ppxscal/embedding_network huggingface dataset:
Fedora 8 and Red Hat Enterprise Linux Bible
Authors: Christopher Negus
Venue:  (2007)

More than a quarter of a million copies sold in previous editions! Freedom is a feature With Fedora's new Online Desktop, you are free to shape your desktop environment to include the services, applications, and online friends you desire. As always, Fedora's total dedication to freedom lets you draw on thousands of free software packages to create the exact desktop or server computer you need. Fedora puts together the software (provided here on CD and DVD). This book acts as a guide to everything from playing music and writing documents to configuring many powerful Web, file, print, DHCP, and database servers. Customize Fedora or Red Hat Enterprise Linux to: Explore your computer or the Internet from GNOME, KDE, or Online Desktops Manage and use documents, spreadsheets, presentations, music, and images Try the new advanced PulseAudio sound server Draw from online software repositories with Package Manager and Package Updater Build an Internet server with e-mail, Web, DNS, FTP, and database services Secure your computer with firewalls, password protection, and SELinux Try out cutting-edge Fedora 8 features: Use Codeina to get legal software to play MP3, Windows media, and other audio/video formats Organize photos, music, friends, docs, and Web favorites in the new experimental Online Desktop Explore the latest in KVM and QEMU virtualization and AIGLX 3D-desktop What's on the DVD and CD-ROM? Install Fedora 8 (8GB) from DVD Boot Fedora 8 GNOME Live CD, and then install its contents to your hard drive System Requirements: Please see the Preface and Appendix A for details and complete system requirements. Open for more! Check out the new Online Desktop Find ten cool things to do with Fedora Run a Fedora 8 quick install Add pop and power with Online Desktop and 3D acceleration Organizing the people, places, and things you need on your desktop is now easier with the new GNOME Online Desktop. Get organized, then pile on some bling with 3D-accelerated desktop effects. Put friends, photos, and fun on your new Online Desktop Your favorite people and your online favorites are totally accessible from the new GNOME Online Desktop. Play with 3D desktop animations Continued improvements in 3D software let you rotate workspaces on a 3D cube, choose 3D minimize effects, and set 3D wobble effects.
Strong Positive Reducibilities
Authors: Andrea Sorbi
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

The need of formalizing a satisfactory notion of relative computability of partial functions leads to enumeration reducibility, which can be viewed as computing with nondeterministic Turing machines using positive information. This paper is dedicated to certain reducibilities that are stronger than enumeration reducibility, with emphasis given to s-reducibility,which appears often in computability theory and applications. We review some of the most notable properties of s-reducibility, together with the main differences distinguishing the s-degrees from the e-degrees, both at the global and local level.
Analysis of Learning Process of Online Discussion in a Large Class
Authors: Kazuharu Toyokawa, Wenli Chen, Chee-Kit Looi
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

We carried out an investigation of online discussion as a supplementary teaching and learning method in a large class in college in Japan, and an analysis of the learning process of students through a content analysis approach. We found that instructors' face-to-face encouragement is important for students' active participation in online discussion, and that learners can and do learn from other opinions and progress in their thinking week by week. We also found students held positive attitudes toward online discussions.
An automated ligand evolution system using Bayesian optimization algorithm
Authors: Masaharu Munetomo, Kiyoshi Akama, Haruki Maeda
Venue: WSEAS Transactions on Information Science and Applications (2009)

Ligand docking checks whether a drug chemical called ligand matches the target receptor protein of human organ or not. Docking by computer simulation is becoming popular in drug design process to reduce cost and time of the chemical experiments. This paper presents a novel approach generating optimal ligand structures from scratch based on de novo ligand design approach employing Bayesian optimization algorithm to realize an automated design of drug and other chemical structures. The proposed approach searches an optimal structure of ligand that minimizes bond energy to the receptor protein, and the structure of ligand is generated by adding small fragments of molecules to the base structure. The decision of adding fragments are controlled by Bayesian optimization algorithm which is considered as a promising approach in probabilistic model-building genetic algorithms. We have built a system that automatically generates an optimal structure of ligand, and through numerical experiments performed on a PC cluster, we show the effectiveness of our approach compared to the conventional approach using classical genetic algorithms.
Contingency Matrix Theory II: Degree of Dependence as Granularity
Authors: Shusaku Tsumoto, Shoji Hirano
Venue: Fundamenta Informaticae (2009)

The degree of granularity of a contingency table is closely related with that of dependence of contingency tables. We investigate these relations from the viewpoints of determinantal devisors and determinants. From the results of determinantal divisors, it seems that the devisors provide information on the degree of dependencies between the matrix of the whole elements and its submatrices and the increase of the degree of granularity may lead to that of dependence. However, the other approach shows that a constraint on the sample size of a contingency table is very strong, which leads to the evaluation formula where the increase of degree of granularity gives the decrease of dependency.
Digital Images: Weighted Automata Theoretical Aspects
Authors: Alexandre Scalzitti, Kazumi Nakamatsu, J. M. Abe
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

This paper is a survey which presents fundamental ideas about the application of weighted automata in digital image processing. We present basic definitions such as semirings, weighted automata and digital images. Then we explain how we can represent an image using a weighted automaton.
Bioinformatics' Challenges to Computer Science: Bioinformatics Tools and Biomedical Modeling
Authors: Mario Cannataro, Rodrigo Weber Dos Santos, Joakim Sundnes
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

The second edition of the workshop on Bioinformatics' Challenges to Computer Science aimed to discuss the gap between bioinformatics tools and biomedical simulation and modeling. This short paper summarizes the papers accepted for the workshop, focusing on bioinformatics applications at the genomics and molecular level as well as simulation and management at the biomedical level, and gives a brief outlook on future developments.
Incremental Network Optimization: Theory and Algorithms
Authors: Onur Şeref, Ravindra K. Ahuja, James B. Orlin
Venue: Operations Research (2009)

In an incremental optimization problem, we are given a feasible solution x0 of an optimization problem P, and we want to make an incremental change in x0 that will result in the greatest improvement in the objective function. In this paper, we study the incremental optimization versions of six well-known network problems. We present a strongly polynomial algorithm for the incremental minimum spanning tree problem. We show that the incremental minimum cost flow problem and the incremental maximum flow problem can be solved in polynomial time using Lagrangian relaxation. We consider two versions of the incremental minimum shortest path problem, where increments are measured via arc inclusions and arc exclusions. We present a strongly polynomial time solution for the arc inclusion version and show that the arc exclusion version is NP-complete. We show that the incremental minimum cut problem is NP-complete and that the incremental minimum assignment problem reduces to the minimum exact matching problem, for which a randomized polynomial time algorithm is known.
Surveillance Robot Utilizing Video and Audio Information
Authors: Xinyu Wu, Haitao Gong, Pei Chen, Zhi Zhong, Yangsheng Xu
Venue: Journal of Intelligent and Robotic Systems (2009)

For the aging population, surveillance in household environments has become more and more important. In this paper, we present a household robot that can detect abnormal events by utilizing video and audio information. In our approach, moving targets can be detected by the robot using a passive acoustic location device. The robot then tracks the targets by employing a particle filter algorithm. To adapt to different lighting conditions, the target model is updated regularly based on an update mechanism. To ensure robust tracking, the robot detects abnormal human behavior by tracking the upper body of a person. For audio surveillance, Mel frequency cepstral coefficients (MFCC) is used to extract features from audio information. Those features are input to a support vector machine classifier for analysis. Experimental results show that the robot can detect abnormal behavior such as "falling down" and "running". Also, a 88.17% accuracy rate is achieved in the detection of abnormal audio information like "crying", "groan", and "gun shooting". To lower the false alarms by abnormal sound detection system, the passive acoustic location device directs the robot to the scene where abnormal events occur and the robot can employ its camera to further confirm the occurrence of the events. At last, the robot will send the image captured by the robot to the mobile phone of master.
Optimal control for stochastic linear quadratic singular system with indefinite control cost and cross term using neural networks
Authors: N. Kumaresan, P. Balasubramaniam
Venue: Neural, Parallel Scientific Computations (2008)

In this paper, optimal control for stochastic linear singular system with indefinite control cost and cross term in the cost functional is obtained using neural networks. The goal is to provide optimal control with reduced calculus effort by comparing the solutions of the matrix Riccati differential equation (MRDE) obtained from well known traditional Runge Kutta (RK) method and nontraditional neural network method. To obtain the optimal control, the solution of MRDE is computed by feed forward neural network (FFNN). Accuracy of the solution of the neural network approach to the problem is qualitatively better. The advantage of the proposed approach is that, once the network is trained, it allows instantaneous evaluation of solution at any desired number of points spending negligible computing time and memory. The computation time of the proposed method is shorter than the traditional RK method. An illustrative numerical example is presented for the proposed method.
Aliasing maps for robot global localization
Authors: Emanuele Frontoni, Primo Zingaretti
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)

In this paper we present a mobile robot localization system that integrates Monte-Carlo localization with an active action-selection approach based on an aliasing map.The main novelty of the approach is in the off-line evaluation of the perceptual aliasing of the environment and in the use of this knowledge to perform localization processes faster and better. Preliminary results show improved performances compared with the classic Monte-Carlo localization approach.
Dimension inference in spreadsheets
Authors: Chris Chambers, Martin Erwig
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

We present a reasoning system for inferring dimension information in spreadsheets. This system can be used to check the consistency of spreadsheet formulas and can be employed to detect errors in spreadsheets. We have prototypically implemented the system as an add-in to Excel. In an evaluation of this implementation we were able to detect dimension errors in almost 50% of the investigated spreadsheets, which shows (i) that the system works reliably in practice and (ii) that dimension information can be well exploited to uncover errors in spreadsheets.
A fast iterative method for dominant points detection of digital curves
Authors: Cecilia Di Ruberto, Andrea Morgera
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

A new algorithm for detecting dominant points of digitized closed curves is presented. At first a process of localization of maximum curvature points is done. The method adds iteratively contour points as dominant points by a criterion that considers the distance of contour points respect to the set of dominant points calculated in previous steps. It follows a final process of refinement. The performance of our method are successfully compared with other dominant point extraction techniques. Finally, some examples of polygonal approximation are showed.
Software Product Quality: Ensuring a Common Goal
Authors: Sebastian Barney, Claes Wohlin
Venue: Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes (2009)

Software qualities are in many cases tacit and hard to measure. Thus, there is a potential risk that they get lower priority than deadlines, cost and functionality. Yet software qualities impact customers, profits and even developer efficiency. This paper presents a method to evaluate the priority of software qualities in an industrial context. The method is applied in a case study, where the ISO 9126 model for software quality is combined with Theory-W to create a process for evaluating the alignment between success-critical stakeholder groups in the area of software product quality. The results of an exploratory case study using this tool is then presented and discussed. It is shown that the method provides valuable information about software qualities.
Reconstruction-based contribution for process monitoring
Authors: Carlos F. Alcala, S. Joe Qin
Venue: Automatica (Journal of IFAC) (2009)

This paper presents a new method to perform fault diagnosis for data-correlation based process monitoring. As an alternative to the traditional contribution plot method, a reconstruction-based contribution for fault diagnosis is proposed based on monitored indices, SPE, T^2 and a combined index @f. Analysis of the diagnosability of the traditional contributions and the reconstruction-based contributions is performed. The lack of diagnosability of traditional contributions is analyzed for the case of single sensor faults with large fault magnitudes, whereas for the same case the proposed reconstruction-based contributions guarantee correct diagnosis. Monte Carlo simulation results are provided for the case of modest fault magnitudes by randomly assigning fault sensors and fault magnitudes.
Does single broadband or multispectral thermal data add information for classification of visible, near-and shortwave infrared imagery of urban areas?
Authors: T. A. Warner, F. Nerry
Venue: International Journal of Remote Sensing (2009)

The potential value of combining broadband and multispectral thermal infrared (TIR) data with multispectral and hyperspectral visible, near-infrared (VNIR) and shortwave infrared (SWIR) data was investigated within the context of urban land-cover classification. Using a case study of airborne Digital Airborne Imaging Spectrometer (DAIS) imagery of Strasbourg, France, the relative contribution of TIR wavelengths to classification accuracy was investigated for hyperspectral and simulated multispectral IKONOS, SPOT and Landsat Thematic Mapper (TM) bands. A support vector machines (SVM) classifier was used because this method was found to be very effective at handling the complex distributions of the heterogeneous land cover classes. The overall classification accuracy varied greatly with different band combinations. The inclusion of a single broad thermal band increased classification accuracy by as much as 20% for simulated IKONOS bands, but only 4% for hyperspectral VNIR and SWIR data. Adding multispectral TIR data raised the average accuracy approximately a further 10% for each band combination studied. Thermal wavelengths were found to be particularly useful for reducing the confusion between road and roof surfaces.
Non-negatively constrained image deblurring with an inexact interior point method
Authors: Silvia Bonettini, Thomas Serafini
Venue: Journal of Computational and Applied Mathematics (2009)

Nonlinear image deblurring procedures based on probabilistic considerations have been widely investigated in the literature. This approach leads to model the deblurring problem as a large scale optimization problem, with a nonlinear, convex objective function and non-negativity constraints on the sign of the variables. The interior point methods have shown in the last years to be very reliable in nonlinear programs. In this paper we propose an inexact Newton interior point (IP) algorithm designed for the solution of the deblurring problem. The numerical experience compares the IP method with another state-of-the-art method, the Lucy Richardson algorithm, and shows a significant improvement of the processing time.
A web-based annotation tool supporting e-learning
Authors: F. Bonifazi, S. Levialdi, P. Rizzo, R. Trinchese
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

A typical user, when learning, annotates text, figures and other contents, so as to better highlight, memorize, and retrieve relevant information. A few annotation programs exist but either change the contents of the document, or do not support distance learning through the web. We report work-in-progress on a <u>u</u>ser-<u>c</u>entered <u>a</u>nnotation <u>t</u>ool (UCAT) which allows students to annotate, following their personal styles, (using different icons, colors and signed versions) any document belonging to authorware within a course. We have chosen Amaya as the working environment since, belonging to the World Wide Web Consortium (W3C), it complies with the semantic web specifications on document formats, like RDF. An example of the deployment of UCAT will be shown in the paper.
Finite-State Local Grammars for Disambiguating Conjunctions in Portuguese Proper Names
Authors: Samuel Eleutério, Elisabete Ranchhod
Venue: Proceeding of the 2009 conference on Finite-State Methods and Natural Language Processing: Post-proceedings of the 7th International Workshop FSMNLP 2008 (2009)

Like common noun phrases, proper names contain ambiguous conjoined phrases that make their delimitation and classification difficult in text. This paper presents a finite-state approach to the disambiguation of Portuguese candidate proper name strings containing the coordinating conjunction e (and). In such name strings, the conjunction can denote a relation between two independent names, but it can also be part of a multiword proper name. The coordination of multiword independent names may involve ellipsis of some lexical constituents, which causes additional difficulties to proper name identification and classification.
Project Management in Easy Steps
Authors: John Carroll
Venue:  (2009)

Written in clear, jargon-free English, this practical guide walks readers through each step of the process of managing a successful project and introduces the key skills that every project manager needs to develop. Emphasizing the importance of starting up a project in a controlled manner an area where many projects go wrong it explains how to select and build a winning team and ensure that all project stakeholders are involved and on the same page. It then takes the reader through each stage of a typical project, using easy-to-follow examples and helpful lists of applicable tasks and deliverables along with valuable insights on risk management and how to plan, lead, organize, and control a project. Finally, it covers the right way to end a project and capture the lessons learned from it, thus benefiting both the managers next project and the business itself.
Intelligent Systems and Signal Processing in Power Engineering, 1st edition
Authors: Abhisek Ukil
Venue:  (2007)

Power engineering has become a multidisciplinary field ranging from linear algebra, electronics, signal processing to artificial intelligence including recent trends like bio-inspired computation, lateral computing and so on. In this book, Ukil builds the bridge between these inter-disciplinary power engineering practices. The book looks into two major fields used in modern power systems: intelligent systems and the signal processing. The intelligent systems section comprises of fuzzy logic, neural network and support vector machine. The author looks at relevant theories on the topics without assuming much particular background. Following the theoretical basics, he studies their applications in various problems in power engineering, like, load forecasting, phase balancing, or disturbance analysis. These application studies are of two types: full application studies explained like in-depth case-studies, and semi-developed application ideas with scope for further extension. This is followed by pointers to further research information. In the second part, the book leads into the signal processing from the basics of the system theory, followed by fundamentals of different signal processing transforms with examples. A section follows about the sampling technique and the digital filters which are the ultimate processing tools. The theoretical basics are substantiated by some of the applications in power engineering, both in-depth and semi-developed as before. This also ends up with pointers to further research information. 'Intelligent Systems and Signal Processing in Power Engineering' is helpful for students, researchers and engineers, trying to solve power engineering problems using intelligent systems and signal processing, or seeking applications of intelligent systems and signal processing in power engineering. 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
Solution Enumeration for Projected Boolean Search Problems
Authors: Martin Gebser, Benjamin Kaufmann, Torsten Schaub
Venue: Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2009)

Many real-world problems require the enumeration of all solutions of combinatorial search problems, even though this is often infeasible in practice. However, not always all parts of a solution are needed. We are thus interested in projecting solutions to a restricted vocabulary. Yet, the adaption of Boolean constraint solving algorithms turns out to be non-obvious provided one wants a repetition-free enumeration in polynomial space. We address this problem and propose a new algorithm computing projective solutions. Although we have implemented our approach in the context of Answer Set Programming, it is readily applicable to any solver based on modern Boolean constraint technology.
A view of the parallel computing landscape
Authors: Krste Asanovic, Rastislav Bodik, James Demmel, Tony Keaveny, Kurt Keutzer, John Kubiatowicz, Nelson Morgan, David Patterson, Koushik Sen, John Wawrzynek, David Wessel, Katherine Yelick
Venue: Communications of the ACM (2009)

Writing programs that scale with increasing numbers of cores should be as easy as writing programs for sequential computers.