ppxscal/embedding_network huggingface dataset:
Letter from the editors
Authors: Tom Stafford, Patrick Y.K. Chau
Venue: ACM SIGMIS Database (2008)

Welcome to another excellent issue of Data Base! It's been an exciting summer, and we're looking forward to an even more interesting Fall and Winter. For instance, we have papers from the Chinese chapter of AIS coming soon. And, we have papers this issue from the very best of the Human Computer Interface research discipline; we agreed to provide SIGHCI with a venue for their best papers, and a good decision it has proven to be! In this issue, premier HCI research: Plummer et al. extend our interest in Web 2.0 technologies to an investigation of Wiki awareness. Many scholars have wondered about the impact of social networking and social information sources on the Internet, but few have questioned what the Web 2.0 functionality would be if it were "aware" of usage patterns. It is provocative enough to think of technology that permits user self-editing; more so, to think of technology of that sort that integrates usage patterns into its response characteristics. Interactivity is taken to yet a new level, and you read it here first! Meanwhile, Ho et al. think that the classic marketing truism of prior experience being the best predictor of future behavior may not pertain in the online world. In specific, they thought that site content closely matched with previous transactions might not be as influential in influencing ongoing site use behavior. Instead, it appears that Web users' personality play considerable influence, moderating the effect of personalized content. Web designers may not be able to rely entirely on stored records of user visits and display content associated with it. Instead, they might have to actually engage in some customer research on the personality characteristics of their users. Wu and Kuo bring us an extension of acceptance research. As well-understood as acceptance is, we probably know little about automatic and non-deliberative use. Technology acceptance is not conceptualized as spontaneous and non-conscious or not effortful. These authors give us new perspectives on usability, from the acceptance theory perspective, with viewpoints not previously seen. Any of us who have seen workstations that utilized multiple screens have probably wondered how they work, if we have not used such configurations ourselves. Truemper et al. bring us an interesting study of the usability of such multiple-monitor workstations. We might tend to think that more than one monitor displaying different information could be potentially distracting. It turns out that users with multi-monitor displays multitask more and achieve higher performance measures than single monitor users. Lastly, we have an errata item in this issue. A table in Henri Barki's fine article about construct conceptualization from our prior issue was omitted. We provide it here, now, with our apologies for the oversight and hope that the omission did not prove unduly inconvenient.
Learners, Technology and the Brain
Authors: Jean Underwood
Venue: Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work (2008)

How do we develop an educational experience fit for twenty-first century learners? There is a perceived malaise at the heart of our education system. The solution to this problem proposed by many governments, although vociferously resisted by some scholars and parent groups, is to use the lure of digital technologies to fix the broken system. Will this work? What evidence is there for the efficacy of digital technologies and particularly video games for learning? A combination of traditional educational evaluations and studies within cognitive neuroscience provide a window on the nature, process and effectiveness of learning with and through digital technologies. Such studies are changing our perception of learning, which is now more brain training than knowledge acquisition. These changes marry both the cognitive and affective aspects of learning.
Using genetic algorithms to evolve a population of topical queries
Authors: Rocío L. Cecchini, Carlos M. Lorenzetti, Ana G. Maguitman, Nélida Beatríz Brignole
Venue: Information Processing and Management: an International Journal (2008)

Systems for searching the Web based on thematic contexts can be built on top of a conventional search engine and benefit from the huge amount of content as well as from the functionality available through the search engine interface. The quality of the material collected by such systems is highly dependant on the vocabulary used to generate the search queries. In this scenario, selecting good query terms can be seen as an optimization problem where the objective function to be optimized is based on the effectiveness of a query to retrieve relevant material. Some characteristics of this optimization problem are: (1) the high-dimensionality of the search space, where candidate solutions are queries and each term corresponds to a different dimension, (2) the existence of acceptable suboptimal solutions, (3) the possibility of finding multiple solutions, and in many cases (4) the quest for novelty. This article describes optimization techniques based on Genetic Algorithms to evolve ''good query terms'' in the context of a given topic. The proposed techniques place emphasis on searching for novel material that is related to the search context. We discuss the use of a mutation pool to allow the generation of queries with new terms, study the effect of different mutation rates on the exploration of query-space, and discuss the use of a especially developed fitness function that favors the construction of queries containing novel but related terms.
A novel and effective particle swarm optimization like algorithm with extrapolation technique
Authors: M. Senthil Arumugam, M. V. C. Rao, Alan W. C. Tan
Venue: Applied Soft Computing (2009)

A novel competitive approach to particle swarm optimization (PSO) algorithms is proposed in this paper. The proposed method uses extrapolation technique with PSO (ePSO) for solving optimization problems. By considering the basics of the PSO algorithm, the current particle position is updated by extrapolating the global best particle position and the current particle positions in the search space. The position equation is formulated with the global best (gbest) position, local best position (pbest) and the current position of the particle. The proposed method is tested with a set of 13 standard optimization benchmark problems and the results are compared with those obtained through two existing PSO algorithms, the canonical PSO (cPSO), the Global-Local best PSO (GLBest PSO). The cPSO includes a time-varying inertia weight (TVIW) and time-varying acceleration co-efficients (TVAC) while the GLBest PSO consists of Global-Local best inertia weight (GLBest IW) with Global-Local best acceleration co-efficient (GLBestAC). The simulation results clearly elucidate that the proposed method produces the near global optimal solution. It is also observed from the comparison of the proposed method with cPSO and GLBest PSO, the ePSO is capable of producing a quality of optimal solution with faster convergence rate. To strengthen the comparison and prove the efficacy of the proposed method a real time application of steel annealing processing (SAP) is also considered. The optimal control objectives of SAP are computed through the above said three PSO algorithms and also through two versions of genetic algorithms (GA), namely, real coded genetic algorithm (RCGA) and hybrid real coded genetic algorithm (HRCGA) and the results are analyzed with the proposed method. From the results obtained through benchmark problems and the real time application of SAP, it is clearly seen that the proposed ePSO method is competitive to the existing PSO algorithms and also to GAs.
Message-passing algorithms for the prediction of protein domain interactions from protein–protein interaction data
Authors: Mudassar Iqbal, Alex A. Freitas, Colin G. Johnson, Massimo Vergassola
Venue: Bioinformatics (2008)

Motivation: Cellular processes often hinge upon specific interactions among proteins, and knowledge of these processes at a system level constitutes a major goal of proteomics. In particular, a greater understanding of protein–protein interactions can be gained via a more detailed investigation of the protein domain interactions that mediate the interactions of proteins. Existing high-throughput experimental techniques assay protein–protein interactions, yet they do not provide any direct information on the interactions among domains. Inferences concerning the latter can be made by analysis of the domain composition of a set of proteins and their interaction map. This inference problem is non-trivial, however, due to the high level of noise generally present in experimental data concerning protein–protein interactions. This noise leads to contradictions, i.e. the impossibility of having a pattern of domain interactions compatible with the protein–protein interaction map. Results: We formulate the problem of prediction of protein domain interactions in a form that lends itself to the application of belief propagation, a powerful algorithm for such inference problems, which is based on message passing. The input to our algorithm is an interaction map among a set of proteins, and a set of domain assignments to the relevant proteins. The output is a list of probabilities of interaction between each pair of domains. Our method is able to effectively cope with errors in the protein–protein interaction dataset and systematically resolve contradictions. We applied the method to a dataset concerning the budding yeast Saccharomyces cerevisiae and tested the quality of our predictions by cross-validation on this dataset, by comparison with existing computational predictions, and finally with experimentally available domain interactions. Results compare favourably to those by existing algorithms. Availability: A C language implementation of the algorithm is available upon request. Contact: mi26@kent.ac.uk
Portraying the practice of decision-making in requirements engineering: a case of large scale bespoke development
Authors: Beatrice Alenljung, Anne Persson
Venue: Requirements Engineering (2008)

Complex decision-making is a prominent aspect of requirements engineering (RE) and the need for improved decision support for RE decision-makers has been identified by a number of authors in the research literature. A first step toward better decision support in requirements engineering is to understand multifaceted decision situations of decision-makers. In this paper, the focus is on RE decision-making in large scale bespoke development. The decision situation of RE decision-makers on a subsystem level has been studied at a systems engineering company and is depicted in this paper. These situations are described in terms of, e.g., RE decision matters, RE decision-making activities, and RE decision processes. Factors that affect RE decision-makers are also identified.
The long tail of recommender systems and how to leverage it
Authors: Yoon-Joo Park, Alexander Tuzhilin
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

The paper studies the Long Tail problem of recommender systems when many items in the Long Tail have only few ratings, thus making it hard to use them in recommender systems. The approach presented in the paper splits the whole itemset into the head and the tail parts and clusters only the tail items. Then recommendations for the tail items are based on the ratings in these clusters and for the head items on the ratings of individual items. If such partition and clustering are done properly, we show that this reduces the recommendation error rates for the tail items, while maintaining reasonable computational performance.
Efficient representation and P-value computation for high-order Markov motifs
Authors: Paulo G. S. da Fonseca, Katia S. Guimarães, Marie-France Sagot
Venue: Bioinformatics (2008)

Motivation: Position weight matrices (PWMs) have become a standard for representing biological sequence motifs. Their relative simplicity has favoured the development of efficient algorithms for diverse tasks such as motif identification, sequence scanning and statistical significance evaluation. Markov chainbased models generalize the PWM model by allowing for interposition dependencies to be considered, at the cost of substantial computational overhead, which may limit their application. Results: In this article, we consider two aspects regarding the use of higher order Markov models for biological sequence motifs, namely, the representation and the computation of P-values for motifs described by a set of occurrences. We propose an efficient representation based on the use of tries, from which empirical position-specific conditional base probabilities can be computed, and extend state-of-the-art PWM-based algorithms to allow for the computation of exact P-values for high-order Markov motif models. Availability: The software is available in the form of a Java objectoriented library from http://www.cin.ufpe.br/~paguso/kmarkov. Contact: paguso@cin.ufpe.br
Mining help desk emails for problem domain identification and email feature engineering for routing incoming emails
Authors: Michael B. Twidale
Venue:  (2008)

Text mining typically involves a variety of decisions to be made about the use of the techniques for mining, including data type, algorithm selection, pre-processing, intermediate processing and parameter setting. Choices within parameter space are mostly regarded as judgment calls made by developers or expert users of the text mining software. This thesis explores the parameter space and associated processing decisions in the context of text mining of emails for technical help. This is a relatively unexplored area, but one of growing economic importance. In doing so it reveals issues relevant to the particular use context, to other applications of text mining of emails, and implications for investigations of other parameter spaces. In this research work, emails from the help desk domain were chosen as the dataset on which text mining techniques were applied to investigate the impact of different features of email on problem domain identification and routing emails. The study investigates the impact of different features of email on problem domain identification by using machine-expert approach. The clustering technique (machine) was used to generate a number of clusters and the knowledge of the experts from the help desk domain was used to label the clusters to identify the problem domains in the help desk. This machine-expert approach was also used to study the impact of different features of an email (such as header, content, reply and signature) on clustering of these emails and identification of problem domains in the help desk area. The Expectation Maximization algorithm was used to generate different numbers of clusters from email data. This study investigated the impact of different features of an email i.e., header, content, reply and signature on the supervised and unsupervised classification of emails to different problem domains. A classification algorithm based on Na&iuml;ve Bayes was used for routing of emails into different problem domains. This work also outlines different pre-processing steps done on email from the help desk domain, such as removal of different types of noise elements and removal of stop words using a customized stop word list, and the outcome of each of these pre-processing steps.
Medical Image Classification Based on Fuzzy Support Vector Machines
Authors: Xing-li Bai, Xu Qian
Venue: Proceedings of the 2008 International Conference on Intelligent Computation Technology and Automation - Volume 02 (2008)

The paper present a novel method for medical image classification using fuzzy support vector machines (FSVM). In this method a membership degree is defined for each training sample, which can resolve the problem of unclassifiable regions in SVM. Experiments on images of mammography with different noise levels were conducted and results show that the proposed method is able to classify the breast cancer in the images of mammography with high precision. In application of this method the cost and time of computation can also be reduced.
Mathematical and computer modeling of dynamic processes in composite media
Authors: O. N. Konovalova
Venue: Cybernetics and Systems Analysis (2008)

Problems of vibrations of a representative element of a composite medium with allowance made for the interphase interaction of components are investigated. The results of computer modeling of plane linear and nonlinear problems and also a three-dimensional problem of dynamic equilibrium of a composite system are considered. The surfaces of solutions for various proportions of reinforcing fibers and interphase layers are obtained and analyzed, and the influence of these layers on the character of vibrational processes is investigated.
Frequency-domain adaptive algorithm for network echo cancellation in VoIP
Authors: Xiang Lin, Andy W. H. Khong, Milos Doroslovački, Patrick A. Naylor
Venue: EURASIP Journal on Audio, Speech, and Music Processing (2008)

We propose a new low complexity, low delay, and fast converging frequency-domain adaptive algorithm for network echo cancellation in VoIP exploiting MMax and sparse partial (SP) tap-selection criteria in the frequency domain. We incorporate these tap-selection techniques into the multidelay filtering (MDF) algorithm in order to mitigate the delay inherent in frequency-domain algorithms. We illustrate two such approaches and discuss their tradeoff between convergence performance and computational complexity. Simulation results show an improvement in convergence rate for the proposed algorithm over MDF and significantly reduced complexity. The proposed algorithm achieves a convergence performance close to that of the recently proposed, but substantially more complex improved proportionate MDF (IPMDF) algorithm.
Approximation hardness of dominating set problems in bounded degree graphs
Authors: M. Chlebík, J. Chlebíková
Venue: Information and Computation (2008)

We study approximation hardness of the Minimum Dominating Set problem and its variants in undirected and directed graphs. Using a similar result obtained by Trevisan for Minimum Set Cover we prove the first explicit approximation lower bounds for various kinds of domination problems (connected, total, independent) in bounded degree graphs. Asymptotically, for degree bound approaching infinity, these bounds almost match the known upper bounds. The results are applied to improve the lower bounds for other related problems such as Maximum Induced Matching and Maximum Leaf Spanning Tree.
Control system simulator for steam boiler parameters
Authors: Camelia Maican, Matei Vinatoru, Gabriela Canureci, Eugen Iancu
Venue: WSEAS Transactions on Systems and Control (2008)

The paper presents the research results related to control of the steam boiler parameters: drum level, furnace pressure and steam pressure. It was developed the mathematical model of the water-steam system and furnace part of the boiler. Also, the paper presents the algorithm for real time detection of model parameter variations. In this context a correction method, validate through simulation was developed.
Upgrade of signaling system on the rapid transit systems
Authors: Ying-Tung Hsiao, Kuang-Chieh Lin
Venue: WSEAS TRANSACTIONS on SYSTEMS (2008)

In this paper, discuss the upgrade system for an old type and extend to new line system of signaling at Taipei Rapid Transit Systems (RTS). Since the track circuits of fixed block are utilized the frequency loops and audio frequency track circuits of train position detected on the automatic train protect system. At present, Neihu line is the new extension construction of Muzha line, due to the new singling system as Communication Based on Train Control (CBTC) has use the new system and upgrade with revenues service system on the Muzha line. How do check and integration between old and new type systems to combination and compatible for the train running of Automatic Train Control (ATC) system shall importance issue. The CBTC system is used the simply construction technology with application to upgrade at Metro systems. In theme also comparison between fixed blocks and moving blocks circuits for conception of design in the Taipei RTS, and study of CBTC system technology manipulate on the system upgrade.
Towards Seamless Merging of Hypertext and Algorithm Animation
Authors: Ville Karavirta
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

The integration of algorithm animations into hypertext is seen as an important topic today. This paper will present a prototype algorithm animation viewer implemented purely using HTML and JavaScript. The viewer is capable of viewing animations in Xaal (eXtensible Algorithm Animation Language). This solution is extremely suitable to be used in hypertext learning material.
Advances and Challenges for Scalable Provenance in Stream Processing Systems
Authors: Archan Misra, Marion Blount, Anastasios Kementsietsidis, Daby Sow, Min Wang
Venue: Provenance and Annotation of Data and Processes: Second International Provenance and Annotation Workshop, IPAW 2008, Salt Lake City, UT, USA, June 17-18, 2008. Revised Selected Papers (2008)

While data provenance is a well-studied topic in both database and workflow systems, its support within stream processing systems presents a new set of challenges. Part of the challenge is the high stream event rate and the low processing latency requirements imposed by many streaming applications. For example, emerging streaming applications in healthcare or finance call for data provenance, as illustrated in the Century stream processing infrastructure that we are building for supporting online healthcare analytics. At anytime, given an output data element (e.g., a medical alert) generated by Century, the system must be able to retrieve the input and intermediate data elements that led to its generation. In this paper, we describe the requirements behind our initial implementation of Century's provenance subsystem. We then analyze its strengths and limitations and propose a new provenance architecture to address some of these limitations. The paper also includes a discussion on the open challenges in this area.
Morphable 3D-mosaics: a hybrid framework for photorealistic walkthroughs of large natural environments
Authors: Nikos Komodakis, Georgios Tziritas
Venue: Advances in Multimedia (2008)

This paper presents a hybrid (geometry- & image-based) framework suitable for providing photorealistic walkthroughs of large, complex outdoor scenes at interactive frame rates. To this end, based just on a sparse set of real stereoscopic views from the scene, a set of morphable 3D-mosaics is automatically constructed first, and then, during rendering, a continuous morphing between those 3D-mosaics that are nearby to the current viewpoint is taking place. The morphing is both photometric, as well as geometric, while we also ensure that it proceeds in a physically valid manner, thus remaining transparent to the user. The effectiveness of our framework has been demonstrated in the 3D visual reconstruction of the Samaria Gorge in Crete, which is one of the largest and most beautiful gorges in Europe.