Vnitřnosti města: pod zemí. Školní interpretace ABSTRACT My diploma thesis deals with subterranean spaces, the insides of a town. It focuses on selected types of a town underground which are described. These types include cellars (common house cellars as well as that of public historical places), a canalization system, metro, catacombs, adits and military underground spaces. I concentrate on the subject through contexts of phenomenology, history, archaeology, literature, and visual arts. The aim of the thesis is mapping subterranean places, trying to find their aspects and using them for a didactic transformation. I try to conceive that by studying the literature as well as by a practical research: I visit several underground places of a different kind. The selected places consist of the personage cellar in Bezděz, the Cemetry church of all Saints in Sedlec - Ossuary, the Corpus Christi Chapel in Kutná Hora, the Old Wastewater Treatment Plant in Bubeneč and the construction tunnel of metro line D in Pankrác. The didactic part transforms basic findings into a number of lessons. These are carried out in a school and out- of-school background. The aim of the didactic project is introducing the topic in its basic forms (mainly cellar, canalization and metro) to the pupils. Hopefully, this can lead them to...

Masters of Science / Much work has been done in building systems that can recognise gestures, e.g. as a component of sign language recognition systems. These systems typically use whole gestures as the smallest unit for recognition. Although high recognition rates have been reported, these systems do not scale well and are computationally intensive. The reason why these systems generally scale poorly is that they recognize gestures by building individual models for each separate gesture; as the number of gestures grows, so does the required number of models. Beyond a certain threshold number of gestures to be recognized, this approach becomes infeasible. This work proposes that similarly good recognition rates can be achieved by building models for subcomponents of whole gestures, so-called cheremes. Instead of building models for entire gestures, we build models for cheremes and recognize gestures as sequences of such cheremes. The assumption is that many gestures share cheremes and that the number of cheremes necessary to describe gestures is much smaller than the number of gestures. This small number of cheremes then makes it possible to recognize a large number of gestures with a small number of chereme models. This approach is akin to phoneme-based speech recognition systems where utterances are recognized as phonemes which in turn are combined into words. We attempt to recognise and classify cheremes found in South African Sign Language (SASL). We introduce a method for the automatic discovery of cheremes in dynamic signs. We design, train and use hidden Markov models (HMMs) for chereme recognition. Our results show that this approach is feasible in that it not only scales well, but it also generalizes well. We are able to recognize cheremes in signs that were not used for training HMMs; this generalization ability is a basic necessity for chemere-based gesture recognition. Our approach can thus lay the foundation for building a SASL dynamic gesture recognition system.

La quantité de données audio disponibles, telles que les enregistrements radio, la musique, les podcasts et les publicités est en augmentation constance. Par contre, il n'y a pas beaucoup d'outils de classification et d'indexation, qui permettent aux utilisateurs de naviguer et retrouver des documents audio. Dans ces systèmes, les données audio sont traitées différemment en fonction des applications. La diversité de ces techniques d'indexation rend inadéquat le traitement simultané de flux audio où différents types de contenu audio coexistent. Dans cette thèse, nous présentons nos travaux sur l'extension de l'approche ALISP, développé initialement pour la parole, comme une méthode générique pour l'indexation et l'identification audio. La particularité des outils ALISP est qu'aucune transcription textuelle ou annotation manuelle est nécessaire lors de l'étape d'apprentissage. Le principe de cet outil est de transformer les données audio en une séquence de symboles. Ces symboles peuvent être utilisés à des fins d'indexation. La principale contribution de cette thèse est l'exploitation de l'approche ALISP comme une méthode générique pour l'indexation audio. Ce système est composé de trois modules: acquisition et modélisation des unités ALISP d'une manière non supervisée, transcription ALISP des données audio et comparaison des symboles ALISP avec la technique BLAST et la distance de Levenshtein. Les évaluations du système proposé pour les différentes applications sont effectuées avec la base de données YACAST et avec d'autres corpus disponibles publiquement pour différentes tâche de l'indexation audio. / The amount of available audio data, such as broadcast news archives, radio recordings, music and songs collections, podcasts or various internet media is constantly increasing. Therefore many audio indexing techniques are proposed in order to help users to browse audio documents. Nevertheless, these methods are developed for a specific audio content which makes them unsuitable to simultaneously treat audio streams where different types of audio document coexist. In this thesis we report our recent efforts in extending the ALISP approach developed for speech as a generic method for audio indexing, retrieval and recognition. The particularity of ALISP tools is that no textual transcriptions are needed during the learning step. Any input speech data is transformed into a sequence of arbitrary symbols. These symbols can be used for indexing purposes. The main contribution of this thesis is the exploitation of the ALISP approach as a generic method for audio indexing. The proposed system consists of three steps; an unsupervised training to model and acquire the ALISP HMM models, ALISP segmentation of audio data using the ALISP HMM models and a comparison of ALISP symbols using the BLAST algorithm and Levenshtein distance. The evaluations of the proposed systems are done on the YACAST and other publicly available corpora for several tasks of audio indexing.

Robotics in rehabilitation provides considerable opportunities to improve the quality of life for persons with disabilities. Computerized and Virtual Environment (VE) training systems for persons with disabilities, many of which utilize the haptic feedback, have gained increasing acceptance in the recent years. Our methodology here is based on creating virtual environments connected to a haptic interface as an input device. This robotic setup introduces the advantages of the haptic rendering features in the environment and also provides tactile feedback to the patients. This thesis aims to demonstrate the efficacy of assistance function algorithms in rehabilitation robotics in virtual environments. Assist functions are used to map limited human input to motions required to perform complex tasks. The purpose is to train individuals in task-oriented applications to insure that they can be incorporated into the workplace. Further, Hidden Markov Model (HMM) based motion recognition and skill learning are used for improving the skill levels of the users. For the Hidden Markov Model based motion recognition, the user's motion intention is combined with environment information to apply an appropriate assistance function. We used this algorithm to perform a commonly used vocational therapy test referred to as the box and the blocks test. The Hidden Markov Model based skill approach can be used for learning human skill and transferring the skill to persons with disabilities. A relatively complex task of moving along a labyrinth is chosen as the task to be modeled by HMM. This kind of training allows a person with disability to learn the skill and improve it through practice. Its application to motion therapy system using a haptic interface helps in improving their motion control capabilities, tremor reduction and upper limb coordination. The results obtained from all the tests demonstrated that various forms of assistance provided reduced the execution times and increased the motion performance in chosen tasks. Two persons with disabilities volunteered to perform the above tasks and both of the disabled subjects expressed an interest and satisfaction with the philosophy behind these concepts.

An early detection of heart disease can save lives, caution individuals and also help to determine the type of treatment to be given to the patients. The first test of diagnosing a heart disease is through auscultation - listening to the heart sounds. The interpretation of heart sounds is subjective and requires a professional skill to identify the abnormalities in these sounds. A medical practitioner uses a stethoscope to perform an initial screening by listening for irregular sounds from the patient's chest. Later, echocardiography and electrocardiography tests are taken for further diagnosis. However, these tests are expensive and require specialized technicians to operate. A simple and economical way is vital for monitoring in homecare or rural hospitals and urban clinics. This dissertation is focused on developing a patient-centered device for initial screening of the heart sounds that is both low cost and can be used by the users on themselves, and later share the readings with the healthcare providers. An innovative mobile health service platform is created for analyzing and classifying heart sounds. Certain properties of heart sounds have to be evaluated to identify the irregularities such as the number of heart beats and gallops, intensity, frequency, and duration. Since heart sounds are generated in low frequencies, human ears tend to miss certain sounds as the high frequency sounds mask the lower ones. Therefore, this dissertation provides a solution to process the heart sounds using several signal processing techniques, identifies the features in the heart sounds and finally classifies them. This dissertation enables remote patient monitoring through the integration of advanced wireless communications and a customized low-cost stethoscope. It also permits remote management of patients' cardiac status while maximizing patient mobility. The smartphone application facilities recording, processing, visualizing, listening, and classifying heart sounds. The application also generates an electronic medical record, which is encrypted using the efficient elliptic curve cryptography and sent to the cloud, facilitating access to physicians for further analysis. Thus, this dissertation results in a patient-centered device that is essential for initial screening of the heart sounds, and could be shared for further diagnosis with the medical care practitioners.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第18055号 / 理博第3933号 / 新制||理||1567(附属図書館) / 30913 / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)准教授 芝内 孝禎, 教授 石田 憲二, 教授 松田 祐司 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

The medical ethics curriculum is an important part of medical education as it helps foster students to become virtuous and compassionate caretakers. The format of the curriculum is intended to expose students to ethical and moral issues early in their careers and allow them to apply their knowledge in clinical situations. However, the implementation of the curriculum is incredibly varied and fraught with challenges. This thesis explores the challenges of the current format of the medical ethics curriculum and the repercussions that will extend throughout medical school and moving into residency and beyond. It will additionally delve into potential solutions that, if implemented conscientiously, can encourage more engaged and thoughtful discussions in the classroom and the clinical setting. It is the ultimate hope that such interventions will result in students’ increased moral development and shape these future physicians into better caretakers, colleagues, and leaders. / Urban Bioethics

In an attempt better to understand the appeal of the Gothic novel during its initial appearance in eighteenth-century England, particularly that of the 'female Gothic'--a sub-genre recently declared by feminist critics such as Claire Kahane, Ellen Moers, and Tania Modleski--this essay considers three novels by Ann Radcliffe, possibly the best-known female writer of her time: The Mysteries of Udolpho (1794), The Romance of the Forest (1791), and The Italian (1797). Beginning with an examination of Radcliffe's unique use of landscapes and her adoption of Burke's Sublime, I postulate a symbology and subtext which address the generally unacknowledged topics of female sexuality and female creativity. The representation of feminine desire, as well as the continued theme of the hidden woman artist, I argue, together comprise the 'hidden discourse' integral to the 'female Gothic' pioneered by Radcliffe. Bearing in mind the emergence in the later eighteenth-century of a large female audience for Radcliffe's novels, l analyse the different physical prospects and personalities associated with heroine and villain as politically polarized 'visions' of reality. The inevitable moral and aesthetic conflict of these visions culminates in the heroine's ultimate triumph over the villain and the patriarchal society he represents. Through this analysis of her fiction's hidden discourse, Radcliffe's contribution to the Gothic genre can be seen as politically subversive, her novels concealing a defiance of her male-dominated culture as well as containing an affirmation of identity for her female readers. / Thesis / Master of Arts (MA)

Lean Production, simply called Lean, is one of the most powerful concepts recently employed by many manufacturers and service providers in order to improve the quality of their products, eliminate any non-value adding activities from operation and reducing the costs of production. Relatively, Lean Services concept is created based on Lean Manufacturing to include service sectors. Many wastes exist within production and potentially all the processes related to that. Seven different types of wastes were being redefined over time to better fit service operations. A significant number of techniques have been defined in the Lean concept; make it possible to execute required actions for achieving such an improvement. Looking closer from different perspectives to operation helps the analyst to find the hidden wastes in the processes. With the help of Lean concept finding bottlenecks and problems will be much easier as wastes are categorized into different forms, so the analyst knows exactly where to look for it. After analyzing the current state, the next effort for executer is to try to eliminate these wastes and optimize the processes by applying Lean and other supply chain techniques. A future state then will be created to solve the problems observed in the current operating state and most importantly this state will offer a much smoother production flow and less wastage in the operation. This thesis is involved with use of Lean and Supply Chain tools in one of the UPS local centers aiming to operate on Lean principles in the end. This will bring the company continues improvement on the processes which helps the company in many aspects.

Indiana University-Purdue University Indianapolis (IUPUI) / Research has repeatedly shown that when groups whose members have varying expertise are combined to make a decision, they tend to discuss common information at a higher rate than unique information, hindering their ability to make the best decision. In response to these findings and the fact that organizations are increasingly using groups rather than individuals to make important decisions, a new intervention was developed based on past research to help groups make better decisions and discuss more unique information. The intervention was developed through three phases to determine which techniques were most powerful. The formal evaluation of the intervention was tested on a total of 228 undergraduate students (44 groups of four and 52 individuals). Groups were randomized into an experimental condition, receiving the intervention, or a control condition. Groups participated in a hidden profile business simulation acting as the top management team of a fictional Hollywood movie studio. Information was distributed so that there was common and unique information for each group. Groups given the intervention made significantly better decisions, shared more unique information, and performed significantly better than individuals. Unique information sharing was positively related to performance and the unique information given to one group member mediated the relationship between the condition and performance. In addition, this study revealed that within the inventory of unique information, different types of information may be more critical in reaching the best possible decision than others. Future research aims and implications are discussed.