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Royal Buddhist architecture of the early Bangkok period : investigations in symbolic planningWeerataweemat, Songyot January 1999 (has links)
No description available.
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Economic plans and the evolution of economic nationalismNambara, Makoto January 1998 (has links)
No description available.
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Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle TrackingZarzar Torano, Jesus Alejandro 05 1900 (has links)
The automation of navigation for different kinds of vehicles is a research problem of great interest. This problem has applications with unmanned aerial vehicles (UAVs) as well as manned vehicles such as cars and planes. The goal of an autonomous vehicle is to navigate safely from one point to another given a set of high-level instructions and data from a set of sensors. This thesis explores an implementation of a modular approach for autonomously driving taxiing planes before proposing methods for object tracking using a LIDAR sensor which can be incorporated into the autonomous driving pipeline. The taxiing algorithm regresses waypoints for the plane to follow given a high-level driving goal such as ”turn left” or ”go straight”, along with RGB images taken from the cockpit and wings. Waypoints are then used with a separate control system to taxi the plane. The training and testing of this autonomous aircraft is done in a photo-realistic simulator which has been adapted for this task. The policy developed in this fashion is capable of learning how to go straight and how to turn. However, the driving policy is not trained to react to other moving objects. To address this issue, and due to the superior reliability of LIDAR over RGB sensors, an object tracking method using only LIDAR point clouds is proposed. The proposed method uses a novel 3D Siamese network to obtain a similarity score between a model and candidate object point clouds. This similarity score is shown to work for tracking by applying it using an exhaustive search and obtaining improved performances when compared with simple baselines. For a realistic application, the similarity score is applied using candidates provided by a search on the BEV projection of the LIDAR point cloud. This method is shown to provide improved tracking results over other search strategies when using a lower number of candidates.
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La question de l'extraterritorialité et ses conséquences judiriques successives concernant les protégés français au Siam, dans le cadre des relations franco-siamoise de 1893 à 1907 / The question of extraterritoriality and its forensic consequences for the French protégés in Siam, in connection with Franco-Siamese relationship from 1893 to 1907Chiraphong, Rippawat 12 September 2016 (has links)
La thèse traite de la question de l'extraterritorialité (ou protection) au Siam des années 1850 aux années 1930, notamment des années 1890 à 1910 caractérisées par une politique offensive de la France à ce sujet. Exigée par les puissances coloniales pour la protection de leurs représentants et employés, afin de ne pas les exposer à des lois et à un système judiciaire "barbares", l'extraterritorialité fut admise par les autorités siamoises lors de la conclusion des premiers traités avec les Occidentaux (1855, 1856). Mais, à partir du moment où la France domina l'Indochine française, l'extraterritorialité devint instrument de colonisation. Avec la création du Laos et sous l'impulsion de Pavie (1893), les autorités françaises exigèrent que toutes les personnes issues de leurs possessions indochinoises et vivant au Siam fussent considérées comme des protégés bénéficiant des privilèges et procédures de l'extraterritorialité. Les Français virent là un moyen de mettre le Siam sous tutelle puis, suite à l'opposition de l'Angleterre, de garantir leur mainmise sur le Laos et d'obtenir la rétrocession de territoires en faveur du Laos et du Cambodge (1904-1907). Les relations s'apaisèrent après 1907 quand la question de la protection constitua un puissant moteur vers l'élaboration d'une législation moderne, à la rédaction de laquelle des conseillers français apportèrent une exceptionnelle contribution, consacrant l'influence de la France dans le domaine du Droit. / This thesis deals with the question of extraterritoriality (or protection) in Siam in the 1850s to the 1930s, particularly the years 1890 to 1910, characterized by an offensive foreign policy by France. Required by the colonial powers in order to protect their officials and employees and not to expose them to "barbaric" legal and judicial system, extraterritoriality was admitted by the Siamese authorities at the conclusion of the First Treaties with Western Powers (1855, 1856). After France had succeeded in taking over French Indochina, extraterritoriality became a colonization instrument. Following the creation of Laos and under the impulse of Pavie (1893), the French authorities demanded that all people from their Indochinese possessions and also those living in Siam were protégés entitled to the privileges and procedures of extraterritoriality. Opposed by England, the French saw a way to put Siam under supervision whilst at the same time ensure French controle over Laos and obtain the surrender of territories backing Laos and Cambodia (1904-1907). Thai-Franco relations subsided after 1907 with the issue of protection. This issue also constituted a powerful engine to the development of modern legislation, the drafting of which the French advisers brought an outstanding contribution, leaving a significant French influence in Thai Laws.
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Breeding Bettas : an interactive study to the breeding and caring of Siamese fighting fish /Alquraini, Ali. January 2008 (has links)
Thesis (M.F.A.)--Rochester Institute of Technology, 2008. / Typescript.
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The Making of Honour and Masculinity of the Siamese Army from the 1900s to 1932 / 1900年代から1932年におけるシャム陸軍の名誉と男性性の形成Pattarat, Phantprasit 24 January 2022 (has links)
京都大学 / 新制・課程博士 / 博士(地域研究) / 甲第23619号 / 地博第290号 / 新制||地||112(附属図書館) / 京都大学大学院アジア・アフリカ地域研究研究科東南アジア地域研究専攻 / (主査)教授 小泉 順子, 教授 玉田 芳史, 准教授 中西 嘉宏, 教授 速水 洋子 / 学位規則第4条第1項該当 / Doctor of Area Studies / Kyoto University / DGAM
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Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcityBrunell, David January 2022 (has links)
Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. The goal of this master project is to develop an artificial neural network-based model for food waste analysis, an area in which large quantities of data is not yet readily available. Given two images an algorithm is expected to identify what has changed in the image, ignore the uncharged areas even though they might contain objects which can be classified and finally classify the change. The approach chosen in this project was to attempt to reduce the problem the machine learning algorithm has to solve by subtracting the images before they are handled by the neural network. In theory this should resolve both object localisation and filtering of uninteresting objects, which only leaves classification to the neural network. Such a procedure significantly simplifies the task to be resolved by the neural network, which results in reduced need for training data as well as keeping the process of gathering data relatively simple and fast. Several models were assessed and theories of adaptation of the neural network to this particular task were evaluated. Test accuracy of at best 78.9% was achieved with a limited dataset of about 1000 images with 10 different classes. This performance was accomplished by a siamese neural network based on VGG19 utilising triplet loss and training data using subtraction as a basis for ground truth mask creation, which was multiplied with the image containing the changed object. / Maskininlärning kräver generellt mycket data, men stora mängder data står inte alltid till förfogande. Generellt ökar behovet av data med problemets komplexitet. Med hjälp av överföringsinlärning, dataaugumentation och problemreduktion kan dock acceptabel prestanda erhållas på begränsad datamängd för flera uppgifter. Målet med denna masteruppsats är att ta fram en modell baserad på artificiella neurala nätverk för matavfallsanalys, ett område inom vilket stora mängder data ännu inte finns tillgängligt. Givet två bilder väntas en algoritm identifiera vad som ändrats i bilden, ignorera de oförändrade områdena även om dessa innehåller objekt som kan klassificeras och slutligen klassificera ändringen. Tillvägagångssättet som valdes var att försöka reducera problemet som maskininlärningsalgoritmen, i detta fall ett artificiellt neuralt nätverk, behöver hantera genom att subtrahera bilderna innan de hanterades av det neurala nätverket. I teorin bör detta ta hand om både objektslokaliseringen och filtreringen av ointressanta objekt, vilket endast lämnar klassificeringen till det neurala nätverket. Ett sådant tillvägagångssätt förenklar problemet som det neurala nätverket behöver lösa avsevärt och resulterar i minskat behov av träningsdata, samtidigt som datainsamling hålls relativt snabbt och simpelt. Flera olika modeller utvärderades och teorier om specialanpassningar av neurala nätverk för denna uppgift evaluerades. En testnoggrannhet på som bäst 78.9% uppnåddes med begränsad datamängd om ca 1000 bilder med 10 klasser. Denna prestation erhölls med ett siamesiskt neuralt nätverk baserat på VGG19 med tripletförlust och träningsdata som använde subtraktion av bilder som grund för framställning av grundsanningsmasker (eng. Ground truth masks) multiplicerade med bilden innehållande förändringen.
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Computer Vision Based Model for Art Skills AssessmentAlghamdi, Asaad 20 December 2022 (has links)
No description available.
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Multi-Template Temporal Siamese Network for Visual Object TrackingSekhavati, Ali 04 January 2023 (has links)
Visual object tracking is the task of giving a unique ID to an object in a video frame, understanding whether it is present or not in a current frame and if it is present, precisely localizing its position. There are numerous challenges in object tracking, such as change of illumination, partial or full occlusion, change of target appearance, blurring caused by camera movement, presence of similar objects to the target, changes in video image quality through time, etc. Due to these challenges, traditional computer vision techniques cannot perform high-quality tracking, especially for long-term tracking. Almost all the state-of-the-art methods in object tracking use artificial intelligence nowadays, and more specifically, Convolutional Neural Networks. In this work, we present a Siamese based tracker which is different from previous works in two ways. Firstly, most of the Siamese based trackers takes the target in the first frame as the ground truth. Despite the success of such methods in previous years, it does not guarantee robust tracking as it cannot handle many of the challenges causing change in target appearance, such as blurring caused by camera movement, occlusion, pose variation, etc. In this work, while keeping the first frame as a template, we add five other additional templates that are dynamically updated and replaced considering target classification score in different frames. Diversity, similarity and recency are criteria to choose the members of the bag. We call it as a bag of dynamic templates. Secondly, many Siamese based trackers are vulnerable to mistakenly tracking another similar looking object instead of the intended target. Many researchers proposed computationally expensive approaches, such as tracking all the distractors and the given target and discriminate them in every frame. In this work, we propose an approach to handle this issue by estimate the next frame position by using the target's bounding box coordinates in previous frames. We use temporal network with past history of several previous frames, measure classification scores of candidates considering templates in the bag of dynamic templates and use tracker sequential confidence value which shows how confident the tracker has been in previous frames. We call it as robustifier that prevents the tracker from continuously switching between the target and possible distractors with this hypothesis in mind. Extensive experiments on OTB 50, OTB 100 and UAV20L datasets demonstrate the superiority of our work over the state-of-the-art methods.
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Environmental Modulation of the Onset of Air-breathing of the Siamese Fighting Fish and the Blue GouramiMendez Sanchez, Jose Fernando 12 1900 (has links)
This study determined the effect of hypoxia on air-breathing onset and physiological and morphological characters in larvae of the air breathing fishes Trichopodus trichopterus and Betta splendens. Larvae were exposed intermittently (12/12 h daily) to 20, 17, and 14 kPa of PO2 from 1 to 40 days post-fertilization. Survival, onset of air breathing, wet body mass, O2, Pcrit were measured every 5 dpf. Hypoxia advanced by 4 days, and delayed by 9 days, the onset of air breathing in Betta and Trichopodus, respectively. Hypoxia increased larval body length, wet mass, and labyrinth organ respiratory surface of Betta, but did not affect these factors in Trichopodus. Hypoxic exposure increased O2 by 50-100% at each day throughout larval development in Betta, but had no effect on larval Trichopodus. Hypoxia decreased Pcrit in Betta by 37%, but increased Pcrit in Trichopodus by 70%. Larval Betta reared in hypoxia showed a modified heart rate:opercular rate ratio (3:1 to 2:1), but these changes did not occur in Trichopodus. Compared to Betta, the blood of Trichopodus had a higher P50 and much smaller Bohr and Root effects. These interspecific differences are likely due to ecophysiological differences: Betta is a non- obligatory air-breather after 36 dpf with a slow lifestyle reflected in its low metabolism, while Trichopodus is an obligatory air-breather past 32 dpf with an athletic fast lifestyle and accompanying high metabolism.
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