Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of OpenMP Compiler for an SMP Cluster

In this paper, we present a design of OpenMP compiler for an SMP cluster. Although clusters of SMPs are expected to be one of the cost-e ective parallel computing platforms, both of inter and intra node parallelism must be exploited to achieve high performance. These two levels of structure complicate parallel programming. The OpenMP is an emerging standard for parallel programming on shared-memory multiprocessors. We extend the OpenMP model for an SMP cluster by "compiler-directed" software distributed shared memory system. Our OpenMP compiler instruments an OpenMP program by inserting remote communication primitives to keep consistency of memory between di erent nodes, and provides a view of shared memory model on the SMP cluster. Di erent from multithreaded programs on conventional software DSMs, an OpenMP program is so well-structured that it allows the compiler to analyze extent of parallel region for the optimization of e cient communication and synchronization. We report some preliminary results of OpenMP programs on a Pentium Pro based SMP cluster, COMPaS.
The Error Coding Method and PICTs

Abstract A new family of plug-in classification techniques has recently been developed in the statistics and machine learning literature. A plug-in classification technique (PICT) is a method that takes a standard classifier (such as LDA or TREES) and plugs it into an algorithm to produce a new classifier. The standard classifier is known as the base classifier. These methods often produce large improvements over using a single classifier. In this article we investigate one of these methods and give some motivation for its success.
A VSSLMS algorithm based on error autocorrelation

This paper proposes a new variable step-size (VSS) LMS algorithm. Since the step-size adjusting process and misadjustment parameter are affected by measurement noise, VSS approaches based on the error signal autocorrelation add some immunity against such an undesired signal. Thus, an existing approach uses a lag(1) error signal autocorrelation function obtaining good results, in the proposed one, lag(1),lag(2),. ,lag(N) error signal autocorrelation functions are used. The computational complexity increase due to the use of several lags is small. Numerical simulations verify the performance of the proposed algorithm, assessed in a system identification problem.
Current Roles and Future Applications of Cardiac CT: Risk Stratification of Coronary Artery Disease

Cardiac computed tomography (CT) has emerged as a noninvasive modality for the assessment of coronary artery disease (CAD), and has been rapidly integrated into clinical cares. CT has changed the traditional risk stratification based on clinical risk to image-based identification of patient risk. Cardiac CT, including coronary artery calcium score and coronary CT angiography, can provide prognostic information and is expected to improve risk stratification of CAD. Currently used conventional cardiac CT, provides accurate anatomic information but not functional significance of CAD, and it may not be sufficient to guide treatments such as revascularization. Recently, myocardial CT perfusion imaging, intracoronary luminal attenuation gradient, and CT-derived computed fractional flow reserve were developed to combine anatomical and functional data. Although at present, the diagnostic and prognostic value of these novel technologies needs to be evaluated further, it is expected that all-in-one cardiac CT can guide treatment and improve patient outcomes in the near future.
Searching for software learning resources using application context

Users of complex software applications frequently need to consult documentation, tutorials, and support resources to learn how to use the software and further their understand-ing of its capabilities. Existing online help systems provide limited context awareness through "what's this? " and simi-lar techniques. We examine the possibility of making more use of the user's current context in a particular application to provide useful help resources. We provide an analysis and taxonomy of various aspects of application context and how they may be used in retrieving software help artifacts with web browsers, present the design of a context-aware augmented web search system, and describe a prototype implementation and initial user study of this system. We conclude with a discussion of open issues and an agenda for further research.
GAs with Applications to Operations Management An Object-Oriented Framework for Rapid Development of Genetic Algorithms with Application to Operations Management and Vehicle Routing

An Object-Oriented Framework for Rapid Development of Genetic Algorithms with Application to Operations Management and Vehicle Routing Andrés L. Medaglia amedagli@uniandes.edu.co Eliécer Gutiérrez egutierr@uniandes.edu.co Centro para la Optimización y Probabilidad Aplicada http://copa.uniandes.edu.co Departmento de Ingeniería Industrial Universidad de los Andes Bogotá D.C., Colombia June 29, 2005 Introduction The purpose of this chapter is to provide readers of this book with a flexible and extensible computational object-oriented tool for rapid prototyping and implementation of evolutionary algorithms. We call this tool JGA, acronym for Java Genetic Algorithm framework. From a practical side, we illustrate in detail the use of JGA and provide examples in the areas of operations management and vehicle routing. This chapter lies in the crossroads of information technology, management science and nature-inspired computing. We hope readers will get an integrated exposition to the theory, algorithmic implementation, and applications of genetic algorithms in various business settings. Finally, we hope readers can benefit directly by using JGA class libraries available at http://copa.uniandes.edu.co/software/jga, to better manage scarce resources and optimize operations using nature-inspired computing.
A combined approach to prevent SQL Injection Attacks

In order to adapt to changing business requirements, information systems are often migrated to the Web but, in doing so, these systems often have their security vulnerabilities exposed to a wider range of attacks. One of the most prominent type of security attacks faced by these systems, according to Mitre Corporation, are SQL Injection Attacks (SQLIA). In this paper, we examine different approaches to detect and protect against SQLIA, each with their strengths and weaknesses, and then propose a combined approach of SQLIA prevention techniques (the fine grained Role Based Access Control [RBAC] and static and dynamic analysis of SQL parse trees) in order to maximise the advantages of each method and to ensure that a second line of defence is provided, in case the first method fails.
Prediction of outcome by early bone marrow response in childhood acute lymphoblastic leukemia treated in the ALL-BFM 95 trial: differential effects in precursor B-cell and T-cell leukemia

Background In the ALL-BFM 95 trial for treatment of acute lymphoblastic leukemia, response to a prednisone pre-phase (prednisone response) was used for risk stratification in combination with age and white blood cell count at diagnosis, response to induction therapy and specific genetic high-risk features. Design and Methods Cytomorphological marrow response was prospectively assessed on Day 15 during induction, and its prognostic value was analyzed in 1,431 patients treated on ALL-BFM 95. Results The 8-year probabilities of event-free survival were 86.1%, 74.5%, and 46.4% for patients with M1, M2, and M3 Day 15 marrows, respectively. Compared to prednisone response, Day 15 marrow response was superior in outcome prediction in precursor B-cell and T-cell leukemia with, however, a differential effect depending on blast lineage. Outcome was poor in T-cell leukemia patients with prednisone poor-response independent of Day 15 marrow response, whereas among patients with prednisone good-response different risk groups could be identified by Day 15 marrow response. In contrast, prednisone response lost prognostic significance in precursor B-cell leukemia when stratified by Day 15 marrow response. Age and white blood cell count retained their independent prognostic effect. Conclusions Selective addition of Day 15 marrow response to conventional stratification criteria applied on ALL-BFM 95 (currently in use in several countries as regular chemotherapy protocol for childhood acute lymphoblastic leukemia) may significantly improve risk-adapted treatment delivery. Even though cutting-edge trial risk stratification is meanwhile dominated by minimal residual disease evaluation, an improved conventional risk assessment, as presented here, could be of great importance to countries that lack the technical and/or financial resources associated with the application of minimal residual disease analysis.
What do Vegans do in their Spare Time? Latent Interest Detection in Multi-Community Networks

Most social network analysis works at the level of interactions between users. But the vast growth in size and complexity of social networks enables us to examine interactions at larger scale. In this work we use a dataset of 76M submissions to the social network Reddit, which is organized into distinct sub-communities called subreddits. We measure the similarity between entire subreddits both in terms of user similarity and topical similarity. Our goal is to find community pairs with similar userbases, but dissimilar content; we refer to this type of relationship as a "latent interest. " Detection of latent interests not only provides a perspective on individual users as they shift between roles (student, sports fan, political activist) but also gives insight into the dynamics of Reddit as a whole. Latent interest detection also has potential applications for recommendation systems and for researchers examining community evolution.
DURIAN RECOGNITION BASED ON MULTIPLE FEATURES AND LINEAR DISCRIMINANT ANALYSIS

Many fruit recognition approaches today are designed to classify different type of fruits but there is little effort being done for content-based fruit recognition specifically focuses on durian species. Durian, known as the king of tropical fruits, have few similar characteristics between different species where the skin have almost the same colour from green to yellowish brown with just slightly different shape and pattern of thorns. Therefore, it is hard to differentiate them with the current methods. It would be valuable to have an automated content-based recognition framework that can automatically represent and recognise a durian species given a durian image as the input. Therefore, this work aims to contribute to a new representation method based on multiple features for effective durian recognition. Two features based on shape and texture is considered in this work. Simple shape signatures which include area, perimeter, and circularity are used to determine the shape of the fruit durian and its base while the texture of the fruit is constructed based on Local Binary Pattern. We extracted these features from 240 durian images and trained this proposed method using few classifiers. Based on 10-fold cross validation, it is found that Logistic Regression, Gaussian Naive Bayesian, and Linear Discriminant Analysis classifiers performed equally well with 100% achievement of accuracy, precision, recall, and F1-score. We further tested the proposed algorithm on larger dataset which consisted of 42337 fruit images (64 various categories). Experimental results based on larger and more general dataset have shown that the proposed multiple features trained on Linear Discriminant Analysis classifier able to achieve 72.38% accuracy, 73% precision, 72% recall, and 72% F1-score.
CULTURE IN EFL: USING AN ELF WRITING PROJECT TO FACILITATE CULTURE AND LANGUAGE LEARNING FOR LOW-PROFICIENCY COLLEGE EFL LEARNERS

This paper aims to present a course design focusing on culture and language learning for low-proficiency EFL classes, and an evaluation of this course. Extensive research has been undertaken discussing cultural content and exploring effective pedagogy to develop learners’ intercultural communicative competence in the context of English as lingua franca (ELF). However, few studies have addressed the issue of teaching low-proficiency students. In light of this, this study integrates an ELF writing project to facilitate culture and language learning for 32 low-proficiency college EFL learners, and investigates the effects of this course using a questionnaire survey, students’ reflection papers and the teacher’s observation and personal notes. The study found positive learning results. As well as these positive results, this study also discusses how the teacher uses students’ writings to teach some essential intercultural communication skills to prepare students as ELF users. Some pedagogical suggestions are also made for teachers with low-proficiency students and curriculum designers. Article visualizations:
Biomimetic Microelectronics for Regenerative Neuronal Cuff Implants

Smart biomimetics, a unique class of devices combining the mechanical adaptivity of soft actuators with the imperceptibility of microelectronics, is introduced. Due to their inherent ability to self-assemble, biomimetic microelectronics can firmly yet gently attach to an inorganic or biological tissue enabling enclosure of, for example, nervous fibers, or guide the growth of neuronal cells during regeneration.
Computationally Comprehensive and Efficient Generalized Poisson's Solution for Better Nanoscale SOI MOSFET

In this paper, for the first time, a computationally comprehensive and efficient generalized Poisson's solution is derived for better nanoscale SOI MOSFET and performance is analyzed for various gate dielectric materials to optimise / predict the better performance. Earlier methods employed for solving the Poisson's equation rigorously for independent gate transistors and long channel asymmetric establish in potential models. But those potential models contain multiple intercoupled implicit equations which are to be solved self-consistently thereby establishing that those models are clearly inefficient for compact modelling. In this work, a novel rigorous method for solving PE has been described to get the potential profile of a single gate SOI MOSFET that incorporates a single implicit equation. The Poisson's solution so obtained in the present work is found to be computationally more efficient for related circuit simulation compared to earlier developed solutions.
GoldenBullet: Automated Classification of Product Data in E-commerce

Internet and Web technology starts to penetrate many aspects of our daily life. Its importance as a medium for business transactions will grow exponentially during the next years. In terms of the involved market volume the B2B area will hereby be the most interesting area. Also it will be the place, where the new technology will lead to drastic changes in established customer relationships and business models. B2B market places provide new kinds of services to their clients. Simple 1-1 connections are getting replaced by n-m relationships between customers and vendors. However, this new flexibility in electronic trading also generates serious challenges for the parties that want to realize it. The main problem here is caused by the heterogeneity of information descriptions used by vendors and customers. Intelligent solutions that help to mechanize the process of structuring, classifying, aligning, and personalizing are a key requisite for successfully overcoming the current bottlenecks of B2B electronic commerce. In this paper, we describe a system called GoldenBullet that applies techniques from information retrieval and machine learning to the problem of product data classification. The system helps to mechanize an important and labor-intensive task of content management for B2B Ecommerce.
Making Sense of Marriage: Gender and the Transition to Adulthood in Nairobi, Kenya.

Objective The objective of this study was to examine how young people in Nairobi, Kenya, are making sense of marriage, both in terms of their own lives and its social significance. Background In many sub-Saharan African communities, marriage has been a fundamental marker of the transition to adulthood. However, union formation is changing, particularly in urban areas-partnering is occurring later and nonmarital cohabitation is increasingly common with the pathways to union formation differing by gender. Young people's perspectives on marriage are valuable for a deeper understanding of these trends. Method A total of 74 in-depth interviews with youth living in the slums of Nairobi, Kenya, were qualitatively analyzed with particular attention to personal and normative understandings of marriage along with how they vary by gender. Results Marriage emerged as an important part of most respondents' life projects, whether or not they considered it key to socially recognized adulthood. Attitudes differed by gender, with young women's greater ambivalence and aversion toward marriage, particularly early marriage, contrasting with young men's frustrated desire for marriage amidst economic constraints. Young men's main worry about marriage was not being able to support a family, whereas young women were often concerned that marrying would thwart their aspirations regarding education and work. Conclusion Marriage continues to be a significant social marker of adulthood despite a shifting demographic reality. Differences in young people's attitudes are related to gendered concerns around marriage and economic independence.
Fine: Fractal indexing based on neighborhood estimation

The structure of a fractal based image indexing system is described. FINE implies image space linearization, a custom clustering strategy, Peano-serialized spatial addressing, ad-hoc heuristics for improving search and specially defined distance functions. The resulting system is invariant, or at least robust, to a large class of typical variations that appear in natural images including rotations, scaling, and changes in color or illumination. The performance of FINE is illustrated, discussed and compared with other present alternatives using standard and custom-based image databases.
Protective Effects of B Vitamins and Antioxidants on the Risk of Arsenic-Related Skin Lesions in Bangladesh

Background An estimated 25–40 million of the 127 million people of Bangladesh have been exposed to high levels of naturally occurring arsenic from drinking groundwater. The mitigating effects of diet on arsenic-related premalignant skin lesions are largely unknown. Objectives The purpose of this study was to clarify the effects of the vitamin B group (thiamin, riboflavin, niacin, pyridoxine, and cobalamin) and antioxidants (vitamins A, C, and E) on arsenic-related skin lesions. Methods We performed a cross-sectional study using baseline data from the Health Effects of Arsenic Longitudinal Study (HEALS), 2000–2002, with individual-level, time-weighted measures of arsenic exposure from drinking water. A total of 14,828 individuals meeting a set of eligibility criteria were identified among 65,876 users of all 5,996 tube wells in the 25-km2 area of Araihazar, Bangladesh; 11,746 were recruited into the study. This analysis is based on 10,628 subjects (90.5%) with nonmissing dietary data. Skin lesions were identified according to a structured clinical protocol during screening and confirmed with further clinical review. Results Riboflavin, pyridoxine, folic acid, and vitamins A, C, and E significantly modified risk of arsenic-related skin lesions. The deleterious effect of ingested arsenic, at a given exposure level, was significantly reduced (ranging from 46% reduction for pyridoxine to 68% for vitamin C) for persons in the highest quintiles of vitamin intake. Conclusions Intakes of B-vitamins and antioxidants, at doses greater than the current recommended daily amounts for the country, may reduce the risk of arsenic-related skin lesions in Bangladesh.
A comprehensive system for facial animation of generic 3D head models driven by speech

A comprehensive system for facial animation of generic 3D head models driven by speech is presented in this article. In the training stage, audio-visual information is extracted from audio-visual training data, and then used to compute the parameters of a single joint audio-visual hidden Markov model (AV-HMM). In contrast to most of the methods in the literature, the proposed approach does not require segmentation/classification processing stages of the audio-visual data, avoiding the error propagation related to these procedures. The trained AV-HMM provides a compact representation of the audio-visual data, without the need of phoneme (word) segmentation, which makes it adaptable to different languages. Visual features are estimated from the speech signal based on the inversion of the AV-HMM. The estimated visual speech features are used to animate a simple face model. The animation of a more complex head model is then obtained by automatically mapping the deformation of the simple model to it, using a small number of control points for the interpolation. The proposed algorithm allows the animation of 3D head models of arbitrary complexity through a simple setup procedure. The resulting animation is evaluated in terms of intelligibility of visual speech through perceptual tests, showing a promising performance. The computational complexity of the proposed system is analyzed, showing the feasibility of its real-time implementation.
Mood Dynamics in Bipolar Disorder-an analysis of 8 patients

Discussion: Nonlinear sample forecasting methods have no advantage over linear methods in out-of-sample forecasting for time series sampled on a weekly basis. These results can mean that either the original series have linear dynamics, the test statistics for distinguishing linear from nonlinear behaviour do not have the power to detect the kind of nonlinearity present, or the process is nonlinear but the sampling is inadequate to represent the dynamics. We suggest that further studies should apply similar techniques to more frequently sampled data.
Degrees of Orality in Speech-like Corpora: Comparative Annotation of Chat and E-mail Corpora

This paper describes and evaluates the automatic grammatical annotation of a chat and an e-mail corpus of together 117 million words, using a modular Constraint Grammar system. We discuss a number of genre-specific issues, such as emoticons and personal pronouns, and offer a linguistic comparison of the two corpora with corresponding annotations of the Europarl corpus and the spoken and written subsections of the BNC corpus, with a focus on orality markers such as linguistic complexity and word class distribution.
Dynamic memory allocation strategies for parallel query execution

In the decision support queries which manipulate large data volumes, it is frequent that a query constituted by several joins can not be computed completely in memory. In this paper, we propose three strategies allowing to assign the memory of a shared-nothing parallel architecture to operation clones of a query. The performance evaluation of the three strategies shows that the strategies which favor the operation clones using a lot of memory obtain a better response time than the strategy which favors the clones using little memory. The main contribution of this paper is to take into account the available memory sizes on every processor and to avoid allotting the same processor to two operation clones that must run in parallel.