Examination of s cene of crime When thinking about the topic of my diploma thesis I had quite clear idea that the topic should be from the area of crown-low or criminology, because both of them are my favourite. I have chosen the topic "Examination of scene of crime", because I think that examination of scene of crime is one of the most important processes within the criminal procedure and only with the correct and detailed examination the criminal can be convicted for perpetrated crime. The significance of examination the scene of crime I see in the fact, that it is the only way, how institutions operating in criminal procedures can get information about the relevant incident directly. The thesis is composed of five chapters, which enable us step by step understand and learn about the examination of scene of crime. The first chapter is an introduction and considers the examination as a criminalistic method. This chapter is divided into six parts. The first one explains the conception, principle and signification of examination. Second part is focused on the legal frame of examination. The third part describes types of examination. The fourth part mentions fundamentals of examination, the fifth shows the subjects of examination and the sixth part is dealing with the negative circumstances of examination....

This thesis deals with the music group Extempore since its foundation by Jaroslav Jeronym Neduha in 1973 until its annulment by Mikolas Chadima in 1981. The thesis shows the important moments of the group and its members. Jaroslav Jeronym Neduha was Extempore's frontman by the year 1979 then he left the group and its management handed to Mikolas Chadima. Both gave to Extempore its characteristic style in the musical aspect, lyrics and performance. Extempore gained lots of fans, so the State Security focused on them as a obnoxius music group. The thesis has the aim to reveal Extempore's role in Czech musical underground. Firstly I defined alternative culture in relation to underground and official culture with focus to the music. Also I described Prague's unofficial big beat scene between 1973 - 1981. Primarily the thesis is focused on alternative music scene and musical underground. The review also contains other noncommercial movements during that time - folk association Safran and younger musical movement New Wave that inspirated Chadima's Extempore. Since the 1979 Extempore has been more and more pressed to the illegality until they got ban to perform their music in any Prague's club. Anyways they pushed for public performances and they kept up in free creation. An important outcome is fact that...

Partant du sonnet « À une passante » de Baudelaire pour aboutir aux écrits de Breton en parcourant un florilège de textes traitant de la première rencontre, nous avons exploré dans un premier temps les spécificités de la scène poétique relativement à la scène romanesque étudiée par Jean Rousset. Dans un second temps, nous avons cherché à saisir les nouvelles caractéristiques du scénario moderne par rapport aux configurations classique et romantique. En adressant à l’inconnue croisée dans une rue de Paris le poème qu’elle a suscité l’instant d’un coup d’œil fugitif, Baudelaire crée un poncif amoureux nouveau. Dans ce sonnet, le cadre spatio-temporel, les acteurs, la rencontre et l’amour portent l’empreinte de la modernité jusqu’à en devenir l’emblème. D’autres poètes reprendront sur le mode de l’imitation ou de la variation le modèle baudelairien, et notamment la figure de la passante. Le poème de la première rencontre devient alors le lieu de la célébration d’une nouvelle figure féminine mais surtout d’une nouvelle lyrique qui n’est rien de moins qu’une érotique de la distance séparatrice. Chaque poème nous montre à sa façon que l’unique scène signifiante est celle du désir (qui déchire le poète et son lecteur) et que l’écriture d’une rencontre sans issue est l’ultime échappatoire contre l’absence. / Starting from the sonnet "To a passer-by" of Baudelaire to lead to the writings of Breton by traversing a group of texts treating of the first meeting, we initially explored specificities of the poetic scene compared to the romantic scene studied by Jean Rousset. In a second step, we sought to understand the new features of modern scenario compared ti the classical and romantic settings. By sending to unknown crossed in a street of Paris the poem that she aroused the moment all at once of escaped eye, Baudelaire creates a new loving common place. In this sonnet, the spatiotemporal frame, the actors, the meeting and the love carry the imprint of the modernity until become the emblem. Other poets will take back on the mode of simulation or of variation the baudelerian model, and notably the figure of the passer-by. The poem of the first meeting becomes then the place of the celebration of a new feminine figure but especially of the lyric news which is nothing at least than an erotic of dividing distance.

The topic of my thesis is the methodology of murder investigation. The thesis deals with trace evidence formed during commission of the crime of murder, typical investigative situations faced by crime investigators, and some of the subsequent acts. The aim of this thesis is to familiarize with the offense of murder and the specifics of crime scene investigation. Furthermore, this work provides a summary of the knowledge obtained through the study of monographs, articles in professional journals, and some of the court relevant decisions. Finally, the work further outlines some selected questions and points out the potential problems related to crime scene investigation. The thesis consists of five chapters, which are further divided in to subchapters. Following the introduction, the first chapter describes the murder under criminal law and outlines the various classifications of murder, which include plain murder, murder committed with forethought or prior consideration, and manslaughter. Moreover, the chapter discusses the legislation pertinent to the concept of murder, and explores its roots under the criminal law of England and Wales. The second chapter describes the various disciplines of criminalistics. Additionally, the chapter provides an assessment of murder investigation by exploring...

Approved for public release, distribution is unlimited / Terrain classification is studied here using the tool of texture analysis of high-spatial resolution panchromatic imagery. This study analyzes the impact and effectiveness of texture analysis on terrain classification within the Elkhorn Slough Estuary and surrounding farmlands within the central California coastal region. Ikonos panchromatic (1 meter) and multispectral (4 meter) imagery data are examined to determine the impact of adding texture analysis to the standard MSI classification approaches. Spectral Angle Mapper and Maximum Likelihood classifiers are used. Overall accuracy rates increased with the addition of the texture processing. The classification accuracy rate rose from 81.0% for the MSI data to 83.9% when the additional texture measures were added. Modest accuracy (55%) was obtained from texture analysis alone. The addition of textural data also enhanced the classifier's ability to discriminate between several different woodland classes contained within the image. / Lieutenant Commander, United States Navy

<p>Alzheimer’s disease (AD), is a devastating neurodegenerative disorder that destroys the patient’s ability to perform daily living task and eventually, takes their lives. Currently, there are 5.8 million people in North America that suffer from AD. This number is projected to by 13.8 million by the year of 2050. For many years, researchers have been dedicated on performing automated diagnosis based on neuroimaging. There are critical needs in two aspects of AD: 1) computer-based AD classification with MRI images; 2) computer-based tools/system to enhance the AD patient’s quality of life. We are addressing these two gaps via two specific objectives in this study.</p> <p>For objective 1, the task is to develop a machine-learning based intelligent model for classification of AD conditions (Normal Control [NC], Mild Cognitive Impairment [MCI], Alzheimer’s disease [AD]) based on MRI images. Specifically, four different deep learning models were developed and assessed. The overall average accuracy for AD classification is 81.5%, provided by Multi-Layer-Output model.</p> <p>For objective 2, a deep learning model was developed and evaluated to recognitze three specific type of indoor scenes (bedroom, living room and dining room). An accuracy of 97% was obtained.</p> <p>This study showed the potential of application in deep learning models for two different aspects of AD - disease classification and intelligent model-based assistive device for AD patients. Further research and development activities are recommended to further validate these findings on larger and different datasets.</p>

A segmentação automática de vídeo em cenas é um problema atual e relevante dado sua aplicação em diversos serviços ligado à área de multimídia. Dentre as diferentes técnicas reportadas pela literatura, as multimodais são consideradas mais promissoras, dado a capacidade de extrair informações de diferentes mídias de maneira potencialmente complementar, possibilitando obter segmentações mais significativas. Ao usar informações de diferentes naturezas, tais técnicas enfrentam dificuldades para modelar e obter uma representação combinada das informações ou com elevado custo ao processar cada fonte de informação individualmente. Encontrar uma combinação adequada de informação que aumente a eficácia da segmentação a um custo computacional relativamente baixo torna-se um desafio. Paralelamente, abordagens baseadas em Aprendizagem Profunda mostraram-se eficazes em uma ampla gama de tarefas, incluindo classificação de imagens e vídeo. Técnicas baseadas em Aprendizagem Profunda, como as Redes Neurais Convolucionais (CNNs), têm alcançado resultados impressionantes em tarefas relacionadas por conseguirem extrair padrões significativos dos dados, incluindo multimodais. Contudo, CNNs não podem aprender adequadamente os relacionamentos entre dados que estão temporalmente distribuídos entre as tomadas de uma mesma cena. Isto pode tornar a rede incapaz de segmentar corretamente cenas cujas características mudam entre tomadas. Por outro lado, Redes Neurais Recorrentes (RNNs) têm sido empregadas com sucesso em processamento textual, pois foram projetadas para analisar sequências de dados de tamanho variável e podem melhor explorar as relações temporais entre as características de tomadas relacionadas, potencialmente aumentando a eficácia da segmentação em cenas. Há uma carência de métodos de segmentação multimodais que explorem Aprendizagem Profunda. Assim, este trabalho de doutorado propõe um método automático de segmentação de vídeo em cenas que modela o problema de segmentação como um problema de classificação. O método conta com um modelo que combina o potencial de extração de padrões das CNNs com o processamento de sequencias das RNNs. O modelo proposto elimina a dificuldade de modelar representações multimodais das diferentes informações de entrada além de permitir instanciar diferentes abordagens para fusão multimodal (antecipada ou tardia). Tal método foi avaliado na tarefa de segmentação em cenas utilizando uma base de vídeos pública, comparando os resultados obtidos com os resultados de técnicas em estado-da-arte usando diferentes abordagens. Os resultados mostram um avanço significativo na eficácia obtida. / Automatic video scene segmentation is a current and relevant problem given its application in various services related to multimedia. Among the different techniques reported in the literature, the multimodal ones are considered more promising, given the ability to extract information from different media in a potentially complementary way, allowing for more significant segmentations. By processing information of different natures, such techniques faces difficulties on modeling and obtaining a combined representation of information and cost problems when processing each source of information individually. Finding a suitable combination of information that increases the effectiveness of segmentation at a relatively low computational cost becomes a challenge. At the same time, approaches based on Deep Learning have proven effective on a wide range of tasks, including classification of images and video. Techniques based on Deep Learning, such as Convolutional Neural Networks (CNNs), have achieved impressive results in related tasks by being able to extract significant patterns from data, including multimodal data. However, CNNs can not properly learn the relationships between data temporarily distributed among the shots of the same scene. This can lead the network to become unable to properly segment scenes whose characteristics change among shots. On the other hand, Recurrent Neural Networks (RNNs) have been successfully employed in textual processing since they are designed to analyze variable-length data sequences and can be developed to better explore the temporal relationships between low-level characteristics of related shots, potentially increasing the effectiveness of scene segmentation. There is a lack of multimodal segmentation methods exploring Deep Learning. Thus, this thesis proposes an automatic method for video scene segmentation that models the problem of segmentation as a classification problem. The method relies on a model developed to combine the potential for extracting patterns from CNNs with the potential for sequence processing of the RNNs. The proposed model, different from related works, eliminates the difficulty of modeling multimodal representations of the different input information, besides allowing to instantiate different approaches for multimodal (early or late) fusion. This method was evaluated in the scene segmentation task using a public video database, comparing the results obtained with the results of state-of-the-art techniques using different approaches. The results show a significant advance in the efficiency obtained.

Scene recognition is a hot research topic in the field of image recognition. It is necessary that we focus on the research on scene recognition, because it is helpful to the scene understanding topic, and can provide important contextual information for object recognition. The traditional approaches for scene recognition still have a lot of shortcomings. In these years, the deep learning method, which uses convolutional neural network, has got state-of-the-art results in this area. This thesis constructs a model based on multi-layer feature extraction of CNN and transfer learning for scene recognition tasks. Because scene images often contain multiple objects, there may be more useful local semantic information in the convolutional layers of the network, which may be lost in the full connected layers. Therefore, this paper improved the traditional architecture of CNN, adopted the existing improvement which enhanced the convolution layer information, and extracted it using Fisher Vector. Then this thesis introduced the idea of transfer learning, and tried to introduce the knowledge of two different fields, which are scene and object. We combined the output of these two networks to achieve better results. Finally, this thesis implemented the method using Python and PyTorch. This thesis applied the method to two famous scene datasets. the UIUC-Sports and Scene-15 datasets. Compared with traditional CNN AlexNet architecture, we improve the result from 81% to 93% in UIUC-Sports, and from 79% to 91% in Scene- 15. It shows that our method has good performance on scene recognition tasks.

Este trabalho tem como objetivo desenvolver um método de segmentação de cenas em vídeos digitais que trate segmentos semânticamente complexos. Como prova de conceito, é apresentada uma abordagem multimodal que utiliza uma definição mais geral para cenas em telejornais, abrangendo tanto cenas onde âncoras aparecem quanto cenas onde nenhum âncora aparece. Desse modo, os resultados obtidos da técnica multimodal foram signifiativamente melhores quando comparados com os resultados obtidos das técnicas monomodais aplicadas em separado. Os testes foram executados em quatro grupos de telejornais brasileiros obtidos de duas emissoras de TV diferentes, cada qual contendo cinco edições, totalizando vinte telejornais / This work aims to develop a method for scene segmentation in digital video which deals with semantically complex segments. As proof of concept, we present a multimodal approach that uses a more general definition for TV news scenes, covering both: scenes where anchors appear on and scenes where no anchor appears. The results of the multimodal technique were significantly better when compared with the results from monomodal techniques applied separately. The tests were performed in four groups of Brazilian news programs obtained from two different television stations, containing five editions each, totaling twenty newscasts

Este trabalho investiga o espaço da cena onde há a presença de elementos aéreos do circo e ilustra, por meio da trajetória e das criações de uma das primeiras companhias cênicas circenses na cidade de São Paulo, o que é um espaço em movimento. Um breve resgate da história das artes do circo, com ênfase na suspensão dos corpos e nas acrobacias aéreas, é desenvolvido para abordar as questões sobre os desenhos e formas específicas e circenses de habitar o espaço da cena. Uma escritura no espaço tridimensional, que é constantemente modificada pela relação do movimento dos corpos no ar, é exemplificada através do histórico da Companhia Cênica Nau de Ícaros. Um olhar íntimo da pesquisadora, a imersão em diversos espetáculos dessa Companhia e a gênese do espetáculo Tirando os pés do chão descrevem uma forma peculiar de ocupar a cena e desvendam os caminhos de um espaço da cena que sofre influência direta do movimento gerado pelos atores-performers e pela cenografia específica circense. / This work investigates the space of the scene where there is the presence of aerial elements of the circus and illustrates, through the trajectory and creations of one of the first circus performing companies in the city of São Paulo, what is a space in movement. A brief rescue of the circus arts history, with emphasis on body suspension and aerial acrobatics, is developed to address questions about the specific circus designs and ways of inhabiting the scene space. A writing in three-dimensional space, which is constantly modified by the relation of the motion of bodies in the air, is exemplified through the history of the Scenic Company Nau de Ícaros. An intimate look of the researcher, the immersion in several spectacles of this Company and the genesis of the spectacle Taking the feet off the floor describes a peculiar way of occupying the scene and unveils the paths of a space of the scene that undergoes direct influence of the movement generated by the actors-performers and the specific circus scenography.