ppxscal/embedding_network huggingface dataset:
Direct torque control with variable voltage duty ratio for inverter fed induction motor drives
Authors: Sanda Victorinne Paturca, Mircea Covrig, Costin Cepisca, Sorin Dan Grigorescu, Stefan Gheorghe
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

Direct Torque Control (DTC) is a high performance control technique introduced for voltage inverter fed induction motor drives. This technique, based on selecting the optimum stator voltage vector of the inverter standard topology, makes the torque and stator flux reference values to be reached quickly, with a small number of changes in inverter switching states, resulting in a very good dynamic response. However, by this switching technique, based on hysteresis, large and small torque and flux errors are not distinguished, which cause a high torque and current ripple in motor steady state operation. To overcome this problem, this paper proposes a solution, which consists in the modulation of the nonzero voltage vector duration over a sampling period, according to the instant values of the torque and stator flux errors. The introduced duty ratio is calculated using a relation containing terms proportional to these errors. The presented results show the torque, flux and current ripple reduction obtained by using the proposed method. The main advantage is that it requires an insignificant additional computation, preserving the simplicity of the classical DTC.
Building an OptIPlanet collaboratory to support microbial metagenomics
Authors: Larry Smarr, Paul Gilna, Phil Papadopoulos, Thomas A. DeFanti, Greg Hidley, John Wooley, E. Virginia Armbrust, Forest Rohwer, Eric Frost
Venue: Future Generation Computer Systems (2009)

We describe early experiments in the adoption of the OptIPuter architecture to provide data-intensive capabilities to several remote users of a large-scale, multi-year effort to organize and make publicly available data describing a wide variety of marine microbial ecologies, their genomic content, and the local environments in which they live-marine microbial metagenomics. Microbial genomes are millions of base pairs in length, requiring both a global view of the genome and the ability to zoom into detail interactively, enabled by the OptIPortal. We describe the design of a scientific data and compute server, enhanced by OptIPuter technologies, and early examples of its use in support of high performance science applications in this emerging scientific field.
Dynamic privacy assessment in a smart house environment using multimodal sensing
Authors: Simon Moncrieff, Svetha Venkatesh, Geoff West
Venue: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) (2008)

Surveillance applications in private environments such as smart houses require a privacy management policy if such systems are to be accepted by the occupants of the environment. This is due to the invasive nature of surveillance, and the private nature of the home. In this article, we propose a framework for dynamically altering the privacy policy applied to the monitoring of a smart house based on the situation within the environment. Initially the situation, or context, within the environment is determined; we identify several factors for determining environmental context, and propose methods to quantify the context using audio and binary sensor data. The context is then mapped to an appropriate privacy policy, which is implemented by applying data hiding techniques to control access to data gathered from various information sources. The significance of this work lies in the examination of privacy issues related to assisted-living smart house environments. A single privacy policy in such applications would be either too restrictive for an observer, for example, a carer, or too invasive for the occupants. We address this by proposing a dynamic method, with the aim of decreasing the invasiveness of the technology, while retaining the purpose of the system.
The Development and Application of Quick Search Engine Based on Special Fields
Authors: Shouning Qu, Bing Zhang, Wei Wang, Xinsheng Yu
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

This paper analyzed some problems existing in the business search engine when it searched the special fields, and then put forward a set of search engine scheme about data warehouse design based on data mining. It applied the improved association rules algorithm to text clustering algorithm. At the same time in combination with the advantages of J2EE architecture in system development, this paper described how to apply J2EE platform to form an exact and efficient intelligent search engine system by the technologies such as JSP, Servlets, EJB, JDBC and so on.
Augmented Reality Based Vision System for Network Based Mobile Robot
Authors: Ho-Dong Lee, Dongwon Kim, Min-Chul Park, Gwi-Tae Park
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The human machine interface is an essential part of intelligent robotic system. Through the human machine interface, human user can interact with the robot. Especially, in tele-robotic environment, the human machine interface can be developed with remarkable extended functionality. In this paper, we introduce a tele-presence vision system for monitoring of a network based mobile robot. The vision system is a vision part of human machine interface with augmented reality for the network based mobile robot. We synchronize head motion of human user and the camera motion of the mobile robot using visual information. So user of the mobile robot can monitor environment of the mobile robot as eyesight of mobile robot. Also, the system partially creates a panoramic image to solve a pose latency problem. In this paper, we evaluate and compare panoramic images from two different methods. One is pattern matching method which is simple and fast, the other is Scale Invariant Feature Transform (SIFT) which is complex and slow. Finally, proposed vision system provides high resolution and wide Field Of View (FOV) to user who is wearing a Head Mounted Display (HMD).
Text Learning and Hierarchical Feature Selection in Webpage Classification
Authors: Xiaogang Peng, Zhong Ming, Haitao Wang
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

One of the solutions of retrieving information from the Internet is by classifying web pages automatically. In almost all classification methods that have been published, feature selection is a very important issue. Although there are many feature selection methods has been proposed. Most of them focus on the features within a category and ignore that the hierarchy of categories also plays an important role in achieving accurate classification results. This paper proposes a new feature selection method that incorporates hierarchical information, which prevents the classifying process from going through every node in the hierarchy. Our test results show that our classification algorithm using hierarchical information reduces the search complexity from n to log(n) and increases the accuracy by 6.2% comparing to a related algorithm.
A Virtual Computing Laboratory
Authors: Joe Kaylor, George K. Thiruvathukal
Venue: Computing in Science and Engineering (2008)

Many institutions choose to do periodic imaging of computers, which is both painstaking and limiting in terms of keeping software up to date. The authors describe an approach that builds on existing virtualization technologies.
Large-Scale Clustering and Complete Facet and Tag Calculation
Authors: Bolette Ammitzbøll Madsen
Venue: Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries (2007)

The State and University Library of Denmark is developing an integrated search system called Summa, and as part of the Summa project a clustering module and a facet module. Simple clusters have been created for a collection of more than six and a half million library metadata records using a linear clustering algorithm. The created clusters are used to enrich the metadata records, and search results are presented to the user using a faceted browsing interface alongside a ranked result list. The most frequent tags in the different facets in the search result can be calculated and presented at a rate of approximately three million records per second per machine.
An Animated Cryptographic Learning Object
Authors: Rachid Anane, Kevin Purohit, Georgios Theodoropoulos
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

Algorithmic animation has been the focus of intense research in many disciplines and its impact on the educational process has been marked by increasing learner autonomy. Research in this field is driven by the belief that algorithm animation can be a more effective means of instruction than manual or verbal modes of delivery. Encryption algorithms in particular offer an interesting domain for the application of animation principles in learner/content interaction. The main challenge however has been how to design effective animations with a pedagogical value. This paper is concerned with the presentation of an animation of the DES algorithm that exhibits many of the features of useful instructional material. Its pedagogical value is expressed in terms of intrinsic qualities and, in particular, the degree of interactivity and the granularity of abstraction.
When Co-learners Work on Complementary Texts: Effects on Outcome Convergence
Authors: Gaëlle Molinari, Mirweis Sangin, Pierre Dillenbourg
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

In this paper, we examined the effect of knowledge interdependence among co-learners on knowledge convergence outcomes. Prior to collaboration, two partners read the same text in the independent condition while each of them read one of two complementary texts in the interdependent condition. In the remote collaboration phase, partners were asked to build a collaborative concept map. While interacting, they were provided with visualizations (concept maps) of both their own- and their partner's knowledge. No effect of interdependence could be found with respect to both outcome knowledge equivalence and shared outcome knowledge. In the independence condition, convergence was mainly due to the fact that partners received the same text before collaboration. In the interdependence condition, shared knowledge did not occur as a result of social interaction. It seems that participants were able to individually link what they learnt from text to complementary information provided by their partner's map.
Comparison of Point Sets and Sequences for Quasi-Monte Carlo and for Random Number Generation
Authors: Pierre L'Ecuyer
Venue: Proceedings of the 5th international conference on Sequences and Their Applications (2008)

Algorithmic random number generators require recurring sequences with very long periods and good multivariate uniformity properties. Point sets and sequences for quasi-Monte Carlo numerical integration need similar multivariate uniformity properties as well. It then comes as no surprise that both types of applications share common (or similar) construction methods. However, there are some differences in both the measures of uniformity and the construction methods used in practice. We briefly survey these methods and explain some of the reasons for the differences.
Method for Evaluating the Security Risk of a Website Against Phishing Attacks
Authors: Young-Gab Kim, Sanghyun Cho, Jun-Sub Lee, Min-Soo Lee, In Ho Kim, Sung Hoon Kim
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

As Internet technologies evolve, phishing and pharming attacks frequently occur and diversify. In order to protect the economic loss and privacy of Internet users against the phishing attacks, several researches such as website authentication and email authentication have been studied. Although, most of them use website black-list (WBL) or website white-list (WWL), there are several weak points, such as validity of WBL DB (database) and the short life-cycle of phishing websites. That is, it is impossible to discriminate between legitimate and forged websites until the phishing attacks are detected and recorded into WBL DB. Furthermore, the existing WBL and WWL approaches hardly counter the new generation of sophisticated malware pharming attacks. In this paper, in order to overcome the limitation of WBL and WWL approaches, new approach based on the WWL approach, which can quantitatively estimate the security risk of websites that is security risk degree representing the phishing websites, is proposed.
E-Commerce Readiness and Diffusion: The Case of Brazil
Authors: Paulo Bastos Tigre
Venue: I-WAYS - The Journal of E-Government Policy and Regulation (2003)

In Brazil, a poor telecommunication infrastructure was considered an important barrier for e-business diffusion. However, from 1998, when the telecom system was privatized, to 2000, telecom investments boosted to an average of 1.36% of GNP a year, a percentage well above both Brazilian and Latin American historical levels. There is now idle capacity and telecommunication infrastructure is no longer considered a major barrier for e-commerce. Brazil's financial sector is the clear leader in adopting information technologies, and is widely considered the leading user of the Internet for marketing, online sales, and service and support. The sum of the survey results suggests that the financial sector has capitalized on its experience with IT in order to adopt e-commerce technologies and to integrate them with existing information systems. E-commerce in Brazil is strongly anchored in information intensive sectors little affected by foreign transactions. Local forces seem to play a more influential role due to Brazil's unique economic history and government policies. For e-commerce diffusion, a factor more important than the sector itself is the scale of information flow among various agents within the economy. Information-intensity is, in part, related to the size of the business. The larger the firm, the easier it obtains scale benefits of digital services. However, some activities demand more information exchange than others. Distribution and finance face similar driving forces for e-commerce diffusion, but are different from manufacturing. The manufacturing industry is driven to achieve, by cost reduction, through inventory reduction and improved logistics. But while productivity growth is the most important driving force for manufacturing, the finance and distribution sectors focus on opportunities to expand and improve their relationships with clients. The Internet is increasing the intensity of competition rather than the number of competitors. Whereas in the recent past e-commerce was dominated by new companies, nowadays-existing market leaders seem to be rapidly gaining business through the new channel. Strong links between users and producers of IT solutions facilitate technological leadership. The case study on the banking industry showed that internal technological capabilities were key for e-commerce leadership, since they enhanced the user-producer links providing capabilities that are flexible and tailored to specific needs. Legal protection is a more important barrier than expected. This includes lack of business laws for e-commerce and inadequate legal protection for Internet purchases, barriers affecting more than 40% of the surveyed Brazilian firms. 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
A game-theoretic analysis of the implications of overlay network traffic on ISP peering
Authors: Jessie Hui Wang, Dah Ming Chiu, John C. S. Lui
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

Inter-ISP traffic flow determines the settlement between ISPs and affects the perceived performance of ISP services. In today's Internet, the inter-ISP traffic flow patterns are controlled not only by ISPs' policy-based routing configuration and traffic engineering, but also by application layer routing. The goal of this paper is to study the economic implications of this shift in Internet traffic control assuming rational ISPs and subscribers. For this purpose, we build a general traffic model that predicts traffic patterns based on subscriber distribution and abstract traffic controls such as caching functions and performance sensitivity functions. We also build a game-theoretic model of subscribers picking ISPs, and ISPs making provisioning and peering decisions. In particular, we apply this to a local market where two ISPs compete for market share of subscribers under two traffic patterns: ''Web'' and ''P2P overlay'', that typifies the transition the current Internet is going through. Our methodology can be used to quantitatively demonstrate that (1) while economy of scale is the predominant property of the competitive ISP market, P2P traffic may introduce unfair distribution of peering benefit (i.e. free-riding); (2) the large ISP can restore more fairness by reducing its private capacity (bandwidth throttling), which has the drawback of hurting business growth; and (3) ISPs can reduce the level of peering (e.g. by reducing peering bandwidth) to restore more fairness, but this has the side-effect of also reducing the ISPs' collective bargaining power towards subscribers.
Discrete model of a TCSC for automation and planning studies of the electrical transmission system in Colombia
Authors: Jorge W. Gonzalez, Hugo Cardona, Idi Isaac, Gabriel Lopez, E. Ruiz
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

This paper presents the development of a discrete Thyristor Controlled Series Capacitor, TCSC, model using the software DIgSILENT PF. The discrete model is based on switchable inductances. The model was inserted in a practical large network of the Electrical Transmission System in Colombia (ETSC) for automation and planning purposes, as much in steady as transient analysis. The results of the studies with the discrete model were very satisfying and allowed to propose further automated solutions to the needs of expanding the ETSC.
Worm 5: Pseudo-organics Computer and Natural Live System
Authors: Yick Kuen Lee, Ying Ying Lee
Venue: Proceedings of the international conference on Life System Modeling and Simulation (2007)

Life began hundred million years ago; it started from simple inorganic substances to intricate multi-cellular organics. Gradually, the brains of higher animals developed emotions and intelligence. These are well illustrated by the learning abilities and social behaviors of man. Those intelligent activities, progress from simple to complicate, primitive to sophisticated processes from incarnate to abstract. Man started to create artificial intelligent to enhance their brain capabilities sixty years ago. Here we are making a comparison between the natural and artificial intelligent, and see what we can emulate more from Nature. And disclose the author's point of view about the creation of natural lives.
Emerging Pattern Based Classification in Relational Data Mining
Authors: Michelangelo Ceci, Annalisa Appice, Donato Malerba
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The usage of descriptive data mining methods for predictive purposes is a recent trend in data mining research. It is well motivated by the understandability of learned models, the limitation of the so-called "horizon effect" and by the fact that it is a multi-task solution. In particular, associative classification, whose main idea is to exploit association rules discovery approaches in classification, gathered a lot of attention in recent years. A similar idea is represented by the use of emerging patterns discovery for classification purposes. Emerging Patterns are classes of regularities whose support significantly changes from one class to another and the main idea is to exploit class characterization provided by discovered emerging patterns for class labeling. In this paper we propose and compare two distinct emerging patterns based classification approaches that work in the relational setting. Experiments empirically prove the effectiveness of both approaches and confirm the advantage with respect to associative classification.
Pseudometrics for State Aggregation in Average Reward Markov Decision Processes
Authors: Ronald Ortner
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

We consider how state similarity in average reward Markov decision processes (MDPs) may be described by pseudometrics. Introducing the notion of adequate pseudometrics which are well adapted to the structure of the MDP, we show how these may be used for state aggregation. Upper bounds on the loss that may be caused by working on the aggregated instead of the original MDP are given and compared to the bounds that have been achieved for discounted reward MDPs.
Medical Knowledge Discovery from a Regional Asthma Dataset
Authors: Sam Schmidt, Gang Li, Yi-Ping Phoebe Chen
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Paediatric asthma represents a significant public health problem. To date, clinical data sets have typically been examined using traditional data analysis techniques. While such traditional statistical methods are invariably widespread, large volumes of data may overwhelm such approaches. The new generation of knowledge discovery techniques may therefore be a more appropriate means of analysis. The primary purpose of this study was to investigate an asthma data set, with the application of various data mining techniques for knowledge discovery. The current study utilises data from an asthma data set (n ≈ 17000). The findings revealed a number of factors and patterns of interest.
Conformal Slit Mapping and Its Applications to Brain Surface Parameterization
Authors: Yalin Wang, Xianfeng Gu, Tony F. Chan, Paul M. Thompson, Shing-Tung Yau
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We propose a method that computes a conformal mapping from a multiply connected mesh to the so-called slit domain, which consists of a canonical rectangle or disk in which 3D curved landmarks on the original surfaces are mapped to concentric or parallel lines in the slit domain. In this paper, we studied its application to brain surface parameterization. After cutting along some landmark curve features on surface models of the cerebral cortex, we obtain multiple connected domains. By computing exact harmonic one-forms, closed harmonic one-forms, and holomorphic one-forms, we are able to build a circular slit mapping that conformally maps the surface to an annulus with some concentric arcs and a rectangle with some slits. The whole algorithm is based on solving linear systems so it is very stable. In the slit domain parameterization results, the feature curves are either mapped to straight lines or concentric arcs. This representation is convenient for anatomical visualization, and may assist statistical comparisons of anatomy, surface-based registration and signal processing. Preliminary experimental results parameterizing various brain anatomical surfaces are presented.