Miracle-dz/UniFAR-FTUs huggingface dataset:
The Usefulness of Related Functions in Web of Science and Scopus

Abstract Objective: This study evaluates the effectiveness of the related search functions in Web of Science and Scopus. Web of Science has one related search function (searching by references) whereas Scopus has three related search functions (searching by references, authors, or keywords). Methods: Thirty queries were searched in both Web of Science and Scopus. For each query, the most relevant document was retrieved and its first thirty related documents were assessed for relevancy to the original query. Results for both databases were compared using the median values of precision. For Scopus the three different methods of relevance were compared using median precision values. Results: The median precision value for the related documents retrieved from Web of Science was 0.63, while the median for those retrieved from Scopus using the related by references function was 0.62. A Wilcoxon test showed no significant difference in the two medians. In the comparison of the three related functions in Scopus, the median precision values were 0.62, 0.42, and 0.43 for the related search functions by references, authors, and keywords respectively. A Friedman's test showed that the median precision value for relatedness by references was significantly higher than the median vales for the other two related functions. In Scopus, the effectiveness of the related search function using all keywords was not as effective when compared to the effectiveness using select keywords. The median precision value with select keywords was 0.17. Conclusions: The related search functions by references for both Web of Science and Scopus were moderately effective in retrieving additional relevant documents on a given topic, and there was no significant difference in their performance. When comparing the three methods available in Scopus, the related search function by references was found to be more effective than the system's related functions by authors and keywords.
Development of a brief screen for substance misuse amongst people with severe mental health problems living in the community

Background: The only specific screening tool for substance misuse by people with severe mental health problems is the Dartmouth Assessment of Lifestyle Instrument (DALI), which was not developed for use amongst community-based people. Aim: To use the DALI to develop a brief community screen to detect the possibility of harmful substance use (N = 216 people with psychosis). Method: Anglicized versions of the DALI (DALI-UK), and the DALI adapted to accommodate changing patterns of drug use (DALI-MOD) were validated against criterion measures of substance misuse. Data from 160 patients were analysed to find which items best predicted problematic alcohol and drug use. A validation group (n = 56) was used to evaluate the scoring system and develop a short version. Results: Using logistic regression, a single item predicted our criterion measure for alcohol problems and two items predicted our criterion measure for drug problems. We developed the Simple Substance Use Screening Scale (SUSS), which correctly classified 86% of participants for problematic alcohol use (sensitivity 88%, specificity 84%) and 84% for problematic drug use (sensitivity 82%, specificity 84%). Conclusion: Because of its brevity and simplicity, SUSS would be a useful screen for use in routine community mental health practice.
Low bit rate multi-pulse speech coder with natural speech quality

This paper proposes a new low bit-rate speech coding algorithm based on a multi-pulse excitation technique. In the algorithm, an excitation signal in a frame, which includes several pitch periods, is effectively represented by pulses during only one pitch period. Excitation signal for other pitch periods in the frame is reproduced by interpolating the pulses. From several experiments to evaluate the new coder, it is found that the new coder produces natural-sounding speech at low bit rates. Subjective evaluation results show that the new coder at 4.8kb/s attains good speech quality which is almost equivalent to that for 6bit/sample/µ-law PCM.
Creative Advertising: Theory and Practice

A comprehensive introduction to the creative side of advertising that gathers into one volume all the important aspects of copywriting, layout and design, and creative message strategy. Providing the underlying theories that explain the practices of the profession three sections cover the advertising process, media specifics and situations and decision. Coverage is extended to the topics of professionalism, the process of advertising, visual communication and new developments in production.
Resource allocation model in software development

In this paper, we apply the queueing theory to model software management and maintenance during the system test, alpha test, and the beta test phases of a software system. The model helps us to verify the progress of the testing phase and estimate its cost. Based on the statistical results derived from the model, we then make a decision about changes in the workforce early rather than letting the product miss the scheduled deadline. Moreover, the model helps developers and managers to measure the product reliability, the quality of service, and to accurately estimate the number of developers needed for product maintenance. Three queue models, M/M/1, M/M/c, and the Jackson network are discussed in this paper. The basic unknown parameters of the models are the fault-report rate and the fixing-fault rate. We also present the technique to estimate the fault report and fixing fault intensities. The model gives us some information about workforce utilization, the average number of fault reports in the queue and system, the response time to customers, and software team missed deadlines. Finally we compare the results obtained from the statistical analysis of real data collected during the testing phase of a computer telephony integration system.
Temporal and Spatio-temporal Data Mining

The recent surge of interest in spatio-temporal databases has resulted in numerous advances, such as: modeling, indexing, and querying of moving objects and spatio-temporal data. Aside from this, rule mining in spatial databases and temporal databases has been studied extensively in data mining research. Temporal and Spatio-Temporal Data Mining examines the problem of mining topological patterns in spatio-temporal databases by imposing the temporal constraints into the process of mining spatial collocation patterns. Temporal and Spatio-Temporal Data Mining presents probable solutions when discovering the spatial sequence patterns by incorporating the spatial information into the sequence of patterns, and introduces two new classes of spatial sequence patterns: flow patterns and generalized spatio-temporal patterns. This innovative book addresses different scenarios when finding complex relationships in spatio-temporal data by modeling them as graphs, giving readers a comprehensive synopsis on two successful partition-based algorithms designed by the authors.
Query Rewriting using Semistructured Views

We consider the problem of rewriting semistructured queries using semistructured views. Given a client semistructured positive non-recursive query and a set of semistructured views, the algorithm nds a rewriting query that is equivalent to the client query and accesses only the views. Our solution is based on appropriately generalizing well understood techniques such as containment mappings and the chase. Furthermore, we develop an equivalence testing algorithm for checking the equivalence of the client query against the composition of the rewriting query with the views. We prove that our algorithm is sound and complete. Finally we investigate a specialized polynomial algorithm for composing the rewritten query with the views, based on which we can show that the semistructured query rewriting problem is NP-complete; i.e., it is no harder than the rewriting problem for conjunctive queries. Research partially sponsored by NSF, under Award Number IRI-9712239, and the Wright Laboratory, Aeronautical Systems Center, Air Force Material Command, USAF, under Grant Number F33615-93-1-1339. Research partially supported by NSF grant IRI{96{31952, ARO grant DAAH04{95{1{0192, Air Force contract F33615{93{1{1339 and the L. Voudouri Foundation.
Improved multi-target tracking using probability hypothesis density smoothing

The optimal Bayesian multi-target tracking is computationally demanding. The probability hypothesis density (PHD) filter, which is a first moment approximation of the optimal one, is a computationally tractable alternative. By evaluating the PHD, one can extract the number of targets as well as their individual states. Recent sequential Monte Carlo (SMC) implementation of the PHD filter paves the way to apply the PHD filter to nonlinear non-Gaussian problems. It seems that the particle implementation of PHD filter is more dependent on current measurements, especially in the case of low observable target problems (i.e., estimates are sensitive to missed detections and false alarms). In this paper, a PHD smoothing algorithm is proposed to improve the capability of the PHD based tracking system. By performing smoothing, which gives delayed estimates, we will get not only better estimates for target states but also better estimate for number of targets. Simulations are performed on proposed method with a multi-target scenario. Simulation results confirm the improved performance of the proposed algorithm.
Crafting a Java virtual machine in silicon

The aJile family of low-power, single-chip, embedded Java microcontrollers provides an efficient platform for embedded and real-time Java execution. The aJile CPU hardware provides direct support for the entire JVM instruction set and thread model, obviating the need for a Java interpreter or just-in-time compiler, as well as the traditional RTOS. aJile's hardware technology also supports multiple JVM contexts executing on the same CPU, enhancing safety and security by guaranteeing space and time allotments for multiple Java applications. Combined with a Java 2 Micro Edition (J2ME) runtime and a back-end target build tool, these technologies allow the development of real-time embedded applications entirely in Java.
Robust Multi-homography Method for Image Stitching under Large Viewpoint Changes

Image stitching technique has many applications in computer vision. Traditional approaches have achieved much success under the assumption that the input images must have little or no parallax. However, this assumption cannot be guaranteed in real-world problems, for example, building images with ground under large viewpoint changes. The traditional methods only use a whole homography for alignment, which will result in severe distortions. To deal with the problem of stitching building images with ground under large viewpoint changes, we propose a robust multi-homography image composition method. It mixes multiple homographies for stitching building images with ground under large viewpoint changes. By calculating different homographies from different types of features, multiple homographies are then be blended with Gaussian weights to construct panorama. The chosen images under various conditions are used to evaluate our proposed method with other methods. The experimental results demonstrate that our proposed method performs higher alignment accuracy and more natural panorama than the traditional projective transformation and some representative state-of-the-art image stitching methods.
Improving the Performance of Text Summarization

This book is concerned with the area of automatic summarization of multiple documents. We propose several methods that improve the accuracy of the summaries. We have explored document density in graph-based multi-document summarization. We have tested the assumption that the higher the density of a document, the higher the salience (score) of its sentences leading to better summaries.We have also done work on user-based models of multi-document summarization. We note that different users can generate rather different summaries on the basis of the same source data and query. We have exploited machine learning techniques to generate models oriented to specific users, but for the same query and source data. Also, we have explored the actor-object relationship (AOR) between sentences. This work lead again to marked improvements in the overall result, particularly when combined with the rather successful approach that involves ensemble summarizing system.
Foot and Ankle Kinematics During Gait Using Foot Mounted Inertial System

A system which provides for generation of alert packets using network interfaces. The alert packets are downloaded into a network interface, for example during a transition from an OS-present state to an OS-absent state. The alert packets are provided with control fields which, in various combinations, indicate alert conditions upon which such packets are to be transmitted, and which indicate a repetition mode for transmission of the packet after a match of the alert condition. Logic in the network interface, causes scanning in the plurality of packets downloaded into the network interface at scan intervals to identify packets having control codes matching alert signals received by the network interface. The process allows for more than one alert packet to be matched with a single alert signal during a given scan interval, and to be transmitted. Also, in one embodiment, each alert packet which matches an alert signal can be transmitted according to a repetition mode indicated in the control fields of the packet.
Preventing Skin Cancer in Adolescent Girls Through Intervention with Their Mothers

Preventing Skin Cancer in Adolescent Girls Through Intervention with Their Mothers by Mary Kate Baker Indoor tanning (IT) before the age of 35 increases one’s risk for melanoma by 75%, and epidemiological data show a 6.1% annual increase in the incidence of melanomas in white women younger than age 44 in the US. Population-based studies reveal that 15% of adolescents and 8% to 14% of their primary caregivers have engaged in IT in the past year. The compelling case for IT being a significant risk factor for melanoma, together with the high rates of IT in teen girls and their mothers, provided a strong rationale for conducting an antitanning intervention directed at mother-daughter dyads. This study evaluated a strategy designed to prevent skin cancer in adolescent girls by using mothers as change agents to effectively communicate the risks of IT and to encourage teens to avoid high risk IT behaviors. Mother-daughter dyads were recruited over the telephone, randomly assigned to the intervention or control group, and surveyed on IT risk constructs including tanning-specific knowledge and
Effect of Arisaema erubescens (Wall) Schott rhizome extract on rheumatoid arthritis

Purpose : To investigate the anti-arthritic activity of the water extract of Rhizoma Arisaematis (WERA) using a collagen II -induced arthritis (CIA) rat model. Methods : CIA was induced in male Sprague-Dawley rats by intradermal injection of bovine collagen II in Complete Freund’s Adjuvant. The rats were treated with daily oral doses of WERA (100, 200, and 400 mg/kg) for 21 consecutive days. Methotrexate (MTX, 3 mg/kg), used as a positive control, was administered orally 2 times/week for 3 weeks. The severity of arthritis was evaluated using indices of paw swelling, arthritic score, body weight, thymus index, and spleen index. In addition, the serum levels of IL-1β, IL-6, IL-10, and TNF-α were measured. Results : All doses of WERA significantly inhibited paw edema (p < 0.01), decreased arthritis scores (p < 0.01) and spleen index (p < 0.05), and alleviated the weight loss associated with CIA in rats. Furthermore, TNF-α, IL-1β, and IL-6 serum levels were significantly decreased (p < 0.05) by all doses of WERA. By contrast, IL-10 serum levels were markedly increased (p < 0.05). Conclusion : WERA exerts therapeutic effects in CIA in rats by decreasing the serum levels of TNF-α, IL-1β, IL-6 and IL-10, suggesting WERA may be an effective candidate drug for treating human rheumatoid arthritis. Keywords : Rhizoma Arisaematis , Rheumatoid arthritis, Inflammatory, Cytokines, Freund’s complete adjuvant
Lenticular Polyester Resin Sculpture: Transparency and Light

The author reviews briefly his outlook on contemporary trends in the plastic arts in the U.S.A. and describes his experience of working in the midst of scientists and engineers at the California Institute of Technology. He discusses his recent sculptures made of transparent polyester resin castings both from the point of view of their conception and of their technical execution. Specific details and instructions are given for casting the material and for polishing its surface to give good transparency for the transmission of light, which, when refracted by the lenticular shapes, produces prismatic colors. In conclusion, he describes a 16 mm color cinema film made of the phenomena within lenticular sculptures and comments upon this recent involvement as regards light and color, and the production of illusions of space. L’auteur rappelle brièvement ses vues sur les tendances actuelles des arts plastiques aux Etats-Unis et il rend compte de son travail parmi des savants et des ingénieurs au California Institute of Technology. Il décrit ses récentes sculptures en résine-polyester transparente, à la fois dans leur conception et dans leur exécution technique. Il donne des détails spécifiques et des instructions sur la façon de couler le matériau et de polir sa surface, de manière à obtenir une transparence telle que la lumière puisse être transmise et réfractée par les formes lenticulaires de la sculpture, produisant ainsi des couleurs prismatiques. En conclusion, l’auteur décrit un film 16 mm en couleur portant sur ce phénomène dans des sculptures lenticulaires, et il commente cet intérêt récent pour le cinéma en ce qui concerne la lumière, la couleur et la production d’illusions spatiales.
Reconhecimento de postes da rede elétrica em vias urbanas em imagens do Google Street View

Ambientes urbanos, tais como ruas, estradas e construcoes, sempre demandam gerenciamento e manutencao para que sejam melhor utilizados. Nesse sentido, ferramentas computacionais que auxiliem seus gestores sao sempre desejaveis. Por outro lado, tais ferramentas geralmente diminuem os gastos tendo em vista que automatizam varias tarefas. Esta pesquisa apresenta uma abordagem para o reconhecimento de postes da rede eletrica em imagens de ruas mapeadas pelo Google Street View. Caracteristicas como cor, textura e forma foram pesquisadas com o objetivo de se encontrar o melhor conjunto de informacoes que represente os objetos de interesse. O reconhecimento foi realizado por uma rede neural do tipo Multilayer Perceptron treinada com o algoritmo Levenberg-Marquardt. Os resultados obtidos demonstram uma acuracia superior no reconhecimento quando se utiliza, de forma combinada, a moda RGB e propriedades de textura como caracteristicas para representar as estruturas presentes nas imagens
The nature of police involvement in mental health transfers

During the course of their duties, police regularly have contact with mentally ill persons who are experiencing psychiatric crisis and require some form of mental health transfer. This study examined 2611 unique mental health transfers completed by police in the Australian state of Victoria over an eight-month period in 2009–2010. The overwhelming majority of mental health transfers performed by police during this period were the result of unplanned calls for assistance. Although police frequently requested assistance from other services, these were often not available. The study findings support a substantial body of anecdotal evidence from police citing lengthy involvement with people experiencing mentally illness, with the average mental health transfer consuming 2.5 h of police time. The frontline responses of police to people in psychiatric crisis need to be more formally acknowledged and creative solutions need to be sought with health and welfare services to better meet the needs of those who are falling between the cracks of community mental health care services.
Speech-Based Human and Service Robot Interaction: An Application for Mexican Dysarthric People

Dysarthria is a motor speech disorder due to weakness or poor coordination of the speech muscles. This condition can be caused by a stroke, traumatic brain injury, or by a degenerative neurological disease. Commonly, people with this disorder also have muscular dystrophy, which restricts their use of switches or keyboards for communication or control of assistive devices (i.e., an electric wheelchair or a service robot). In this case, speech recognition is an attractive alternative for interaction and control of service robots, despite the difficulty of achieving robust recognition performance. In this paper we present a speech recognition system for human and service robot interaction for Mexican Spanish dysarthric speakers. The core of the system consisted of a Speaker Adaptive (SA) recognition system trained with normal-speech. Features such as on-line control of the language model perplexity and the adding of vocabulary, contribute to high recognition performance. Others, such as assessment and text-to-speech (TTS) synthesis, contribute to a more complete interaction with a service robot. Live tests were performed with two mild dysarthric speakers, achieving recognition accuracies of 90–95% for spontaneous speech and 95–100% of accomplished simulated service robot tasks.
Study of an investigation on factors influencing human resources productivity in Shiraz University of Medical Sciences

Introduction: Human resources development is one of the most important components of any organization and detecting important factors influencing human resources management plays an essential role in the success of the firms. In this study, we investigated different factors influencing human resources productivity of Shiraz University of Medical Sciences staff.Method: The present research was a cross-sectional study. Sample size was calculated 208 individuals. To access information about the human resource productivity, a valid and reliable questionnaire was used. The data were analyzed using SPSS software. Pearson correlation was used for statistical analysis of the data (p=0.05). Results:The results showed that there was a statistically significant relationship (p-value<0.001) between human resources productivity and factors affecting the productivity of human resources (motivational factors, leadership style, creativity and innovation, general and applied education, and competitive spirit). Motivational factors (r =0.89) and general education (r =0.65) had the most and the least effects on human resources productivity.Conclusion: Considering the fact that motivational factors were the most effective factors on human resource productivity, we recommend that managers should care more than before about this factor; also, in order to motivate the employees, they should consider the staff’s individual differences.Keywords: Resource, Human resource, Productivity