ppxscal/embedding_network huggingface dataset:
Truthful Bundle/Multiunit Double Auctions
Authors: Leon Yang Chu
Venue: Management Science (2009)

We address the mechanism design problem for a market with multiple buyers and sellers. Each buyer demands some bundle(s) of various commodities, and each seller supplies multiple units of one commodity. To design truthful double-auction mechanisms, we propose a novel “padding” method that intentionally creates imbalances between the supply availability and demand requirement by introducing a phantom buyer with unlimited budget. To the best of our knowledge, this “padding” method leads to a class of mechanisms that are the first strategy-proof, individually rational, budget-balanced, and asymptotically efficient mechanisms for the specified exchange environment. Furthermore, these mechanisms dominate known truthful bundle/single-unit mechanisms with higher efficiency, lower buying prices, and higher selling prices.
Applying autonomous control in apparel manufacturing
Authors: Scholz-Reiter Bernd, Teucke Michael, Sowade Steffen, Rippel Daniel, Özsahin Mehmet-Emin, Hildebrandt Torsten
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

Problems caused by manual handling of garments in the apparel industry can be improved by automated data management based on radio frequency identification technology. Autonomous control can be established on top to increase the system robustness and to enable smaller production lot sizes. Different system architectures are defined for autonomous control and technical solutions are proposed to implement autonomous control in apparel manufacturing.
Learning with Animation: Research Implications for Design, 1st edition
Authors: Richard Lowe, Wolfgang Schnotz
Venue:  (2007)

The use of animations has recently become common in multimedia teaching and learning. Animations are assumed to increase interest and motivation, direct attention, illustrate procedures, and explain how things work. Recent research shows that animations are not inherently effective. Their educational effectiveness depends on how the characteristics of animations interact with the psychological functioning of the learner. Clarifying and integrating the major themes of current research, this book explores requirements for the principled design of learning resources that incorporate animation. Such materials can only be successful if their design reflects principles governing how learners develop understandings with animations, and the goal of this book is to improve the way educational animations are designed and used within a variety of learning contexts.
Prediction of protein cellular localization sites using a hybrid method based on artificial immune system and fuzzy k-NN algorithm
Authors: Abdulkadir Sengur
Venue: Digital Signal Processing (2009)

The use of artificial intelligence methods in biological data analysis has been increased recent since performance of the classification and detection systems have improved considerably to help medical experts in diagnosing. In this paper, we investigate the performance of an artificial immune system (AIS) based fuzzy k-NN algorithm with and without cross validation in a class of imbalanced problems in bioinformatics. Furthermore, we devise an unsupervised AIS algorithm in a supervised manner which contains a training stage for data reduction and a classification stage using fuzzy k-NN algorithm. The experiments show the efficacy of the proposed method with promising results. Using the Escherichia coli and yeast database, we compare the classification accuracy of the proposed method with those of other methods which have been proposed in the literature. The proposed hybrid system produced much more accurate results than the Horton and Nakai's method [P. Horton, K. Nakai, Better prediction of protein cellular localization sites with the k-nearest neighbors classifier, in: Proceedings of Intelligent Systems in Molecular Biology, Halkidiki, Greece, 1997, pp. 368-383]. Besides the improvement on the classification accuracy, one of the important aspects of the proposed method is the complexity. As the proposed AIS method incorporates data reduction in the training stage, the training complexity is considerably low comparing with the k-NN classifier.
Fast Shape from Shading for Phong-Type Surfaces
Authors: Oliver Vogel, Michael Breuß, Thomas Leichtweis, Joachim Weickert
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

Shape from Shading (SfS) is one of the oldest problems in image analysis that is modelled by partial differential equations (PDEs). The goal of SfS is to compute from a single 2-D image a reconstruction of the depicted 3-D scene. To this end, the brightness variation in the image and the knowledge of illumination conditions are used. While the quality of models has reached maturity, there is still the need for efficient numerical methods that enable to compute sophisticated SfS processes for large images in reasonable time. In this paper we address this problem. We consider a so-called Fast Marching (FM) scheme,which is one of the most efficient numerical approaches available. However, the FM scheme is not trivial to use for modern non-linear SfS models. We show how this is done for a recent SfS model incorporating the non-Lambertian reflectance model of Phong. Numerical experiments demonstrate that --- without compromising quality --- our FM scheme is two orders of magnitude faster than standard methods.
The Best of Photographic Lighting: Techniques and Images for Digital Photographers, 2nd edition
Authors: Bill Hurter
Venue:  (2007)

Bill Hurter explains the characteristics of lightboth natural and artificialin this in-depth guide. Fully exploring color balance, exposure, and light ratios, the handbook expands on skills learned in the studio to explain how to harness the beauty of less predictable lighting situations, like those shot outdoors or on location. Packed with tips from more than 30 top professionals on wedding, portrait, and commercial photography, this resource is sure to both educate and inspire. 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
Belief Revision in a Fact-Rule Agent's Belief Base
Authors: Hai H. Nguyen
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

When there is much incoming information with different levels of reliability, the agent's belief base could become inconsistent, and therefore it needs a revision procedure. The algorithm which implements this revision should be rational and computationally efficient. Besides, because an agent's belief could be either a fact or a rule, it is essential to perform belief revision by removing not only facts but also rules. In this paper, the work presented in [1] and [2] is extended to implement contraction by rules as well as by facts in polynomial time.
ARIMA models versus gene expression programming in precipitation modeling
Authors: Alina Barbulescu, Elena Bautu
Venue: Proceedings of the 10th WSEAS international conference on evolutionary computing (2009)

In this paper we present a case study: the application of some conceptually different approaches to the problem of identifying a model for a hydrological time series. The problem is particularly challenging, due to the size of the time series and more importantly, to the many complex phenomena that influence such time series and that reflect in the characteristics of the data. We use well established statistical methods to detect change points in the time series, and we model the subseries obtained by ARIMA, GEP and the adaptive variant and a combination of the two. The models obtained state the efficiency of combining pure statistical tests and methods with heuristic approaches.
Sturm Sequences and Random Eigenvalue Distributions
Authors: James T. Albrecht Cy P. Chan, Alan Edelman
Venue: Foundations of Computational Mathematics (2009)

This paper proposes that the study of Sturm sequences is invaluable in the numerical computation and theoretical derivation of eigenvalue distributions of random matrix ensembles. We first explore the use of Sturm sequences to efficiently compute histograms of eigenvalues for symmetric tridiagonal matrices and apply these ideas to random matrix ensembles such as the &#x03b2;-Hermite ensemble. Using our techniques, we reduce the time to compute a histogram of the eigenvalues of such a matrix from O(n 2+m) to O(mn) time where n is the dimension of the matrix and m is the number of bins (with arbitrary bin centers and widths) desired in the histogram (m is usually much smaller than n). Second, we derive analytic formulas in terms of iterated multivariate integrals for the eigenvalue distribution and the largest eigenvalue distribution for arbitrary symmetric tridiagonal random matrix models. As an example of the utility of this approach, we give a derivation of both distributions for the &#x03b2;-Hermite random matrix ensemble (for general &#x03b2;). Third, we explore the relationship between the Sturm sequence of a random matrix and its shooting eigenvectors. We show using Sturm sequences that assuming the eigenvector contains no zeros, the number of sign changes in a shooting eigenvector of parameter &#x03bb; is equal to the number of eigenvalues greater than &#x03bb;. Finally, we use the techniques presented in the first section to experimentally demonstrate a O(log&#x2009;n) growth relationship between the variance of histogram bin values and the order of the &#x03b2;-Hermite matrix ensemble.
Fusion of LSB and DWT Biometric Watermarking Using Offline Handwritten Signature for Copyright Protection
Authors: Cheng-Yaw Low, Andrew Beng-Jin Teoh, Connie Tee
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Biometric watermarking was introduced as the synergistic integration of biometrics and digital watermarking technology. This paper proposes a novel biometric watermarking technique, which embeds offline handwritten signature in host image for copyright protection. We propose to combine the conventional LSB-based and DWT-based watermarking techniques into a unison framework, which is known as LSB-DWT in this paper. The proposed LSB-DWT technique is evaluated against various simulated security attacks, i.e. JPEG compression, Gaussian low-pass filtering, median filtering, Gaussian noise, scaling, rotation and cropping. The experimental results demonstrate that the proposed LSB-DWT technique exhibits remarkable watermark imperceptibility and watermark robustness.
Model-independent differences
Authors: Patrick Konemann
Venue: Proceedings of the 2009 ICSE Workshop on Comparison and Versioning of Software Models (2009)

Computing differences (diffs) and merging different versions is well-known for text files, but for models it is a very young field - especially patches for models are still matter of research. Text-based and model-based diffs have different starting points because the semantics of their structure is fundamentally different. This paper reports on our ongoing work on model-independent diffs, i.e. a diff that does not directly refer to the models it was created from. Based on that, we present an idea of how the diff could be generalized, e.g. many atomic diffs are merged to a new, generalized diff. One use of these concepts could be a patch for models as it already exists for text files. The advantage of such a generalized diff compared to ‘normal’ diffs is that it is applicable to a higher variety of models.
Indexing correlated probabilistic databases
Authors: Bhargav Kanagal, Amol Deshpande
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc., effectively managing and querying them has become an important research direction. While there is an exhaustive body of literature on querying independent probabilistic data, supporting efficient queries over large-scale, correlated databases remains a challenge. In this paper, we develop efficient data structures and indexes for supporting inference and decision support queries over such databases. Our proposed hierarchical data structure is suitable both for in-memory and disk-resident databases. We represent the correlations in the probabilistic database using a junction tree over the tuple-existence or attribute-value random variables, and use tree partitioning techniques to build an index structure over it. We show how to efficiently answer inference and aggregation queries using such an index, resulting in orders of magnitude performance benefits in most cases. In addition, we develop novel algorithms for efficiently keeping the index structure up-to-date as changes (inserts, updates) are made to the probabilistic database. We present a comprehensive experimental study illustrating the benefits of our approach to query processing in probabilistic databases.
Speech enhancement and intelligibility modeling in cochlear implants
Authors: Shrikanth Narayanan, Qian-Jie Fu
Venue:  (2008)

Accompanying cochlear implant (CI) performance improvement over years, CI speech recognition increasingly showed unique patterns and huge inter-subject performance difference that are different from that of normal hearing (NH) listeners. Previous literatures have not paid enough attention to such unique patterns, regardless of numerous evidences. To further improve speech perception with the next generation CI device, it is critical to integrate such unique patterns into the CI framework. The thesis addressed speech enhancement and intelligibility modeling from systematic approaches. Speech enhancement utilized unique speech recognition patterns as feedback to modify input auditory signals to CI devices. Speech intelligibility modeling unified CI device settings and psychoacoustic responses from individual subjects to predict inter-subject performance difference. Although speech recognition with NH listeners are highly robust even when acoustic information is lost or variant, such listening conditions are very challenging for CI users. A speech enhancement framework was proposed and realized to improve CI speech recognition in the context of telephone speech and different talker speech. The proposed speech enhancement framework significantly improved CI speech recognition; individual CI users showed substantially different recognition patterns in terms of the effect of speech enhancement, speech bandwidth and different talkers. Speech intelligibility modeling was further studied to explore the observed inter-subject performance difference. An acoustic distance based intelligibility model was proposed to integrate variant CI device settings (e.g., frequency partition, electric stimulation rate, and acoustic-to-electric mapping) and psychoacoustic responses (e.g., electrode confusion patterns, intensity resolution, and dynamic range), aiming to capture complex and highly non-linear distortion of acoustic features through CI devices. Three phases of this work were involved. Firstly, a general speech intelligibility model was studied and validated under variant parametric effect in CI processing for averaged CI performance. Secondly, the effect of CI electrode confusion patterns was studied by smearing the spectral contrast of acoustic features. Thirdly, individual CI MAP and psychoacoustic response patterns were unified into the proposed model. Compared to the general speech intelligibility model, the customized model significantly boosted the linear prediction ability of inter-subject performance difference. The contributions of different psychoacoustic responses to inter-subject performance difference were further discussed.
Recursive least squares algorithms applied to satellite orbit determination, using GPS signals
Authors: Paula C. P. M. Pardal, Helio Koiti Kuga, Rodolpho Vilhena De Moraes
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

Using signals of the GPS constellation and least squares algorithms through sequential Givens rotations as a method of estimation, the principal target is to determine the orbit of an artificial satellite. This approach aims to improve the performance of the orbit estimation process and, at the same time, to minimize the computational procedure cost. Perturbations up to high order geopotential and direct solar radiation pressure were taken into account. It was also considered the position of the GPS antenna on the satellite body. An application has been done, using real data from the TOPEX/POSEIDON satellite. In a process of high accuracy orbit determination, frequently a sinusoidal residual behavior is observed during its error analysis. Assuming that we cope with the unmodeled accelerations, which have no direct physical reasons, or that the modeling effort is not worthwhile, these anomalous accelerations will also be analyzed, empirically.
Supporting Collaborative Idea Generation: A Closer Look Using Statistical Process Analysis Techniques
Authors: Hao-Chuan Wang, Carolyn P. Rosé
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

We are developing a conversational agent called VIBRANT to provide adaptive support for brainstorming in pairs in a scientific inquiry context. Our previous experimental study indicated that although adaptive support was effective for learning, it did not mitigate the negative influence of social interaction on idea generation. In this paper, we present a process analysis that makes the effect of the adaptive support on the idea generation process more apparent and suggests directions for future work.
Introduction to Part II
Authors: Heiner Stuckenschmidt, Christine Parent, Stefano Spaccapietra
Venue: Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization (2009)

In an ideal world, ontologies would be build in a modular way from the start thus showing the benefits well known from modularization in software engineering. The first part of this book contained an example of how this can be done for databases. Unfortunately, the field of ontology engineering has not yet developed comprehensive models and methods to fully support the development of modular ontologies. There are some approaches aiming at developing principles and formalisms in this direction, but they have not yet found their way into mainstream ontology engineering. As a result, existing ontologies are monolithic models without a clear internal structuring. As the size and complexity of these models can be quite significant (the NCI cancer ontology contains about 27.500 the Gene ontology about 22.000 concepts and the Formal Model of Anatomy (FMA) even 75.000 concepts). A viable way of handling such large models is to chop them up into manageable parts. This part of the book deals with approaches for this task of partitioning large ontologies into smaller parts.
An ontology in OWL for legal case-based reasoning
Authors: Adam Wyner
Venue: Artificial Intelligence and Law (2008)

The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation LCBR. Ontologies for different systems allows comparison and contrast between them. OWL Ontologies are standardised, machine-readable formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and to LCBR are discussed. Two LCBR systems (AS-CATO, which is based on CATO, and IBP) are analysed in terms of basic and intermediate concepts. Central components of the OWL ontologies for these systems are presented, pointing out differences and similarities. The main novelty of the paper is the ontological analysis and representation in OWL of LCBR systems. The paper also emphasises the important issues concerning the representation and reasoning of intermediate concepts.
Use of competition detection in TCP for simple topology networks
Authors: Soohyun Cho, Riccardo Bettati
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

The fairness (or TCP-friendliness) of recent high-speed TCP proposals for high bandwidth-delay product networks is generally poor. We believe that the lack of TCP-friendliness of high-speed TCP proposals stems from their ineffectiveness in detecting competing TCP flows. We suggest a competition detection mechanism for a single TCP flow to detect the presence of competing TCP flows. We propose a new TCP, called Adaptive TCP (A-TCP) to demonstrate the usefulness of the competition detection mechanism. A-TCP uses the competition detection mechanism to control its aggressiveness: If it does not detect competing flows, a single A-TCP flow increases its sending rate aggressively in order to highly utilize the network. Otherwise, it behaves like a standard TCP flow to fairly share network resources with competing flows. We implemented A-TCP as part of Linux as well as in ns-2. Experimental results show that A-TCP achieves better fairness than existing high-speed TCP proposals when they compete against standard TCP in simple topology networks.
Fabrication of SiGe HBT BiCMOS Technology, 1st edition
Authors: John D. Cressler
Venue:  (2007)

SiGe HBT BiCMOS technology is the obvious groundbreaker of the Si heterostructures application space. To date virtually every major player in the communications electronics market either has SiGe up and running in-house or is using someone elses SiGe fab as foundry for their designers. Key to this success lies in successful integration of the SiGe HBT and Si CMOS, with no loss of performance from either device. Filled with contributions from leading experts, Fabrication of SiGe HBT BiCMOS Technologies brings together a complete discussion of these topics into a single resource. Drawn from the comprehensive and well-reviewed Silicon Heterostructure Handbook, this volume examines the design, fabrication, and application of silicon heterostructure transistors. A novel aspect of this book the inclusion of numerous snapshot views of the industrial state-of-the-art for SiGe HBT BiCMOS technology. It has been carefully designed to provide a useful basis of comparison for the current status and future course of the global industry. In addition to the copious technical material and the numerous references contained in each chapter, the book includes easy-to-reference appendices on the properties of Si and Ge, the generalized Moll-Ross relations, integral charge-control relations, and sample SiGe HBT compact model parameters. 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