ppxscal/embedding_network huggingface dataset:
Massive user enabled evolving web systems
Authors: Stephen Lu
Venue:  (2008)

User-Generated Content Websites [1], or "social media" Websites [2], such as YouTube [3] or Flickr [4], have gained tremendous success for their ability to use user-generated meta-content to further their user experience. However, current UGC developments resemble the ad-hoc Web developments of the 1990s and Software developments of the 1960s [5]. Past history has shown what these approaches can lead to, and there are already failed UGC developments caused by these uninformed approaches. In this thesis, the research will be geared towards finding a theoretical framework that target the unique behavior of UGCs, and discovering means to remedy their problems and complexities. The ad-hoc approaches to UGC developments are caused by a lack of fundamental understanding these systems' behaviors. This work will illustrate that these UGCs are Massive User Enabled Evolving Web Systems (MUEEWS), where user-generated meta-content are used to evolve system functionalities. By making users a key stakeholder in enabling its functionalities, MUEEWS creates an evolution that occurs during the usage phase of the software. Current Software and Web Engineering models do not explain the effects of this phenomenon [6], and current UGC research target specific applications that are difficult to apply extensively. Since the evolutions of the functionalities are dependent on the contributions of very large group, MUEEWS contains a number of collective action issues that can create system failures. The lack of fundamental understanding creates many complexities for MUEEWS in both the development and usage phase. Therefore, for the improvement of future MUEEWS developments, this work will provide a theoretical framework to guide its development and manage its complexities. The theoretical framework is evaluated using functional complexity analysis and validated through simulations and test scenarios. The findings illustrate that the application of the theoretical framework can greatly reduce the probability of system failure in MUEEWS and can improve its meta-content and system functionality performances. This thesis focuses on the users' contributions, and how to leverage those contributions to improve system functionality. Since the current field of UGC is not focused on theoretical or system approaches of MUEEWS, this research topic can be used to make various important contributions to the field of UGC.
Maintaining Generalized Arc Consistency on Ad-hoc n-ary Boolean Constraints
Authors: Kenil C. K. Cheng, Roland H. C. Yap
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)

Binary decision diagrams (BDDs) can compactly rep-resent ad-hoc n-ary Boolean constraints. However, there is no gen-eralized arc consistency (GAC) algorithm which exploit BDDs. For example, the global case constraint by SICStus Prolog for ad-hoc constraints is designed for non-Boolean domains. In this paper, we introduce a new GAC algorithm, bddc, for BDD constraints. Our empirical results demonstrate the advantages of a new BDD-based global constraint --bddc is more efficient both in terms of mem-ory and time than the case constraint when dealing with ad-hoc Boolean constraints. This becomes important as the size of the ad-hoc constraints becomes large.
Exploring technologies for building collaborative learning communities among diverse student populations
Authors: Nicole Anderson, Chi-Cheng Lin
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

Collaborative learning has long been recognized as an effective approach to enhance the learning process. The purpose of this research was to investigate mechanisms for building an inclusive collaborative learning community outside the classroom that connects students with diverse backgrounds and ultimately enhances students' learning experience. To accomplish this, we conducted a study using blogs and user groups to support virtual collaborative communities in our upper division computer science courses. Our results show that blogs are an effective tool for bringing together these diverse student groups to create an inclusive learning environment.
Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey
Authors: Asaf Shabtai, Robert Moskovitch, Yuval Elovici, Chanan Glezer
Venue: Information Security Tech. Report (2009)

This research synthesizes a taxonomy for classifying detection methods of new malicious code by Machine Learning (ML) methods based on static features extracted from executables. The taxonomy is then operationalized to classify research on this topic and pinpoint critical open research issues in light of emerging threats. The article addresses various facets of the detection challenge, including: file representation and feature selection methods, classification algorithms, weighting ensembles, as well as the imbalance problem, active learning, and chronological evaluation. From the survey we conclude that a framework for detecting new malicious code in executable files can be designed to achieve very high accuracy while maintaining low false positives (i.e. misclassifying benign files as malicious). The framework should include training of multiple classifiers on various types of features (mainly OpCode and byte n-grams and Portable Executable Features), applying weighting algorithm on the classification results of the individual classifiers, as well as an active learning mechanism to maintain high detection accuracy. The training of classifiers should also consider the imbalance problem by generating classifiers that will perform accurately in a real-life situation where the percentage of malicious files among all files is estimated to be approximately 10%.
Jacobi&#x2019;s bound for independent systems of algebraic partial differential equations
Authors: M. V. Kondratieva, A. V. Mikhalev, E. V. Pankratiev
Venue: Applicable Algebra in Engineering, Communication and Computing (2009)

In this paper we prove Jacobi’s bound for systems of n partial differential polynomials in n differential variables, which are independent over a prime differential ideal . This generalizes on the one hand our result (Kondratieva et al. in On Jacobi’s bound for systems of differential polynomials, algebra. Moscow University Press, Moscow, pp 79–85, 1982) about Jacobi’s bound for ordinary differential polynomials independent over a prime differential ideal and, on the other hand, the result by Tomasovic (A generalized Jacobi conjecture for arbitrary systems of algebraic differential equations. PhD thesis, Columbia University, 1976), who proposed a version of Jacobi’s bound for partial differential polynomials and proved it in the linear case. In Kondratieva et al. (Differential and difference dimension polynomials, Kluwer, Dordrecht, 1999) we gave another proof of this result by Tomasovic. The exposition in the present paper follows our proof in Kondratieva et al. (Differential and difference dimension polynomials, Kluwer, Dordrecht, pp 273–280, 1999).
Automatic generation of instruction sequences for software-based self-test of processors and systems-on-a-chip
Authors: Jacob A. Abraham
Venue:  (2008)

At-speed functional tests are an important part of the manufacturing test flow of processors. With delay defects becoming more common due to the properties of the newer process technologies, at-speed functional tests have become indispensable. Traditionally, functional tests needed expensive automatic testing equipment due to the memory and speed requirements associated. This cost issue was solved by native-mode testing which uses the intelligence of the processor to test itself. In the native-mode self-test (also known as software-based self-test) paradigm, instruction sequences are loaded into the cache to test the processor for defects. Generally, only random instructions are used in native-mode tests. As with any random sequence based testing, there are faults that are left undetected by random instructions. Manual effort is necessary to generate the tests that can detect those faults, requiring a detailed knowledge of the instruction set architecture and the micro-architecture of the processor. We propose an automatic technique that alleviates the need for such manual effort. Our technique has a hierarchical approach. We use traditional automatic test pattern generation (ATPG) algorithms for generating tests at the local level (module or combinational blocks). These tests are mapped to instructions at the global level using a verification engine. We also have feedback between these two levels for more efficient testing. We demonstrate the technique on a publicly available processor. We then enhance the technique to test an entire system-on-a-chip (SOC). A typical SOC has an embedded processor. We use this embedded processor to test the other blocks in the SOC. In general, most of these blocks are designed by the design reuse methodology. Therefore, these blocks may be available only as black-boxes. Our technique is well suited to test such blocks. We use existing test vectors for the core and present a technique that generates instruction sequences that when executed by the processor generates the given vectors at the boundaries of the blocks. We designed an SOC using an ARM core and a publicly available encryption core and experimented on it to demonstrate the effectiveness of our technique.
A framework to refine particle clusters produced by EMAN
Authors: Liya Fan, Fa Zhang, Gongming Wang, Zhiyong Liu
Venue: Bioinformatics (2009)

Motivation: EMAN is one of the most popular software packages for single particle reconstruction. But the particle clusters produced during its model refining stage are of low qualities. We attempt to refine the particle clusters by more accurately determining orientations of particles, and thereby achieving higher resolutions of consequent 3D structures. Results: A particle reclustering framework (PRF) is introduced, which consists of three components. Each of them is responsible for one of the basic tasks of PRF: normalization, threshold determination and reclustering. Our implementation is also described and proved to meet the constraints proposed by PRF. Experiments revealed that our implementation improved resolutions of consequent structures for most cases, but only a little extra execution time was incurred. Therefore, it is practical to incorporate PRF in EMAN to improve qualities of generated 3D structures. Availability and Implementation: Implementation of our algorithm is available upon request from the authors. Contact:fanliya@ict.ac.cn; zf@ncic.ac.cn
Estimation of Boar Sperm Status Using Intracellular Density Distribution in Grey Level Images
Authors: Lidia Sánchez, Nicolai Petkov
Venue: Similarity-Based Clustering: Recent Developments and Biomedical Applications (2009)

In this work we review three methods proposed to estimate the fraction of alive sperm cells in boar semen samples. Images of semen samples are acquired, preprocessed and segmented in order to obtain images of single sperm heads. A model of intracellular density distribution characteristic of alive cells is computed by averaging a set of images of cells assumed to be alive by veterinarian experts. We quantify the deviation of the distribution of a cell from this model and use it for classification deploying three different approaches. One is based on a decision criterion used for single cell classification and gives misclassification error of 20.40%. The other two methods are focused on estimating the fraction of alive sperm in a sample, instead of single cell classification. One of them applies the least squares method, achieving an absolute error below 25% for 89% of the considered sample images. The other uses an iterative procedure to find an optimal decision criterion that equalizes the number of misclassifications of alive and dead cells. It provides an estimation of the fraction of alive cells that is within 8% of its actual value for 95% of the samples.
VHDL 2008: Just the New Stuff
Authors: Peter J. Ashenden, Jim Lewis
Venue: Systems On Silicon (2007)

VHDL-2008: Just the New Stuff, as its title says, introduces the new features added to the latest revision of the IEEE standard for the VHDL hardware description language. Written by the Chair and Technical Editor of the IEEE working group, the book is an authoritative guide to how the new features work and how to use them to improve design productivity. It will be invaluable for early adopters of the new language version, for tool implementers, and for those just curious about where VHDL is headed. * First in the market describing the new features of VHDL 2008;* Just the new features, so existing users and implementers can focus on what's new; * Helps readers to learn the new features soon, rather than waiting for new editions of complete VHDL reference books. * Authoritative, written by experts in the area; * Tutorial style, making it more accessible than the VHDL Standard Language Reference Manual.
Fuzzy Sets and Their Extensions: Representation, Aggregation and Models Intelligent Systems from Decision Making to Data Mining, Web Intelligence and ..., 1st edition
Authors: Humberto Bustince, Francisco Herrera, Javier Montero
Venue: Studies In Fuzziness And Soft Computing (2007)

This carefully edited book presents an up-to-date state of current research in the use of fuzzy sets and their extensions, paying attention to foundation issues and to their application to four important areas where fuzzy sets are seen to be an important tool for modelling and solving problems. The book contains 34 chapters divided into two parts. The first part is divided into two sections. Section 1 contains four review papers introducing some non standard representations that extend fuzzy sets (type-2 fuzzy sets, Atanassovs IFS, fuzzy rough sets and computing with words under the fuzzy sets perspective). Section 2 reviews different aggregation issues from a theoretical and practical point of view; this second part is divided into four sections. Section 3 is devoted to decision making, with seven papers that show how fuzzy sets and their extensions are an important tool for modelling choice problems. Section 4 includes eight papers that cover different aspects on the use of fuzzy sets and their extensions in data mining, giving an illustrative review of the state of the art on the topic. Section 5 is devoted to the emergent topic of web intelligence and contains four papers that show the use of fuzzy sets theory in some problems that can be tackled in this topic. Section 6 is devoted to the use of fuzzy sets and their extensions in the field of computer vision, suggesting how these can be an useful tool in this area. This volume will be extremely useful to any non-expert reader who is keen to get a good overview on the latest developments in this research field. It will also support those specialists who wish to discover the latest resultsand trends in the abovementioned areas.
An agent-based commodity trading simulation
Authors: Shih-Fen Cheng, Yee Pin Lim, Chao-Chih Liu
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In recent years, the study of trading in electronic markets has received significant amount of attention, particularly in the areas of artificial intelligence and electronic commerce. With increasingly sophisticated technologies being applied in analyzing information and making decisions, fully autonomous software agents are expected to take up significant roles in many important fields. This trend is most obvious in the financial domain, where speed of reaction is highly valued and significant investments have been made in information and communication technologies.
Crystal-growth-inspired algorithms for computational grids
Authors: Yuriy Brun, Nenad Medvidovic
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

Biological systems surpass man-made systems in many important ways. Most notably, systems found in nature are typically self-adaptive and self-managing, capable of surviving drastic changes in their environments, such as internal failures and malicious attacks on their components. Large distributed software systems have requirements common to those of some biological systems, particularly in the number and power of individual components and in the qualities of service of the system. However, it is not immediately clear how engineers can extract useful properties from natural systems and inject them into software systems. In this paper, we explore the nature's process of crystal growth and develop mechanisms inspired by that process for designing large distributed computational grid systems. The result is the tile architectural style, a set of design principles for building distributed software systems that solve complex computational problems. Systems developed using the tile style scale well to large computations, tolerate faults and malicious attacks, and preserve the privacy of the data.
Understanding Variation in Managers' Ambidexterity: Investigating Direct and Interaction Effects of Formal Structural and Personal Coordination Mechanisms
Authors: Tom J. M. Mom, Frans A. J. van den Bosch, Henk W. Volberda
Venue: Organization Science (2009)

Previous research focuses on firm and business unit level ambidexterity. Therefore, conceptual and empirically validated understanding about ambidexterity at the individual level of analysis is very scarce. This paper addresses this gap in the literature by investigating managers' ambidexterity, delivering three contributions to theory and empirical research on ambidexterity: first, by proposing three related characteristics of ambidextrous managers; second, by developing a model and associated hypotheses on both the direct and interaction effects of formal structural and personal coordination mechanisms on managers' ambidexterity; and third, by testing the hypotheses based on a sample of 716 business unit level and operational level managers. Findings regarding the formal structural mechanisms indicate that a manager's decision-making authority positively relates to this manager's ambidexterity, whereas formalization of a manager's tasks has no significant relationship with this manager's ambidexterity. Regarding the personal coordination mechanisms, findings indicate that both the participation of a manager in cross-functional interfaces and the connectedness of a manager to other organization members positively relate to this manager's ambidexterity. Furthermore, results show positive interaction effects between the formal structural and personal coordination mechanisms on managers' ambidexterity. The paper's theoretical contributions and empirical results increase our understanding about managers' ambidexterity and about how different types and combinations of coordination mechanisms relate to variation in managers' ambidexterity.
SIM-DLA: A Novel Semantic Similarity Measure for Description Logics Reducing Inter-concept to Inter-instance Similarity
Authors: Krzysztof Janowicz, Marc Wilkes
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

While semantic similarity plays a crucial role for human categorization and reasoning, computational similarity measures have also been applied to fields such as semantics-based information retrieval or ontology engineering. Several measures have been developed to compare concepts specified in various description logics. In most cases, these measures are either structural or require a populated ontology. Structural measures fail with an increasing expressivity of the used description logic, while several ontologies, e.g., geographic feature type ontologies, are not populated at all. In this paper, we present an approach to reduce inter-concept to inter-instance similarity and thereby avoid the canonization problem of structural measures. The novel approach, called SIM-DLA, reuses existing similarity functions such as co-occurrence or network measures from our previous SIM-DL measure. The required instances for comparison are derived from the completion tree of a slightly modified DL-tableau algorithm as used for satisfiability checking. Instead of trying to find one (clash-free) model, the new algorithm generates a set of proxy individuals used for comparison. The paper presents the algorithm, alignment matrix, and similarity functions as well as a detailed example.
Stable free surface flows with the lattice Boltzmann method on adaptively coarsened grids
Authors: Nils Th&#x00fc;rey, Ulrich R&#x00fc;de
Venue: Computing and Visualization in Science (2009)

In this paper we will present an algorithm to perform free surface flow simulations with the lattice Boltzmann method on adaptive grids. This reduces the required computational time by more than a factor of three for simulations with large volumes of fluid. To achieve this, the simulation of large fluid regions is performed with coarser grid resolutions. We have developed a set of rules to dynamically adapt the coarse regions to the movement of the free surface, while ensuring the consistency of all grids. Furthermore, the free surface treatment is combined with a Smagorinsky turbulence model and a technique for adaptive time steps to ensure stable simulations. The method is validated by comparing the position of the free surface with an uncoarsened simulation. It yields speedup factors of up to 3.85 for a simulation with a resolution of 4803 cells and three coarser grid levels, and thus enables efficient and stable simulations of free surface flows, e.g. for highly detailed physically based animations of fluids.
Nonlinear channel equalization for wireless communication systems using Legendre neural networks
Authors: Jagdish C. Patra, Pramod K. Meher, Goutam Chakraborty
Venue: Signal Processing (2009)

In this paper, we present a computationally efficient neural network (NN) for equalization of nonlinear communication channels with 4-QAM signal constellation. The functional link NN (FLANN) for nonlinear channel equalization which we had proposed earlier, offers faster mean square error (MSE) convergence and better bit error rate (BER) performance compared to multilayer perceptron (MLP). Here, we propose a Legendre NN (LeNN) model whose performance is better than the FLANN due to simple polynomial expansion of the input in contrast to the trigonometric expansion in the latter. We have compared the performance of LeNN-, FLANN- and MLP-based equalizers using several performance criteria and shown that the performance of LeNN is superior to that of MLP-based equalizer, in terms of MSE convergence rate, BER and computational complexity, especially, in case of highly nonlinear channels. LeNN-based equalizer has similar performance as FLANN in terms of BER and convergence rate but it provides significant computational advantage over the FLANN since the evaluation of Legendre functions involves less computation compared to trigonometric functions.
Two-level compact implicit schemes for three-dimensional parabolic problems
Authors: Samir Karaa, Mohamed Othman
Venue: Computers Mathematics with Applications (2009)

We derive a class of two-level high-order implicit finite difference schemes for solving three-dimensional parabolic problems with mixed derivatives. The schemes are fourth-order accurate in space and second- or lower-order accurate in time depending on the choice of a weighted average parameter @m. Numerical results with @m=0.5 are presented to confirm the high accuracy of the derived scheme and to compare it with the standard second-order central difference scheme. It is shown that the improvement in accuracy does not come at a higher cost of computation and storage since it is possible to choose the grid parameters so that the present scheme requires less work and memory and gives more accuracy than the standard central difference scheme.