ppxscal/embedding_network huggingface dataset:
Recommender system for software project planning one application of revised CBR algorithm
Authors: Heng-Li Yang, Cheng-Su Wang
Venue: Expert Systems with Applications: An International Journal (2009)

Project management is an experience-driven and knowledge-centralized activity. Therefore, project managers require some assistance to reduce the uncertainty at the early stage of constructing project plans. To overcome the predicament faced by project managers, this investigation proposes a hierarchical criteria architecture (HCA) to enable project managers to describe project requirements adequately. Furthermore, to solve HCA problems, a revised case-based reasoning (RCBR) algorithm, is presented and a recommender system for software project planning is implemented, based on multiple objectives decision techniques and the mining approach. Finally, the proposed RCBR algorithm is successfully applied to analyze 41 real projects from a software consultancy in Taiwan. Experimental results demonstrate that RCBR can efficiently provide related information to help project managers to construct project plans at an early stage. Additionally, the knowledge discovery process of RCBR provides project managers with results similar to what-if analysis. The knowledge can enable project managers to obtain feasible information to re-schedule project resources, and bargain with their customers in the early project planning stage.
Localization Model of Synthesized Sound Image Using Precedence Effect in Sound Field Reproduction Based on Wave Field Synthesis
Authors: Toshiyuki Kimura, Yoko Yamakata, Michiaki Katsumoto, Kazuhiko Kakehi
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

Although it is very important to conduct listening tests when constructing a practical sound field reproduction system based on wave field synthesis, listening tests are very expensive. A localization model of synthesized sound images that predicts the results of listening tests is proposed. This model reduces the costs of constructing a reproduction system because it makes it possible to omit the listening tests. The proposed model uses the precedence effect and predicts the direction of synthesized sound images based on the inter-aural time difference. A comparison of the results predicted by the proposed model and the localized results of listening tests shows that the model accurately predicts the localized results.
The parameterized complexity of the induced matching problem
Authors: Hannes Moser, Somnath Sikdar
Venue: Discrete Applied Mathematics (2009)

Given a graph G and an integer k>=0, the NP-complete Induced Matching problem asks whether there exists an edge subset M of size at least k such that M is a matching and no two edges of M are joined by an edge of G. The complexity of this problem on general graphs, as well as on many restricted graph classes has been studied intensively. However, other than the fact that the problem is W[1]-hard on general graphs, little is known about the parameterized complexity of the problem in restricted graph classes. In this work, we provide first-time fixed-parameter tractability results for planar graphs, bounded-degree graphs, graphs with girth at least six, bipartite graphs, line graphs, and graphs of bounded treewidth. In particular, we give a linear-size problem kernel for planar graphs.
Database access and patterns in Erlang/OTP
Authors: Laura M. Castro, Víctor M. Gulías, Carlos Abalde, Javier París
Venue: Proceedings of the 8th conference on Applied informatics and communications (2008)

Databases are an essential component in most software applications, whether they be critical or not, regardless of their scope and scale. Erlang/OTP is a very suitable framework, based on the functional programming paradigm, to develop robust highly available distributed systems. In its way to a place in the industry world, Erlang/OTP faces the challenge of getting on with traditional Database Management Systems (DBMS). To do so, there is no better way than using abstraction and high-level software engineering tools, i.e. design patterns.
Research of Coal and Gas Outburst Forecasting Based on Immune Genetic Neural Network
Authors: Yu Zhu, Hong Zhang, Ling-dong Kong
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Because there were a lot of facts that affect the intensity of coal and gas outburst, a BP neural network model for forecasting the intensity was constructed. Aimed at the shortcoming of the BP neural network, such as the slow training speed, easy to be trapped into the local optimums, and the premature convergence of Genetic Algorithm (GA) BP neural network, a method to design the BP neural network based on Immune Genetic Algorithm was proposed. The mechanisms of diversity maintaining and antibody density regulation exhibited in a biological immune system were introduced into IGA based on genetic algorithm. The proposed algorithm overcame the problems of GA on search efficiency，individual diversity and premature，and enhanced the convergent performance effectively. The results show that the IGA-BP neural network have better performance in convergent speed and global convergence, and the forecasting accuracy is improved.
LCSH, SKOS and linked data
Authors: Ed Summers, Antoine Isaac, Clay Redding, Dan Krech
Venue: Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications (2008)

A technique for converting Library of Congress Subject Headings MARCXML to Simple Knowledge Organization System (SKOS) RDF is described. Strengths of the SKOS vocabulary are highlighted, as well as possible points for extension, and the integration of other semantic web vocabularies such as Dublin Core. An application for making the vocabulary available as linked-data on the Web is also described.
Theoretical Modeling of Inter-Frame Prediction Error for High Frame-Rate Video Signal
Authors: Yukihiro Bandoh, Kazuya Hayase, Seishi Takamura, Kazuto Kamikura, Yoshiyuki Yashima
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

Realistic representations using extremely high quality images are becoming increasingly popular. For example, digital cinemas can now display moving pictures composed of high-resolution digital images. Although these applications focus on increasing the spatial resolution only, higher frame-rates are being considered to achieve more realistic representations. Since increasing the frame-rate increases the total amount of information, efficient coding methods are required. However, its statistical properties are not clarified. This paper establishes for high frame-rate video a mathematical model of the relationship between frame-rate and bit-rate. A coding experiment confirms the validity of the mathematical model.
Criteria for choosing a rough set model
Authors: Joseph P. Herbert, JingTao Yao
Venue: Computers Mathematics with Applications (2009)

One of the challenges a decision maker faces in using rough sets is to choose a suitable rough set model for data analysis. We investigate how two rough set models, the Pawlak model and the probabilistic model, influence the decision goals of a user. Two approaches use probabilities to define regions in the probabilistic model. These approaches use either user-defined parameters or derive the probability thresholds from the cost associated with making a classification. By determining the implications of the results obtained from these models and approaches, we observe that the availability of information regarding the analysis data is crucial for selecting a suitable rough set approach. We present a list of decision types corresponding to the available information and user needs. These results may help a user match their decision requirements and expectations to the model which fulfills these needs.
Activity-based scenarios for and approaches to ubiquitous e-Learning
Authors: Paul Lefrere
Venue: Personal and Ubiquitous Computing (2009)

This paper presents scenarios for ubiquitous e-Learning in heterogeneous networks. It concludes by arguing for the development of a learning-focused analogue, activity-based e-Learning extensions (ABLE), of activity-based computing (ABC). The goal would be to offer the learning-support/performance-support equivalent of ABC's support for human activities in a ubiquitous computing environment, relevant to areas that are hard to model today: informal on-the-job learning; peer-to-peer support and informal sharing of content in ad hoc work groups; formal and informal ways to capture and share knowledge-focused insights and processes; content and systems to aid reflection. Just as ABC supplements traditional computing approaches (in ABC, data- and application-oriented) to suit "multiple, parallel and mobile work activities" (Bardram et al. in Support for ABC in a personal computing operating system. CHI 2006 proceedings. Montréal, Québec, Canada, 22---27 April 2006, pp 211---220), so ABLE could supplement traditional e-Learning approaches (often largely content-focused, sometimes little more than page-turning) to suit those same work activities, and make e-Learning potentially more resilient to interruptions, more fun and more memorable.
A Genetic Algorithm Approach for Optimum Operator Assignment in CMS
Authors: Ali Azadeh, Hamrah Kor, Seyed-Morteza Hatefi
Venue: Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 01 (2009)

This paper presents a decision making approach based on a hybrid GA for determining the most efficient number of operators and the efficient measurement of operator assignment in cellular manufacturing system (CMS).The objective is to determine the labor assignment in CMS environment with the optimum performance. We use The GA for getting near optimum ranking of the alternative with accordance to fitness function. Also, the GA approach is performed by employing the number of operator, average lead time of demand, average waiting time of demand, number of completed parts, operator utilization and average machine utilization as attributes, and Entropy method for determining the weight of attributes. Furthermore, values of the attributes procured by means of simulation.
Improving Doctor---Patient Communication: Examining Innovative Modalities Vis-à-vis Effective Patient-Centric Care Management Technology
Authors: Gerald-Mark Breen, Thomas T. Wan, Ning Jackie Zhang, Shriram S. Marathe, Binyam K. Seblega, Seung Chun Paek
Venue: Journal of Medical Systems (2009)

This analysis investigates what patients and practitioners can do to improve their interactive communications to achieve optimal patient-centric (PC) care. One goal of this clinical practice approach is to improve patient satisfaction, compliance, and outcomes. The mutual responsibilities required of both the patients and practitioners to attain PC care are discussed. Innovative, information technology techniques in the healthcare environment in general and in care delivery in particular are explored. Practitioner-to-patient encouragement vis-à-vis self education on their conditions is also provided.
Mutual inductance between coaxial circular coils of rectangular cross section and thin coaxial circular coils with constant current density in air (filament method)
Authors: Cevdet Akyel, Slobodan I. Babic
Venue: Proceedings of the 6th conference on Applications of electrical engineering (2007)

This paper deals with an efficient and fast approach for determining the mutual inductance between coaxial circular coils of rectangular cross section in combination with thin coaxial circular coils as the thin wall solenoid, the thin disk coil and the filamentary coil. This approach is based on the filament method where conductors are approximated by the set of Maxwell's coils. The obtained expressions are expressed over the complete elliptical integrals of the first and second kind and permit fast calculation of the mutual induction for mentioned systems. These new expressions are accurate and simple for useful applications. The paper also points out the computational cost and the accuracy.
Variability Tolerant Audio Motif Discovery
Authors: Armando Muscariello, Guillaume Gravier, Frédéric Bimbot
Venue: Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling (2009)

Mining of repeating patterns is useful in inferring structure in streams and in multimedia indexing, as it allows to summarize even large archives by small sets of recurrent items. Techniques for their discovery are required to handle large data sets and tolerate a certain amount of variability among instances of the same underlying pattern (like spectral variability and temporal distortion). In this paper, early approaches and experiments are described for the retrieval of such variable patterns in audio, a task that we call audio motif discovery, for analogy with its counterpart in biology. The algorithm is based on a combination of ARGOS [4] to segment the data and organize the search of the motifs, and a novel technique based on segmental dynamic time warping to detect similarities in the audio data. Moreover, precision-recall measures are defined for evaluation purposes and preliminary experiments on the word discovery case are discussed.
The variational gaussian approximation revisited
Authors: Manfred Opper, Cédric Archambeau
Venue: Neural Computation (2009)

The variational approximation of posterior distributions by multivariate gaussians has been much less popular in the machine learning community compared to the corresponding approximation by factorizing distributions. This is for a good reason: the gaussian approximation is in general plagued by an <inline-formula><inline-graphic xlink="neco.2008.08-07-592inline1.gif"/></inline-formula> number of variational parameters to be optimized, <inline-formula><inline-graphic xlink="neco.2008.08-07-592inline2.gif"/></inline-formula> being the number of random variables. In this letter, we discuss the relationship between the Laplace and the variational approximation, and we show that for models with gaussian priors and factorizing likelihoods, the number of variational parameters is actually <inline-formula><inline-graphic xlink="neco.2008.08-07-592inline3.gif"/></inline-formula>. The approach is applied to gaussian process regression with nongaussian likelihoods.
On some algebraic aspects of multivariate interpolation
Authors: Corina Simian, Dana Simian
Venue: Proceedings of the 12th WSEAS international conference on Computers (2008)

The aim of this paper is to present some results which illustrate how different multivariate interpolation schemes are related to partial differential operators. In order to prove our main results we use the connection between multivariate interpolation and reduction process with respect to a H-basis of an ideal. A general result for a set of arbitrary interpolation conditions which define an ideal interpolation scheme is obtained.
Dirichlet Process Based Evolutionary Clustering
Authors: Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, Bo Long
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Evolutionary Clustering has emerged as an important research topic in recent literature of data mining, and solutions to this problem have found a wide spectrum of applications, particularly in social network analysis. In this paper, based on the recent literature on Dirichlet processes, we have developed two different and specific models as solutions to this problem: DPChain and HDP-EVO. Both models substantially advance the literature on evolutionary clustering in the sense that not only they both perform better than the existing literature, but more importantly they are capable of automatically learning the cluster numbers and structures during the evolution. Extensive evaluations have demonstrated the effectiveness and promise of these models against the state-of-the-art literature.
The equipartition of curves
Authors: Costas Panagiotakis, Konstantin Athanassopoulos, Georgios Tziritas
Venue: Computational Geometry: Theory and Applications (2009)

In this paper we analyze the problem of partitioning a continuous curve into n parts with equal successive chords, the curve EquiPartition problem (EP). The goal is to locate n-1 consecutive curve points, so that the curve can be divided into n segments with equal chords under a distance function. We adopt a level set approach to prove that for any continuous injective curve in a metric space and any number n there always exists at least one n-equipartition (EP). A new approximate algorithm, that is the first EP algorithm, inspired from the level set approach is proposed for finding all solutions with high accuracy. Finally, EP based applications are presented and special properties of their solutions are discussed.
CVD synthesis of hierarchical 3D MWCNT/carbon-fiber nanostructures
Authors: Toma Susi, Albert G. Nasibulin, Hua Jiang, Esko I. Kauppinen
Venue: Journal of Nanomaterials (2008)

Multiwalled carbon nanotubes (MWCNTs) were synthesized by CVD on industrially manufactured highly crystalline vapor-grown carbon fibers (VGCFs). Two catalyst metals (Ni and Fe) and carbon precursor gases (C2H2 and CO) were studied. The catalysts were deposited on the fibers by sputtering and experiments carried out in two different reactors. Samples were characterized by electron microscopy (SEM and TEM). Iron was completely inactive as catalyst with both C2H2 and CO for reasons discussed in the paper. The combination of Ni and C2H2 was very active for secondary CNT synthesis, without any pretreatment of the fibers. The optimal temperature for CNT synthesis was 750°C, with total gas flow of 650 cm3min-1 of C2H2, H2, and Ar in 1.0:6.7:30 ratio.
The existence of positive solutions for second-order multi-point BVPs with the first derivative
Authors: Weihua Jiang
Venue: Journal of Computational and Applied Mathematics (2009)

By using the fixed-point index theory, several theorems of existence of positive solutions for second-order m-point boundary value problem with the first derivative are obtained, where the nonlinear term may be noncontinuous. An example illustrating the main results is given.
Knowledge Discovery for Counterterrorism and Law Enforcement, 1 edition
Authors: David Skillicorn
Venue: Chapman & Hall/Crc Data Mining And Knowledge Discovery (2008)

Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings. Reveals How Criminals Conceal Information This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to criminals and reveals some of the tactics that can aid in detecting them. He reviews what is known about the different technologies for each area and evaluates their effectiveness. The book also supplies a preview of technologies currently under development and describes how they will fit in to existing approaches to knowledge discovery. Provides Proactive Formulas for Staying One Step Ahead of Adversaries While all knowledge-discovery systems are susceptible to manipulation, designers and users of algorithmic systems who are armed with the knowledge of these subversive tactics are better able to create systems to avoid these vulnerabilities. This book delineates an effective process for integrating knowledge-discovery tools, provides a unique understanding of the limits of the technology, and contains a clear presentation of the upsides and pitfalls of data collection. It is a powerful weapon in the arsenal of anyone confronting the increasingly sophisticated tactics employed by lawbreakers and other unsavory individuals.
Modeling the cost of poor quality
Authors: Claudia Barbará, Edmundo Eutrópio C. de Souza, Rosangela Catunda
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

The paper presents the Oi experience on the implementation, through simulations, of a model for reducing non quality process costs of three categories: non-conformance issues, service failures and loss of income due to lack of quality. The model is based on concepts of improved quality, and enables the identification of the cost of non-quality factors. The simulations allow a quick view of the process cost reduction with the scenario of the improvements identified in the studies.
Finding out general tendencies in speckle noise reduction in ultrasound images
Authors: Juan L. Mateo, Antonio Fernández-Caballero
Venue: Expert Systems with Applications: An International Journal (2009)

This article investigates and compiles some of the techniques mostly used in the smoothing or suppression of speckle noise in ultrasound images. With this information, a comparison of all the methods studied is done based on an experiment, using quality metrics to test their performance and show the benefits each one can contribute. To test the methods, a synthetic, noise-free image of a kidney is created and later simulations using Field II program to corrupt it are performed. This way, the smoothing techniques can be compared using numeric metrics, taking the noise-free image as a reference. Since real ultrasound images are already noise corrupted images and real noise-free images do not exist, conventional metrics cannot be used to indicate the quality obtained with filtering. Nevertheless, we propose the use of the tendencies observed in our study in real images.
VPR 5.0: FPGA cad and architecture exploration tools with single-driver routing, heterogeneity and process scaling
Authors: Jason Luu, Ian Kuon, Peter Jamieson, Ted Campbell, Andy Ye, Wei Mark Fang, Jonathan Rose
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

The VPR toolset [6, 7] has been widely used to perform FPGA architecture and CAD research, but has not evolved over the past decade to include many architectural features now present in modern FPGAs. This paper describes a new version of the toolset that includes four significant features: first, it now supports a broad range of single-driver routing architectures [29, 4, 16]. Single-driver routing has significantly different architectural and electrical properties from the multi-driver approach previously modelled, and is now employed in the majority of FPGAs sold. Second, the new release can now model a heterogeneous selection of hard logic blocks, which could include the hard memory and multipliers that are now ubiquitous in FPGAs. Third, we provide optimized electrical models of a wide range of architectures in different process technologies, including a range of area-delay tradeoffs for each single architecture. Prior releases of VPR did not publish even one architecture file with accurate resistance and capacitance parameters. Finally, to maintain robustness and to support future development the release includes a set of regression tests to check functionality and quality of result of the output of the tools. To illustrate the use of the new features, we present a new look at the FPGA area vs. logic block LUT size question that shows that small LUT sizes, with the use of carefully optimized electrical design and single-driver architectures, have better area (relative to 4-LUTs) than previously thought. Another experiment shows that several of the previous architectural results are invariant in moving from multi-driver to single-driver routing architecture and across a range of process technologies.