Global ETD Search

151	"I Won't Let Anyone Come Between Us" Representations of Mental Illness, Queer Identity, and Abjection in High Tension Wise, Krista Michelle 10 April 2014 (has links) No description available. Film Studies High Tension Alexandre Aja horror slasher slasher films queer identity Julia Kristeva mental illness queer representation mental illness representation cultural studies film studies Bowling Green State University Krista Wise Popular Culture
152	Approximation of Information Rates in Non-Coherent MISO wireless channels with finite input signals Bothenna, Hasitha Imantha January 2017 (has links) No description available. Mathematics Electrical Engineering Computer Engineering Cumulative Distribution Function Channel State Information at Receiver Channel State Information at Transmitter Mutual Information Multiple Input Single Output Multiple Input Multiple Output Piece Wise Linear Curve Fitting
153	Nonlinear dynamics of one-way clutches and dry friction tensioners in belt-pulley systems Zhu, Farong 25 September 2006 (has links) No description available. Engineering, Mechanical Tensioner Dry friction Harmonic balance method Arc-length continuation Piece-wise linear system Belt-pulley system Serpentine belt Front end accessory drive Perturbation analysis Nonlinear dynamics Softening nonlinearity Dynamic analysis
154	[pt] APLICAÇÕES DE APRENDIZADO PROFUNDO NO MONITORAMENTO DE CULTURAS: CLASSIFICAÇÃO DE TIPO, SAÚDE E AMADURECIMENTO DE CULTURAS / [en] APPLICATIONS OF DEEP LEARNING FOR CROP MONITORING: CLASSIFICATION OF CROP TYPE, HEALTH AND MATURITY GABRIEL LINS TENORIO 18 May 2020 (has links) [pt] A eficiência de culturas pode ser aprimorada monitorando-se suas condições de forma contínua e tomando-se decisões baseadas em suas análises. Os dados para análise podem ser obtidos através de sensores de imagens e o processo de monitoramento pode ser automatizado utilizando-se algoritmos de reconhecimento de imagem com diferentes níveis de complexidade. Alguns dos algoritmos de maior êxito estão relacionados a abordagens supervisionadas de aprendizagem profunda (Deep Learning) as quais utilizam formas de Redes Neurais de Convolucionais (CNNs). Nesta dissertação de mestrado, empregaram-se modelos de aprendizagem profunda supervisionados para classificação, regressão, detecção de objetos e segmentação semântica em tarefas de monitoramento de culturas, utilizando-se amostras de imagens obtidas através de três níveis distintos: Satélites, Veículos Aéreos Não Tripulados (UAVs) e Robôs Terrestres Móveis (MLRs). Ambos satélites e UAVs envolvem o uso de imagens multiespectrais. Para o primeiro nível, implementou-se um modelo CNN baseado em Transfer Learning para a classificação de espécies vegetativas. Aprimorou-se o desempenho de aprendizagem do transfer learning através de um método de análise estatística recentemente proposto. Na sequência, para o segundo nível, implementou-se um algoritmo segmentação semântica multitarefa para a detecção de lavouras de cana-de-açúcar e identificação de seus estados (por exemplo, saúde e idade da cultura). O algoritmo também detecta a vegetação ao redor das lavouras, sendo relevante na busca por ervas daninhas. No terceiro nível, implementou-se um algoritmo Single Shot Multibox Detector para detecção de cachos de tomate. De forma a avaliar o estado dos cachos, utilizaram-se duas abordagens diferentes: uma implementação baseada em segmentação de imagens e uma CNN supervisionada adaptada para cálculos de regressão capaz de estimar a maturação dos cachos de tomate. De forma a quantificar cachos de tomate em vídeos para diferentes estágios de maturação, empregou-se uma implementação de Região de Interesse e propôs-se um sistema de rastreamento o qual utiliza informações temporais. Para todos os três níveis, apresentaram-se soluções e resultados os quais superam as linhas de base do estado da arte. / [en] Crop efficiency can be improved by continually monitoring their state and making decisions based on their analysis. The data for analysis can be obtained through images sensors and the monitoring process can be automated by using image recognition algorithms with different levels of complexity. Some of the most successful algorithms are related to supervised Deep Learning approaches which use a form of Convolutional Neural Networks (CNNs). In this master s dissertation, we employ supervised deep learning models for classification, regression, object detection, and semantic segmentation in crop monitoring tasks, using image samples obtained through three different levels: Satellites, Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). Both satellites and UAVs levels involve the use of multispectral images. For the first level, we implement a CNN model based on transfer learning to classify vegetative species. We also improve the transfer learning performance by a newly proposed statistical analysis method. Next, for the second level, we implement a multi-task semantic segmentation algorithm to detect sugarcane crops and infer their state (e.g. crop health and age). The algorithm also detects the surrounding vegetation, being relevant in the search for weeds. In the third level, we implement a Single Shot Multibox detector algorithm to detect tomato clusters. To evaluate the cluster s state, we use two different approaches: an implementation based on image segmentation and a supervised CNN regressor capable of estimating their maturity. In order to quantify the tomato clusters in videos at different maturation stages, we employ a Region of Interest implementation and also a proposed tracking system which uses temporal information. For all the three levels, we present solutions and results that outperform state-of-the art baselines. [pt] APRENDIZADO PROFUNDO [pt] AGRICULTURA DE PRECISAO [pt] SEGMENTACAO SEMANTICA [pt] REDES NEURAIS CONVOLUCIONAIS [pt] TRANSFERENCIA DE APRENDIZADO [en] DEEP LEARNING [en] PRECISION AGRICULTURE [en] PIXEL-WISE SEMANTIC SEGMENTATION [en] CONVOLUTIONAL NEURAL NETWORKS [en] TRANSFER LEARNING
155	Deep Convolutional Neural Networks for Real-Time Single Frame Monocular Depth Estimation Schennings, Jacob January 2017 (has links) Vision based active safety systems have become more frequently occurring in modern vehicles to estimate depth of the objects ahead and for autonomous driving (AD) and advanced driver-assistance systems (ADAS). In this thesis a lightweight deep convolutional neural network performing real-time depth estimation on single monocular images is implemented and evaluated. Many of the vision based automatic brake systems in modern vehicles only detect pre-trained object types such as pedestrians and vehicles. These systems fail to detect general objects such as road debris and roadside obstacles. In stereo vision systems the problem is resolved by calculating a disparity image from the stereo image pair to extract depth information. The distance to an object can also be determined using radar and LiDAR systems. By using this depth information the system performs necessary actions to avoid collisions with objects that are determined to be too close. However, these systems are also more expensive than a regular mono camera system and are therefore not very common in the average consumer car. By implementing robust depth estimation in mono vision systems the benefits from active safety systems could be utilized by a larger segment of the vehicle fleet. This could drastically reduce human error related traffic accidents and possibly save many lives. The network architecture evaluated in this thesis is more lightweight than other CNN architectures previously used for monocular depth estimation. The proposed architecture is therefore preferable to use on computationally lightweight systems. The network solves a supervised regression problem during the training procedure in order to produce a pixel-wise depth estimation map. The network was trained using a sparse ground truth image with spatially incoherent and discontinuous data and output a dense spatially coherent and continuous depth map prediction. The spatially incoherent ground truth posed a problem of discontinuity that was addressed by a masked loss function with regularization. The network was able to predict a dense depth estimation on the KITTI dataset with close to state-of-the-art performance. deep learning machine learning mono vision system lightweight CNN convolutional neural network depth estimation lidar kitti vehicle camera mono camera camera real-time real time ad autonomous driving adas advanced driver assistance systems mono depth computer vision regression pixel-wise pixel wise object detection general object detection pedestrian detection vehicle detection supervised learning supervised tensorflow python keras opencv autoliv
156	Pharmacological studies on the contribution of the neuropeptide proctolin to the cephalic control of singing behavior in grasshopper Chorthippus biguttulus (L.1758) / Pharmakologische Untersuchungen zu der Beteiligung des Neuropeptides Proctolin an der Cephalen Kontrolle der Stridulation bei der Heuschreke Chorthippus biguttulus (L.1758) / Фарамакологично изследване на ролята на невропептида проктолин в мозъчния контрол на стридулацията (пеенето) при скакалеца Chorthippus biguttulus (L.1758) Vezenkov, Stoyan Raykov 02 November 2004 (has links) No description available. 570 Biowissenschaften, Biologie Mathematics and Computer Science neuropeptide proctolin singing behavior stridulation Chorthippus biguttulus insect brain neuronal circuit phonotactic approach step-wise making decision mAChR nAChR co-transmission modulation oscillation glutamate central pattern generator signal transduction glycine GABA histamine dopamine AC PLC PKC Ca2+ signaling Li+ pharma neuropeptide proctolin singing behavior stridulation Chorthippus biguttulus insect brain neuronal circuit phonotactic approach step-wise making decision mAChR nAChR co-transmission modulation oscillation glutamate central pattern generator signal transduction glycine GABA histamine dopamine AC PLC PKC Ca2+ signaling Li+ pharma 42.63 Tierphysiologie
157	Cotton Mathers's Wonders of the Invisible World: An Authoritative Edition Wise, Paul Melvin 12 January 2005 (has links) ABSTRACT Although Cotton Mather, as the official chronicler of the 1692 Salem witch trials, is infamously associated with those events, and excerpts from his apologia on Salem, Wonders of the Invisible World, are widely anthologized today, no annotated critical edition of the entire work has appeared in print since the nineteenth century. This present edition of Wonders seeks to remedy this lacuna in modern scholarship. In Wonders, Mather applies both his views on witchcraft and on millennialism to events at Salem. This edition to Mather's Wonders presents this seventeenth-century text beside an integrated theory of the initial causes of the Salem witch panic. The juxtaposition of the probable natural causes of Salem's bewitchment with Mather's implausible explanations exposes the disingenuousness of his writing about Salem. My theory of what happened at Salem includes the probability that a group of conspirators led by the Rev. Samuel Parris deliberately orchestrated the "witchcraft" and that a plant, the thorn apple, used in Algonquian initiation rites, caused the initial symptoms of bewitchment (39-189). Furthermore, key spectral evidence used at the Salem witch trials and recorded by Mather in Wonders appears to have been generated by intense nightmares, commonly thought at the time to be witch visitations, resulting from what is today termed sleep paralysis (215-310). This dissertation provides a detailed look at some of the testimony given in the Salem court records and in Wonders of the Invisible World as it relates to the interpretation in folklore of the phenomenology of nightmares associated with sleep paralysis. The third chapter of this dissertation focuses extensively on Mather's text as a disingenuous response to the Salem witch trials (320-456). The final section of chapter three posits a "Scythian" or Eurasian connection between Swedish and Salem witchcraft. Similarities in shamanic practices among respective indigenous populations of Lapland, Eurasia, Asia, and New England, caused the devil's involvement in both the visible and invisible worlds to appear more than theoretical to writers like Jose Acosta, Johannes Scheffer, Nicholas Fuller, Joseph Mede, Anthony Horneck, and Cotton Mather, inducing Mather to include a lengthy abstract of the Swedish account in Wonders (404-449). folk magic folklore witchcraft Salem Cotton Mather Sweden Lapland Algonquian Indians Native Americans Samuel Parris jimson weed thorn apple datura stramonium poisoning initiation ceremonies nightmares huskanaw Wonders of the Invisible World fly-agaric mushroom reindeer Sami shamanism drums Paul Wise Georgia State University Doctor of Philosophy
158	Electricity in Rural Areas of North Texas Greathouse, Charles Simmons 01 1900 (has links) "This study shows three things: (1) a precedent for the expenditure of public funds to teach electricity in our public high schools has already been established by the school system in the larger school systems of Texas, (2) the rural families living on electrified farms in the North Texas area want instruction of this type given to the boys and girls in their communities, and (3) both the rural people and the professional people of the North Texas area believe that instruction dealing with the use of electricity and electrical equipment had spread until by 1935 more than twenty-one million homes, about eighty percent of the total in America at that time, were electrified, only eleven American farms out of every 100 had central-station electricity. More than five million American farms lacked electric service. "--leaf 50. rural electrification Texas history electricity instruction public school curriculum Baylor County (Tex.) -- History. Archer County (Tex.) -- History. Clay County (Tex.) -- History. Collin County (Tex.) -- History. Denton County (Tex.) -- History. Grayson County (Tex.) -- History. Jack County (Tex.) -- History. Montague County (Tex.) -- History. Wise County (Tex.) -- History. Young County (Tex.) -- History.
159	NATO continuity and change : the Atlantic Alliance as an institution, organization and force by reference to Articles 4, 5, and 6 of the Washington Treaty Branikas, Spyros 12 1900 (has links) Approved for public release; distribution in unlimited. / This thesis examines the evolution of NATO as an institution in the International System by reference to Articles 4, 5 and 6 of the Washington Treaty of 1949. Initially, the thesis considers NATO from an international relations perspective. It then proceeds to examine the institutional evolutionary process of the Alliance since its inception and implementation in 1949. Furthermore, it explores the significance and the meaning of the aforementioned Articles. This thesis utilizes the case study method and refers to four distinct events that have shaped allied policies and strategies: the Suez Crisis of 1956, the establishment of the politico-military consultation process, the Yom Kippur War (1973), and the end of the Cold War (1989-1991). It also examines the allied policies after the events of September 11, 2001. Moreover, it identifies a general pattern of events pertinent to crisis creation inside NATO when the organization is facing a defense issue outside the Euro-Atlantic area. Finally, the thesis concludes that NATO is more than an ordinary military Alliance, as advocated by its longevity, agility and adaptability, which allows the Alliance to maintain a central position in the International System as a robust politico-military organization. / Lieutenant Commander, Hellenic Navy Cold War International relations Military art and science World politics National security NATO Atlantic Alliance Suez Crisis Yom Kippur war Out-of-area operations end of Cold War three Wise Men Afghanistan political consultation Article 4 Article 5 Article 6 North Atlantic Treaty crisis
160	Conscious Conclusions: The Effect of Positive-Attitude Cues on Teacher Candidate Dispositions about Mathematics Baker, Shelletta 01 January 2018 (has links) The purpose of this study was to use elements for developing teacher identity, personal philosophy, beliefs about teaching and learning, and reflection to frame an examination of the effect of Positive-Attitude Cues (PACs) on teacher candidates’(n = 135) mathematics anxiety and expressive writing. Participants were randomly assigned to a treatment (PACs) or control group (No-PAC) and their dispositions about mathematics were examined using the Revised Mathematics Anxiety Rating Scale (MARS-R); which had a Cronbach’s alpha of 0.96 and an expressive writing task before and after the intervention. A significant main effect of test time showed that participants in the posttest condition: (M = 67.54, SD = 19.06) responded with less total mathematics anxiety than participants in the pretest condition (M = 73.22, SD = 19.78), F (1, 133) = 40.61, p < .001, d = -.29; (M = 41.56, SD = 11.82) responded with less learning mathematics anxiety than participants in the pretest condition (M = 45.36, SD = 12.98), F (1, 133) = 38.56, p < .001, d = -.31; and (M = 25.98, SD = 8.03) responded with less mathematics test anxiety than participants in the pretest condition (M = 27.88, SD = 7.74), F (1, 133) = 29.55, p < .001, d = -.24. Also, there was a significant increase in the percentage of positive expressive writing tasks by PAC participants pre (N = 27) (M = .40, SD = .49) versus post (N = 56) (M = .84, SD = .37) intervention; p < .001 (2-sided); and no-PAC participants pre (N = 24) (M = .35, SD = .48) versus post (N = 60) (M = .88, SD = .33) intervention; p < .001 (2-sided). The results of this study can inform leadership and policy related to educator preparation. Thesis University of North Florida UNF Teacher Candidate Dispositions Mathematics Anxiety Positive-Attitude Cues Wise Intervention Curriculum and Instruction Educational Leadership Educational Methods Educational Psychology Secondary Education

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