Dissertations / Theses on the topic 'Theory of applied learning of competencivism'
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Mauricio, Palacio Sebastián. "Machine-Learning Applied Methods." Doctoral thesis, Universitat de Barcelona, 2020. http://hdl.handle.net/10803/669286.
Full textZhang, Yue. "Sparsity in Image Processing and Machine Learning: Modeling, Computation and Theory." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1523017795312546.
Full textAndersson, Carl. "Deep learning applied to system identification : A probabilistic approach." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-397563.
Full textMouton, Hildegarde Suzanne. "Reinforcement learning : theory, methods and application to decision support systems." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/5304.
Full textENGLISH ABSTRACT: In this dissertation we study the machine learning subfield of Reinforcement Learning (RL). After developing a coherent background, we apply a Monte Carlo (MC) control algorithm with exploring starts (MCES), as well as an off-policy Temporal-Difference (TD) learning control algorithm, Q-learning, to a simplified version of the Weapon Assignment (WA) problem. For the MCES control algorithm, a discount parameter of τ = 1 is used. This gives very promising results when applied to 7 × 7 grids, as well as 71 × 71 grids. The same discount parameter cannot be applied to the Q-learning algorithm, as it causes the Q-values to diverge. We take a greedy approach, setting ε = 0, and vary the learning rate (α ) and the discount parameter (τ). Experimentation shows that the best results are found with set to 0.1 and constrained in the region 0.4 ≤ τ ≤ 0.7. The MC control algorithm with exploring starts gives promising results when applied to the WA problem. It performs significantly better than the off-policy TD algorithm, Q-learning, even though it is almost twice as slow. The modern battlefield is a fast paced, information rich environment, where discovery of intent, situation awareness and the rapid evolution of concepts of operation and doctrine are critical success factors. Combining the techniques investigated and tested in this work with other techniques in Artificial Intelligence (AI) and modern computational techniques may hold the key to solving some of the problems we now face in warfare.
AFRIKAANSE OPSOMMING: Die fokus van hierdie verhandeling is die masjienleer-algoritmes in die veld van versterkingsleer. ’n Koherente agtergrond van die veld word gevolg deur die toepassing van ’n Monte Carlo (MC) beheer-algoritme met ondersoekende begintoestande, sowel as ’n afbeleid Temporale-Verskil beheer-algoritme, Q-leer, op ’n vereenvoudigde weergawe van die wapentoekenningsprobleem. Vir die MC beheer-algoritme word ’n afslagparameter van τ = 1 gebruik. Dit lewer belowende resultate wanneer toegepas op 7 × 7 roosters, asook op 71 × 71 roosters. Dieselfde afslagparameter kan nie op die Q-leer algoritme toegepas word nie, aangesien dit veroorsaak dat die Q-waardes divergeer. Ons neem ’n gulsige aanslag deur die gulsigheidsparameter te verstel na ε = 0. Ons varieer dan die leertempo ( α) en die afslagparameter (τ). Die beste eksperimentele resultate is behaal wanneer = 0.1 en as die afslagparameter vasgehou word in die gebied 0.4 ≤ τ ≤ 0.7. Die MC beheer-algoritme lewer belowende resultate wanneer toegepas op die wapentoekenningsprobleem. Dit lewer beduidend beter resultate as die Q-leer algoritme, al neem dit omtrent twee keer so lank om uit te voer. Die moderne slagveld is ’n omgewing ryk aan inligting, waar dit kritiek belangrik is om vinnig die vyand se planne te verstaan, om bedag te wees op die omgewing en die konteks van gebeure, en waar die snelle ontwikkeling van die konsepte van operasie en doktrine lei tot sukses. Die tegniekes wat in die verhandeling ondersoek en getoets is, en ander kunsmatige intelligensie tegnieke en moderne berekeningstegnieke saamgesnoer, mag dalk die sleutel hou tot die oplossing van die probleme wat ons tans in die gesig staar in oorlogvoering.
Grieve, Susan M. "Cognitive Load Theory Principles Applied to Simulation Instructional Design for Novice Health Professional Learners." Diss., NSUWorks, 2019. https://nsuworks.nova.edu/hpd_pt_stuetd/78.
Full textChim, Tat-mei Alice, and 詹達美. "An instructional design theory guide for blended learning courses." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30406213.
Full textHu, Qiao Ph D. Massachusetts Institute of Technology. "Application of statistical learning theory to plankton image analysis." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/39206.
Full textIncludes bibliographical references (leaves 155-173).
A fundamental problem in limnology and oceanography is the inability to quickly identify and map distributions of plankton. This thesis addresses the problem by applying statistical machine learning to video images collected by an optical sampler, the Video Plankton Recorder (VPR). The research is focused on development of a real-time automatic plankton recognition system to estimate plankton abundance. The system includes four major components: pattern representation/feature measurement, feature extraction/selection, classification, and abundance estimation. After an extensive study on a traditional learning vector quantization (LVQ) neural network (NN) classifier built on shape-based features and different pattern representation methods, I developed a classification system combined multi-scale cooccurrence matrices feature with support vector machine classifier. This new method outperforms the traditional shape-based-NN classifier method by 12% in classification accuracy. Subsequent plankton abundance estimates are improved in the regions of low relative abundance by more than 50%. Both the NN and SVM classifiers have no rejection metrics. In this thesis, two rejection metrics were developed.
(cont.) One was based on the Euclidean distance in the feature space for NN classifier. The other used dual classifier (NN and SVM) voting as output. Using the dual-classification method alone yields almost as good abundance estimation as human labeling on a test-bed of real world data. However, the distance rejection metric for NN classifier might be more useful when the training samples are not "good" ie, representative of the field data. In summary, this thesis advances the current state-of-the-art plankton recognition system by demonstrating multi-scale texture-based features are more suitable for classifying field-collected images. The system was verified on a very large real-world dataset in systematic way for the first time. The accomplishments include developing a multi-scale occurrence matrices and support vector machine system, a dual-classification system, automatic correction in abundance estimation, and ability to get accurate abundance estimation from real-time automatic classification. The methods developed are generic and are likely to work on range of other image classification applications.
by Qiao Hu.
Ph.D.
Shi, Bin. "A Mathematical Framework on Machine Learning: Theory and Application." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3876.
Full textYoungleson, Penelope. "Flourishing in fragility: how to build antifragile ecosystems of learning, that nurture healthy vulnerability, in fragile environments in the Western Cape (South Africa) with at-risk learners." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/32352.
Full textOpdenbosch, Patrick. "Auto-Calibration and Control Applied to Electro-Hydraulic Poppet Valves." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19758.
Full textYu, Shen. "A Bayesian machine learning system for recognizing group behaviour." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:8881/R/?func=dbin-jump-full&object_id=32565.
Full textGard, Rikard. "Design-based and Model-assisted estimators using Machine learning methods : Exploring the k-Nearest Neighbor metod applied to data from the Recreational Fishing Survey." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-72488.
Full textRumantir, Grace Widjaja. "Minimum message length criterion for second-order polynomial model selection applied to tropical cyclone intensity forecasting." Monash University, School of Computer Science and Software Engineering, 2003. http://arrow.monash.edu.au/hdl/1959.1/5813.
Full textAgerberg, Jens. "Statistical Learning and Analysis on Homology-Based Features." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273581.
Full textStable rank har föreslagits som en sammanfattning på datanivå av resultatet av persistent homology, en metod inom topologisk dataanalys. I detta examensarbete utvecklar vi metoder inom statistisk analys och maskininlärning baserade på stable rank. Eftersom stable rank kan ses som en avbildning i ett Hilbertrum kan en kärna konstrueras från inre produkten i detta rum. Först undersöker vi denna kärnas egenskaper när den används inom ramen för maskininlärningsmetoder som stödvektormaskin (SVM). Därefter, med grund i teorin för inbäddning av sannolikhetsfördelningar i reproducing kernel Hilbertrum, undersöker vi hur kärnan kan användas för att utveckla ett test för statistisk hypotesprövning. Slutligen, som ett alternativ till metoder baserade på kärnor, utvecklas en avbildning i ett euklidiskt rum med optimerbara parametrar, som kan användas som ett ingångslager i ett neuralt nätverk. Metoderna utvärderas först på syntetisk data. Vidare utförs ett statistiskt test på OASIS, ett öppet dataset inom neuroradiologi. Slutligen utvärderas metoderna på klassificering av grafer, baserat på ett dataset insamlat från Reddit.
QC 20200523
Abbas, Kaja Moinudeen. "Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5302/.
Full textDanielson, Jared Andrew. "The Design, Development and Evaluation of a Web-based Tool for Helping Veterinary Students Learn How to Classify Clinical Laboratory Data." Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/28511.
Full textPh. D.
Liu, Yukang. "Virtualized Welding Based Learning of Human Welder Behaviors for Intelligent Robotic Welding." UKnowledge, 2014. http://uknowledge.uky.edu/ece_etds/51.
Full textLindahl, Fred. "Detection of Sparse and Weak Effects in High-Dimensional Supervised Learning Problems, Applied to Human Microbiome Data." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288503.
Full textDetta projekt studerar signaldetekterings- och identifieringsproblemet i högdimensionell brusig data och möjligheten att använda det på mikrobiomdata från människor. En omfattande simuleringsstudie utfördes på genererad data samt ett mikrobiomdataset som samlats in på patienter med Parkinsons sjukdom, med hjälp av ett antal goodness-of-fit-metoder: Donoho och Jins Higher criticis , Jager och Wellners phi-divergenser och Stepanova och Pavelenkos CsCsHM. Vi presenterar några nya tillvägagångssätt baserade på vedertagen teori som visar sig fungera bättre än befintliga metoder och visar att det är möjligt att använda signalidentifiering för att upptäcka olika funktioner i mikrobiomdata. Även om de nya metoderna ger goda resultat saknar de betydande matematiska grunder och bör undvikas om teoretisk formalism är nödvändigt. Vi drar också slutsatsen att medan vi har funnit att det är möjligt att använda signalidentifieringsmetoder för att hitta information i mikrobiomdata, är ytterligare experiment nödvändiga innan de kan användas på ett korrekt sätt i forskning.
Grady, Daniel J. "A Critical Review of the Application of Kolb?s Experiential Learning Theory Applied Through the use of Computer Based Simulations Within Virtual Environments 2000-2016." Thesis, State University of New York at Albany, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10282034.
Full textThis integrative research review aims to examine the application of Kolb’s theory of experiential learning through the use of simulations within virtual learning environments. It will first cover the framework of experiential learning as stated by Kolb, a learning theory that is finding new life within the context of simulations, role-playing games (RPGs), massive multiplayer role playing games (MMORPGs) and virtual environments. This analysis was conducted by making use of combined research strategies that focused specifically on both qualitative and quantitative reviews that utilized Kolb’s experiential theory of learning (ELT) within the context of the application of computer based simulations in virtual environments used to facilitate learning. The review was guided by three principle questions: From the year 2000 to 2016, which research studies that examine the use of simulations to facilitate learning, use experiential learning theory as its foundational theoretical approach? Of the works that were selected, which studies were computer based simulations in virtual environments and demonstrated firm connections between Kolb’s ELT and the results of the study? And lastly, within the final group of studies identified what patterns emerge through the application of Kolb’s ELT within the context of computer based simulations in virtual environments?
Pastorek, Lukáš. "Bio-Inspired Prototype-Based Models and Applied Gompertzian Dynamics in Cluster Analysis." Doctoral thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-200218.
Full textElentari, Aruna. "Evaluating the effect of the Sensavis visual learning tool on student performance in a Swedish elementary school." Thesis, Umeå universitet, Institutionen för psykologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136302.
Full textEnligt “dual coding theory” hjälper det att kombinera flera sätt att inta information (t.ex. visuellt, verbalt) inom lärandet. Presentation av information genom 3D-bilder och 3D-animationer verkar förbättra prestation bland elever, men resultaten är inkonsekventa i flera studier. Denna studie undersökte effekten av ett visuellt verktyg från Sensavis, en pedagogisk programvara med 3D-animationer, på prestation inom kemi bland elever i en svensk grundskola. Trettiosju elever från årskurs 7 och 9 använde en 3D-animering om kemisk bindning förutom föreläsningar, medan nitton elever i årskurs 8 fick traditionell undervisning. ANCOVA-resultat som kontrollerade för ålder och kemibetyg visade att kontrollgruppen presterade bättre än bägge experimentgrupperna. Dessa resultat tyder på att Sensavis-verktyget inte hade en positiv effekt på lärande i kemi jämfört med traditionell undervisning. Tolkningen av resultaten presenteras i diskussion.
Brückner, Michael. "Prediction games : machine learning in the presence of an adversary." Phd thesis, Universität Potsdam, 2012. http://opus.kobv.de/ubp/volltexte/2012/6037/.
Full textEine der Aufgabenstellungen des Maschinellen Lernens ist die Konstruktion von Vorhersagemodellen basierend auf gegebenen Trainingsdaten. Ein solches Modell beschreibt den Zusammenhang zwischen einem Eingabedatum, wie beispielsweise einer E-Mail, und einer Zielgröße; zum Beispiel, ob die E-Mail durch den Empfänger als erwünscht oder unerwünscht empfunden wird. Dabei ist entscheidend, dass ein gelerntes Vorhersagemodell auch die Zielgrößen zuvor unbeobachteter Testdaten korrekt vorhersagt. Die Mehrzahl existierender Lernverfahren wurde unter der Annahme entwickelt, dass Trainings- und Testdaten derselben Wahrscheinlichkeitsverteilung unterliegen. Insbesondere in Fällen in welchen zukünftige Daten von der Wahl des Vorhersagemodells abhängen, ist diese Annahme jedoch verletzt. Ein Beispiel hierfür ist das automatische Filtern von Spam-E-Mails durch E-Mail-Anbieter. Diese konstruieren Spam-Filter basierend auf zuvor empfangenen E-Mails. Die Spam-Sender verändern daraufhin den Inhalt und die Gestaltung der zukünftigen Spam-E-Mails mit dem Ziel, dass diese durch die Filter möglichst nicht erkannt werden. Bisherige Arbeiten zu diesem Thema beschränken sich auf das Lernen robuster Vorhersagemodelle welche unempfindlich gegenüber geringen Veränderungen des datengenerierenden Prozesses sind. Die Modelle werden dabei unter der Worst-Case-Annahme konstruiert, dass diese Veränderungen einen maximal negativen Effekt auf die Vorhersagequalität des Modells haben. Diese Modellierung beschreibt die tatsächliche Wechselwirkung zwischen der Modellbildung und der Generierung zukünftiger Daten nur ungenügend. Aus diesem Grund führen wir in dieser Arbeit das Konzept der Prädiktionsspiele ein. Die Modellbildung wird dabei als mathematisches Spiel zwischen einer lernenden und einer datengenerierenden Instanz beschrieben. Die spieltheoretische Modellierung ermöglicht es uns, die Interaktion der beiden Parteien exakt zu beschreiben. Dies umfasst die jeweils verfolgten Ziele, ihre Handlungsmöglichkeiten, ihr Wissen übereinander und die zeitliche Reihenfolge, in der sie agieren. Insbesondere die Reihenfolge der Spielzüge hat einen entscheidenden Einfluss auf die spieltheoretisch optimale Lösung. Wir betrachten zunächst den Fall gleichzeitig agierender Spieler, in welchem sowohl der Lerner als auch der Datengenerierer keine Kenntnis über die Aktion des jeweils anderen Spielers haben. Wir leiten hinreichende Bedingungen her, unter welchen dieses Spiel eine Lösung in Form eines eindeutigen Nash-Gleichgewichts besitzt. Im Anschluss diskutieren wir zwei verschiedene Verfahren zur effizienten Berechnung dieses Gleichgewichts. Als zweites betrachten wir den Fall eines Stackelberg-Duopols. In diesem Prädiktionsspiel wählt der Lerner zunächst das Vorhersagemodell, woraufhin der Datengenerierer in voller Kenntnis des Modells reagiert. Wir leiten ein relaxiertes Optimierungsproblem zur Bestimmung des Stackelberg-Gleichgewichts her und stellen ein mögliches Lösungsverfahren vor. Darüber hinaus diskutieren wir, inwieweit das Stackelberg-Modell bestehende robuste Lernverfahren verallgemeinert. Abschließend untersuchen wir einen Lerner, der auf die Aktion des Datengenerierers, d.h. der Wahl der Testdaten, reagiert. In diesem Fall sind die Testdaten dem Lerner zum Zeitpunkt der Modellbildung bekannt und können in den Lernprozess einfließen. Allerdings unterliegen die Trainings- und Testdaten nicht notwendigerweise der gleichen Verteilung. Wir leiten daher ein neues integriertes sowie ein zweistufiges Lernverfahren her, welche diese Verteilungsverschiebung bei der Modellbildung berücksichtigen. In mehreren Fallstudien zur Klassifikation von Spam-E-Mails untersuchen wir alle hergeleiteten, sowie existierende Verfahren empirisch. Wir zeigen, dass die hergeleiteten spieltheoretisch-motivierten Lernverfahren in Summe signifikant bessere Spam-Filter erzeugen als alle betrachteten Referenzverfahren.
Van, Heerden Thomas. "A cultural-historical activity theory based analysis of lecturer and student understanding of learning in the Department of Mathematics and Applied Mathematics at the University of Cape Town." Master's thesis, Faculty of Humanities, 2019. http://hdl.handle.net/11427/30135.
Full textFuglesang, Rutger. "Particle-Based Online Bayesian Learning of Static Parameters with Application to Mixture Models." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279847.
Full textDetta examensarbete undersöker möjligheten att använda Sekventiella Monte Carlo metoder (SMC) för att utveckla en algoritm med syfte att utvinna parametrar i realtid givet en okänd modell. Då statistisk slutledning från dataströmmar medför svårigheter, särskilt i parameter-modeller, kommer arbetets fokus ligga i utvecklandet av en Monte Carlo algoritm vars uppgift är att sekvensiellt nyttja modellens posteriori fördelningar. Resultatet är att okända, statistiska parametrar kommer att förflyttas mot det krympande stödet av posterioren med hjälp utav en artificiell Markov dynamik, vilket tillåter en korrekt pseudo-marginalisering utav mål-distributionen. Algoritmen kommer sedan att testas på en enkel Gaussisk-modell, en Gaussisk mixturmodell (GMM) och till sist en GMM vars dimension är okänd. Kodningen i detta projekt har utförts i Matlab.
Samuelsson, Emma. "Using activity theory to describe patient safety : How Region Östergötland supports patient safety development in a low and middle-income country’s healthcare system." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-170095.
Full textSuta, Adin. "Multilabel text classification of public procurements using deep learning intent detection." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252558.
Full textData i form av text är en av de mest utbredda formerna av data och mängden tillgänglig textdata runt om i världen ökar i snabb takt. Text kan tolkas som en följd av bokstäver eller ord, där tolkning av text i form av ordföljder är absolut vanligast. Genombrott inom artificiell intelligens under de senaste åren har medfört att fler och fler arbetsuppgifter med koppling till text assisteras av automatisk textbearbetning. Modellerna som introduceras i denna uppsats är baserade på djupa artificiella neuronnät med sekventiell bearbetning av textdata, som med hjälp av regression förutspår tillhörande ämnesområde för den inmatade texten. Flera modeller och tillhörande hyperparametrar utreds och jämförs enligt prestanda. Datamängden som använts är tillhandahållet av e-Avrop, ett svenskt företag som erbjuder en webbtjänst för offentliggörande och budgivning av offentliga upphandlingar. Datamängden består av titlar, beskrivningar samt tillhörande ämneskategorier för offentliga upphandlingar inom Sverige, tagna från e-Avrops webtjänst. När texterna är märkta med ett flertal kategorier, föreslås en algoritm baserad på ett djupt artificiellt neuronnät med sekventiell bearbetning, där en mängd klassificeringsmodeller används. Varje sådan modell använder en av de märkta kategorierna tillsammans med den tillhörande texten, som skapar en mängd av text - kategori par. Målet är att utreda huruvida dessa klassificerare kan uppvisa olika former av uppsåt som teoretiskt sett borde vara medfört från de olika datamängderna modellerna mottagit.
Allbrink, Sofie, and Rebecka Sundin. "INDIVIDUELLA IDROTTARES FÖRUTSÄTTNINGAR FÖR SJÄLVREGLERAT LÄRANDE." Thesis, Umeå universitet, Institutionen för psykologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-183873.
Full textSelf-Regulated Learning (SRL) has proven to be a useful strategy for athletes' learning and development. What conditions are given to athletes from their surrounding environment can both promote and inhibit these processes of learning and development. However, few studies have examined this relationship in a sports context. Thus, the present study aimed to investigate Self-Regulated Learning in individual sports based on self-efficacy, gender and environmental conditions. The environmental conditions were defined as leadership behaviors that promote motivation, according to Self-Determination Theory (SDT), and Self-Regulated Learning. The sample consisted of individual athletes, ranging from 16-60 years, with a coach (N = 251). The athletes competed in 28 different individual sports and identified themselves as women (n = 144), men (n = 106) and other (n = 1). The participants answered the self-report questionnaires Self-Regulated Learning in Sport Practice (SRL-SP), Self-Regulated Environment (SRE) and Interpersonal Supportiveness Scale - Coach (ISS-C). Using multiple and hierarchical regression analyses, this study provided support that self-efficacy positively influenced the outcome measures planning, monitoring, and reflection, but not effort. Gender did not appear to moderate this relationship. The environmental conditions associated with SRL was mainly the coaches' ability to create opportunities for SRL. Additionally, athletes' SRL were negatively influenced by how often the coach was present. The conclusion is that athletes, to beneficially engage in their own development, need to have a belief in their own ability and also be in an environment that enhances opportunities for SRL. However, this relationship is influenced by the coach's presence at practice. Future studies can further examine the relationship between the environmental conditions and SRL, and if the results may differ depending on sport.
Amethier, Patrik, and André Gerbaulet. "Sales Volume Forecasting of Ericsson Radio Units - A Statistical Learning Approach." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288504.
Full textEricsson har en väletablerad intern process för prognostisering av försäljningsvolymer, där produktnära samt kundnära roller samarbetar med inköpsorganisationen för att säkra noggranna uppskattningar angående framtidens efterfrågan. Syftet med denna studie är att evaluera tidigare prognoser, och sedan utveckla en ny prediktiv, statistisk modell som prognostiserar baserad på historisk data. Studien fokuserar på produktkategorin radio, och utvecklar en två-stegsmodell bestående av en trädmodell och ett neuralt nätverk. För att testa hypotesen att en 1-3 års prognos för en produkt kan göras mer noggran med en datadriven modell, tränas modellen på attribut kopplat till produkten, till exempel historiska volymer för produkten, och volymtrender inom produktens marknadsområden och kundgrupper. Detta resulterade i flera prognoser på olika tidshorisonter, nämligen 1-12 månader, 13-24 månader samt 25-36 månder. Majoriteten av wMAPE-felen för dess prognoser visades ligga under 5%, vilket kan jämföras med wMAPE på 9% för Ericssons befintliga 1-årsprognoser, 13% för 2-årsprognerna samt 22% för 3-årsprognoserna. Detta pekar på att datadrivna, statistiska metoder kan användas för att producera gedigna prognoser för framtida försäljningsvolymer, men hänsyn bör tas till jämförelsen mellan de kvalitativa uppskattningarna och de statistiska prognoserna, samt de höga varianserna i felen.
Nilsson, Viktor. "Prediction of Dose Probability Distributions Using Mixture Density Networks." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273610.
Full textUnder de senaste åren har maskininlärning börjat nyttjas i extern strålbehandlingsplanering. Detta involverar automatisk generering av behandlingsplaner baserade på datortomografibilder och annan rumslig information, såsom placering av tumörer och organ. Nyttan ligger i att avlasta klinisk personal från arbetet med manuellt eller halvmanuellt skapa sådana planer. I stället för att predicera en deterministisk plan finns det stort värde att modellera den stokastiskt, det vill säga predicera en sannolikhetsfördelning av dos utifrån datortomografibilder och konturerade biologiska strukturer. Stokasticiteten som förekommer i strålterapibehandlingsproblemet beror på att en rad olika planer kan vara adekvata för en patient. Den särskilda fördelningen kan betraktas som förekomsten av preferenser bland klinisk personal. Att ha mer information om utbudet av möjliga planer representerat i en modell innebär att det finns mer flexibilitet i utformningen av en slutlig plan. Dessutom kommer modellen att kunna återspegla de potentiellt motstridiga kliniska avvägningarna; dessa kommer påträffas som multimodala fördelningar av dosen i områden där det finns en hög varians. På RaySearch används en probabilistisk random forest för att skapa dessa fördelningar, denna metod är en utökning av den klassiska random forest-algoritmen. En aktuell forskningsriktning är att generera in sannolikhetsfördelningen med hjälp av djupinlärning. Ett oprövat parametriskt tillvägagångssätt för detta är att låta ett lämpligt djupt neuralt nätverk approximera parametrarna för en Gaussisk mixturmodell i varje volymelement. Ett sådant neuralt nätverk är känt som ett mixturdensitetsnätverk. Den här uppsatsen fastställer teoretiska resultat för artificiella neurala nätverk, främst det universella approximationsteoremet, tillämpat på de aktiveringsfunktioner som används i uppsatsen. Den fortsätter sedan att utforska styrkan av djupinlärning i att predicera dosfördelningar, både deterministiskt och stokastiskt. Det primära målet är att undersöka lämpligheten av mixturdensitetsnätverk för stokastisk prediktion. Forskningsfrågan är följande. U-nets och mixturdensitetsnätverk kommer att kombineras för att predicera stokastiska doser. Finns det ett sådant nätverk som är tillräckligt kraftfullt för att upptäcka och modellera bimodalitet? Experimenten och undersökningarna som utförts i denna uppsats visar att det faktiskt finns ett sådant nätverk.
Waggoner, Alexander A. "Triple Non-negative Matrix Factorization Technique for Sentiment Analysis and Topic Modeling." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1550.
Full textHerron, Christopher, and André Zachrisson. "Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273419.
Full textImplicita volatilitetsytor är ett viktigt vektyg för front office- och riskhanteringsfunktioner hos Nasdaq och andra finansiella institut som behöver omvärdera deras portföljer bestående av derivat under dagen men också för att mäta risk i handeln. Baserat på ovannämnda affärsbehov är det eftertraktat att kunna kalibrera de implicita volatilitets ytorna som skapas i slutet av dagen nästkommande dag baserat på ny marknadsinformation. I denna uppsats används statistisk inlärning för att kalibrera dessa ytor. Detta görs genom att uttnytja historiska ytor från optioner i OMXS30 under 2019 i kombination med optioner nära at the money för att träna 3 Maskininlärnings modeller. Modellerna inkluderar Feed Forward Neural Network, Recurrent Neural Network och Gaussian Process som vidare jämfördes baserat på data som var bearbetat på olika sätt. Den bästa Maskinlärnings modellen jämfördes med ett basvärde som bestod av att använda föregående dags yta där resultatet inte innebar någon större förbättring. Samtidigt hade modellen en lägre spridning samt genomsnittligt fel i jämförelse med basvärdet som indikerar att det finns potential att använda Maskininlärning för att kalibrera dessa ytor.
Svanberg, Philip. "Officersprogrammets etik- och moralutbildning : En idealtypsanalys." Thesis, Försvarshögskolan, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-10106.
Full textFredriksson, Gustav, and Anton Hellström. "Restricted Boltzmann Machine as Recommendation Model for Venture Capital." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252703.
Full textIn this thesis, we introduce restricted Boltzmann machines (RBMs) as a recommendation model in the context of venture capital. A network of connections is used as a proxy for investors’ preferences of companies. The main focus of the thesis is to investigate how RBMs can be implemented on a network of connections and investigate if conditional information can be used to boost RBMs. The network of connections is created by using board composition data of Swedish companies. For the network, RBMs are implemented with and without companies’ place of origin as conditional data, respectively. The RBMs are evaluated by their learning abilities and their ability to recreate withheld connections. The findings show that RBMs perform poorly when used to recreate withheld connections but can be tuned to acquire good learning abilities. Adding place of origin as conditional information improves the model significantly and show potential as a recommendation model, both with respect to learning abilities and the ability to recreate withheld connections.
Åkerström, Otto. "Multi-Agent System for Coordinated Defence." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273582.
Full textDagens försvarssystem blir allt mer komplexa när tekniken utvecklas och det blir allt viktigare att utforska nya sätt att lösa problem för att ha ett toppmodernt försvar. I synnerhet används Artificiell intelligens (AI) i ett ökande antal branscher så som logistik, lagerhantering och försvar. Detta arbete kommer att utvärdera möjligheten att använda Förstärkt inlärning (RL) i ett Koordinerat luftförsvar (ADC) scenario hos Saab AB. För att utvärdera RL, löses ett förenklat ADC-scenario med två olika metoder, Q-learning och Deep Q-learning (DQL). Resultatet av de två metoderna diskuteras så väl som begränsningar för Q-learning. Å andra sidan visar sig DQL vara relativt enkelt att tillämpa i ett mer komplext scenario. Slutligen görs ett sista experiment med ett mycket mer komplicerat scenario för att visa skalbarheten för DQL och skapa en naturlig övergång till framtida arbete.
Karlsson, Anton, and Torbjörn Sjöberg. "Synthesis of Tabular Financial Data using Generative Adversarial Networks." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273633.
Full textDigitaliseringen har fört med sig stora mängder tillgänglig kunddata och skapat möjligheter för datadriven innovation. För att skydda kundernas integritet måste dock uppgifterna hanteras varsamt. Generativa Motstidande Nätverk (GANs) är en ny lovande utveckling inom generativ modellering. De kan användas till att syntetisera data som underlättar dataanalys samt bevarar kundernas integritet. Tidigare forskning på GANs har visat lovande resultat på bilddata. I det här examensarbetet undersöker vi gångbarheten av GANs inom finansbranchen. Vi undersöker två framstående GANs designade för att syntetisera tabelldata, TGAN och CTGAN, samt en enklare GAN modell som vi kallar för WGAN. Ett omfattande ramverk för att utvärdera syntetiska dataset utvecklas för att möjliggöra jämförelse mellan olika GANs. Resultaten indikerar att GANs klarar av att syntetisera högkvalitativa dataset som bevarar de statistiska egenskaperna hos det underliggande datat, vilket möjliggör en gångbar och reproducerbar efterföljande analys. Alla modellerna som testades uppvisade dock problem med att återskapa numerisk data.
Ragland, Debra A. "The Structural Basis for the Interdependence of Drug Resistance in the HIV-1 Protease." eScholarship@UMMS, 2012. http://escholarship.umassmed.edu/gsbs_diss/879.
Full textRagland, Debra A. "The Structural Basis for the Interdependence of Drug Resistance in the HIV-1 Protease." eScholarship@UMMS, 2016. https://escholarship.umassmed.edu/gsbs_diss/879.
Full textGrossman, Mikael. "Proposal networks in object detection." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-241918.
Full textLokalisering av användbar data från bilder är något som har revolutionerats under det senaste decenniet när datorkraften har ökat till en nivå då man kan använda artificiella neurala nätverk i praktiken. En typ av ett neuralt nätverk som använder faltning passar utmärkt till bilder eftersom det ger möjlighet för nätverket att skapa sina egna filter som tidigare skapades för hand. För lokalisering av objekt i bilder används huvudsakligen Faster R-CNN arkitekturen. Den fungerar i två steg, först skapar RPN boxar som innehåller regioner där nätverket tror det är störst sannolikhet att hitta ett objekt. Sedan är det en detektor som verifierar om boxen är på ett objekt .I denna uppsats går vi igenom den nuvarande litteraturen i artificiella neurala nätverk, objektdektektering, förslags metoder och presenterar ett nytt förslag att generera förslag på regioner. Vi visar att genom att byta ut RPN med vår metod (MPN) ökar vi precisionen med 12% och reducerar tiden med 10%.
Guazzelli, Alex. "Aprendizagem em sistemas hibridos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1994. http://hdl.handle.net/10183/25776.
Full textThis dissertation presents two new connectionist models based on the adaptive resonance theory (ART): Simplified Fuzzy ARTMAP and Semantic ART (SMART). The modeling, adaptation, implementation and validation of these models are described, in their association to HYCONES, a hybrid connectionist expert system to solve classification problems. HYCONES integrates the knowledge representation mechanism of frames with neural networks, incorporating the inherent qualities of the two paradigms. While the frames mechanism provides flexible constructs for modeling the domain knowledge, neural networks, implemented in HYCONES' first version by the combinatorial neuron model (CNM), provide the means for automatic knowledge acquisition from a case database, enabling, as well, the implementation of deductive and inductive learning. The Adaptive Resonance Theory (ART) deals with a system involving selfstabilizing input patterns into recognition categories, while maintaining a balance between the properties of plasticity and stability. ART includes a series of different connectionist models: Fuzzy ARTMAP, Fuzzy ART, ART 1, ART 2, and ART 3. Among them, the Fuzzy ARTMAP one stands out for being capable of learning analogical patterns, using two basic ART modules. The Simplified Fuzzy ARTMAP model is a simplification of the Fuzzy ARTMAP neural network. Constrating the first model, the new one is capable of learning analogical patterns using only one ART module. This module is responsible for the categorization of the input patterns. However, it has one more layer, which is responsible for receiving and propagating the target patterns through the network. The presence of a single ART module does not hamper the Simplified Fuzzy ARTMAP model. The same performance levels are attained when the latter one runs without the second ART module. This is certified by the match-tracking strategy, that conjointly maximizes generalization and minimizes predictive error. Two medical domains were chosen to validate HYCONES performance: congenital heart diseases (CHD) and renal syndromes. To build up the CHD case base, 66 medical records were extracted from the cardiac surgery database of the Institute of Cardiology RS (ICFUC-RS). These records cover the period from January 1986 to December 1990 and describe 22 cases of Atrial Septal Defect (ASD), 29 of Ventriculal Septal Defect (VSD), and 15 of Atrial- Ventricular Septa! Defect (AVSD), the three most frequent congenital heart diseases. For validation purposes, 33 additional cases, from the same database and period mentioned above, were also extracted. From these cases, 13 report ASD, 10 VSD and 10 AVSD. To build the renal syndromes case base, 381 medical records from the database of the Escola Paulista de Medicina were analyzed and 58 evidences, covering the patients' clinical history and physical examination data, were semiautomatically extracted. From the total number of selected cases, 136 exhibit Uremia, 85 Nephritis, 100 Hypertension, and 60 Calculosis. From the 381 cases analyzed, 245 were randomically chosen to build the training set, while the remaining ones were used to build the testing set. To validate HYCONES II, 46 versions of the hybrid knowledge base (HKB) with congenital heart diseases were built; for the renal domain, another set of 46 HKB versions were constructed. For both medical domains, the HKBs were automatically generated from the training databases. From these 46 versions, one operates with the CNM model and the other 45 deals with two ART models. These ART versions are divided in three groups: 15 versions were built using the Simplified Fuzzy ARTMAP model; 15 used the Simplified Fuzzy ARTMAP model without the normalization of the input patterns, and 15 used the Semantic ART model. HYCONES II - Simplified Fuzzy ARTMAP and HYCONES - CNM performed similarly for the CH D domain. The first one pointed out correctly to 29 of the 33 testing cases (87,9%), while the second one indicated correctly 31 of the same cases (93,9%). In the renal syndromes domain, however, the performance of HYCONES II - Simplified Fuzzy ARTMAP was superior to the one exhibited by CNM (p < 0,05). Both versions pointed out correctly, respectively, 108 (85%) and 95 (74.8%) diagnoses of the 127 testing cases presented to the system. HYCONES II - Simplified Fuzzy ARTMAP, therefore, displayed a satisfactory performance. However, the semantic contents of the neural nets it generated were completely different from the ones stemming from the CNM version. The networks that pointed out the final diagnosis in HYCONES - CNM were very similar to the knowledge graphs elicited from experts in congenital heart diseases. On the other hand, the networks activated in HYCONES II - Simplified Fuzzy ARTMAP operated with far more evidences than the CNM version. Besides this quantitative difference, there was a striking qualitative discrepancy among these two models. The Simplified Fuzzy ARTMAP version, even though pointing out to the correct diagnoses, used evidences that represented the complementary coding of the input pattern. This coding, inherent to the Simplified Fuzzy ARTMAP model, duplicates the input pattern, generating a new one depicting the evidence observed (on-cell) and, at the same time, the absent evidence, in relation to the total evidence employed to represent the input cases (off-cell). This coding shuts out the HYCONES explanation mechanism, since medical doctors usually reach a diagnostic conclusion rather from a set of observed evidences than from their absence. The next step taken was to improve the semantic contents of the Simplified Fuzzy ARTMAP model. To achieve this, the complement coding process was removed and the modified model was, then, revalidated, through the same testing sets as above described. In the CHD domain, the performance of HYCONES II - Simplified Fuzzy ARTMAP, without complementary coding, proved to be inferior to the one presented by CNM (p < 0,05). The first model singled out correctly 25 out of the 33 testing cases (75,8%), while the second one singled out correctly 31 out of the same 33 cases (93,9%). In the renal syndromes domain, the performances of HYCONES II - Simplified Fuzzy ARTMAP, without complementary coding, and HYCONES - CNM were similar. The first pointed out correctly to 98 of the 127 testing cases (77,2%), while the second one pointed out correctly to 95 of the same cases (74.8%). However, the recognition categories formed by this modified Simplified Fuzzy ARTMAP still presented quantitative and qualitative differences in their contents, when compared to the networks activated by CNM and to the knowledge graphs elicited from experts. This discrepancy, although smaller than the one observed in the original Fuzzy ARTMAP model, still restrained HYCONES explanation mechanism. The Semantic ART model (SMART) was, then, proposed. Its goal was to improve the semantic contents of ART recognition categories. To build this new model, the Simplified Fuzzy ARTMAP archictecture was preserved, while its learning algorithm was replaced by the CNM inductive learning mechanism (the punishments and rewards algorithm, associated with the pruning and normalization mechanisms). A new validation phase was, then, performed over the same testing sets. For the CHD domain, the perfomance comparison among SMART, Simplified Fuzzy ARTMAP, and CNM versions showed similar results. The first and the second versions pointed out correctly to 29 of the 33 testing cases (87,9%), while the third one singled out correctly 31 of the same testing cases (93,9%). For the renal syndromes domain, the performance of HYCONES II - SMART was superior to the one presented by the CNM version (p < 0,05), and equal to the performance presented by the Simplified Fuzzy ARTMAP version. SMART and Simplified Fuzzy ARTMAP singled out correctly 108 of the 127 testing cases (85%), while the CNM version pointed out correctly 95 of the same 127 testing cases (74.8%). Finally, it was observed that the neural networks generated by HYCONES II - SMART had a similar content to the networks generated by CNM and to the knowledge graphs elicited from multiple experts. The main contributions of this dissertation are: the design, implementation and validation of the Simplified Fuzzy ARTMAP and SMART models. The latter one, however, stands out for its learning mechanism, which provides a higher semantic value to the recognition categories, when compared to the categories formed by conventional ART models. This important enhancement is obtained by incorporating specificity and relevance concepts to ART's dynamics. This dissertation, however, represents not only the design and validation of two new connectionist models, but also, the enrichment of HYCONES. This is obtained through the continuation of a previous MSc dissertation, under the same supervision supervision. From the present work, therefore, it is given to the knowledge engineering, the choice among three different neural networks: CNM, Semantic ART and Simplified Fuzzy ARTMAP, all of which, display good performance. Indeed, the first and second models, in contrast to the third, support the context in a semantic way.
Bergström, Sebastian. "Customer segmentation of retail chain customers using cluster analysis." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252559.
Full textI denna uppsats har klusteranalys tillämpats på data bestående av kunders konsumtionsvanor hos en detaljhandelskedja för att utföra kundsegmentering. Metoden som använts bestod av en två-stegs klusterprocedur där det första steget bestod av att skapa variabler, tillämpa en kvadratrotstransformation av datan för att hantera kunder som spenderar långt mer än genomsnittet och slutligen principalkomponentanalys för att reducera datans dimension. Detta gjordes för att mildra effekterna av att använda en högdimensionell datamängd. Det andra steget bestod av att tillämpa klusteralgoritmer på den transformerade datan. Metoderna som användes var K-means klustring, gaussiska blandningsmodeller i MCLUST-familjen, t-fördelade blandningsmodeller från tEIGEN-familjen och icke-negativ matrisfaktorisering (NMF). För klustring med NMF användes förbehandling av datan, mer specifikt genomfördes ingen PCA. Klusterpartitioner jämfördes baserat på silhuettvärden, Davies-Bouldin-indexet och ämneskunskap, som avslöjade att K-means klustring med K=3 producerar de rimligaste resultaten. Denna algoritm lyckades separera kunderna i olika segment beroende på hur många köp de gjort överlag och i dessa segment finns vissa skillnader i konsumtionsvanor. Med andra ord finns visst stöd för påståendet att kundsegmenten har en del variation i sina konsumtionsvanor.
Silva, Daniel Lucas Alves da. "Racismo antinegro no português brasileiro e uma proposta de avaliação para professores de PLE." Universidade Estadual Paulista (UNESP), 2018. http://hdl.handle.net/11449/153687.
Full textRejected by Elza Mitiko Sato null (elzasato@ibilce.unesp.br), reason: Solicitamos que realize correções na submissão seguindo as orientações abaixo: Problema 01) Está faltando o LOGO da Universidade na capa do seu trabalho.(este item é obrigatório) Problema 02)Solicitamos que faça correção na descrição na folha de rosto e de aprovação. Agradecemos a compreensão. on 2018-04-20T15:49:09Z (GMT)
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Na esteira do crescente interesse em português como língua estrangeira, doravante PLE, este trabalho se propõe a contribuir para a formação de professores de PLE quanto a seu entendimento da dinâmica das relações étnico-raciais que marcam a língua portuguesa na sua variante brasileira, sobretudo, no que diz respeito ao racismo antinegro. Espera-se que, por meio de um instrumento de avaliação voltado a professores de PLE, o EPPLE-PLE, esta formação seja melhor informada para a condução do debate acerca da temática racial e, por consequência, a prática docente destes profissionais possa instanciar uma maior sensibilização por parte de professores e aprendentes da língua para esta dimensão cultural que perpassa a historicidade do português brasileiro. Para tanto, valemo-nos da teoria racial crítica aplicada à formação de professores de língua estrangeira como apresentada por Ferreira (2015) e um seu desdobramento, qual seja o letramento racial segundo Skerret (2011), do conceito de washback by design conforme Messick (1989) e da teoria sociocultural nos termos de Vigostski (1987) para este que é um processo de legitimação da elaboração e da proposição de itens para o referido exame. Trata-se de um processo de legitimação de uma proposição de itens e sua posterior elaboração para o que se pretende possa ser uma intervenção benéfica para a prática de professores de PLE.
In the context of increasing interest in Portuguese as a foreign language (henceforth PFL) this project contributes to the understanding of teachers of PFL regarding the racial dynamics that manifest themselves in Brazilian Portuguese, in particular anti-black racism. We argue that considerations about race should form part of the elaboration of an assessment instrument designed for teachers of PFL, the EPPLE-PLE (a proficiency exam for teachers of foreign languages in its Portuguese acronym). In doing so, as an expected result, teaching can inculcate more awareness, both on the part of teachers and learners of PFL, regarding this cultural dimension that forms part of the history of Brazilian Portuguese. To this end, we make use of critical race theory applied to the education of teachers of a foreign language as presented by Ferreira (2015) and the idea of racial literacy according to Skerret (2011), the concept of washback by design by Messick (1989) and the theory of sociocultural perspective by Vigostki (1987), for the selection of items for the aforementioned exam. This is a legitimation process of the proposition of items and their elaboration for an exam that we deem can be a beneficial intervention in the practice of PFL teachers.
Bori, Pau. "Anàlisi crítica de llibres de text de català per a no catalanoparlants adults en temps de neoliberalisme." Doctoral thesis, Universitat Pompeu Fabra, 2015. http://hdl.handle.net/10803/350798.
Full textThis thesis studies contemporary course books for Catalan as a foreign language published from 2005 to 2015 from a critical perspective. Two main objectives of this study are: (a) to describe in what way the macro context influences the nature of the studied materials, and (b) to examine the relationship between the content of the course books and the socio-economical conditions in the latest phase of capitalism. In order to accomplish the first objective, the study explores the ways foreign and second language learning processes and textbook design evolved relating them to the wider macro context. The study suggests that the language policies from the Council of Europe have a major impact on foreign language teaching in Europe and are subsequently influencing on curriculum and course book design of Catalan as a foreign language. This institution has been actively involved in creation and promotion of the communicative language teaching with the emphasis on instrumental language. It has also been a firm promoter of the processes of standardization, centralization and homogenization of foreign language learning and course book design. The Council of Europe’s projects for language learning, have been developed in accord with the mercantilist spirit of neoliberalism that extends to all spheres of live. To accomplish the second objective a quantitative analysis of the corpus was developed followed by a more interpretative one centered on the topics of work, housing and travel. The results suggest that practices and values of neoliberalism usually appear in a positive, naturalized way without mentioning their negative aspects or limitations. Moreover, the course books analyzed propose activities which support and develop the roles of consumers and entrepreneurs in students that the current economic order requires.
Malmgren, Henrik. "Revision of an artificial neural network enabling industrial sorting." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-392690.
Full textAzemikhah, Homayoon. "The Double Heuristic Method: perspectives on how teachers deal with an alternative model for teaching in the VET sector." Thesis, 2013. http://hdl.handle.net/2440/86274.
Full textThesis (Ph.D.) -- University of Adelaide, School of Education, 2013
Gordon, Denise. "A Case Study of the Applied Learning Academy: Reconceptualized Quantum Design of Applied Learning." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7612.
Full textTsai, Ching-Horng, and 蔡青宏. "Learning Theory and Regional Development of Applied Research in Taichung City." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/65628053278253873474.
Full text逢甲大學
土木暨水利工程博士學位學程
99
The information technology had given rise to information explosion which led to the transformation from the traditional mode mainly supported by material and energy techniques to the Internet mode supported by information technology. The transformation resulted in the changes of producing methods and life style. Moreover, it became the common concern of many disciplines such as philosophy, sociology, economics and geography. Regions were the study core of geography, regional development was the main field of geography, and the advance of technology was the internal action of regional development. The information era brought opportunities and challenges. In order to adjust to an era of rapid changes and uncertainty, how to use information and create knowledge became the key of all regional development. The study synthesized the theories and approaches of applied economics, sociology, economic geography, regional science and so on. It also regarded regions as a development organism. A strong interaction existed between regions and the environment. The regions were the internal cause of regional development, while the environment was the external one. The initiative and creativity of regions determined the direction of their development. The study core was the mechanism for the formation and development of a learning region which included the development of action mechanism, cooperation mechanism, regional difference mechanism and adjustment mechanism in a learning region. From the enterprise, industrial and regional levels, the development causes of a learning region were viewed to explore the relationship between learning and regional economy, to analyze the connection between knowledge production and value actualization and regional development, to expound the intrinsic logic and to construct a complete development framework of a learning region. First, the study analyzed the theory of regional development and basic theory of an innovative city, and it also summarized and evaluated the results of a learning region. From the aspects of information, globalization and a dynamic market, it promulgated the macroscopic background derived from it. Next, the action mechanism was used to analyze regional development, and it also specifically analyzed the reformation of knowledge production, the reasons of enterprises becoming the main body of knowledge production, and the mechanism of the knowledge production mode of enterprises and the mechanism of the requirements of industry cooperation. Last but not the least, it analyzed time and space evolution, and explored the adjustment mechanism and measures of a learning region and an innovative city. Take the case study of home and abroad for example, the basic features and types of an innovative country and the development mode and evolution of an innovative city were addressed. The instance of a learning region in Scotland was reviewed, and it inspired others. The reforming practice study of our country was cited to illustrate the change from a city of a regional technology center to an innovative city. Take Taichung for example, the theory of a learning region was applied on the developmental problems of the city from a historical perspective to determine and analyze low learning abilities and to propose some measures for its regional development.
CHEN, YUAN-KENG, and 陳源庚. "The Analyses of Teaching Effectiveness Based Learning Community Theory Applied on Interactive Whiteboard." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/76092394381970282962.
Full text亞洲大學
光電與通訊學系碩士在職專班
102
This study is to design an instructional model with the utilization of interactive whiteboard (IWB) in accordance with the theory of “learning community “proposed by professor misaki satoto to emphasize the interaction of teacher-student as well as peers and to investigate the advantages of the proposed instructional model for promoting learning effectiveness. The IWB system can be applied on the learning development of the self-construction knowledge and self-learning. The participants, who are students from two elementary schools in Nantou County, took the test during the experiment period. The descriptive results were obtained by t-test using statistics software SPSS based on the research hypotheses of the topic of the study. The findings in this research were concluded that with the application of the learning community theory being associated with the IWB instruction to turn into the so called “LCIWB”, the learning effectiveness of nature and life technology course in elementary school is remarkable with about 10 grade points being promoted. Therefore, the proposed LCIWB methodlogy is helpful to students for promotion of learning effectiveness at nature and life technology course in elementary school.
Fuentes, Erika. "Statistical and Machine Learning Techniques Applied to Algorithm Selection for Solving Sparse Linear Systems." 2007. http://trace.tennessee.edu/utk_graddiss/171.
Full textWu, Mei-Chih, and 吳美枝. "A Research on the Learning Effect of Cooperative Learning Applied to Music Theory Teaching of the Junior High School." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/60004120145997113773.
Full text國立臺中教育大學
教育學系課程與教學碩士班
100
The main purpose of this research is to investigate the effects of the cooperative learning applied to music theory teaching of the junior high school. A nonequivalent pretest-posttest quasi-experimental design was adopted. Students of two classes in the junior high school were assigned into experimental group and control group. The experimental group was taught by the method of cooperative learning, and the control group was taught by the method of traditonal teaching. All the teaching contents, teacher, time length, and classroom for the students of the two groups were the same, and the experimental treatment had lasted for 9 weeks in the amout of 18 classes. Research data were collected through the self-designed instruments, including “ Music Theory Test A ”, “ Music Theory Test B”, “Questionnaire of Students’ Opinion about Cooperative Learning”…etc. The main findings of this research are listed below: 1. The learning achievements of experimental group were significantly effective in enhancing students’ ability of the basic music theory. But, there were no statistical differences between both the learning achievements of the experimental and the control groups. 2. Applying the Cooperative Learning to the music theory teaching of the junior high School Students was effective in increasing students’ learning motivation, cultivating the spirit of mutual assistance and cooperation among the peers, and producing the positive impact for the classroom climate. 3. Applying the Cooperative Learning to the music theory teaching of the junior high School Students was effective in promoting researcher’s expertise and changing her belief in teaching. According to the results, some suggestions were made for music teaching and future researches.
Tong-Fa, Li, and 李同法. "Situational Learning Theory Applied to Display Research and Creation - take the results of the researcher company as an example." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/92rnqn.
Full text樹德科技大學
視覺傳達設計系碩士班
106
The main functions of the museum are collection, research, display, and education. Museums provides visitors with spontaneous and joyful environment by displaying. Exhibitions are visual feasts of comprehensive technology and arts. They construct interactive platforms between exhibits and visitors. The purpose of the research is to discuss how to design a “people-oriented “exhibition which cannot only offer people a great learning environment, but also be the exhibition design strategy. In this digital generation, people rely on computer, communication and consumer products to interact, which mean people can easily search for the specific information. Here comes to a question. How to stimulate the audience to spontaneously see the exhibition? How to design a real, exciting, and moving real-life display environment to enhance the audience''s enjoyment of learning and gaining knowledge is an important topic that must be addressed at present. Due to the rapid development of digital technology, how to balance the use of virtual images, the integration of real exhibits in the exhibition and the use of technology, art, creativity to construct a new interactive and interesting learning environment are the purposes of this research. Based on Lave''s "situational learning theory", we believe that the layout of learning environments is the key to success. Knowledge should be constructed in real activities. The audience should use the knowledge they learned to comprehend the contents and meanings behind exhibitions. By applying this theory, the individual''s exploration learning, teammates'' mutual learning, and mentoring learning can all generate knowledge exchange and recognition. In this paper, the researcher has been engaged in display design for many years and has rich practical experiences. In recent years, the case of the firm has focused on the display production of reservoir anti-silting tunnel engineering, designing virtual animation films and physical models of reservoirs, and integrating the design methods of “virtual” and “real”. Creating a dynamic situation display project for the anti-sludge tunnel project and using the company''s performance case to analyze the "situation learning theory", sharing the design development process, and making the most clear expression are strong proofs of the exhibition design research. Exploring the "situational learning theory" is proved that people have received great learning results.