ppxscal/embedding_network huggingface dataset:
A Systematic Review of Usability Evaluation in Web Development
Authors: Emilio Insfran, Adrian Fernandez
Venue: Proceedings of the 2008 international workshops on Web Information Systems Engineering (2008)

The challenge of developing more usable Web applications has motivated the appearance of a number of techniques, methods and tools to address Web usability issues. Although there are many proposals for supporting the development of usable Web applications, many developers are not aware of them and many organizations do not properly apply them. This paper reports on a systematic review of the use of usability evaluation methods in Web development. The objective of the review is to investigate what usability evaluation methods have been employed by researchers to evaluate Web artifacts and how they were employed. A total of 51 research papers have been reviewed from an initial set of 410 papers. The results show that 45% of the papers reviewed reported the use of evaluation methods specifically crafted for the Web and that the most employed method is user testing. In addition, the results of the review have identified several research gaps. Specifically, 80% of the evaluations are still performed at the implementation phase of Web applications development and 47% of the papers did not present any validation of the usability evaluation method(s) employed.
Characters with Character
Authors: Isabel Machado Alexandre
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

How good is a story without a good protagonist, or even a good plot? One of the flaws that are pointed to edutainment and entertainment applications is that they do not have an underlying story, and their characters end up without character. With this we mean that each character do not exhibit any qualities or features that distinguishes one person, group or thing from another. If the characters that populate a game, an educational or an edutainment application do not have specific goals, behaviours or more generally a role, the aim of such application can be seen as shallow and might contribute to poor interactions. This paper explores novel and alternative ways to enrich such characters with more social capabilities, promoting a more engaging experience for the users.
A Distributed Approach for QoS Service Multicast with
Authors: Klara Nahrstedt, Jingwen Jin
Venue: IEEE Distributed Systems Online (2003)

The service routing problem emerged from the distributed and composable services model. Using service multicast instead of service unicast for group delivery saves bandwidth and resources. The authors describe a distributed approach for building QoS-assured, delay-efficient service multicast trees that uses geometric location information and explore hybrid multicasting (service multicasting plus data multicasting).
Product Data Models
Authors: J. Morbach, B. Bayer, A. Yang, W. Marquardt
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

This contribution summarizes the results of more than a decade of product data modeling at the authors' institute. In this effort, a series of consecutive product data models has been developed for the domain of chemical engineering, starting with the chemical engineering data model VeDa, followed then by the conceptual information model CLiP and finally by the domain ontology OntoCAPE. The evolution of these different models is described, and their similarities and differences are discussed with regard to scope, structural design, conceptualization, representation language, and intended usage.
Use of Artificial Neural Networks in Near-Infrared Spectroscopy Calibrations for Predicting Glucose Concentration in Urine
Authors: Weiling Liu, Weidong Yang, Libing Liu, Qilian Yu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

In this paper, Glucose concentration in urine sample were determined by means of Near-infrared spectroscopy combination with artificial neural networks (ANNs). Distinct ANN models were developed for the multicomponent analysis of biological samples. The developed prediction algorithms were tested on unseen data and exhibited high level of accuracy, comparable to the partial least squares (PLS) regression method. Near-infrared (NIR) spectra in the 10000~4000 cm¿ 1 region were measured for human urine glucose with various concentrations at 37 °C. The most informative spectral ranges of 4400~4700 cm¿ 1 was selected by principle component analysis (PCA) for glucose in the mixtures. For glucose, the correlation coefficient (R) of 0.999 and the root mean square error of prediction (RMSEP) of 20.61 mg/dl were obtained. The presented algorithms can be used as a rapid and reliable tool for quantitative analysis of glucose in biological sample, since the concentration can be determined based on NIR measurement.
Sedimentological Analysis of Sands
Authors: Cristina Lira, Pedro Pina
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

This paper presents a practical sequence to study sand grains at the macroscopical scale. The approach consists of two mains phases, the recognition of the grains and the assessment of some of its characteristics. The method is validated on the dimensional features by comparison with a sieving procedure through the analysis of eight large sand samples of different locations.
Reverse Breakdown Voltage Measurement for Power P+NN+ Rectifier
Authors: Guangyu Huang, Cher Ming Tan
Venue: Journal of Electronic Testing: Theory and Applications (2008)

The measurement of the reverse breakdown voltage for power rectifier is an important test. Two test methods for the reverse breakdown voltage measurement are employed in the industry, namely the forced voltage test (FVT) and the forced current test (FCT). In this work, we perform a systematic study to explain the different breakdown voltages obtained from the two test methods and the possible damage mechanisms to the device under test during FVT and FCT. The study shows that FVT has a much shorter test time while FCT is less destructive to the device under test.
Developing and Applying a Consolidated Evaluation Framework to Analyze Test Process Improvement Approaches
Authors: Ayaz Farooq, Reiner R. Dumke
Venue: Software Process and Product Measurement: International Conference, IWSM-Mensura 2007, Palma de Mallorca, Spain, November 5-8, 2007. Revised Papers (2007)

Following the general software process improvement initiatives, improvement models particular to the software test process have also been developed. Although these models have been based on nearly similar principles, yet they differ in a variety of aspects. To compare and critically analyze strengths and weaknesses of these test process models, we need a common analysis framework. Existing SPI evaluation frameworks focus only on some basic and key process characteristics and elements. A number of critical success factors for software process improvement have been identified in literature which impose higher level of requirements on SPI approaches. We present a consolidated evaluation framework derived from critical success factors/literature review and apply it to analyze well known test process improvement approaches.
A Graph-Theoretic Visualization Approach to Network Risk Analysis
Authors: Scott O'Hare, Steven Noel, Kenneth Prole
Venue: Proceedings of the 5th international workshop on Visualization for Computer Security (2008)

This paper describes a software system that provides significant new capabilities for visualization and analysis of network attack graphs produced through Topological Vulnerability Analysis (TVA). The TVA approach draws on a database of known exploits and system vulnerabilities to provide a connected graph representing possible cyber-attack paths within a given network. Our visualization approach builds on the extensive functionality of the yWorks suite of graphing tools, providing customized new capabilities for importing, displaying, and interacting with large scale attack graphs, to facilitate comprehensive network security analysis. These visualization capabilities include clustering of attack graph elements for reducing visual complexity, a hierarchical dictionary of attack graph elements, high-level overview with detail drilldown, interactive on-graph hardening of attacker exploits, and interactive graph layouts. This new visualization system is an integrated component of the CAULDRON attack graph tool developed at George Mason University.
Sensitivity and Uniformity in Detecting Motion Artifacts
Authors: Wen-Chuang Chou, Michelle Liou, Hong-Ren Su
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Removing artifacts due to head motion is a preprocessing procedure necessary for any fMRI analysis. In fMRI tool boxes, there have been standard algorithms for correcting motion artifacts. However, those tool boxes fail to indicate the extent to which the correction has been successfully done. Without knowing motion contamination especially after correction, the subsequent analysis using averaged fMRI data across subjects could be misleading. In this study, we proposed seven summary indices for measuring motion artifacts. The indices can be applied after motion correction by the image registration algorithms. In the simulation studies, we analyzed a real fMRI data set using a statistical method and estimated the brain activation maps. The real image data were then randomly shifted or rotated to simulate different degrees of head motion. The data contaminated by random motion were then corrected using the SPM image coregistration algorithms. The indices of motion contamination were computed using the corrected images. The corrected images were then analyzed again using the same statistical method. The consistency between the brain activation maps based on real data and those based on simulated data was used as a standard to evaluate the usefulness of the proposed seven indices. The results show that some indices are informative with regards to the degree of motion contamination in preprocessed fMRI data.
Fuzzy Representation and Synthesis of Concepts in Engineering Design
Authors: Vassilis C. Moulianitis, Nikos A. Aspragathos, Argiris J. Dentsoras
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

In the present paper a new mathematical fuzzy-logic-based formulation of the design objects and the rules that govern a design problem during the conceptual design phase is presented.. A procedure for the automatic generation of degrees of satisfaction of the design specifications for each feasible solution - subjected to design constraints - is introduced. A table containing the satisfaction degrees is used for the derivation of the set of all possible synthesized solutions. The determination of this set, which is a subset of the set of the synthesised solutions, is based on a suitable partition of the Euclidean space. An illustrative example of a knowledge based system for the conceptual design of grippers for handling fabrics is presented. The advantages of this model are revealed via a comparison with previous implementations of the conceptual design phase based on crisp production rules or certainty factors.
Superposition for Fixed Domains
Authors: Matthias Horbach, Christoph Weidenbach
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

Superposition is an established decision procedure for a variety of first-order logic theories represented by sets of clauses. A satisfiable theory, saturated by superposition, implicitly defines a perfect term-generated model for the theory. Proving universal properties with respect to a saturated theory directly leads to a modification of the perfect model's term-generated domain, as new Skolem functions are introduced. For many applications, this is not desired. Therefore, we propose the first superposition calculus that can explicitly represent existentially quantified variables and can thus compute with respect to a given domain. This calculus is sound and complete for a first-order fixed domain semantics. For some classes of formulas and theories, we can even employ the calculus to prove properties of the perfect model itself, going beyond the scope of known superposition based approaches.
The Texas Instruments TMS320C25 Digital Signal Microcomputer
Authors: Gene Frantz, Kun-shan Lin, Jay Reimer, Jon Bradley
Venue: IEEE Micro (1986)

Capable of 10 million operations per second, the newest member of the TMS320 family can serve as an inexpensive alternative to bit-slice processors or custom ICs in digital signal processing applications.
Self-organization of intertidal snails facilitates evolution of aggregation behavior
Authors: Richard Stafford, Mark S. Davies, Gray A. Williams
Venue: Artificial Life (2008)

Many intertidal snails form aggregations during emersion to minimize desiccation stress. Here we investigate possible mechanisms for the evolution of such behavior. Two behavioral traits (following of mucus trails, and crevice occupation), which both provide selective advantages to individuals that possess the traits over individuals that do not, result in self-organization of aggregations in crevices in the rock surface. We suggest that the existence of self-organizing aggregations provides a mechanism by which aggregation behavior can evolve. The inclusion of an explicitly coded third behavior, aggregation, in a simulated population produces patterns statistically similar to those found on real rocky shores. Allowing these three behaviors to evolve using an evolutionary algorithm, however, results in aggregation behavior being selected against on shores with high crevice density. The inclusion of broadcast spawning dispersal mechanisms in the simulation, however, results in aggregation behavior evolving as predicted on shores with both high crevice density and low crevice density (evolving in crevices first, and then both in crevices and on flat rock), indicating the importance of environmental interactions in understanding evolutionary processes. We propose that self-organization can be an important factor in the evolution of group behaviors.
John William Mauchly, 1907-1980
Authors: Nancy Stern
Venue: IEEE Annals of the History of Computing (1980)

John Mauchly died in Abington, Pennsylvania, on JANUARY-MARCH 8, 1980. The New York Times obituary (Smolowe 1980) described Mauchly as a "co-inventor of the first electronic computer," but his accomplishments went far beyond that simple description. 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
An improved error-correcting output coding framework with kernel-based decoding
Authors: Dijun Luo, Rong Xiong
Venue: Neurocomputing (2008)

This paper presents a novel framework of error-correcting output coding (ECOC) addressing the problem of multi-class classification. By weighting the output space of each base classifier which is trained independently, the distance function of decoding is adapted so that the samples are more discriminative. A criterion generated over the Extended Pair Samples (EPS) is proposed to train the weights of output space. We first conduct empirical studies on UCI datasets to verify the presented framework with four frequently used coding matrixes and then apply it in RoboCup domain to enhance the performance of agent control. Color-based image segmentation is also tested in this paper. Experimental results show that our supervised learned decoding scheme improves the accuracy of classification significantly and betters the ball control of agents in a soccer game after learning from experience. Some properties still hold in the new framework: any classifier, as well as distance function, is still applicable. Besides, it is allowed in the new framework to implement nonlinear decoding processes using kernel tricks.
The Logical Difference Problem for Description Logic Terminologies
Authors: Boris Konev, Dirk Walther, Frank Wolter
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

We consider the problem of computing the logical difference between distinct versions of description logic terminologies. For the lightweight description logic $\mathcal{ EL}$, we present a tractable algorithm which, given two terminologies and a signature, outputs a set of concepts, which can be regarded as the logical difference between the two terminologies. As a consequence, the algorithm can also decide whether they imply the same concept implications in the signature. A prototype implementation CEX of this algorithm is presented and experimental results based on distinct versions of $\textsc{Snomed ct}$, the Systematized Nomenclature of Medicine, Clinical Terms, are discussed. Finally, results regarding the relation to uniform interpolants and possible extensions to more expressive description logics are presented.
System for Automated Deduction (SAD): A Tool for Proof Verification
Authors: Konstantin Verchinine, Alexander Lyaletski, Andrei Paskevich
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

In this paper a proof assistant called SAD is presented. SAD deals with mathematical texts that are formalized in the ForTheL language (a brief description of which is also given) and checks their correctness. We give a short description of SAD and a series of examples that show what can be done with it. Note that abstract notion of correctness on which the implementation is based, can be formalized with the help of a calculus (not presented here).
Recurrent Neural Networks on Duty of Anomaly Detection in Databases
Authors: Jaroslaw Skaruz, Franciszek Seredynski
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In the paper we present a new approach based on application of neural networks to detect SQL attacks. SQL attacks are those attacks that take advantage of using SQL statements to be performed. The problem of detection of this class of attacks is transformed to time series prediction problem. SQL queries are used as a source of events in a protected environment. To differentiate between normal SQL queries and those sent by an attacker, we divide SQL statements into tokens and pass them to our detection system, which predicts the next token, taking into account previously seen tokens. In the learning phase tokens are passed to recurrent neural network (RNN) trained by backpropagation through time (BPTT) algorithm. Teaching data are shifted by one token forward in time with relation to input. The purpose of the testing phase is to predict the next token in the sequence. All experiments were conducted on Jordan and Elman networks using data gathered from PHP Nuke portal. Experimental results show that the Jordan network outperforms the Elman network predicting correctly queries of the length up to ten.
An AER-Based Actuator Interface for Controlling an Anthropomorphic Robotic Hand
Authors: A. Linares-Barranco, A. Jiménez-Fernandez, R. Paz-Vicente, S. Varona, G. Jiménez
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

Bio-Inspired and Neuro-Inspired systems or circuits are a relatively novel approaches to solve real problems by mimicking the biology in its efficient solutions. Robotic also tries to mimic the biology and more particularly the human body structure and efficiency of the muscles, bones, articulations, etc. Address-Event-Representation (AER) is a communication protocol for transferring asynchronous events between VLSI chips, originally developed for neuro-inspired processing systems (for example, image processing). Such systems may consist of a complicated hierarchical structure with many chips that transmit data among them in real time, while performing some processing (for example, convolutions). The information transmitted is a sequence of spikes coded using high speed digital buses. These multi-layer and multi-chip AER systems perform actually not only image processing, but also audio processing, filtering, learning, locomotion, etc. This paper present an AER interface for controlling an anthropomorphic robotic hand with a neuro-inspired system.
On the price of anarchy for non-atomic congestion games under asymmetric cost maps and elastic demands
Authors: Deren Han, Hong K. Lo, Hai Yang
Venue: Computers Mathematics with Applications (2008)

We derive several bounds for the price of anarchy of the noncooperative congestion games with elastic demands and asymmetric linear or nonlinear cost functions. The bounds established depend on a constant from the cost functions as well as the ratio between user benefit and social surplus at Nash equilibrium. The results can be viewed a generalization of that of Chau and Sim [C.K. Chau, K.M. Sim, The price of anarchy for non-atomic congestion games with symmetric cost maps and elastic demands, Operations Research Letters 31 (2003) 327-334] for the symmetric case, or a generalization of Perakis [G. Perakis, The price of anarchy when costs are nonseparable and asymmetric, Lecture Notes in Computer Science 3064 (2004) 46-58] to the elastic demand.
Bandwidth Allocation for Elastic Real-Time Flows in Multihop Wireless Networks Based on Network Utility Maximization
Authors: Praveen Jayachandran, Tarek Abdelzaher
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

In this paper, we consider distributed utility maximizing rate allocation in cyber-physical multihop wireless networks carrying prioritized elastic flows with different end-to-end delay requirements. This scenario arises in military wireless networks (dominated by audio and video flows) that must satisfy end-to-end deadlines. Due to the inherent difficulty in providing hard guarantees in such wireless environments, the problem is cast as one of utility maximization, where utility depends on meeting deadlines. Based on a recent result in real-time scheduling, we relate end-to-end delay of prioritized flows to flow rates and priorities, then impose end-to-end delay constraints that can be expressed in a decentralized manner in terms of flow information available locally at each node. The problem of utility maximization in the presence of these constraints is formulated, where utility depends on the ability to meet deadlines. The solution to the network utility maximization (NUM) problem yields a distributed rate control algorithm that nodes can independently execute to collectively maximize global network utility, taking into account delay constraints. Results from simulations demonstrate that a low deadline miss ratio is achieved for real-time packets, without significantly impacting throughput, resulting in a higher total utility compared to a previous state-of-the-art approach.