performance. We present the details of the implementation of the ScaLAPACK factorization routines, as well as performance and scalability results on the Intel iPSC/860, Intel Touchstone Delta, and Intel Paragon System.
Mixed Integer Linear Programming for Maximum-Parsimony Phylogeny Inference
Authors: Srinath Sridhar, Fumei Lam, Guy E. Blelloch, R. Ravi, Russell Schwartz
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.
Non-linear test pattern generators for built-in self-test
Authors: Dandan Qi, Jon C. Muzio
Venue: International Journal of Communication Networks and Distributed Systems (2008)

Various linear finite state machines have been widely used as pseudo-random test pattern generators for the built-in self-test of integrated circuits. These generators are inexpensive to use as they have the advantage of low hardware overhead. However, the Geffe generator, a classic type of non-linear finite state machine, has not been frequently studied or used in similar applications. It is known that a Geffe generator, when used as a pattern generator for digital system testing gives improved fault detection. Unfortunately, the area overhead involved is sufficiently high, thus, such a generator becomes impractical for built-in self-test. To solve such problems, we introduce two possible new designs of the Geffe generator. These new designs are based on the generator's original architecture, so they preserve the non-linear structure. Our optimal goal is to achieve a very sharp reduction of the area overhead, and maintain a satisfactory fault detection capability. These two new designs are exercised in the fault simulations of benchmark sequential circuits. The experimental results demonstrate both of our designs can lead to fault coverage, which significantly exceeds the fault coverage of linear machines, and is comparable to the original Geffe generator.
Grid workflow optimization regarding dynamically changing resources and conditions
Authors: Erich Schikuta, Helmut Wanek, Irfan Ul Haq
Venue: Concurrency and Computation: Practice Experience (2008)

Automatic construction of workflows on the Grid is a challenging task. The problems that have to be solved are manifold: How can existing services be integrated into a workflow that is able to accomplish a specific task? How can an optimal workflow be constructed with respect to changing resource characteristics during the optimization process? How to cope with dynamically changing or incomplete knowledge of the goal function of the optimization process? and finally: How to react to service failures during workflow execution? In this paper, we propose a method to optimize a workflow based on a heuristic A* approach that allows to react to dynamics in the environment. Changes in the Grid infrastructure and in the users' requirements can be handled during the optimization process as well as during the execution of the workflow. Our algorithm also allows the workflow to recover from failing resources during the execution phase. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Massively parallel volume rendering using 2-3 swap image compositing
Authors: Hongfeng Yu, Chaoli Wang, Kwan-Liu Ma
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

The ever-increasing amounts of simulation data produced by scientists demand high-end parallel visualization capability. However, image compositing, which requires interprocessor communication, is often the bottleneck stage for parallel rendering of large volume data sets. Existing image compositing solutions either incur a large number of messages exchanged among processors (such as the direct send method), or limit the number of processors that can be effectively utilized (such as the binary swap method). We introduce a new image compositing algorithm, called 2-3 swap, which combines the flexibility of the direct send method and the optimality of the binary swap method. The 2-3 swap algorithm allows an arbitrary number of processors to be used for compositing, and fully utilizes all participating processors throughout the course of the compositing. We experiment with this image compositing solution on a supercomputer with thousands of processors, and demonstrate its great flexibility as well as scalability.
MOpiS: A Multiple Opinion Summarizer
Authors: Fotis Kokkoras, Efstratia Lampridou, Konstantinos Ntonas, Ioannis Vlahavas
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

Product reviews written by on-line shoppers is a valuable source of information for potential new customers who desire to make an informed purchase decision. Manually processing quite a few dozens, or even hundreds, of reviews for a single product is tedious and time consuming. Although there exist mature and generic text summarization techniques, they are focused primarily on article type content and do not perform well on short and usually repetitive snippets of text found at on-line shops. In this paper, we propose MOpiS, a multiple opinion summarization algorithm that generates improved summaries of product reviews by taking into consideration metadata information that usually accompanies the on-line review text. We demonstrate the effectiveness of our approach with experimental results.
Reusing Program Investigation Knowledge for Code Understanding
Authors: Martin P. Robillard, Putra Manggala
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

Software maintenance tasks typically involve an important amount of program investigation effort on the part of software developers. To what extent can we benefit from prior program investigation activities to decrease this effort? To investigate this question, we studied the revision history of two systems to determine how knowledge derived from prior investigation activities could have been reused to support other change tasks. Our initial investigation used a tool, ConcernDetector, that can recommend sets of program elements associated with a high-level concern when elements in the set overlap with elements currently being modified. We discovered that simple overlap-based techniques for retrieving prior investigation knowledge have important limitations, and that effective reuse of prior program investigation knowledge requires analyses that can partially infer the nature and intent of a task.
A Framework for Titled Document Categorization with Modified Multinomial Naivebayes Classifier
Authors: Hang Guo, Lizhu Zhou
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Titled Documents (TD) are short text documents that are segmented into two parts: Heading Part and Excerpt Part. With the development of the Internet, TDs are widely used as papers, news, messages, etc. In this paper we discuss the problem of automatic TDs categorization. Unlike traditional text documents, TDs have short headings which have less useless words comparing to their excerpts. Though headings are usually short, their words are more important than other words. Based on this observation we propose a titled document classification framework using the widely used MNB classifier. This framework puts higher weight on the heading words at the cost of some excerpt words. By this means heading words play more important roles in classification than the traditional method. According to our experiments on four datasets that cover three types of documents, the performance of the classifier is improved by our approach.
A Model-Based Framework for Security Policy Specification, Deployment and Testing
Authors: Tejeddine Mouelhi, Franck Fleurey, Benoit Baudry, Yves Traon
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

In this paper, we propose a model-driven approach for specifying, deploying and testing security policies in Java applications. First, a security policy is specified independently of the underlying access control language (OrBAC, RBAC). It is based on a generic security meta-model which can be used for early consistency checks in the security policy. This model is then automatically transformed into security policy for the XACML platform and integrated in the application using aspect-oriented programming. To qualify test cases that validate the security policy in the application, we inject faults into the policy. The fault model and the fault injection process are defined at the meta-model level, making the qualification process language-independent. Empirical results on 3 case studies explore both the feasibility of the approach and the efficiency of a full design test MDE process.
Automating Signature Evolution in Logical Theories
Authors: Alan Bundy
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

The automation of reasoning as deduction in logical theories is well established. Such logical theories are usually inherited from the literature or are built manually for a particular reasoning task. They are then regarded as fixed. We will argue that they should be regarded as fluid. 1 As Pólya and others have argued, appropriate representation is the key to successful problem solving [Pólya, 1945]. It follows that a successful problem solver must be able to choose or construct the representation best suited to solving the current problem. Some of the most seminal episodes in human problem solving required radical representational change. 1 Automated agents use logical theories called ontologies. For different agents to communicate they must align their ontologies. When a large, diverse and evolving community of autonomous agents are continually engaged in online negotiations, it is not practical to manually pre-align the ontologies of all agent pairs - it must be done dynamically and automatically. 1 Persistent agents must be able to cope with a changing world and changing goals. This requires evolving their ontologies as their problem solving task evolves. The W3C call this ontology evolution.
Catalysts and Inhibitors for Momentum in the Software Product Line Industry
Authors: Charles W. Krueger
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

For Software Product Line Engineering (SPLE) to become a standard and accepted practice in the industry, it must be widely embraced by large corporations, major software tool and service vendors, industry analysts, and technology press. We have seen steady but slow progress in all of these areas over the past few years. What can we do to better control or influence the future trends? Technology adoption at the industry scale is about building and sustaining momentum. Through a feedback loop comprising successes and failures, credible validation and invalidation, credible communication, leaps of faith, competitive opportunities, perceptions about perceptions, and so forth, momentum is gained or lost. Catalysts and inhibitors in the loop ultimately determine whether momentum will accelerate or be dampened. In this panel, we bring together an esteemed group of industry leaders from the key areas that impact momentum of new technology adoption, all of whom have been involved in the early stages of the industry's SPLE momentum. In this panel we will search for insights across a broad industry spectrum into the current catalysts and inhibitors, as well as opportunities for the Software Product Line Conference (SPLC) community to positively contribute to the momentum.
Research on Personalized Community E-Learning Recommendation Service System by Using Adaptive Filtering Algorithm
Authors: Liang Zhao, Qi Luo
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

To meet the needs of education in the learning community, an adaptive filtering algorithm for teaching resources based on vector space model was proposed in the paper. First, feature selection and pseudo feedback were used to select the initial filtering profiles and thresholds through training algorithm. Then user feedback was utilized to modify the profiles and thresholds adaptively through filtering algorithm. The algorithm had two advantages, the first was that it could carry on self-study to improve the precision; the second was that the execution did not need massive initial texts in the process of filtering. The result manifested that the algorithm was effective.
Evolving in Real Time a Neural Net Controller of Robot-Arm: Track and Evolve
Authors: Ahmed Lehireche, Abdellatif Rahmoune
Venue: Informatica (2004)

Evolutionary Engineering (EE) is defined to be &ldquo;the art of using evolutionary algorithms approach such as genetic algorithms to build complex systems&rdquo;. This paper deals with a neural net based system. It analyses ability of genetically trained neural nets to control Simulated robot arm, witch tries to track a moving object. In difference from classical Approaches neural network learning is performed on line, i.e., in real time. Usually systems are built/evolved, i.e., genetically trained separately of their utilization. That is how it is commonly done. It's a fact that evolution process is heavy on time; that's why Real-Time approach is rarely taken into consideration. The results presented in this paper show that such approach (Real-Time EE) is possible. These successful results are essentially due to the &ldquo;continuity&rdquo; of the target's trajectory. In EE terms, we express this by the Neighbourhood Hypothesis (NH) concept.
VoiceXML and the W3C Speech Interface Framework
Authors: James A. Larson
Venue: IEEE MultiMedia (2003)

VoiceXML is a markup language for creating voice-user interfaces. It uses speech and telephone touchtone recognition for input and prerecorded audio and text-to-speech synthesis (TTS) for output. It's based on the World Wide Web Consortium's (W3C's) Extensible Markup Language (XML) and leverages the Web paradigm for application development and deployment. By having a common language, application developers, platform vendors, and tool providers all can benefit from code portability and reuse.
MOBAIS: A Bayesian Artificial Immune System for Multi-Objective Optimization
Authors: Pablo A. Castro, Fernando J. Zuben
Venue: Proceedings of the 7th international conference on Artificial Immune Systems (2008)

Significant progress has been made in theory and design of artificial immune systems (AISs) for solving multi-objective problems accurately. However, an aspect not yet widely addressed by the research reported in the literature is the lack of ability of the AIS to deal effectively with building blocks (high-quality partial solutions coded in the antibody). The available AISs present mechanisms for evolving the population that do not take into account the relationship among the variables of the problem, causing the disruption of these high-quality partial solutions. Recently, we proposed a novel immune-inspired approach for single-objective optimization as an attempt to avoid this drawback. Our proposal replaces the traditional mutation and cloning operators with a probabilistic model, more specifically a Bayesian network representing the joint distribution of promising solutions and, subsequently, uses this model for sampling new solutions. Now, in this paper we extend our methodology for solving multi-objective optimization problems. The proposal, called Multi-Objective Bayesian Artificial Immune System (MOBAIS), was evaluated in the well-known multi-objective Knapsack problem and its performance compares favorably with that produced by contenders such as NSGA-II, MISA, and mBOA.
Bound for the L2 Norm of Random Matrix and Succinct Matrix Approximation
Authors: Rong Liu, Nian Yan, Yong Shi, Zhengxin Chen
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

This work furnished a sharper bound of exponential form for the L 2 norm of an arbitrary shaped random matrix. Based on the newly elaborated bound, a non-uniform sampling method was developed to succinctly approximate a matrix with a sparse binary one and hereby to relieve the computation loads in both time and storage. This method is not only pass-efficient but query-efficient also since the whole process can be completed in one pass over the input matrix and the sampling and quantizing are naturally combined in a single step.
Fuzzy C-Means Segmentation on Brain MR Slices Corrupted by RF-Inhomogeneity
Authors: Edoardo Ardizzone, Roberto Pirrone, Orazio Gambino
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Brain MR Images corrupted by RF-Inhomogeneity exhibit brightness variations in such a way that a standard Fuzzy C-Means (fcm) segmentation algorithm fails. As a consequence, modified versions of the algorithm can be found in literature, which take into account the artifact. In this work we show that the application of a suitable pre-processing algorithm, already presented by the authors, followed by a standard fcm segmentation achieves good results also. The experimental results ones are compared with those obtained using SPM5, which can be considered the state of the art algorithm oriented to brain segmentation and bias removal.
Edge-Based Data Structures for Solid Modeling in Curved-Surface Environments
Authors: Kevin Weiler
Venue: IEEE Computer Graphics and Applications (1985)

CAD/CAM applications need quick and easy access to topological information about objects. Here, four structures for representing this information are evaluated for sufficiency, efficiency, and ease of implementation.
Constrained versions of Sauer's lemma
Authors: Joel Ratsaby
Venue: Discrete Applied Mathematics (2008)

Let [n]={1,...,n}. For a function h:[n]->{0,1}, x@?[n] and y@?{0,1} define by the width@w"h(x,y) of h at x the largest nonnegative integer a such that h(z)=y on x-a@?z@?x+a. We consider finite VC-dimension classes of functions h constrained to have a width @w"h(x"i,y"i) which is larger than N for all points in a sample @z={(x"i,y"i)}"1^@? or a width no larger than N over the whole domain [n]. Extending Sauer's lemma, a tight upper bound with closed-form estimates is obtained on the cardinality of several such classes.
The Penna Model for Biological Aging and Speciation
Authors: Suzana Moss de Oliveira, Jorge S. Sa Martins, Paulo Murilo C. de Oliveira, Karen Luz-Burgoa, Armando Ticona, Thadeu J. P. Penna
Venue: Computing in Science and Engineering (2004)

Recent results obtained by the application of the Penna model to problems of evolutionary theory are reviewed. The genesis of diploid organisms is studied and compared to other forms of polyploidity. The addition of phenotype-dependent selection and its consequences, considering ecological and/or sexual selection traits, are discussed. This addition made possible the analysis of the mechanism through which sympatric speciation may be driven by changes in the ecology, and the microscopic validation of the handicap principle.