ppxscal/embedding_network huggingface dataset:
Attributes of Web Site Usability: A Study of Web Users with the Repertory Grid Technique
Authors: Lai Tung, Yun Xu Felix Tan
Venue: International Journal of Electronic Commerce (2009)

Research on Web site usability using the Microsoft Usability Guidelines (MUG) have (1) assumed the MUG categories and subcategories as a given and (2) focused on the relationships between these attributes and site usability, thereby largely ignoring their underlying meaning. Using the Repertory Grid Technique, the present research elicits the attributes that Web users consider important when using business-to-consumer (B2C) Web sites. The results support the MUG framework but identify three additional attributes that warrant being MUG subcategories: quality of Web site content, Web site appearance, and extent to which the site provides convenient services to facilitate on-line activities. An enhanced MUG is presented. The implications for research and practice are discussed.
An innovative approach to identify the IP address in denial-of-service (DoS) attacks based on Cauchy's integral theorem
Authors: Mateus Mosca Viana, Riverson Rios, Rossana Maria de Castro Andrade, José Neuman de Souza
Venue: International Journal of Network Management (2009)

Denial-of-service (DoS) and distributed denial-of-service (DDoS) are two of the most severe attacks against computer networks, especially the Internet. Despite its destructive effect, planning these attacks is a feasible task. Given that most attackers usually spoof the source address in packet headers, countermeasures can be based on two steps. First of all, some information from the attack space of the offender must be gathered. Fortunately, packets that reach a victim carry important data that can be acquired by means of a data collection process. One possibility is to use the probabilistic packet marking (PPM) approach for data acquisition. Once this is achieved, the next step consists of reconstructing the attack path, which can be carried out by several methods available in the literature. However, none of them provides a precise solution. In this paper, a new theoretical tracking model for the identification of DoS attackers is presented. The model unites the PPM approach and the concept of winding number, derived from the well-known Cauchy's integral theorem. The winding number is a hydraulic analogy of the amount of attacking packets growing from a router. A suitable transformation allows seeing the packet traffic, in the attack environment, as a fluid flux in the space of complex variables. The method of solving the tracking problem and identifying the sources of attack presents an additional motivation: the use of continuous techniques when approaching a problem that occurs in a discrete environment. Such association will contribute to the development of further solutions possibly more robust than the one dealt with here. This paper shows that the new model can correctly identify the IP address of the router from which the attack comes by using an integral equation derived from the winding number expression.
ISO 9241-9 evaluation of video game controllers
Authors: Daniel Natapov, Steven J. Castellucci, I. Scott MacKenzie
Venue: Proceedings of Graphics Interface 2009 (2009)

Fifteen participants completed a study comparing video game controllers for point-select tasks. We used a Fitts' law task, as per ISO 9241-9, using the Nintendo Wii Remote for infrared pointing, the Nintendo Classic Controller for analogue stick pointing, and a standard mouse as a baseline condition. The mouse had the highest throughput at 3.78 bps. Both game controllers performed poorly by comparison. The Wii Remote throughput was 31.5% lower, at 2.59 bps, and the Classic Controller 60.8% lower at 1.48 bps. Comparing just the video game controllers, the Wii Remote presents a 75% increase in throughput over the Classic Controller. Error rates for the mouse, Classic Controller, and the Wii Remote were 3.53%, 6.58%, and 10.2%, respectively. Fourteen of 15 participants expressed a preference for the Wii Remote over the Classic Controller for pointing tasks in a home entertainment environment.
Intelligent MAS for Electronic Customer Relationship Development
Authors: Javad Soroor
Venue: Proceeding of the 2005 conference on Self-Organization and Autonomic Informatics (I) (2005)

Customer relationship management encompasses all the aspects of the interaction with customer and it joins all the customer related elements within an organization together in an intelligent manner. Despite its numerous benefits for organizations, there are some serious concerns regarding the implementation of CRM. Customer relationship management projects are usually complicated, long-term and resource-consuming with outstanding results for far future. The new conceptual model of CRM introduced here is a Multi-Agent System (MAS) called 'agent-based CRD'. It is the process of developing electronic context and content within customer relationships on a collaborative basis using intelligent agents. Agent-based CRD comprises three essential building blocks: single view, intelligent electronic dialogue, and opportunity spotting. A general structure for agent-based CRD framework, which is easy to understand and implement is presented graphically, theoretically, and technically in full details.
Motion estimation analysis for unsupervised training for lip reading user authentication systems
Authors: Hanan A. Mahmoud, Khaled Alghathbar, Fahad Bin Muhaya
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

This paper proposes a lip reading technique for speech recognition by using motion estimation analysis. Motion estimation is done for lip movement image sequences representing speech. In this methodology, the motion estimation is computed without extracting the speaker's lip contours and location. This leads to obtaining robust visual features for lip movements representing utterances. Our methodology comprises of two phases, a training phase and a recognition phase. In both phases an n × n video frame of the image sequence for an utterances (can be an alphanumeric character, word or a sentence in more complicated analysis) is divided into m × m blocks. Our method calculates and fits eight curves for each frame. Each curve represents motion estimation of this frame in a specific direction. These eight curves are representing set of features of a specific frame and are extracted in an unsupervised manner. The feature set consists of the integral values of the motion estimation. These features are expected to be extremely effective in the training phase. The feature sets are used to characterize specific utterances with no additional acoustic feature set. A corpus of utterances and their motion estimation features are built in the training phase. The recognition phase is accomplished by extracting the feature set,from the new image sequence of lip movement of an utterance, and compare it to the corpus using the mean square error metric for recognition.
iPhone Pocket Guide, 2nd edition
Authors: Christopher Breen
Venue:  (2007)

Here's your essential companion to Apples iPhone. This handy, low-priced book is packed with quick results so you can jump in and master the iPhone right away. Snappy writing, eye-catching graphics, and a fresh design walks you through the most common iPhone tasks. The iPhone Pocket Guide shows you how to: Set up and quickly start using your phone/iPod/Internet device. Make and receive calls and send text messages with your phone. Sync calendar and contacts between the iPhone and your Mac or Windows PC. Send email using AT&Ts wireless network or a Wi-Fi connection. Listen to songs and watch movies and TV shows (and YouTube!). Surf the Web using the built-in Safari browser. View photos and take pictures with the built-in camera. Get instant info using the built-in Stocks, Maps, Weather, and Clock applications. Run the numbers with Calculator and jot quick reminders with Notes. Fix common problems and learn what to do if you cant fi x them yourself. 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
The Lattice-Boltzmann Method on Optimal Sampling Lattices
Authors: Usman R. Alim, Alireza Entezari, Torsten Möller
Venue: IEEE Transactions on Visualization and Computer Graphics (2009)

In this paper, we extend the single relaxation time Lattice-Boltzmann Method (LBM) to the 3D body-centered cubic (BCC) lattice. We show that the D3bQ15 lattice defined by a 15 neighborhood connectivity of the BCC lattice is not only capable of more accurately discretizing the velocity space of the continuous Boltzmann equation as compared to the D3Q15 Cartesian lattice, it also achieves a comparable spatial discretization with 30 percent less samples. We validate the accuracy of our proposed lattice by investigating its performance on the 3D lid-driven cavity flow problem and show that the D3bQ15 lattice offers significant cost savings while maintaining a comparable accuracy. We demonstrate the efficiency of our method and the impact on graphics and visualization techniques via the application of line-integral convolution on 2D slices as well as the extraction of streamlines of the 3D flow. We further study the benefits of our proposed lattice by applying it to the problem of simulating smoke and show that the D3bQ15 lattice yields more detail and turbulence at a reduced computational cost.
Getting back to basics: Promoting the use of a traceability information model in practice
Authors: Patrick Mader, Orlena Gotel, Ilka Philippow
Venue: Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering (2009)

It is widely assumed that following a process is a good thing if you want to achieve and exploit the benefits of traceability on a software development project. A core component of any such process is the definition and use of a traceability information model. Such models provide guidance as to those software development artifacts to collect and those relations to establish, and are designed to ultimately support required project analyses. However, traceability still tends to be undertaken in rather ad hoc ways in industry, with unpredictable results. We contend that one reason for this situation is that current software development tools provide little support to practitioners for building and using customized project-specific traceability information models, without which even the simplest of processes are problematic to implement and gain the anticipated benefits from. In this paper, we highlight the typical decisions involved in creating a basic traceability information model, suggest a simple UML-based representation for its definition, and illustrate its central role in the context of a modeling tool. The intent of this paper is to re-focus attention on very practical ways to apply traceability information models in practice so as to encourage wider adoption.
Data reduction for data analysis
Authors: Carlo Dell'Aquila, Francesco Di Tria, Ezio Lefons, Filippo Tangorra
Venue: Proceedings of the 2nd conference on European computing conference (2008)

In decision support activities, it is very important to provide the user with feasible strategies to answer complex queries, besides furnishing fast query response time. The alternative to the time-consuming scan of huge amounts of data in data warehouses is provided by the use of data reduction for data analysis and a suitable approximate query processing strategy.
Alfabetizaci&oacute;n tecnol&oacute;gica: el reto del gobierno electr&oacute;nico en M&eacute;xico
Authors: Enrique Gabriel Munive Aportela, Erika Yamel Munive Cortés
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

The aim of this study is to review strategies, policies and the institutional agenda from the Mexican e-government; also explains the combined effect of environment (internal and external forces) in the National System named "e-M&eacute;xico", this info can be used as a guidelines to manage risks of digital government by leaders. Digital government can be viewed as a complicated game "crossword puzzle", composed of individual rules and players, when all players join up properly, the entertainment is granted, this could be established only by a "cross-effort puzzle", based on continuous learning and improvement, this change is critical to the success of the Mexican effort. This paper suggest that a new emphasis should be placed on the capacity to use information and knowledge in new and transformative ways like the civic training used in Mexico.
Discriminative Joint Context for Automatic Landmark Set Detection from a Single Cardiac MR Long Axis Slice
Authors: Xiaoguang Lu, Bogdan Georgescu, Arne Littmann, Edgar Mueller, Dorin Comaniciu
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Cardiac magnetic resonance (MR) imaging has advanced to become a powerful diagnostic tool in clinical practice. Automatic detection of anatomic landmarks from MR images is important for structural and functional analysis of the heart. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, context, around the target. Conventional context is associated with each individual landmark to encode local shape and appearance evidence. We extend this concept to a landmark set, where multiple landmarks have connections at the semantic level, e.g., landmarks belonging to the same anatomy. We propose a joint context approach to construct contextual regions between landmarks. A discriminative model is learned to utilize inter-landmark features for landmark set detection as an entirety. This helps resolve ambiguities of individual landmark detection results. A probabilistic boosting tree is used to learn a discriminative model based on contextual features. We adopt a marginal space learning strategy to efficiently learn and search a high dimensional parameter space. A fully automatic system is developed to detect the set of three landmarks of the left ventricle, the apex and the two basal annulus points, from a single cardiac MR long axis image. We test the proposed approach on a database of 795 long axis images from 116 patients. A 4-fold cross validation results show that about 15% reduction of the errors is obtained by integrating joint context into a conventional landmark detection system.
Monitoring the Execution of a Multi-Agent Plan: Dealing with Partial Observability
Authors: Roberto Micalizio, Pietro Torasso
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

The paper addresses the task of monitoring and diagnosing the execution of a multi-agent plan (MAP) which involves actions concurrently executed by a team of cooperating agents. The paper describes a weak commitment strategy to deal with cases where observability is only partial and it is not sufficient for inferring the outcome of all the actions executed so far. The paper discusses the role of target actions in providing sufficient conditions for inferring the pending outcomes in a finite time window. The action outcome provides the basis for computing plan diagnosis and for singling out the goals which will not be achieved because of an action failure.
Multi Activity Recognition Based on Bodymodel-Derived Primitives
Authors: Andreas Zinnen, Christian Wojek, Bernt Schiele
Venue: Proceedings of the 4th International Symposium on Location and Context Awareness (2009)

We propose a novel model-based approach to activity recognition using high-level primitives that are derived from a human body model estimated from sensor data. Using short but fixed positions of the hands and turning points of hand movements, a continuous data stream is segmented in short segments of interest. Within these segments, joint boosting enables the automatic discovery of important and distinctive features ranging from motion over posture to location. To demonstrate the feasibility of our approach we present the user-dependent and across-user results of a study with 8 participants. The specific scenario that we study is composed of 20 activities in quality inspection of a car production process.
Density Functional Theory Study of Ag-Cluster/CO Interactions
Authors: Paulo H. Acioli, Narin Ratanavade, Michael R. Cline, Sudha Srinivas
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The interactions between carbon monoxide and small clusters of silver atoms are examined. Optimal geometries of the cluster-molecules complexes, i.e. silver cluster - carbon monoxide molecule, are obtained for different sizes of silver clusters and different numbers of carbon monoxide molecules. This analysis is performed in terms of different binding energy of these complexes and analysis of the frontier orbitals of the complex compared to those of its constituents. The silver atom and the dimer (Ag2) bond up to three carbon monoxide molecules per Ag atom, while the larger clusters appear to saturate at two CO's per Ag atom. Analysis of the binding energy of each CO molecule to the cluster reveals that the general trend is a decrease with the number of CO molecules, with the exception of Ag where the second CO molecule is the strongest bound. A careful analysis of the frontier orbitals shows that the bent structures of AgCO and Ag2CO are a result from the interaction of the highest occupied orbital of Ag (5s) and Ag2 (¿) with the lowest unoccupied orbital of CO (¿ *). The same bent structure also appears in the bonding of CO to some of the atoms in the larger clusters. Another general trend is that the CO molecules have a tendency to bond atop of an atom rather than on bridge or face sites. These results can help us elucidate the catalytic properties of small silver clusters at the atomic level.
A data analysis model based on control charts to monitor online learning processes
Authors: Angel A. Juan, Thanasis Daradoumis, Javier Faulin, Fatos Xhafa
Venue: International Journal of Business Intelligence and Data Mining (2009)

This paper discusses the convenience of using data analysis techniques to monitor e-learning processes. It also proposes a model to monitor online students' academic activity and performance. Using data from log files and databases, this model determines which information has to be provided to online instructors and students. These reports allow instructors to: classify students according to their activity and learning outcomes, track their evolution, and identify those who might need immediate assistance. They also provide students with a periodical feedback which makes them aware of how they are performing as compared with the rest of the class.
Efficient codebooks for fast and accurate low resource ASR systems
Authors: Leila Zouari, Gérard Chollet
Venue: Speech Communication (2009)

Today, speech interfaces have become widely employed in mobile devices, thus recognition speed and resource consumption are becoming new metrics of Automatic Speech Recognition (ASR) performance. For ASR systems using continuous Hidden Markov Models (HMMs), the computation of the state likelihood is one of the most time consuming parts. In this paper, we propose novel multi-level Gaussian selection techniques to reduce the cost of state likelihood computation. These methods are based on original and efficient codebooks. The proposed algorithms are evaluated within the framework of a large vocabulary continuous speech recognition task.
Qualitative properties of some higher order difference equations
Authors: H. El-Metwally
Venue: Computers Mathematics with Applications (2009)

We present sufficient conditions which guarantee that all positive solutions of some higher order rational difference equations are global asymptotically stable. The boundedness of the solutions and the existence of prime period two solutions of such equations are also investigated.
Understanding interaction in contemporary digital music: From instruments to behavioural objects
Authors: Oliver Bown, Alice Eldridge, Jon Mccormack
Venue: Organised Sound (2009)

Throughout the short history of interactive digital music, there have been frequent calls for a new language of interaction that incorporates and acknowledges the unique capabilities of the computational medium. In this paper we suggest that a conceptualisation of possible modes of performance–time interaction can only be sensibly approached in light of the ways that computers alter the social–artistic interactions that are precursive to performance. This conceptualisation hinges upon a consideration of the changing roles of composition, performer and instrument in contemporary practice. We introduce the term behavioural object to refer to software that has the capacity to act as the musical and social focus of interaction in digital systems. Whilst formative, this term points to a new framework for understanding the role of software in musical culture. We discuss the potential for behavioural objects to contribute actively to musical culture through two types of agency: performative agency and memetic agency.
Estimation of Eye Blinking Using Biopotentials Measurements for Computer Animation Applications
Authors: Robert Krupiński, Przemysław Mazurek
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

In the paper, the estimation algorithm of eye blinking for a computer animation system using biopotentials occurring on an actor's face is considered. The measuring system incorporates minimal 3---electrodes configuration, which is relatively cheap solution. The proposed algorithm allows both the measurement of eyes orientation and detection of eyes blinking.
Landfill gas emission prediction using Voronoi diagrams and importance sampling
Authors: K. R. Mackie, C. D. Cooper
Venue: Environmental Modelling Software (2009)

Municipal solid waste (MSW) landfills are among the nation's largest emitters of methane, a key greenhouse gas, and there is considerable interest in quantifying the surficial methane emissions from landfills. There are limitations in obtaining accurate emissions data by field measurements, and in characterizing an entire landfill with only a few such emissions measurements. This paper proposes an emissions prediction approach using numerous ambient air volatile organic compound (VOC) measurements above the surface of a landfill that are more easily obtained. Many large landfills are already collecting ambient air methane data based on existing regulations. The proposed method is based on the inverse solution of the standard Gaussian dispersion equations. However, only the VOC concentrations and locations are required. The locations of maximum likelihood of the point sources are predicted using Voronoi diagrams, and importance sampling is performed to further refine the locations. Point source strengths are calculated using non-negative least squares, and the point emission rates are then summed to give the total landfill emission rate. The proposed method is successfully demonstrated on a series of four landfill case studies. Three hypothetical landfills were selected for validation studies by forward and backward solution of the dispersion equations. The fourth case study is an active central Florida MSW landfill. The proposed method shows promise in accurately and robustly predicting landfill gas emissions, and requires only measured ambient VOC concentrations and locations.