837 resultados para Web-based tools
Resumo:
Não é novidade que o paradigma vigente baseia-se na Internet, em que cada vez mais aplicações mudam o seu modelo de negócio relativamente a licenciamento e manutenção, para passar a oferecer ao utilizador final uma aplicação mais acessível no que concerne a licenciamento e custos de manutenção, já que as aplicações se encontram distribuídas eliminando os custos de capitais e operacionais inerentes a uma arquitetura centralizada. Com a disseminação das Interfaces de Programação de Aplicações (Application Programming Interfaces – API) baseadas na Internet, os programadores passaram a poder desenvolver aplicações que utilizam funcionalidades disponibilizadas por terceiros, sem terem que as programar de raiz. Neste conceito, a API das aplicações Google® permitem a distribuição de aplicações a um mercado muito vasto e a integração com ferramentas de produtividade, sendo uma oportunidade para a difusão de ideias e conceitos. Este trabalho descreve o processo de conceção e implementação de uma plataforma, usando as tecnologias HTML5, Javascript, PHP e MySQL com integração com ®Google Apps, com o objetivo de permitir ao utilizador a preparação de orçamentos, desde o cálculo de preços de custo compostos, preparação dos preços de venda, elaboração do caderno de encargos e respetivo cronograma.
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Globalization has been accompanied by the rapid spread of infectious diseases, and further strain on working conditions for health workers globally. Post-SARS, Canadian occupational health and infection control researchers got together to study how to better protect health workers, and found that training was indeed perceived as key to a positive safety culture. This led to developing information and communication technology (ICT) tools. The research conducted also showed the need for better workplace inspections, so a workplace audit tool was also developed to supplement worker questionnaires and the ICT. When invited to join Ecuadorean colleagues to promote occupational health and infection control, these tools were collectively adapted and improved, including face-to-face as well as on-line problem-based learning scenarios. The South African government then invited the team to work with local colleagues to improve occupational health and infection control, resulting in an improved web-based health information system to track incidents, exposures, and occupational injury and diseases. As the H1N1 pandemic struck, the online infection control course was adapted and translated into Spanish, as was a novel skill-building learning tool that permits health workers to practice selecting personal protective equipment. This tool was originally developed in collaboration with the countries from the Caribbean region and the Pan American Health Organization (PAHO). Research from these experiences led to strengthened focus on building capacity of health and safety committees, and new modules are thus being created, informed by that work. The products developed have been widely heralded as innovative and interactive, leading to their inclusion into “toolkits” used internationally. The tools used in Canada were substantially improved from the collaborative adaptation process for South and Central America and South Africa. This international collaboration between occupational health and infection control researchers led to the improvement of the research framework and development of tools, guidelines and information systems. Furthermore, the research and knowledge-transfer experience highlighted the value of partnership amongst Northern and Southern researchers in terms of sharing resources, experiences and knowledge.
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This paper presents a new approach to achieving interoperability between Web-based construction products catalogues. It first introduces the current development of electronic catalogues of construction products. The common system architecture of Web-based electronic products catalogues is discussed, which is followed by a discussion on construction products information standardization and the latest distributed-systems technologies for the communication and exchange of construction products information. The latter part of this paper presents a model of interoperable Web-based construction products catalogue and an implementation of Web services in E-commerce systems to enable the sharing of construction products information.
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Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.
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Understanding Digital Literacies provides an accessible and timely introduction to new media literacies. It supplies readers with the theoretical and analytical tools with which to explore the linguistic and social impact of a host of new digital literacy practices. Each chapter in the volume covers a different topic, presenting an overview of the major concepts, issues, problems and debates surrounding the topic, while also encouraging students to reflect on and critically evaluate their own language and communication practices. Features include: coverage of a diverse range of digital media texts, tools and practices including blogging, hypertextual organisation, Facebook, Twitter, YouTube, Wikipedia, websites and games an extensive range of examples and case studies to illustrate each topic, such as how blogs have affected our thinking about communication, how the creation and sharing of digital images and video can bring about shifts in social roles, and how the design of multiplayer online games for children can promote different ideologies a variety of discussion questions and mini-ethnographic research projects involving exploration of various patterns of media production and communication between peers, for example in the context of Wikinomics and peer production, social networking and civic participation, and digital literacies at work end of chapter suggestions for further reading and links to key web and video resources a companion website providing supplementary material for each chapter, including summaries of key issues, additional web-based exercises, and links to further resources such as useful websites, articles, videos and blogs.
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Background: There is evidence that physical activity (PA) can attenuate the influence of the fat mass- and obesity-associated (FTO) genotype on the risk to develop obesity. However, whether providing personalized information on FTO genotype leads to changes in PA is unknown. Objective: The purpose of this study was to determine if disclosing FTO risk had an impact on change in PA following a 6-month intervention. Methods: The single nucleotide polymorphism (SNP) rs9939609 in the FTO gene was genotyped in 1279 participants of the Food4Me study, a four-arm, Web-based randomized controlled trial (RCT) in 7 European countries on the effects of personalized advice on nutrition and PA. PA was measured objectively using a TracmorD accelerometer and was self-reported using the Baecke questionnaire at baseline and 6 months. Differences in baseline PA variables between risk (AA and AT genotypes) and nonrisk (TT genotype) carriers were tested using multiple linear regression. Impact of FTO risk disclosure on PA change at 6 months was assessed among participants with inadequate PA, by including an interaction term in the model: disclosure (yes/no) × FTO risk (yes/no). Results: At baseline, data on PA were available for 874 and 405 participants with the risk and nonrisk FTO genotypes, respectively. There were no significant differences in objectively measured or self-reported baseline PA between risk and nonrisk carriers. A total of 807 (72.05%) of the participants out of 1120 in the personalized groups were encouraged to increase PA at baseline. Knowledge of FTO risk had no impact on PA in either risk or nonrisk carriers after the 6-month intervention. Attrition was higher in nonrisk participants for whom genotype was disclosed (P=.01) compared with their at-risk counterparts. Conclusions: No association between baseline PA and FTO risk genotype was observed. There was no added benefit of disclosing FTO risk on changes in PA in this personalized intervention. Further RCT studies are warranted to confirm whether disclosure of nonrisk genetic test results has adverse effects on engagement in behavior change.
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Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor quality articles and should be removed from the database. The aim of this study is to classify the articles of Wikipedia into two classes class 0 (poor quality) and class 1(good quality) using the Adaptive Neuro Fuzzy Inference System (ANFIS) and data mining techniques. Two ANFIS are built using the Fuzzy Logic Toolbox [1] available in Matlab. The first ANFIS is based on the rules obtained from J48 classifier in WEKA while the other one was built by using the expert’s knowledge. The data used for this research work contains 226 article’s records taken from the German version of Wikipedia. The dataset consists of 19 inputs and one output. The data was preprocessed to remove any similar attributes. The input variables are related to the editors, contributors, length of articles and the lifecycle of articles. In the end analysis of different methods implemented in this research is made to analyze the performance of each classification method used.
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O propósito deste texto é discutir a avaliação de um curso superior oferecido por uma universidade sueca. Para tanto, parti de uma análise das avaliações feitas pelos estudantes, no ano de 2011-2012, quanto ao conteúdo, as aulas ministrada e a relação estabelecida entre o professor e os estudantes. O curso analisado foi o de Brasil Contemporâneo, da Universidade de Dalarna. O curso é oferecido na forma EBW e faz parte da graduação em Português. As conclusões alcançadas e fundamentadas na análise do questionários apontam para uma necessidade de uma sistematização do conteúdo e de uma melhor exposição do mesmo. Os estudantes, na sua maoria estrangeiros, têm uma percepção sobre a realidade brasileira que ao se contrapor à literatura do curso leva-os a reverem e a redefinirem a imagem que os mesmos tinham sobre o Brasil. Entrentanto, as avaliações apontam para a necessidade de desenvolvimento e formento de trabalhos em grupos que auxiliam na aprendizagem dos estudantes. Esta é um importante desáfio dos cursos baseados na Web, na rede de ensino superior sueca.
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Background: A test battery consisting of self-assessments and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting. Objectives: To develop and evaluate a web-based system that delivers decision support information to the treating clinical staff for assessing PD symptoms in their patients based on the test battery data. Methods: The test battery is currently being used in a clinical trial (DAPHNE, EudraCT No. 2005-002654-21) by sixty five patients with advanced Parkinson’s disease (PD) on 9991 test occasions (four tests per day during in all 362 week-long test periods) at nine clinics around Sweden. Test results are sent continuously from the hand unit over a mobile net to a central computer and processed with statistical methods. They are summarized into scores for different dimensions of the symptom state and an ‘overall test score’ reflecting the overall condition of the patient during a test period. The information in the web application is organized and presented graphically in a way that the general overview of the patient performance per test period is emphasized. Focus is on the overall test score, symptom dimensions and daily summaries. In a recent preliminary user evaluation, the web application was demonstrated to the fifteen study nurses who had used the test battery in the clinical trial. At least one patient per clinic was shown. Results: In general, the responses from nurses were positive. They claimed that the test results shown in the system were consistent with their own clinical observations. They could follow complications, changes and trends within their patients. Discussion: In conclusion, the system is able to summarise the various time series of motor test results and self-assessments during test periods and present them in a useful manner. Its main contribution is a novel and reliable way to capture and easily access symptom information from patients’ home environment. The convenient access to current symptom profile as well as symptom history provides a basis for individualized evaluation and adjustment of treatments.
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Objective: To investigate whether advanced visualizations of spirography-based objective measures are useful in differentiating drug-related motor dysfunctions between Off and dyskinesia in Parkinson’s disease (PD). Background: During the course of a 3 year longitudinal clinical study, in total 65 patients (43 males and 22 females with mean age of 65) with advanced PD and 10 healthy elderly (HE) subjects (5 males and 5 females with mean age of 61) were assessed. Both patients and HE subjects performed repeated and time-stamped assessments of their objective health indicators using a test battery implemented on a telemetry touch screen handheld computer, in their home environment settings. Among other tasks, the subjects were asked to trace a pre-drawn Archimedes spiral using the dominant hand and repeat the test three times per test occasion. Methods: A web-based framework was developed to enable a visual exploration of relevant spirography-based kinematic features by clinicians so they can in turn evaluate the motor states of the patients i.e. Off and dyskinesia. The system uses different visualization techniques such as time series plots, animation, and interaction and organizes them into different views to aid clinicians in measuring spatial and time-dependent irregularities that could be associated with the motor states. Along with the animation view, the system displays two time series plots for representing drawing speed (blue line) and displacement from ideal trajectory (orange line). The views are coordinated and linked i.e. user interactions in one of the views will be reflected in other views. For instance, when the user points in one of the pixels in the spiral view, the circle size of the underlying pixel increases and a vertical line appears in the time series views to depict the corresponding position. In addition, in order to enable clinicians to observe erratic movements more clearly and thus improve the detection of irregularities, the system displays a color-map which gives an idea of the longevity of the spirography task. Figure 2 shows single randomly selected spirals drawn by a: A) patient who experienced dyskinesias, B) HE subject, and C) patient in Off state. Results: According to a domain expert (DN), the spirals drawn in the Off and dyskinesia motor states are characterized by different spatial and time features. For instance, the spiral shown in Fig. 2A was drawn by a patient who showed symptoms of dyskinesia; the drawing speed was relatively high (cf. blue-colored time series plot and the short timestamp scale in the x axis) and the spatial displacement was high (cf. orange-colored time series plot) associated with smooth deviations as a result of uncontrollable movements. The patient also exhibited low amount of hesitation which could be reflected both in the animation of the spiral as well as time series plots. In contrast, the patient who was in the Off state exhibited different kinematic features, as shown in Fig. 2C. In the case of spirals drawn by a HE subject, there was a great precision during the drawing process as well as unchanging levels of time-dependent features over the test trial, as seen in Fig. 2B. Conclusions: Visualizing spirography-based objective measures enables identification of trends and patterns of drug-related motor dysfunctions at the patient’s individual level. Dynamic access of visualized motor tests may be useful during the evaluation of drug-related complications such as under- and over-medications, providing decision support to clinicians during evaluation of treatment effects as well as improve the quality of life of patients and their caregivers. In future, we plan to evaluate the proposed approach by assessing within- and between-clinician variability in ratings in order to determine its actual usefulness and then use these ratings as target outcomes in supervised machine learning, similarly as it was previously done in the study performed by Memedi et al. (2013).
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Background qtl.outbred is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/qtl. Findings Using qtl.outbred, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL. Conclusion qtl.outbred will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.
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This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.
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Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic. The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.
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Neste trabalho, é realizado um estudo dos processos de avaliação de alunos em ambiente WBT (Web Based Training). Para tanto, foram analisadas várias ferramentas de avaliação disponíveis no mercado. Com base nestas análises, foi proposto um sistema de gerência de questões e aplicação de avaliações, onde o termo “gerência” é utilizado com o objetivo de (i) atender requisições dos professores para elaboração de avaliações, (ii) escolher o nível de dificuldade das questões que comporão a avaliação e (iii) usar estratégias interativas para aplicação de provas, como por exemplo, a utilização de níveis de dificuldade progressivos das questões submetidas aos alunos, dependendo de suas respostas anteriores. Integrando o sistema de gerência de questões foi proposto um módulo de auto-avaliações, com retorno imediato para o aluno sobre qual é a resposta correta juntamente com uma explicação do professor, auxiliando no entendimento do estudante sobre a matéria ao invés de simplesmente atribuir determinada nota. Enfim, foi implementado um protótipo demonstrando a viabilidade das idéias presentes no modelo de avaliação aqui proposto. A proposta conceitual estabelecida para o modelo é bem mais ampla e flexível do que a atual versão da implementação realizada.
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This paper describes the development of a multimedia educational system to teach and learn robotic systems. Multimedia resources have been used to build a virtual laboratory where users are able to utilize functions of a robotic arm, by moving and clicking the mouse without worrying about the detailed robot internal operation. The multimedia system is integrated with a real robotic arm, which was also developed at the university. Through robotic topic presentations and interactive capabilities provided by this system and its tools, students can devote themselves on the learning process just as they do in the traditional face-to-face classes. and the target public of this system are the engineering students themselves.