Miracle-dz/UniFAR-FTUs huggingface dataset:
FLO67: a case study in scalable programming

We describe a scalable version of the FLO67 program written in the loop style that is characteristic of Fortran 77. This single scalable source program can be compiled and run on conventional scalar processors, vector computers, or massively parallel computers, with respectable performance on all platforms. Initial runs have been on the IBM RISC System/6000, the Sun SPARC, and the Connection Machine supercomputer. This article presents and discusses interesting fragments of the program, focusing on issues of code scalability
Dual screen and confirm rapid test does not reduce overtreatment of syphilis in pregnant women living in a non-venereal treponematoses endemic region: a field evaluation among antenatal care attendees in Burkina Faso

Objectives In resource-limited settings, screening pregnant women for syphilis using rapid diagnostic tests (RDTs) is a key tool in the prevention of congenital syphilis. However, most syphilis RDTs detect only treponemal antibodies (T-RDT), meaning antibiotics may be provided unnecessarily to previously treated pregnant women, particularly in non-venereal treponematoses endemic regions. We estimated the potential reduction in overtreatment when comparing T-RDT (SD Bioline) to a newer rapid test (Dual Path Platform (DPP) Screen and Confirm Assay, Chembio) detecting both treponemal and non-treponemal antibodies. Methods Pregnant women in Déou, Burkina Faso, screened for syphilis during antenatal care (ANC) visits were prospectively enrolled in the study after providing consent. DPP and T-RDT tests were performed on whole blood specimens. Plasma was tested in an international reference laboratory by Treponema pallidum passive particle agglutination (TPPA) and quantitative rapid plasma reagin (RPR). Presumptive active syphilis was defined as a result that was both TPPA and RPR reactive. Results Of the 242 pregnant women included in the study, 91 (37.6%) had presumptive active syphilis and 19.0% had RPR titres ≥8. DPP testing did not reduce the number of pregnant women who would have been overtreated compared with T-RDT (0.0% vs 2.5%; p=0.218) and had a higher proportion of underdiagnosis (48.4% vs 2.2%; p<0.001). Seven women with high RPR titres ≥8 would not have received treatment had only DPP testing been used. Conclusion In the first evaluation comparing DPP with traditional screening methods in pregnant women, we saw no reduction in unnecessarily treated syphilis and an underestimation of those needing treatment. High seroprevalence in the population may indicate the presence of other treponemal infections in the area, and further study of DPP in a variety of Sahelian and other contexts is warranted.
Analysis of the Social Network in Serial Publications: representation in the Journal of Documentation

THE CONSTRUCTION OF MAPS OF SOCIAL NETWORKS IS SHOWN BASED IN THE JOURNAL OF DOCUMENTATION DURING THE PERIOD 1988-2005. THE ANALYSIS IS MADE BY: (I) AUTHORS THAT PRODUCE THE MOST WITHIN THE PUBLICATION, (II) AUTHORS WITH THE GREATEST CENTRALITY AND FREQUENCY IN QUOTES RECEIVED, (III) THE DOCUMENTS WITH THE HIGHEST NUMBER OF CITATIONS DURING THE PERIOD, AND (IV) THE JOURNALS MOST USED IN THE CONSUMPTION OF INFORMATION. 681 ENTRIES WERE RETRIEVED, WHICH WERE DIVIDED INTO 288 BOOK REVIEWS, 172 JOURNAL ARTICLES, 14 EDITORIAL MATERIALS, 12 ARTICLE REVIEWS, 9 REPRINTS AND 2 BIBLIOGRAPHIC ITEMS. THE BIBLIOGRAPHIC INFORMATION OF THE INSTITUTE FOR SCIENTIFIC INFORMATION (ISI) WAS THE ORIGINAL SOURCE FOR THE TREATMENT OF THE DATA AND THE PROGRAM USED WAS CITESPACE, WHICH AUTOMATICALLY GENERATES THE MAPS OF RELATIONSHIPS.
Video summarization using event‐related potential responses to shot boundaries in real‐time video watching

Our aim was to develop an event‐related potential (ERP)‐based method to construct a video skim consisting of key shots to bridge the semantic gap between the topic inferred from a whole video and that from its summary. Mayer's cognitive model was examined, wherein the topic integration process of a user evoked by a visual stimulus can be associated with long‐latency ERP components. We determined that long‐latency ERP components are suitable for measuring a user's neuronal response through a literature review. We hypothesized that N300 is specific to the categorization of all shots regardless of topic relevance, N400 is specific for the semantic mismatching process for topic‐irrelevant shots, and P600 is specific for the context updating process for topic‐relevant shots. In our experiment, the N400 component led to more negative ERP signals in response to topic‐irrelevant shots than to topic‐relevant shots and showed a fronto‐central scalp pattern. P600 elicited more positive ERP signals for topic‐relevant shots than for topic‐irrelevant shots and showed a fronto‐central scalp pattern. We used discriminant and artificial neural network (ANN) analyses to decode video shot relevance and observed that the ANN produced particularly high success rates: 91.3% from the training set and 100% from the test set.
Further experiments in Fuzzy Classifier Systems for mobile robot control

We present a Michigan-style Fuzzy Classifier System architecture, which operates at the level of individual rules. We compare performance of this architecture with a Pittsburgh Fuzzy Classifier System investigated previously it operates at the level of whole rule-bases. The application domain is mobile robotics, and the problem is autonomous acquisition of an "investigative" obstacle avoidance competency. In our work, both Fuzzy Classifier System types are restricted to operating on the rules of fuzzy controllers with pre-defined fuzzy membership functions (MFs). Generally, both approaches were capable of producing fuzzy controllers with competencies that exceeded that of the hand-coded fuzzy controller presented in this paper. The previously investigated Pittsburgh architecture yielded a more stable convergence on high performance solutions than the Michigan architecture that was created to operate at the level of individual rules.
Adaptive noise reduction and image sharpening for digital video compression

This paper presents a framework of digital video preprocessing for digital video compression. The purpose of this preprocessing is to reduce the noise and thus improve the video compression efficiency. A four stage processing system has been proposed. The first process is a median filter to remove the 2D impulse noise. The second process is a 2D spatial filter that is controllable by the video encoder parameters. The third process is an image sharpening operation to enhance the image resolution or details so that the decoded video from the encoded bitstream still gives high resolution content. The last process is a recursive temporal filter that is used to reduce the temporal noise. The recursive filter is designed to adapt to the video content so that high quality temporal filtering is achieved.
A Campylobacter rectus Subdural Empyema

Campylobacter species in the oral cavity have been noted to be the culprits in periodontal disease, but have only rarely been reported to cause extraoral infections. We report an unusual case of a Campylobacter rectus subdural empyema in a diabetic patient. (Infect Dis Clin Pract 2008;16:332Y334) Campylobacter is a genus of motile, nonYspore-forming, comma-shaped, gram-negative bacillus that does not ferment carbohydrates. It is known to cause infection worldwide, both diarrheal and systemic. Within this genus, the major pathogen causing extraintestinal disease is Campylobacter fetus. Although best known as enteric pathogens, Campylobacter species may occasionally cause extraintestinal infections as well as exist as a normal flora in the oral cavity. Those species of the Campylobacter genus that reside in the oral cavity have been noted to be the culprits in periodontal disease, but have only rarely been reported to cause extraoral infection. An unusual case of a Campylobacter rectus subdural empyema is presented and reinforces the need to consider these pathogens as the potential culprits in extraoral diseases.
Fair home-away tables in sports scheduling

This paper considers fair home–away tables in sports scheduling. A home–away table deﬁnes where each match is held in a round-robin tournament, and the quality of the tournament schedule strongly depends on the home–away table. Although some home–away tables considering fairness have been proposed, some unfair aspects remain in them. We propose three kinds of home–away tables, an even-breaks table, a consecutive-breaks table, and a k -interval table, which are fairer than the previously proposed home–away tables. To ﬁnd consecutive-breaks and k -interval home–away tables consistent with a given timetable, we propose algorithms based on 2-satisﬁability. We also introduce a necessary condition on the number of teams where consecutive-breaks and k -interval home–away tables exist.
Mahout in Action

SummaryMahout in Action is a hands-on introduction to machine learning with Apache Mahout. Following real-world examples, the book presents practical use cases and then illustrates how Mahout can be applied to solve them. Includes a free audio- and video-enhanced ebook. About the TechnologyA computer system that learns and adapts as it collects data can be really powerful. Mahout, Apache's open source machine learning project, captures the core algorithms of recommendation systems, classification, and clustering in ready-to-use, scalable libraries. With Mahout, you can immediately apply to your own projects the machine learning techniques that drive Amazon, Netflix, and others. About this BookThis book covers machine learning using Apache Mahout. Based on experience with real-world applications, it introduces practical use cases and illustrates how Mahout can be applied to solve them. It places particular focus on issues of scalability and how to apply these techniques against large data sets using the Apache Hadoop framework.This book is written for developers familiar with Java - no prior experience with Mahout is assumed. What's InsideUse group data to make individual recommendations Find logical clusters within your data Filter and refine with on-the-fly classification Free audio and video extrasTable of ContentsMeet Apache Mahout PART 1 RECOMMENDATIONS Introducing recommenders Representing recommender data Making recommendations Taking recommenders to production Distributing recommendation computations PART 2 CLUSTERING Introduction to clustering Representing data Clustering algorithms in Mahout Evaluating and improving clustering quality Taking clustering to production Real-world applications of clustering PART 3 CLASSIFICATION Introduction to classification Training a classifier Evaluating and tuning a classifier Deploying a classifier Case study: Shop It To Me
Customizing and Implementing Training Evaluation

One barrier that human resource managers may face in evaluating their training programs is lack of expertise in how to customize and implement an evaluation model. Using a case study approach, we conducted a research study to document the process and results of customizing and implementing a training program evaluation model in an organization. In this article, we describe the steps that the HRD managers in one organization used to customize and implement the Training Effectiveness Evaluation (TEE) model (Swanson & Sleezer, 1987), and the decisions and actions that were required to move from the model to actual practice. We also describe how the decisions and actions in implementing the model influenced the evaluation results. When the project began, the HRD managers lacked expertise in customizing and implementing an evaluation model. By the end of the project, they had overcome this barrier and gained new skills. They had learned to use the tools of the TEE model and had customized the model to meet the needs of their organization.
Predicting individual fusional range from optometric data

A model was developed to predict the range of disparities that can be fused by an individual user from optometric measurements. This model uses parameters, such as dissociated phoria and fusional reserves, to calculate an individual user’s fusional range (i.e., the disparities that can be fused on stereoscopic displays) when the user views a stereoscopic stimulus from various distances. This model is validated by comparing its output with data from a study in which the individual fusional range of a group of users was quantified while they viewed a stereoscopic display from distances of 0.5, 1.0, and 2.0 meters. Overall, the model provides good data predictions for the majority of the subjects and can be generalized for other viewing conditions. The model may, therefore, be used within a customized stereoscopic system, which would render stereoscopic information in a way that accounts for the individual differences in fusional range. Because the comfort of an individual user also depends on the user’s ability to fuse stereo images, such a system may, consequently, improve the comfort level and viewing experience for people with different stereoscopic fusional capabilities.
An application of neural network for harmonic detection in active filter

This paper describes the method which uses neural networks for the harmonic detection process in an active filter. Originally, Fourier transformation is used to analyze the distorted wave from the power line and a low-pass filter is used to eliminate the fundamental wave before each harmonic component is detected. Due to these complicated processes, the behavior of the active filter is delayed such that it is difficult to compensate the harmonics in real time. In order to improve the processing speed and simplify the harmonic detection process, a neural network is used to detect the harmonics in the distorted wave instead of Fourier transformation and low-pass filter. The authors simulated the distorted wave including 3rd, 5th and 7th harmonics and used a neural network to recognize each harmonic. The results shows that a neural network enable to detect each harmonic effectively. <<ETX>>
Sparse Distributed Memory

From the Publisher: Motivated by the remarkable fluidity of memory the way in which items are pulled spontaneously and effortlessly from our memory by vague similarities to what is currently occupying our attention Sparse Distributed Memory presents a mathematically elegant theory of human long term memory. The book, which is self contained, begins with background material from mathematics, computers, and neurophysiology; this is followed by a step by step development of the memory model. The concluding chapter describes an autonomous system that builds from experience an internal model of the world and bases its operation on that internal model. Close attention is paid to the engineering of the memory, including comparisons to ordinary computer memories. Sparse Distributed Memory provides an overall perspective on neural systems. The model it describes can aid in understanding human memory and learning, and a system based on it sheds light on outstanding problems in philosophy and artificial intelligence. Applications of the memory are expected to be found in the creation of adaptive systems for signal processing, speech, vision, motor control, and (in general) robots. Perhaps the most exciting aspect of the memory, in its implications for research in neural networks, is that its realization with neuronlike components resembles the cortex of the cerebellum. Pentti Kanerva is a scientist at the Research Institute for Advanced Computer Science at the NASA Ames Research Center and a visiting scholar at the Stanford Center for the Study of Language and Information. A Bradford Book.
Psychiatric intensive care and low secure units: where are we now?

The last decade has seen clinicians and policy makers develop psychiatric intensive care units and low secure units from the so-called ‘special care wards’ of the 1980s and 1990s. Psychiatric intensive care units are for short-term care, while low secure units are for care for up to about 2 years. Department of Health standards have been set for these units. A national survey has shown that there are two main patient groups in the low secure units: patients on forensic sections coming down from medium secure units and those on civil sections who are transferred from general psychiatric facilities. Recent clinical opinion has emphasised the important role both psychiatric intensive care units and low secure units play in providing a bridge between forensic and general mental health services.
pembangunan Prototaip Koswer Pembelajaran Pendidikan Islam Kbsm Dibawah Tajuk Solat Jama Dan Qasar Berasaskan Teori Pembelajaran Kognitif

Perkembangan teknologi maklumat (IT) semakian pesat apada hari ini hingga turut mempengaruhi dunia pendidikan. Teknologi yang berkembang sebegini pesat memungkinkan proses pembelajaran dilakuakn berbantukan komputer sepenuhnya atau dikenalai sebagai Pembelajaran Berbnatukan Komputer (PBK). Selaras dengan hasrat kementerian pelajaran Malaysia untuk mewujudkan Sekolah Besatri, maka projek sarjana ini memilih untuk membangunkan dan menilai keberkesanan sebuah koswer Pembelajaran Solat Jama dan Qasar di sekolah. Koswer ini dibangunkan menggunakan perisian Bahasa Gubahan Macromedia Authorware 6.5. Selain itu, beberapa perisian sokongan turut digunakan antaranya Adobe Photoshop 7.0, Sonic Foundry Sound Forge 6 dan sebagainya. Ini tidak laian untuk mewujudkan ciri-ciri multimedia dalam koswer agar pembelajaran menjadi lebih terangsang. Teori pembelajaran kognitif telah diterapkan melalui lima cirri dalam pembangunan koswer ini yang menggunakan model pembangaunan Hannafin dan Peck (1985). Teori pembelajaran kognitif berpotensi menggarap kemahiarn penaakulan dan pembinaan persepsi oleh pelajar. Koswer diui dengan kajian berbentuk kuasi-eksperimental dengan 15 sampel menggunakan kajian pra dan pos. Instrumen ujian, soal selidik dan pemerhatian digunakan bagi mendapatkan data. Dapatan kemudiannya dianalisis menggunakan perisian Statistical package For Social Science (SPSS) versi 11.0 untuk Windows. Dapatan kajian seterusnya boleh diguankan untuk kajian lanjutan atau rujukan mana-mana pihak. Semoga koswer yang dibangunkan akan memberi manfaat kepada semua yang menggunakannya.
Review on ethnomedicinal uses and phytopharmacology of memory boosting herb Convolvulus pluricaulis Choisy.

Convolvulus pluricaulis Choisy: a rasayana drug which is mainly advocated for use in mental stimulation and rejuvenation therapy. It is known as Shankhpushpi by Ayurvedic practitioners in ancient systems of Indian medicine as it was a prominent memory improving drug, a psychostimulant and tranquiliser in traditional Indian medicine. The plant contains several alkaloids, flavanoids and coumarins as active chemicals that bring about its biological effects. Little human research has been published in the Western medical literature regarding this plant. Preclinical (in vivo and vitro) investigations have demonstrated nootropic, anxiolytic, tranquillising, antidepressant, antistress, neurodegenerative, antiamnesic, antioxidant, hypolipidemic, immunomodulatory, anti- inflammatory, analgesic, antimicrobial, insecticidal, antifungal, antibacterial, antidiabetic, antiulcer, anticatatonic and cardiovascular activity. Clinical studies of its polyherbal formulation justified its potential for the ancient claim of brain tonic. The present review is an attempt to compile information on various ethnomedical aspects of Convolvulus pluricaulis, shankhpushpi of Indian traditional
A 3.8-ns CMOS 16*16-b multiplier using complementary pass-transistor logic

A 3.8-ns, 257-mW, 16*16-b CMOS multiplier with a supply voltage of 4 V is described. A complementary pass-transistor logic (CPL) is proposed and applied to almost the entire critical path. The CPL consists of complementary inputs/outputs, an nMOS pass-transistor logic network, and CMOS output inverters. The CPL is twice as fast as conventional CMOS due to lower input capacitance and high logic functionality. Its multiplication time is the fastest ever reported, even for bipolar and GaAs ICs, and it can be enhanced further to 2.6 ns with 60 mW at 77 K. >
Learning Algorithms for RBF Functions and Subspace

Among extensive studies on radial basis function (RBF), one stream consists of those on normalized RBF (NRBF) and extensions. Within a probability theoretic framework, NRBF networks relates to nonparametric studies for decades in the statistics literature, and then proceeds in the machine learning studies with further advances not only to mixture-of-experts and alternatives but also to subspace based functions (SBF) and temporal extensions. These studies are linked to theoretical results adopted from studies of nonparametric statistics, and further to a general statistical learning framework called Bayesian Ying Yang harmony learning, with a unified perspective that summarizes maximum likelihood (ML) learning with the EM algorithm, RPCL learning, and BYY learning with automatic model selection, as well as their extensions for temporal modeling. This chapter outlines these advances, with a unified elaboration of their corresponding algorithms, and a discussion on possible trends.
The Development of Computer-based Case Simulations for Psychological Counseling

Computer-based Case Simulations (CCS) is the world-class medical clinical simulation system. Computer-based Case Simulations for Psychological Counseling (CCSPC) is suited with psychological counseling settings. CCSPC is developed in this study in order to measure the subjects’ practical skills and decision-making styles during the psychological counseling progress, as well as the related knowledge of concepts, principles and methods, to get a whole assessment of the subjects’ counseling skills. C#2003 is used to realize the visualized interfaces, and SQL2005 is in charge of the database. The stability and reliability of CCSPC is considerably acceptable.
Immersive VR in Phantom Limb Pain Therapy of Amputee Patients Due to Critical Limb Ischemia

Abstract Introduction: Phantom limb pain (PLP) occurs in approximately 75% of patients who undergo limb amputation. In identifying the etiopathogenic mechanisms, multidisciplinary approaches are increasingly important in explaining the causality based on neurological and psychological factors. PLP has many negative effects on the amputee's physical and mental integrity, which is why a variety of treatments have been conceived, whose effectiveness is rather limited. Objective: The purpose of this study is to evaluate the effectiveness of an immersive virtual reality (IVR) intervention program using the mirror therapy principles in decreasing PLP. Method: Twenty participants suffering from PLP were randomly assigned to one of the two intervention groups: IVR and kinesiotherapy, respectively. Pre- and post-intervention measurements were performed both on pain level and on several psychological variables: depression and anxiety symptoms, pain catastrophizing, quality of life, body representation and coping strategies. Results: Preliminary data show a significant pain relief in patients in the IVR group compared to those in the kinesiotherapy group. Besides, significant improvement was found in the case of the patients in the IVR group, in terms of life quality improvement, reducing irrational pain catastrophizing-related thoughts and positive coping strategies (positive refocusing and reappraisal). There were no differences identified between the two groups in terms of anxiety and depression symptoms. Despite expectations, patients in the IVR group experienced a significant increase in one negative coping strategy: rumination. Conclusions: The results obtained are advocating the use of IVI intervention as a method phantom limb pain alleviation, with positive consequences on patients' life quality.