賽局理論(Game Theory)大多假設理性決策，單一回合賽局通常可由理論證明均衡(Equilibrium)或是最佳決策，然而如果賽局重複進行，不見得只存在單一均衡，光從理論推導可能無法找到所有均衡。以囚犯困境(Prisoner Dilemma)為例，理論均衡為不合作，若重複的賽局中存有互利關係，不合作可能不是最佳選擇。近年來，經濟學家藉由和統計實驗設計類似的賽局實驗(Game Experiment)，探討賽局在理論與實際間的差異，並以學習模型(Learning Model)描述參賽者的決策及行為，但學習模型的優劣大多依賴誤差大小判定，但誤差分析結果可能與資料有關(Data Dependent)。有鑑於學習模型在模型選取上的不足，本文引進統計分析的模型選取及殘差檢定，以實證資料、配合電腦模擬評估學習模型。 本文使用的實證資料，屬於囚犯困境的重複賽局(Repeated Game)，包括四種不同的實驗設定，參加賽局實驗者（或是「玩家」）為政治大學大學部學生；比較學習模型有四種：增強學習模型(Reinforcement Learning model)、延伸的增強學習模型(Extend Reinforcement Learning Model)、信念學習模型(Belief Learning Model)、加權經驗吸引模型(Experience-Weighted Attraction Model)。實證及模擬分析發現，增強學習模型較適合用於描述囚犯困境資料，無論是較小的誤差或是適合度分析，增強學習模型都有較佳的結果；另外，也發現玩家在不同實驗設定中的反應並不一致，將玩家分類後會有較佳的結果。 / In game theory, the optimal strategy (or equilibrium) of one-shot games usually can be solved theoretically. But, the optimal strategies of repeated games are likely not unique and are more difficult to find. For example, the defection is the optimal decision for the one-shot Prisoner Dilemma (PD) game. But for the repeated PD game, if the players can benefit from cooperation between rounds then the defection won’t be the only optimal rule. In recent years, economists design game experiments to explore the behavior in repeated games and use the learning models to evaluate the player’s choices. Most of the evaluation criteria are based on the estimation and prediction errors, but the results are likely to be data dependent. In this study, we adapt the model selection process in regression analysis and apply the idea to evaluate learning models. We use empirical data, together with Monte Carlo simulation, to demonstrate the evaluation process. The empirical data used are repeated PD game, including four different experimental settings, and the players of the game are from National Chengchi University in Taiwan. Also, we consider four learning models: Reinforcement learning (RL) model, Extend Reinforcement learning (ERL) model, Belief Learning (BL) model, and Experience-weighted attraction (EWA) model. We found that the RL model is more appropriate to describe the PD data. In addition, the behaviors of players in a group can be quite different and separating the players into different sets can reduce the estimation errors.

Considering the context of large city schools, this study explores what variables in a kindergarten classroom may impact the process of children’s engagement with nature. In particular I examine the central role of children and teacher in co-constructing their own unique understanding, knowledge, and attitude towards the natural world. In this study, I examine nature-child’s connection considering the complexity of nature beyond a pre-packaged concept (Louv, 2007) and avoiding a linear identification of a cause and effect relationship between children’s learning experiences and nature, (Kellert, 2005). This qualitative case study is based on extensive classroom observations, in which 20 kindergarten children and their teacher participate. The children’s direct, indirect, and vicarious experiences with nature are documented using digital photography, video-audio recording, and collection of artifacts. I interview the classroom teacher two times and invite the parents to fill up a questionnaire about their children’s experiences with nature outside the school time. I use the techniques and procedure of the grounded theory to analyze the data. A comparative analysis of the five learning episodes demonstrates four major factors that when all woven together encourage and sustain the children’s engagement with nature. These factors are: investigating children’s meaningful and autotelic questions, encountering and experiencing nature in familiar contexts, developing emotional bonding, and having sufficient time. The findings show the crucial role of the classroom teacher in creating five main conditions to engage the children in the process of each inquiry. She offers the children many opportunities to use their prior skills and knowledge, take responsibility of their own learning, and experiment with learning as a process. She often responds positively to the children’s learning endeavours and communicates her high confidence and expectations for them. This study makes an important contribution to the field of early childhood education and environmental education by demonstrating the possibilities and challenges in actively and holistically engaging children with nature in school settings. The findings shed light on our understanding of children and teacher’s sense of ownership and motivation as two driving forces of learning.

Considering the context of large city schools, this study explores what variables in a kindergarten classroom may impact the process of children’s engagement with nature. In particular I examine the central role of children and teacher in co-constructing their own unique understanding, knowledge, and attitude towards the natural world. In this study, I examine nature-child’s connection considering the complexity of nature beyond a pre-packaged concept (Louv, 2007) and avoiding a linear identification of a cause and effect relationship between children’s learning experiences and nature, (Kellert, 2005). This qualitative case study is based on extensive classroom observations, in which 20 kindergarten children and their teacher participate. The children’s direct, indirect, and vicarious experiences with nature are documented using digital photography, video-audio recording, and collection of artifacts. I interview the classroom teacher two times and invite the parents to fill up a questionnaire about their children’s experiences with nature outside the school time. I use the techniques and procedure of the grounded theory to analyze the data. A comparative analysis of the five learning episodes demonstrates four major factors that when all woven together encourage and sustain the children’s engagement with nature. These factors are: investigating children’s meaningful and autotelic questions, encountering and experiencing nature in familiar contexts, developing emotional bonding, and having sufficient time. The findings show the crucial role of the classroom teacher in creating five main conditions to engage the children in the process of each inquiry. She offers the children many opportunities to use their prior skills and knowledge, take responsibility of their own learning, and experiment with learning as a process. She often responds positively to the children’s learning endeavours and communicates her high confidence and expectations for them. This study makes an important contribution to the field of early childhood education and environmental education by demonstrating the possibilities and challenges in actively and holistically engaging children with nature in school settings. The findings shed light on our understanding of children and teacher’s sense of ownership and motivation as two driving forces of learning.

內容感知的應用在今日已經變的越來越熱門，而位置資訊的可知也因此衍生出許多研究的議題。這篇論文提出了一套精準的室內無線網路系統名為Precise Indoor Location System (PILS)。大部分擁有良好定位精準度的定位系統都必須在事情花費許多的人力在收集大量的訊號上面，使得定位系統的變的不實用與需求過多的人力資源。在這篇論文裡，我們將目標放在減少在建置訊號地圖上的人力資源耗費並且保持住定位系統的精準度在一個可以接受的範圍。我們也提出了在資料收集上、訊號內插上、以及位置估計上的模型。另外我們也考慮了一連串連續訊號的相關度來提高準確度。無線網路訊號傳遞的特性也是我們研究的一部份，大小範圍的遮蔽包含在我們所研究的訊號傳遞現象裡面。最後我們提出了一套學習的模型來調整我們的訊號地圖，以改進因為測量數目的減少所造成的精準度下降。 / Context-aware applications become more and more popular in today’s life. Location-aware information derives a lot of research issues. This thesis presents a precise indoor RF-based WLAN (IEEE 802.11) locating system named Precise Indoor Locating System (PILS). Most proposed location systems acquire well location estimation results but consume high level of manual efforts to collect huge amount of signal data. As a consequence, the system becomes impractical and manpower-wasted. In this thesis, we aim to reduce the manual efforts in constructing radio map and maintain high accuracy in our system. We propose the models for data calibration, interpolating, and location estimation in PILS. In the data calibration and location estimation models, we consider the autocorrelation of signal samples to enhance accuracy. Large scale and small scale fading are involved in the wireless channel propagation model. We also propose a learning model to adjust radio map for improving the accuracy down caused by calibrated data reduction.

Notre thèse de pharmacie clinique est une contribution à l’optimisation de l’efficience du traitement antirétroviral (TAR) par des méthodes de modélisation en Côte d’Ivoire. La première étude a été consacrée à une modélisation de la réponse antirétrovirale par taxonomie des trajectoires de taux de CD4 en utilisant un modèle de méta-apprentissage des trajectoires d’indicateurs biomédicaux. Ce modèle appliqué à la taxonomie des trajectoires des taux de CD4 a montré son intérêt dans la mise en évidence de classes distinctes de patients avec des caractéristiques particulières justifiant et/ou déterminant le profil particulier de méta-trajectoires de leur marqueur immunologique au cours du traitement. La deuxième tâche a consisté en une évaluation de l’impact de principaux déterminants des méta-trajectoires de taux de CD4 sur divers types de réponse immunologique à partir d’un modèle explicatif avec une équation de régression logistique. Les réponses immunologiques considérées ont été exprimées en termes d’absence de gain de CD4, de gain sub-optimal et de gain optimal de CD4 à différentes périodes de suivi du TAR. Enfin l’évaluation de l’efficience des stratégies antirétrovirales de première ligne en Côte d’Ivoire, a été abordée dans la dernière partie avec un modèle pharmaco-économique. Nous avons effectué une étude préliminaire ouvrant des perspectives pour encourager la mise en oeuvre d’évaluations pharmaco-économiques complètes par modélisation en Côte d’Ivoire. Elle a permis de mettre en exergue les parties méthodologiques pouvant être sujettes à caution dans une étude de modélisation pharmaco-économique des TAR de première ligne dans un contexte de ressources limitées / Our thesis of Clinical pharmacy is a contribution to optimize the efficiency of antiretroviral therapy (ART) by modeling methods in Côte d'Ivoire. The first study was devoted to modeling the antiretroviral response from taxonomy of CD4 counts trajectories, using a meta-learning model of biomedical markers trajectories. This model applied to the taxonomy of the CD4 counts trajectories showed its interest in the identification of distinct classes of patients with particular characteristics justifying and/or determining the specific profile of meta-trajectories of the immunological marker during treatment. The second task was an assessment of the impact of key determinants of CD4 counts meta-trajectories on various types of immune response from an explanatory model with a logistic regression equation. Antiretroviral immune responses considered were expressed in terms of absence of CD4 gain, sub-optimal gain and optimal gain of CD4 at different periods of follow-up of ART. Finally the evaluation of the efficiency of first-line antiretroviral strategies in Côte d'Ivoire, was discussed in the last part with a projective pharmaco-economic model. We conducted a preliminary exploratory study opening up prospects to encourage the implementation of comprehensive pharmaco-economic assessments by modeling in Côte d'Ivoire. This study helped to highlight the unreliable methodological sections in a pharmaco-economic modeling of first-line ART in resource-limited settings

Förbrukat kärnbränsle är mycket radioaktivt och behöver därför lagras i djupa geologiska förvar i tusentals år innan det säkert kan återföras till naturen. På grund av de långa lagringsperioderna görs säkerhetsanalyser av de djupa geologiska förvaren. Under säkerthetsanalyserna görs upplösningsexperiment på förbrukat kärnsbränsle för att utvärdera konsekvenserna av att grundvatten läcker in i bränslet vid barriärbrott. Dessa experiment är både dyra och tidskrävande, varför beräkningsmodeller som kan förutsäga förburkat kärnbränsles upplösningsbeteende är önskvärda. Denna avhandling fokuserar på att samla in tillgängliga experimentella data från upplösningsexperiment för att uppdatera och utöka en databas. Med hjälp av databasen har upplösningsbeteendet för varje radionuklid utvärderats och jämförts med tidigare kunskap från befintlig litteratur. Även om det var svårt att vara avgörande om beteendet hos element där en begränsad mängd data fanns tillgänglig, motsvarar de upplösningsbeteenden som hittats för olika radionuklider i denna avhandling inte bara tidigare studier utan ger också ett verktyg för att hantera och jämföra förbrukat kärnbränsles upplösningsdata från olika utgångsmaterial, bestrålningshistorik och betingeleser under upplösning. Dessutom gjorde sammanställningen av en så stor mängd experimentella data det möjligt att förstå var framtida experimentella ansträngningar bör fokuseras, exempelvis finns det en brist på data under reducerande förhållanden. Dessutom utvecklades och kördes maskininlärningsmodeller med hjälp av Artificial Neural Network (ANN), Random Forest (RF) och XGBoost-algoritmer med hjälp av databasen, varefter prestandan utvärderades. Prestanda för varje algoritm jämfördes för att få en förståelse för vilken modell som presterade bäst, men också för att förstå om dessa typer av modeller är lämpliga verktyg för att förutspå förbrukat kärnbränsles upplösningsbeteende. Den bäst presterande modellen, med träning och test R2 resultat nära 1, var XGBoost-modellen. Även om XGBoost hade en hög prestanda, drogs slutsatsen att mer experimentell data behövs innan maskininlärningsmodeller kan användas i verkliga situationer. / Spent nuclear fuel (SNF) is highly radioactive and therefore needs to be stored in deep geological repositories for thousands of years before it can be safely returned to nature. Due to the long storage times, performance assessments (PA) of the deep geological repositories are made. During PA dissolution experiments of SNF are made to evaluate the consequences of groundwater leaking into the fuel canister in case of barrier failure. These experiments are both expensive and time consuming, which is why computational models that can predict SNF dissolution behaviour are desirable.  This thesis focuses on gathering available experimental data of dissolution experiments to update and expand a database. Using the database, the dissolution behaviour of each radionuclide (RN) has been evaluated and compared to previous knowledge from existing literature. While it was difficult to be conclusive on the behaviour of elements where a limited amount of data was available, the dissolution behaviours found of different radionuclides in this thesis not only correspond to previous studies but also provide a tool to manage and compare SNF leaching data from different starting materials, irradiation history and leaching conditions. Moreover, the compilation of such a large amount of experimental data made it possible to understand where future experimental efforts should be focused, i.e. there is a lack of data during reducing conditions. In addition, machine learning models using Artificial Neural Network (ANN), Random Forest (RF) and XGBoost algorithms were developed and run using the database after which the performances were evaluated. The performances of each algorithm were compared to get an understanding of which model performed best, but also to understand whether these kinds of models are suitable tools for SNF dissolution behaviour predictions. The best performing model, with training and test R2 scores close to 1, was the XGBoost model. Although XGBoost, had a high performance, it was concluded that more experimental data is needed before machine learning models can be used in real situations.

В работе была произведена разработка модели машинного обучения на языке программирования Python, а также проведена ее валидация на этапах жизненного цикла. Целью создания модели машинного обучения является прогнозирование магнитных свойств нанокристаллических сплавов на основе железа по химическому составу и условиям обработки. Процесс валидации модели машинного обучения позволяет не только произвести контроль за соблюдением требований, предъявляемых при разработке и эксплуатации модели, к результатам, полученных с помощью моделирования, но и способствует внедрению модели в процесс производства. Процесс валидации включал в себя валидацию данных, в ходе которой были оценены типы, пропуски данных, соответствие цели исследования, распределения признаков и целевых характеристик, изучены корреляции признаков и целевых характеристик; валидацию алгоритмов, применяемых в модели: были проанализированы параметры алгоритмов с целью соблюдения требования о корректной обобщающей способности модели (отсутствие недо- и переобучения); оценку работы модели, благодаря которой был произведен анализ полученных результатов с помощью тестовых данных; верификацию результатов с помощью актуальных данных, полученных из статей, опубликованных с 2010 по 2022 год. В результате валидации модели было показано высокое качество разработанной модели, позволяющее получить оценки качества R2 0,65 и выше. / In this work machine learning model was developed by Python programming language, and also was validated at stages of model’s life cycle. The purpose of creating the machine learning model is to predict the magnetic properties of Fe-based nanocrystalline alloys by chemical composition and processing conditions. The validation of machine learning models allows not only to control the requirements for development and operation of the models, for the results obtained by modeling, but also contrib¬utes to the introduction of the model into production process. The validation process included: data validation: data types and omissions, compliance with the purpose of the study, dis¬tribution of features and target characteristics were evaluated, correlations of features and target characteristics were studied; flgorithms validation: the parameters of the algorithms were analyzed in order to comply with the requirement for the correct generalizing ability of the model (without under- and overfit¬ting); evaluation of the model work: the analysis of the obtained results was carried out using test data; verification of results using actual data obtained from articles published since 2010 to 2022. As a result of the model validation, the high quality of the developed model was shown, which makes it possible to obtain quality metric R2 0.65 and higher.

No description available.

Huvudsyftet med studien har varit att utvärdera hur en fem timmar lång kommunikationsutbildning riktad till sjukgymnaster på habilitering påverkar sjukgymnasternas kommunikativa stil i interaktion med barn/ungdomar som på grund av cerebral pares saknar tal. Utbildningen utformades som en inlärningsmodell i åtta delmoment (åttastegsmodellen). I utbildningen och studien ingick sex habiliteringssjukgymnaster som interagerade med var sitt barn/ungdom som till följd av cerebral pares kommunicerar med alternativt och kompletterande kommunikation (AKK) i form av kommunikationskartor. Interaktionen videofilmades vid tre separata tillfällen: en inspelning före utbildning, en inom två veckor efter utbildningen samt en sista filmning tre månader efter avslutad utbildning. Analys av videomaterialet gjordes med hjälp av en kombination av kvantitativ och kvalitativ analysmetod. Analysformuläret KOMMUNIKATIV användes för att analysera sjukgymnasternas kommunikation och kompletterades med en mer detaljerad kvalitativ samtalsanalys (Conversation Analysis, CA) där interaktionen mellan individerna analyserades. Utöver detta besvarade sjukgymnasterna en enkät. Utbildningens utformning baserades på tidigare forskning i form av av miljömodifierande strategier, responsiv kommunikationsstil samt AKK-modell i form av att pekprata. Resultatet av KOMMUNIKATIV påvisade en statistiskt signifikant förändring av sjukgymnasternas kommunikativa beteende efter avslutad utbildning. Det fanns även en fortsatt mätbar, men inte statistiskt signifikant, förändring mellan andra och tredje mättillfället. Sjukgymnasterna möjliggjorde, efter utbildning, att barnen/ungdomen i större utsträckning kunde kommunicera med sin kommunikationskarta. De pekpratade i större utsträckning och var mer lyhörda för barnets/ungdomens kommunikation. Endast en av tio kommunikativa förmågor som analyseras i KOMMUNIKATIV försämrades: sjukgymnastens förmåga att förtydliga sig. Samtalsanalysen bekräftade den kvantitativa analysen på flera sätt och visade att barnet/ungdomen efter utbildning anpassade sig till sjukgymnasternas förändrade beteende och uttryckte sig i längre fraser. Interaktionsmönstret ändrades från att före utbildning vara mer styrt av sjukgymnasten till att barnet/ungdomen efter utbildning kunde införa nya ämnen och delta i reparerande sekvenser. Samtalsanalysen visade även hur sjukgymnasterna ändrade sin användning av en engagerad röstkvalitet. Före kursen användes den i flera olika kontexter, inklusive problematiska kommunikativa kontexter där den snarare förvärrade problemen. Efter kursen varierade sjukgymnasterna sina strategier för att lösa olika typer av problematiska situationer, och undvek därmed i högre grad kommunikativa problem. Åttastegsmodellen som provades i genomförandet av kursen var framgångsrik på två olika sätt. Dels medgav den att varje deltagare fick en individuell målsättning baserad på en förmätning, och dels medförde modellen ett aktivt lärande vilket bidrog till att befästa den nya kunskapen. En slutsats av utvärderingen är att en interventionsutbildning enligt åttastegsmodellen med fördel kan användas för att lära ut kommunikativa strategier till habiliteringspersonal. / The main purpose of this study was to examine how a five hour communication course given to physiotherapists working at a habilitation center changes their communication when interacting with non-speaking children and teenagers with cerebral palsy. An instructional model for teaching learning strategies in eight steps was tested. Six physiotherapists took part of a five hour communication course on three occasions. The course contained receptive communication, environmental arrangements and aided language stimulation as suggested by previous research. Interaction between physiotherapist and child/teenager communicating with a communication board was videotaped just before the course, within two weeks after the course and also three month later. The course was analyzed using a combination of quantitative and qualitative methods. KOMMUNIKATIV is a quantitative method measuring ten communication abilities of the physiotherapists. Conversation Analysis (CA) was used as a detailed qualitative complementary analysis to KOMMUNIKATIV in order to examine the interaction between physiotherapist and child/teenager. Results from KOMMUNIKATIV showed a statistically significant change within two weeks after the course. Continued changes were measured between the second and the third point of measure but that change was not statistically significant. These results strongly indicate that the physiotherapists adopted a more receptive communication style after the course. They made it possible for the child/teenager to communicate with the communication board and they increased the number of AAC-modeling. One aspect, the physiotherapists’ ability to simplify the communication, declined from the first to the second and third point of measure. The child´s/teenager´s communication adapted in some ways to the changed communicational behavior of the physiotherapists. After the course, the child/teenager used longer phrases and started to make repairs. The detailed interaction analysis verified the change in communicative behavior in several ways. One significant change was the way the physiotherapists used an engaged voice quality to encourage the child/teenager to respond to requests for action. Before the course this voice quality was used in many different contexts, including communicatively problematic contexts, where it increased the problems. After the course the physiotherapists used a more varied set of strategies to solve problematic situations, thereby avoiding communicative problems. The instructional model for teaching communicative strategies in eight steps that was used in the study was successful in two ways. Firstly, the model provides the possibility to set individual goals for each member based on preassessments. Secondly, this model enables active learning which seem to consolidate the new ability. A conclusion from the evaluation of the eight step model is that it can be used for teaching communicative strategies to professionals.

1 ABSTRACT The thesis discusses possibilities of application of the concept of lifelong education in Basic Art Schools. The goal of the thesis is to propose a basic model of adult education which could be applied in Basic Art Schools. It focuses on the analysis of the literature on lifelong learning, lifewide learning, further education, and also on the analysis of strategic documents of the European Union and the Czech Republic in the field of lifelong learning and further education. Based on the analyses of the documents and external environment, a model of adult education in Basic Art Schools is proposed, the applicability of which is verified by a research investigation. A survey research examines the existence of education of diverse target groups of adults (both laymen and experts) in Basic Art Schools in Prague, the ratio of adult to younger students and the employed methods of their education. Structured interviews among five headteachers of Basic Art Schools in Prague clarify specific details of the process of educating adults in Basic Art Schools and provide more observations on the topic. The thesis contributes to the advancement of the concept of lifelong learning in the sphere of Basic Art Schools. Also, it brings forward possibilities of use of vacancies in Basic Art Schools for adult...