ppxscal/embedding_network huggingface dataset:
A Case for Database Filesystems
Authors: Philip A. Adams, John C. Hax
Venue: Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (2009)

Data intensive science is offering new challenges and opportunities for Information Technology and traditional relational databases in particular. Database file systems offer the potential to store Level Zero data and analyze Level 1 and Level 3 data within the same database system. Scientific data is typically composed of both unstructured files and scalar data. Oracle SecureFiles is a new database file system feature in Oracle Database 11g that is specifically engineered to deliver high performance and scalability for storing unstructured or file data inside the Oracle database. SecureFiles presents the best of both the file system and the database worlds for unstructured content. Data stored inside SecureFiles can be queried or written at performance levels comparable to that of traditional file systems while retaining the advantages of the Oracle database.
Research on Optimizing Build Parameters for Stereolithography Technology
Authors: Guangshen Xu, Jing Jin, Sheng Luo, Ronghua Qiu, Huan Pan
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Abstract—The dimension accuracy in scanning plane of high-resolution stereolithography (SL) system with building parameters (laser beam scanning speed (factor A), cured line width compensation (factor B), hatch spacing (factor C) and the coefficient of resin's shrinkage compensation (CRSC, factor D)) were investigated in this study. A L27orthogonal array and signal-to-noise (S/N) were employed to analyze the effect of building parameters. Using Taguchi method for design of a robust experiment, the interactions among factors are also investigated. The experimental results indicate that hatch spacing, CRSC and A´C are recognized to make the most significant contribution to the overall performance. For the dimension accuracy, the optimal combination building parameters is A2B1C2D1 (i.e. laser beam scanning speed:450mm/s, cured line width compensation:0.02mm, hatch spacing:0.04mm, CRSC:1.025). With the optimal factors combination, an error of 0.003mm in scanning plane has been reached using the high-resolution SL system. Confirmation experiment results showed that the dimension accuracy has been significantly improved with the optimal factors combination.
Feature structures, unification and finite-state transducers
Authors: Rémi Zajac
Venue: Proceedings of the International Workshop on Finite State Methods in Natural Language Processing (1998)

We present a new framework for describing morphological models which combines several types of descriptions in a single unified declarative language: simple morphological rules relate strings to feature structures; rules can be grouped into inheritance hierarchies of paradigms; rules can be composed for describing simple agglutinative morphology; they can also be combined to describe more complex morphotactic structures. Rules are compiled as extended finite-state transducers where left projections are characters and right projections are feature structures: unification is used instead of concatenation to compute the output of a transduction.
Edge-preserving multiscale image decomposition based on local extrema
Authors: Kartic Subr, Cyril Soler, Frédo Durand
Venue: ACM SIGGRAPH Asia 2009 papers (2009)

We propose a new model for detail that inherently captures oscillations, a key property that distinguishes textures from individual edges. Inspired by techniques in empirical data analysis and morphological image analysis, we use the local extrema of the input image to extract information about oscillations: We define detail as oscillations between local minima and maxima. Building on the key observation that the spatial scale of oscillations are characterized by the density of local extrema, we develop an algorithm for decomposing images into multiple scales of superposed oscillations. Current edge-preserving image decompositions assume image detail to be low contrast variation. Consequently they apply filters that extract features with increasing contrast as successive layers of detail. As a result, they are unable to distinguish between high-contrast, fine-scale features and edges of similar contrast that are to be preserved. We compare our results with existing edge-preserving image decomposition algorithms and demonstrate exciting applications that are made possible by our new notion of detail.
ITIL V3 Service Capability PPO - Planning, Protection and Optimization of IT Services Best Practices Study and Implementation Guide
Authors: Tim Malone, Ivanka Menken, Gerard Blokdijk
Venue:  (2009)

This book centers on the ability of an IT organization to deliver and support IT services on a day to day basis. The focus is on practical aspects of the ITIL v3 Service Lifecycle and processes associated with Planning, Protection and Optimization which ensures IT departments can cost-effectively manage customer demand, availability and capacity while mitigating risk. This book covers practical guidance on the design and implementation of integrated end-to-end processes based on proven industry best practice guidelines. It provides in-depth knowledge of the ITIL PPO areas: Availability Management, Capacity Management, IT Service Continuity Management, Information Security Management, Demand Management, Risk Management and Continual Service Improvement. Planning, Protection and Optimization Best Practices is designed to complement the certified ITIL V3 Capability Programs for IT Service Management. This book focuses on describing the industry best practices for the Planning, Protection and Optimization of IT Services, including: Introduction and Overview Core Planning, Protection and Optimization Processes: Capacity Management Availability Management IT Service Continuity Management (ITSC) Information Security Management Demand Management Risk Management Roles and Responsibilities Technology and Implementation Considerations Common Service Activities Continual Service Improvement The information provided in this book is based on version 3 of the ITIL framework, Other guidance provided includes: * Example templates. * Suggested criteria for implementing Planning, Protection and Optimization (PPO) processes. * Explanation of the more abstract ITIL concepts to improve understanding. * Review questions to assist study for the ITIL PPO exam.
Fraud Detection by Human Agents: A Pilot Study
Authors: Vinicius Almendra, Daniel Schwabe
Venue: Proceedings of the 10th International Conference on E-Commerce and Web Technologies (2009)

Fraud is a constant problem for online auction sites. Besides failures in detecting fraudsters, the currently employed methods yield many false positives: bona fide sellers that end up harassed by the auction site as suspects. We advocate the use of human computation (also called crowdsourcing) to improve precision and recall of current fraud detection techniques. To examine the feasibility of our proposal, we did a pilot study with a set of human subjects, testing whether they could distinguish fraudsters from common sellers before negative feedback arrived and looking just at a snapshot of seller profiles. Here we present the methodology used and the obtained results, in terms of precision and recall of human classifiers, showing positive evidence that detecting fraudsters with human computation is viable.
The asymptotic behaviour of recurrence coefficients for orthogonal polynomials with varying exponential weights
Authors: A. B. J. Kuijlaars, P. M. J. Tibboel
Venue: Journal of Computational and Applied Mathematics (2009)

We consider orthogonal polynomials {p"n","N(x)}"n"="0^~ on the real line with respect to a weight w(x)=e^-^N^V^(^x^) and in particular the asymptotic behaviour of the coefficients a"n","N and b"n","N in the three-term recurrence x@p"n","N(x)=@p"n"+"1","N(x)+b"n","N@p"n","N(x)+a"n","N@p"n"-"1","N(x). For one-cut regular V we show, using the Deift-Zhou method of steepest descent for Riemann-Hilbert problems, that the diagonal recurrence coefficients a"n","n and b"n","n have asymptotic expansions as n->~ in powers of 1/n^2 and powers of 1/n, respectively.
Improving the Quality of EEG Data in Patients with Alzheimer's Disease Using ICA
Authors: François-Benoit Vialatte, Jordi Solé-Casals, Monique Maurice, Charles Latchoumane, Nigel Hudson, Sunil Wimalaratna, Jaeseung Jeong, Andrzej Cichocki
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Does Independent Component Analysis (ICA) denature EEG signals? We applied ICA to two groups of subjects (mild Alzheimer patients and control subjects). The aim of this study was to examine whether or not the ICA method can reduce both group differences and within-subject variability. We found that ICA diminished Leave-One-Out root mean square error (RMSE) of validation (from 0.32 to 0.28), indicative of the reduction of group difference. More interestingly, ICA reduced the inter-subject variability within each group (¿= 2.54 in the ¿ range before ICA, ¿= 1.56 after, Bartlett p = 0.046 after Bonferroni correction). Additionally, we present a method to limit the impact of human error (¿ 13.8%, with 75.6% inter-cleaner agreement) during ICA cleaning, and reduce human bias. These findings suggests the novel usefulness of ICA in clinical EEG in Alzheimer's disease for reduction of subject variability.
A capacity scaling heuristic for the multicommodity capacitated network design problem
Authors: N. Katayama, M. Chen, M. Kubo
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper, we propose a capacity scaling heuristic using a column generation and row generation technique to address the multicommodity capacitated network design problem. The capacity scaling heuristic is an approximate iterative solution method for capacitated network problems based on changing arc capacities, which depend on flow volumes on the arcs. By combining a column and row generation technique and a strong formulation including forcing constraints, this heuristic derives high quality results, and computational effort can be reduced considerably. The capacity scaling heuristic offers one of the best current results among approximate solution algorithms designed to address the multicommodity capacitated network design problem.
Adaptive supervisory WCMAC neural network controller (SWC) for nonlinear systems
Authors: Ching-Hung Lee, Bo-Hang Wang
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2008)

This paper proposes a wavelet-based cerebellar model arithmetic controller neural network (called WCMAC) and develops an adaptive supervisory WCMAC control (SWC) scheme for nonlinear uncertain systems. The WCMAC is modified from the traditional CMAC for obtaining high approximation accuracy and convergent rate using the advantages of wavelet functions and fuzzy TSK-model. For nonlinear uncertain systems, a PD-type WCMAC controller with filter is constructed to approximate an ideal control signal. The corresponding adaptive supervisory controller is used to recover the residual of approximation error. Finally, the adaptive SWC scheme is applied to chaotic system identification and control including Mackey&#x2013;Glass time-series prediction, control of inverted pendulum system, and control of Chua circuit system. These demonstrate the effectiveness of our adaptive SWC approach for nonlinear uncertain systems.
Error bounds for approximate value iteration
Authors: Rémi Munos
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Approximate Value Iteration (AVI) is an method for solving a Markov Decision Problem by making successive calls to a supervised learning (SL) algorithm. Sequence of value representations Vn are processed iteratively by Vn+1 = ATVn where T is the Bellman operator and A an approximation operator. Bounds on the error between the performance of the policies induced by the algorithm and the optimal policy are given as a function of weighted Lp-norms (p ≥ 1) of the approximation errors. The results extend usual analysis in L∞-norm, and allow to relate the performance of AVI to the approximation power (usually expressed in Lp-norm, for p = 1 or 2) of the SL algorithm. We illustrate the tightness of these bounds on an optimal replacement problem.
Morpho challenge: evaluation of algorithms for unsupervised learning of morphology in various tasks and languages
Authors: Mikko Kurimo, Sami Virpioja, Ville Turunen, Teemu Hirsimäki
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Demonstration Session (2009)

After the release of the open source software implementation of Morfessor algorithm, a series of several open evaluations has been organized for unsupervised morpheme analysis and morpheme-based speech recognition and information retrieval. The unsupervised morpheme analysis is a particularly attractive approach for speech and language technology for the morphologically complex languages. When the amount of distinct word forms becomes prohibitive for the construction of a sufficient lexicon, it is important that the words can be segmented into smaller meaningful language modeling units. In this presentation we will demonstrate the results of the evaluations, the baseline systems built using the open source tools, and invite research groups to participate in the next evaluation where the task is to enhance statistical machine translation by morpheme analysis.
Real-Time Monitoring of Ubiquitous Wearable ECG Sensor Node for Healthcare Application
Authors: Do-Un Jeong, Hsein-Ping Kew
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

Wireless technologies and sensors network give new possibilities for monitoring of vital parameters with wearable biomedical sensors and allow patients the freedom to be mobile and still be under continuously monitoring and thereby provide better healthcare services. In this paper, a new concept for wireless and ubiquitous wearable belt-type ECG sensor node transmitting signal via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signal is detected using ECG receiver sensor node. An ECG Monitoring Program is implemented at the end user. The measured ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. Variable threshold method is used to detect the R-peak which is more accurate and efficient compare to fixed threshold value. For evaluate the performance analysis, R-peak detection using MIT-BIH databases and long term real-time ECG is performed in this research.
Transductive Classification via Dual Regularization
Authors: Quanquan Gu, Jie Zhou
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Semi-supervised learning has witnessed increasing interest in the past decade. One common assumption behind semi-supervised learning is that the data labels should be sufficiently smooth with respect to the intrinsic data manifold. Recent research has shown that the features also lie on a manifold. Moreover, there is a duality between data points and features, that is, data points can be classified based on their distribution on features, while features can be classified based on their distribution on the data points. However, existing semi-supervised learning methods neglect these points. Based on the above observations, in this paper, we present a dual regularization, which consists of two graph regularizers and a co-clustering type regularizer. In detail, the two graph regularizers consider the geometric structure of the data points and the features respectively, while the co-clustering type regularizer takes into account the duality between data points and features. Furthermore, we propose a novel transductive classification framework based on dual regularization, which can be solved by alternating minimization algorithm and its convergence is theoretically guaranteed. Experiments on benchmark semi-supervised learning data sets demonstrate that the proposed methods outperform many state of the art transductive classification methods.
Improving Multi Step-Ahead Model Prediction through Backward Elimination Method in Multiple Neural Networks Combination
Authors: Zainal Ahmad, Rabiatul Adawiah Noor
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Combining multiple neural networks appears to be a very promising approach in improving neural network generalization since it is very difficult, if not impossible, to develop a solution that is close to global optimum using single neural network. In this paper, individual networks are developed from bootstrap re-sample of the original training and testing data sets. Instead of combining all the developed networks, this paper proposed backward elimination. In backward elimination, all the individual networks are initially aggregated and some of the individual networks are then gradually eliminated until the aggregated network error on the original training and testing data sets cannot be further reduced. The proposed techniques are applied to nonlinear process modeling and application results demonstrate that the proposed techniques can significantly improve model performance better than aggregating all the individual networks.
Formant Vowel Structure Tracking by Goertzel Algorithm
Authors: Boo Tomas, Marko Obad
Venue: Proceedings of the 2009 Fourth International Conference on Digital Telecommunications (2009)

Formant frequencies structure gives a good view to determine linguistic as well as non-linguistic speech meaning and it represents a significant parameter within the synthesis and speech recognition procedure. In fact formants are groups of harmonics enhanced by the vocal tract resonance. There is a resonance i.e. the enhancement of spectral energy in speech signal spectrum at formant frequencies. Formant vowel /a/ structure tracking by Goertzel algorithm is presented in this paper.
Disciplinary differences in the use of internet discussion groups: differential communication needs or trust problems?
Authors: Uwe Matzat
Venue: Journal of Information Science (2009)

This paper tests empirically the claim that the successful application of information and communication technologies (ICTs) depends on the social context of their use. There are striking differences in the prevalence of ICT use between researchers in different academic disciplines. Nevertheless it is unclear whether and how they depend on disciplinary differences of the academic communication system. This paper presents several existing and new hypotheses that specify how disciplinary differences in communication systems influence whether researchers make use of so-called internet discussion groups (IDGs). The hypotheses either argue that specific trust problems inhibit IDG subscription or that IDGs fulfil discipline-specific communication needs, which gives incentives for subscription. They are tested with data of a sample of university researchers in the natural and social sciences and the humanities. The trust hypotheses are not confirmed. The idea that IDGs have a distinct orientation function that diminishes deficiencies in the existing communication systems of some disciplines finds support. Scholars who work in research fields that are difficult to overview, that is fields with a high number of journals, have a special incentive to subscribe to IDGs.
Game theory pragmatics: a challenge for AI
Authors: Yoav Shoham
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Game theory has been playing an increasingly visible role in computer science in general and AI in particular, most notably in the area of multi agent systems. I briefly list the areas where most of the action has been in the past decade or so. I then suggest that going forward, the most dramatic interaction between computer science and game theory - with a special role for AI - could be around what might be called game theory pragmatics.
An online lifestyle diary with a persuasive computer assistant providing feedback on self-management
Authors: Olivier A. Blanson Henkemans, Paul J. M. van der Boog, Jasper Lindenberg, Charles A. P. G. van der Mast, Mark A. Neerincx, Bertie J. H. M. Zwetsloot-Schonk
Venue: Technology and Health Care (2009)

In accordance with the global trend, in The Netherlands approximately 45% of the population is overweight. Existing studies show that patient self-management can reduce these figures, but medical non-adherence is a persistent problem. eHealth can potentially increase adherence to self-management. Consequently, we designed a persuasive computer assistant and evaluated its influence on self-management, i.e., the use of an online lifestyle diary called DieetInzicht.nl. The assistant is represented by an animated iCat, which shows different facial expressions and provides cooperative feedback following principles from the motivational interviewing method. We conducted a randomized controlled trial with 118 overweight people over a period of four weeks and studied the difference between diary use with and without computer assistant feedback. Results show that the computer assistant contributed to filling in the diary more frequently, reduced the decline in motivation to perform self-management, lowered the (reported) BMI, and improved the ease of use. Furthermore, diary use increased knowledge of maintaining a healthy lifestyle. Finally, personal characteristics, i.e., locus of control, vocabulary, computer experience, age, gender, education level and initial BMI, explained the variance in the diary use and its outcome. Of the 118 participants 35 filled in the closing survey, covering motivation, BMI, lifestyle knowledge and ease of use, which implies that the findings based on these results are mainly representative for motivated participants. In general, this study shows that the Dieetinzicht eHealth service, including a personal computer assistant, is likely to support motivated overweight people and lifestyle related diseases to get a better insight in and adhere to their self-management.
Algorithm for Surface Directly Interpolated Used in 5-Axis Computer Numerical Controlled System
Authors: Liangji Chen
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

A parametric surface directly interpolation method with a flat-end cutter has been presented in this paper. Distance between two adjacent CC paths has been calculated to facilitate the calculation of the increment of parameter. A CC path is interpolated to get a CC point, which is then transferred to CL data. Through adding post-process to the CNC system, the CL data is transformed into the control commands of 5-axis machine.