ppxscal/embedding_network huggingface dataset:
FEATUREHOUSE: Language-independent, automated software composition
Authors: Sven Apel, Christian Kastner, Christian Lengauer
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Superimposition is a composition technique that has been applied successfully in many areas of software development. Although superimposition is a general-purpose concept, it has been (re)invented and implemented individually for various kinds of software artifacts. We unify languages and tools that rely on superimposition by using the language-independent model of feature structure trees (FSTs). On the basis of the FST model, we propose a general approach to the composition of software artifacts written in different languages, Furthermore, we offer a supporting framework and tool chain, called FEATUREHOUSE. We use attribute grammars to automate the integration of additional languages, in particular, we have integrated Java, C#, C, Haskell, JavaCC, and XML. Several case studies demonstrate the practicality and scalability of our approach and reveal insights into the properties a language must have in order to be ready for superimposition.
Wavelet-based multiresolution analysis of ridges for fingerprint liveness detection
Authors: Shankar Bhausaheb Nikam, Suneeta Agarwal
Venue: International Journal of Information and Computer Security (2009)

In this paper, a new wavelet-based perspiration detection algorithm is proposed for fingerprint liveness detection. It is based on processing time-series ridge lines in the wavelet domain. The existing perspiration detection algorithm proposed in the literature captures perspiration information by processing ridge lines in the time (spatial) domain. However, for some kinds of fingers (e.g., dry and perspiration-saturated fingers), changes in perspiration are minute. These changes are difficult to extract from the grey-level intensities processed in the time domain. Due to this, such fingers may be misclassified, thus reducing overall accuracy. In practice, we often encounter poor quality, dry or wet fingers. Therefore, it is necessary to take due care of such fingers, and have an enhanced algorithm that can process these fingers as well. To alleviate the problem, this paper discusses a new algorithm that processes time-series ridge lines using the multiresolution theory of wavelets. Major sweating changes are extracted at the coarse level, and then resolution is gradually increased to notice minute details. Such a coarse-to-fine strategy provides us with rich sweating information compared to that obtained directly from grey-level intensities in the time domain, which naturally leads to improved liveness results.
A comparative study of data transport protocols in wireless sensor networks
Authors: Faisal Karim Shaikh, Abdelmajid Khelil, Neeraj Suri
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Several proposals describing transport layer protocols for sensor networks appear in the literature. As each proposal is typically evaluated in the context of carefully selected parameters and scenarios, the benefits can be subjective. Also, given the limited details available of different proposals, it is difficult for developers of sensor network applications to select from the range of alternative transport protocols. This paper develops a common basis for evaluation of varied proposals. We first classify and review the existing protocols and evaluate them by measuring their performance in terms of responsiveness and efficiency in a conformal simulation environment and for a wide range of operational conditions. Common sources of poor performance are identified. Based on this experience, a set of design principles for the designers of applications and future transport protocols is presented.
Online Character Recognition using Regression Techniques
Authors: Nirup Reddy, R Kandan, K Shashikiran, Suresh Sundaram, A G. Ramakrishnan
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.
Use of voice input to enhance cursor control in mainstream gaming applications
Authors: Aidan Kehoe, Flaithri Neff, Ian Pitt
Venue: Universal Access in the Information Society (2009)

There are opportunities for use of voice input to enhance the effectiveness of continuous cursor control in mainstream gaming. This paper describes a program that uses voice input to manipulate the cursor gain parameter within the context of a game. For some use groups the ability to dynamically manipulate this parameter can be important in making games more accessible. The program makes use of readily-available speech technology, and can be used in conjunction with existing games.
Resonant frequency sensitive MEMS bandpass filter using capacitive sensing scheme
Authors: In-Hyouk Song, Yves-Alain Peter, Michel Meunier
Venue: Microsystem Technologies (2009)

This paper presents the theoretical and experimental behaviour of microelectromechanical bandpass filters. The proposed bandpass filter can detect frequencies of monitoring structures with high sensitivity using the resonant frequency of micro-resonator of sensor. The micro-resonator contains a proof mass and four supported beams fabricated using a bulk silicon micromachining technology on a silicon-on-insulator wafer. When applying an external force to the system, the device generates a capacitance change, which is converted into a voltage by an electrical circuitry. In good agreement with finite element simulations of the device, experimental results validate that the filter has a center frequency of about 3.3&#x00a0;kHz, a 3&#x00a0;dB bandwidth of 0.562&#x00a0;kHz and a quality factor Q of 5.9 in atmospheric pressure. This paper demonstrates a parallel-resonator filter to increase a monitoring bandwidth. A 3&#x00a0;dB bandwidth of the parallel filter is measured to be 1.25&#x00a0;kHz at atmospheric pressure.
Explanation of a Clustered Case Memory Organization
Authors: Albert Fornells, Eva Armengol, Elisabet Golobardes
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

One of the key issues in Case-Based Reasoning (CBR) is the efficient retrieval of cases when the case base is huge. In this paper we propose a case memory organization in two steps: 1) the case memory is organized using an unsupervised clustering technique, and 2) explanations for each cluster are constructed using all the cases associated to each one. The role of the explanations is twofold. On one hand they index the memory and allow CBR to do a selective retrieval. On the other hand, the explanation provide to the user additional information about why the cases have been both clustered together and retrieved.
A New Classification of Collectives
Authors: Zena Wood, Antony Galton
Venue: Proceeding of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008) (2008)

We are surrounded by collective phenomena, with examples existing on many levels of granularity. Despite our frequent experiences of such phenomena they seem to have been largely ignored within the field of ontology. In this paper, existing ontologies are examined to determine the extent to which they can adequately represent collective phenomena, and are found wanting in a number of important respects. Our goal is to find good ways of representing collective phenomena in a way which does justice to the often subtle relationship that exists between the view of a collective as a whole and its constitution as a plurality of individual participants. An important prerequisite for this is to determine the range of variation that exists within the broad class of collectives. A number of example collective phenomena have been studied to extract appropriate classification criteria. The results from this study are used to produce a new typology of collectives which is intended to establish a basis for the adequate treatment of collectives within an ontology. The paper concludes with a set of further research questions that have been raised during the development of the classification.
Attacks recognition using recurrent neural network
Authors: Araceli Barradas-Acosta, Eleazar Aguirre-Anaya, Mariko Nakano-Miytake Hector Perez-Meana
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

The influence of computer technology on the human activities has greatly increased during the last three decades, due to major developments in the VLSI technology. However this widespread use of computer equipments has generated computer a considerable increase of computer crimes. To reduce this problem it is necessary to carried out a network analysis using the computer network traffic. However the increase of network traffic is huge, doing the analysis of traffic data complicated. Thus it is required to develop an effective and automatic algorithm to carry out the traffic network analysis, facilitating I such way the expert forensic work. This paper proposes a network analysis algorithm using recurrent neural network that can analyze computer network attacks facilitating the evidence extraction. Proposed algorithm can reduce time and cost of forensic analysis.
Algorithms and Experiments for Clique Relaxations--Finding Maximum s-Plexes
Authors: Hannes Moser, Rolf Niedermeier, Manuel Sorge
Venue: Proceedings of the 8th International Symposium on Experimental Algorithms (2009)

We propose new practical algorithms to find degree-relaxed variants of cliques called s-plexes. An s-plex denotes a vertex subset in a graph inducing a subgraph where every vertex has edges to all but at most s vertices in the s-plex. Cliques are 1-plexes. In analogy to the special case of finding maximum-cardinality cliques, finding maximum-cardinality s-plexes is NP-hard. Complementing previous work, we develop combinatorial, exact algorithms, which are strongly based on methods from parameterized algorithmics. The experiments with our freely available implementation indicate the competitiveness of our approach, for many real-world graphs outperforming the previously used methods.
Review: Finite element-based approach to modeling heterogeneous objects
Authors: Su Wang, Nanfei Chen, Chin-Sheng Chen, Xinxiong Zhu
Venue: Finite Elements in Analysis and Design (2009)

Advances in materials and rapid prototyping technology, makes developing rapid-prototype heterogeneous parts possible. This paper proposes a finite element-based approach for modeling heterogeneous parts to facilitate rapid prototyping. In this approach, traditional geometrical and topological data are blended with materials information in the CAD model. It builds on a CAD system to create parts' geometry which is then subdivided into a set of tetrahedral finite elements. With this, the design problem of material distribution in the whole body can be handled at the finite element level. The material composition of each point inside a finite element is formulated in terms of four control nodes of the finite element and a blending function. Moreover, design rules for modeling heterogeneous parts are introduced in the paper, making the modeling solution more robust.
Mechanism design for task procurement with flexible quality of service
Authors: E. H. Gerding, A. Rogers, K. Larson, N. R. Jennings
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In this paper, we consider the problem faced by an agent contracting multiple self-interested service providers, that are able to flexibly manipulate their quality of service in order to maximise their own utility, to complete a single computational task. We extend an existing model of such service providers, and derive optimal task procurement mechanisms in the setting where the agent has full knowledge of the cost functions of these service providers (considering both simultaneously and sequentially procurement). We then extend these results to the incomplete information setting where the agent must elicit cost information from the service providers, and we characterise a family of incentive-compatible and individually-rational mechanisms. Sequential procurement always generates greater utility for an agent than simultaneous procurement, and contracting multiple providers is preferable to contracting just one.
Memory Representations in Rewriting Logic Semantics Definitions
Authors: Mark Hills
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

The executability of rewriting logic makes it a compelling environment for language design and experimentation; the ability to interpret programs directly in the language semantics develops assurance that definitions are correct and that language features work well together. However, this executability raises new questions about language semantics that don't necessarily make sense with non-executable definitions. For instance, suddenly the performance of the semantics, not just language interpreters or compilers based on the semantics, can be important, and representations must be chosen carefully to ensure that executing programs directly in language definitions is still feasible. Unfortunately, many obvious representations common in other semantic formalisms can lead to poor performance, including those used to represent program memory. This paper describes two different memory representations designed to improve performance: the first, which has been fully developed, is designed for use in imperative programs, while the second, still being developed, is intended for use in a variety of languages, with a special focus on pure object-oriented languages. Each representation is described and compared to the initial representation used in the language semantics, with thoughts on reuse also presented.
Generic versus Salient Region-Based Partitioning for Local Appearance Face Recognition
Authors: Hazım Kemal Ekenel, Rainer Stiefelhagen
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

In this paper, we investigate different partitioning schemes for local appearance-based face recognition. Five different salient region-based partitioning approaches are analyzed and they are compared to a generic partitioning scheme. Extensive experiments have been conducted on the AR, CMU PIE, FRGC, Yale B, and Extend Yale B face databases. The experimental results show that generic partitioning provides better performance than salient region-based partitioning schemes.
Representing Semantic Graphs in a Self-Organizing Map
Authors: Marshall R. Mayberry, Risto Miikkulainen
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

A long-standing problem in the field of connectionist language processing has been how to represent detailed linguistic structure. Approaches have ranged from the encoding of syntactic trees in Raam to the use of a mechanism to query meanings in a "gestalt layer". In this article, a technique called semantic self-organization is presented that allows for the optimal allocation and explicit representation of semantic dependency graphs on a Som-based grid. This technique has been successfully used in a connectionist natural language processing architecture called InSomNet to scale up the subsymbolic approach to represent sentences in the LinGO Redwoods HPSG Treebank drawn from the VerbMobil Project and annotated with rich semantic information. InSomNet was also shown to retain the cognitively plausible behavior detailed in psycholinguistics research. Consequently, semantic self-organization holds considerable promise as a basis for real-world natural language understanding systems that mimic human linguistic performance.
Quantum Methods With Mathematica, 2nd edition
Authors: J. M. Feagin
Venue:  (2007)

The first quantum mechanics text published that ties directly into a computer algebra system, this book exploits Mathematica(r) throughout for symbolic, numeric, and graphical computing. It is a work designed for computer interaction in an upper-division undergraduate or first-year graduate quantum mechanics course. It is also a toolbox for the practicing physicist seeking to automate a variety of algebraic and numerical tasks with the computer. The book is divided into two parts: "Systems in One Dimension" and "Quantum Dynamics." Part I emphasizes topics from a first-year course on quantum mechanics, while Part II includes more advanced topics. Although the text requires some familiarity with Mathematica, appendices are provided for gaining experience with the software and are referenced throughout the book. The text is task-oriented and integrated with numerous problems and exercises, with hints for working on the computer. James M. Feagin is a Professor of Physics at California State University, Fullerton. He was educated at Georgia Tech and the University of North Carolina, Chapel Hill, where he received a Ph.D. in theoretical physics in 1980. He is a Fellow of the Alexander von Humboldt Foundation and has served as visiting Professor at the University of Freiburg, Germany. Feagin is the author of numerous articles on collision physics and the dynamics of few-body systems. He has given a number of invited talks and hosted workshops on incorporating computers into the physics curriculum and is presently helping to introduce computing into the Introductory University Physics Project (IUPP) sponsored by the American Institute of Physics. 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
Creating High-Quality Products in Open Content Virtual Communities - Exploring Wikipedia, the Free Encyclopedia
Authors: Kevin Carillo
Venue:  (2007)

The open content movement is enabling the advent of a major turn in information- based products through the enormous potential of collective intelligence. The Linux operating system, the Firefox internet browser, the online encyclopedia Wikipedia, the Public Library of Science, or the MIT's Open- CourseWare project, are all striking successes. What are the factors that contribute to such high-quality products in open content practices? This study uses a group perspective to examine the group factors that lead to high-quality products in open content communities. A theoretical model is developed, based on the Input-Process-Output approach of group research in social psychology and on the Time, Interaction, and Performance Theory proposed by McGrath (1991). A quantitative study of the detailed activity logs of Wikipedia was designed and tested. The analysis should help to answer the questions: - Can a group perspective provide valuable insights in explaining the success of open content projects? What makes open content practices so different from other types of practices? The book is addressed to professionals whose field is related to information-based products, open content and open source communities. It is also directed towards researchers in Business Administration and Social Psychology. 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
Modelling land-cover types using multiple endmember spectral mixture analysis in a desert city
Authors: S. W. Myint, G. S. Okin
Venue: International Journal of Remote Sensing (2009)

Spectral mixture analysis is probably the most commonly used approach among sub-pixel analysis techniques. This method models pixel spectra as a linear combination of spectral signatures from two or more ground components. However, spectral mixture analysis does not account for the absence of one of the surface features or spectral variation within pure materials since it utilizes an invariable set of surface features. Multiple endmember spectral mixture analysis (MESMA), which addresses these issues by allowing endmembers to vary on a per pixel basis, was employed in this study to model Landsat ETM+ reflectance in the Phoenix metropolitan area. Image endmember spectra of vegetation, soils, and impervious surfaces were collected with the use of a fine resolution Quickbird image and the pixel purity index. This study employed 204 (3×17×4) total four-endmember models for the urban subset and 96 (6×6×2×4) total five-endmember models for the non-urban subset to identify fractions of soil, impervious surface, vegetation and shade. The Pearson correlation between the fraction outputs from MESMA and reference data from Quickbird 60 cm resolution data for soil, impervious, and vegetation were 0.8030, 0.8632, and 0.8496 respectively. Results from this study suggest that the MESMA approach is effective in mapping urban land covers in desert cities at sub-pixel level.
A hybrid novelty score and its use in keystroke dynamics-based user authentication
Authors: Pilsung Kang, Sungzoon Cho
Venue: Pattern Recognition (2009)

The purpose of novelty detection is to detect (novel) patterns that are not generated by the identical distribution of the normal class. A distance-based novelty detector classifies a new data pattern as ''novel'' if its distance from ''normal'' patterns is large. It is intuitive, easy to implement, and fits naturally with incremental learning. Its performance is limited, however, because it relies only on distance. In this paper, we propose considering topological relations as well. We compare our proposed method with 13 other novelty detectors based on 21 benchmark data sets from two sources. We then apply our method to a real-world application in which incremental learning is necessary: keystroke dynamics-based user authentication. The experimental results are promising. Not only does our method improve the performance of distance-based novelty detectors, but it also outperforms the other non-distance-based algorithms. Our method also allows efficient model updates.