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The Global ETD Search service is a free service for researchers
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Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 61 to 70 of 70 (0.03 seconds)Spelling suggestions: "subject:"data tet"" "subject:"data feet""
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The teaching practice of senior phase technology education teachers in selected schools of Limpopo Province : an action research studyMapotse, Tomé Awshar 08 1900 (has links)
This is an Action Research (AR) study with the senior phase Technology teachers at selected schools of Limpopo Province. The study was motivated by the fact that Technology Education is a foreign concept to many teachers and a new learning area in school curriculum both nationally and internationally. This was exacerbated by the many educational changes that took place in South Africa in the last 18 years. These changes include the overhauling of curriculum, which was the strategic and symbolic change since the first democratic election of 1994, but followed by its review. Thus, a new curriculum known as Curriculum 2005 (reviewed twice already) was developed in which Technology was introduced as a new subject. These changes drastically affected Technology Education and teachers’ coping demands on both the subject content and pedagogy escalated. In this study, AR, a strategy for a systematic, objective investigation with Technology teachers’ who are un- and under- qualified to teach Technology was considered. The study aimed at establishing intervention strategies to empower and emancipate senior phase Technology teachers in Mankweng Circuit from the said challenges above. Thus, the study sought to address the question: How could action research intervention be used to improve the teaching of senior phase Technology teachers who are un- and/or under-qualified? The intervention strategies were implemented through the AR cycles in spiral activities of planning, implementation and observation, action and reflection, whose principles were operationalized to develop participants from the situations that they face in their Technology teaching contexts.
The study was designed from both critical theory perspective and participatory paradigm. The following instruments were used as a means to gather data: observations, interviews, questionnaires, field notes, video recording of lesson plans and logs of meetings. The study managed to come up with guidelines to develop and kick start AR with teachers. From the
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findings an AR model was developed to emancipate the un- and under-qualified Technology teachers. Themes from the challenges and AR were used to draft a six weeks plan to empower incapacitated Technology teachers. This investigation was shaped by the initial reflection or preliminary study conducted with the participants called reconnaissance study which revealed specific challenges that Technology teachers encountered daily in their classes. These challenges were turned into the themes, which together with the findings from the preliminary study and interview reflection per cycle were used to design the intervention strategies for the next main cycle. The findings of the study from both the preliminary investigation (presented in Chapter Two) and main AR (presented in Chapter Five) reveal an improvement in the teachers’ understanding and implementation of Technology – they were emancipated to a greater extent from the challenges prior to the AR intervention and post the AR intervention. It is true that coming together as AR co-researchers was the beginning of Technology teaching practice problem identification; keeping together was progressive in Technology teaching; but working together remains our success in Technology teaching then, now and in the future – post doctoral studies. / Curriculum and Instructional Studies / D. Ed. (Curriculum Studies)
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Analýza klasifikačních metod / Analysis of Classification MethodsJuríček, Jakub January 2019 (has links)
This work deals with the classification methods used in the knowledge discovery from data process and discusses the possibilities of their validation and comparison. Through experiments, the work focuses on the analysis of four selected methods: Naive Bayes classificator, decision tree, neural network and SVM. Factors influencing basic characteristics such as training speed, classification speed, accuracy are examined. A part of the thesis is a desktop application, which is a tool for training, testing and validation of individual methods. Eleven reference data sets are selected for experimental purposes. At the end of this work experimental results of comparison and observed characteristics of classification methods are summarized.
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Detekce dopravních značek a semaforů / Detection of Traffic Signs and LightsOškera, Jan January 2020 (has links)
The thesis focuses on modern methods of traffic sign detection and traffic lights detection directly in traffic and with use of back analysis. The main subject is convolutional neural networks (CNN). The solution is using convolutional neural networks of YOLO type. The main goal of this thesis is to achieve the greatest possible optimization of speed and accuracy of models. Examines suitable datasets. A number of datasets are used for training and testing. These are composed of real and synthetic data sets. For training and testing, the data were preprocessed using the Yolo mark tool. The training of the model was carried out at a computer center belonging to the virtual organization MetaCentrum VO. Due to the quantifiable evaluation of the detector quality, a program was created statistically and graphically showing its success with use of ROC curve and evaluation protocol COCO. In this thesis I created a model that achieved a success average rate of up to 81 %. The thesis shows the best choice of threshold across versions, sizes and IoU. Extension for mobile phones in TensorFlow Lite and Flutter have also been created.
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A data-driven discrete elastic rod model for shells and solidsPatarroyo, Keith Y. 12 1900 (has links)
Les structures en forme de tige sont omniprésentes dans le monde aujourd'hui. Désormais, prédire avec précision leur comportement pour l'ingénierie et les environnements virtuels est indispensable pour de nombreuses industries, notamment l'infographie, l'animation par ordinateur et la conception informatique. Dans ce mémoire, nous explorons un nouveau modèle de calcul pour les tiges élastiques qui exploite les données de simulation pour reproduire les effets de coque et de solide présents dans les tiges qui brisent les hypothèses de la théorie classique de la tige de Kirchhoff, présentant ainsi une voie d'amélioration possible pour de nombreux états de l'art techniques.
Notre approche consiste à prendre un ensemble de données de simulations à partir de solides volumétriques ou de coques pour former un nouveau modèle d'énergie définie positive polynomiale d'ordre élevé pour une tige élastique. Cette nouvelle énergie élargit la gamme des comportements des matériaux qui peuvent être modélisés pour la tige, permettant ainsi de capturer une plus large gamme de phénomènes. Afin de proposer et tester ce modèle, nous concevons un pipeline expérimental pour tester les limites de la théorie linéaire des tiges et étudier les géométries d'interface entre les cas coque à tige et volume à coque pour observer les effets d'un modèle de matériau non linéaire et une section transversale non elliptique dans la déformation de la tige. Nous étudions également la relation entre la courbure de la tige et la déformation de la section transversale et la courbure pour introduire une modification sur le terme de flexion de l'énergie. Cela nous permet de reproduire à la fois le comportement de flexion asymétrique présent dans les poutres volumétriques minces et les poutres à coque avec des sections transversales non convexes. Des suggestions pour de nouvelles améliorations des modèles et des techniques expérimentales sont également données. / Rod-like structures are ubiquitous in the world today. Henceforth accurately predicting their behavior for engineering and virtual environments are indispensable for many industries including computer graphics, computer animation, and computational design. In this thesis we explore a new computational model for elastic rods that leverages simulation data to reproduce shell and solid-like effects present in rods that break the assumptions of the classical Kirchhoff rod theory, thus presenting a possible improvement avenue to many states-of-the-art techniques.
Our approach consists of taking a data set of simulations from both volumetric solids or shells to train a novel high-order polynomial positive-definite energy model for an elastic rod. This new energy increases the range of material behaviors that can be modeled for the rod, thus allowing for a larger range of phenomena to be captured. In order to propose and test this model, we design an experimental pipeline to test the limits of the linear theory of rods and investigate the interface geometries between the Shell-Rod and Volume-Shell cases to observe the effects of a nonlinear material model and a non-elliptical cross-section in the rod deformation. We also investigate the relation between rod curvature and deformation of the cross-section and curvature to introduce a modification on the bending term of the energy. This allows us to reproduce both the asymmetric bending behavior present in thin volumetric solid and shell beams with non-convex cross-sections. Suggestions for further improvements in models and experimental techniques are also given.
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Анализ корневых причин (RCA) возникновения инцидента методами машинного обучения : магистерская диссертация / Root cause analysis (RCA) of an incident using machine learning methodsПодлягин, А. В., Podlyagin, A. V. January 2023 (has links)
Объект исследования – кибер-физические системы, подверженные различным инцидентам, отказам и сбоям в своей работе. Цель работы – разработка модели машинного обучения для определения корневых причин сбоев в производственной системе, а также исследование возможности использования машинного обучения для определения причин будущих сбоев. Методы исследования: сбор, анализ и синтез данных, сравнение, обобщение, классификация, аналогия, эксперимент, измерение, описание. Результаты работы: разработана и обучена модель машинного обучения для анализа корневых причин инцидентов производственной установки методом классификации на выбранном наборе «сырых» данных небольшого объема с последующей проверкой качества ее работы на тестовых данных. Область применения – обучение модели корневым причинам инцидентов (отказов, сбоев) производственных систем на имеющихся данных с последующим оперативным обнаружением причин аномальной работы систем в тандеме с работой алгоритма по автоматическому обнаружению и прогнозированию аномалий. / The object of research is cyber-physical systems that are susceptible to various incidents, failures and malfunctions in their operation. The goal of the work is to develop a machine learning model to determine the root causes of failures in a production system, as well as to explore the possibility of using machine learning to determine the causes of future failures. Research methods: collection, analysis and synthesis of data, comparison, generalization, classification, analogy, experiment, measurement, description. Results of the work: a machine learning model was developed and trained to analyze the root causes of incidents in a production facility using the classification method on a selected set of small-volume “raw” data, followed by checking the quality of its work on test data. Scope of application: training a model for the root causes of incidents (failures, failures) of production systems using available data, followed by prompt detection of the causes of abnormal operation of systems in tandem with the work of the algorithm for automatic detection and prediction of anomalies.
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Exploring the understanding of routinely collected data by the health practitioners in a primary health care settingMolefi, Zachariah Modise 11 1900 (has links)
Health practitioners collect health data on a daily basis at health facility levels in order to monitor and evaluate the performance of priority national health programmes (District Health Plan 2012:6). Routine data quality for health programmes monitoring need a collective intervention to ensure clear understanding for what data to be collected at primary health care setting. The aim of the study is to explore the understanding of routine health data, determine the use of routine data and feedback mechanism at primary health care clinic setting. Quantitative descriptive research design was used to answer the research question on this research study. Structured data collection questionnaire was used for the study to accomplish the research purpose and reach the study objectives. A total of 400 participants was sampled, and 247 responded. One of the findings was that the understanding of routine health data by Health Practitioners was at 82.6% (% = f/n*100, f= 3242 and n= 3926). / Health Studies
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Exploring the understanding of routinely collected data by the health practitioners in a primary health care settingMolefi, Zachariah Modise 11 1900 (has links)
Health practitioners collect health data on a daily basis at health facility levels in order to monitor and evaluate the performance of priority national health programmes (District Health Plan 2012:6). Routine data quality for health programmes monitoring need a collective intervention to ensure clear understanding for what data to be collected at primary health care setting. The aim of the study is to explore the understanding of routine health data, determine the use of routine data and feedback mechanism at primary health care clinic setting. Quantitative descriptive research design was used to answer the research question on this research study. Structured data collection questionnaire was used for the study to accomplish the research purpose and reach the study objectives. A total of 400 participants was sampled, and 247 responded. One of the findings was that the understanding of routine health data by Health Practitioners was at 82.6% (% = f/n*100, f= 3242 and n= 3926). / Health Studies
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Enhanching the Human-Team Awareness of a RobotWåhlin, Peter January 2012 (has links)
The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot. / Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot. / <p>The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.</p>
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教育システムの動態分析のための指標開発とデータベース作成潮木, 守一, 菊池, 城司, 矢野, 真和, 藤田, 英典 03 1900 (has links)
科学研究費補助金 研究種目:試験研究(2) 課題番号:59810007 研究代表者:潮木 守一 研究期間:1984－1986年度
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Automatic classification of cardiovascular age of healthy people by dynamical patterns of the heart rhythmkurian pullolickal, priya January 2022 (has links)
No description available.
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