60 research outputs found

    A Scheme for Automatically Building 3D Morphometric Anatomical Atlases: application to a Skull Atlas

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    International audienceWe present a general scheme for automatically building a morphometric anatomical atlas. We detail each stage of the method, including the non-rigid registration algorithm, three-dimensional line averaging and statistical processes. We apply the method to obtain a quantitative atlas of skull crest lines. Finally, we use the resulting atlas to study a craniofacial disease; we show how we can obtain qualitative and quantitative results by contrasting a skull affected by a mandible deformation with the atlas

    Design and evaluation of a VLIW processor for real-time systems

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    Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2016.Atualmente, aplicações de tempo estão tornando-se cada vez mais complexas e, conforme os requisitos destes sistemas aumentam, maior é a demanda por capacidade de processamento. Contudo, o correto funcionamento destas aplicações não está em função somente da correta resposta lógica, mas também no tempo que ela é produzida. O projeto de processadores de propósito geral gera dificuldades para análises de tempo real devido ao seu comportamento não determinista causado pelo uso de memórias cache, previsores de fluxo dinâmicos, execução especulativa e fora de ordem. Nesta tese, investiga-se uma arquitetura de processador Very-Long Instruction Word (VLIW) especificamente projetada para sistemas de tempo real considerando sua análise do pior tempo de computação (Worst-case Execution Time WCET). Técnicas para obtenção do WCET para máquinas VLIW são consideradas e quantifica-se a importância de técnicas de hardware como previsor de fluxo estático, predicação, bem como velocidade do processador para instruções complexas como acesso a memória e multiplicação. Arquitetura de memória não faz parte do escopo deste trabalho e para tal utilizamos uma estrutura determinista formada por uma memória cache com mapeamento direto para instruções e uma memória de rascunho (scratchpad) para dados. Nós também consideramos a implementação em VHDL do protótipo para inferir suas características temporais mantendo compatibilidade com o conjunto de instruções (ISA) HP VLIW ST231. Em termos de avaliação, foi utilizado um conjunto representativo de código exemplos da Universidade de Mälardalen que é amplamente utilizado em avaliações de sistemas de tempo real.Abstract : Nowadays, many real-time applications are very complex and as the complexity and the requirements of those applications become more demanding, more hardware processing capacity is necessary. The correct functioning of real-time systems depends not only on the logically correct response, but also on the time when it is produced. General purpose processor design fails to deliver analyzability due to their non-deterministic behavior caused by the use of cache memories, dynamic branch prediction, speculative execution and out-of-order pipelines. In this thesis, we design and evaluate the performance of VLIW (Very Long Instruction Word) architectures for real-time systems with an in-order pipeline considering WCET (Worst-case Execution Time) performance. Techniques on obtaining the WCET of VLIW machines are also considered and we make a quantification on how important are hardware techniques such as static branch prediction, predication, pipeline speed of complex operations such as memory access and multiplication for high-performance real-time systems. The memory hierarchy is out of scope of this thesis and we used a classic deterministic structure formed by a direct mapped instruction cache and a data scratchpad memory. A VLIW prototype was implemented in VHDL from scratch considering the HP VLIW ST231 ISA. We also show some compiler insights and we use a representative subset of the Mälardalen s WCET benchmarks for validation and performance quantification. Supporting our objective to investigate and evaluate hardware features which reconcile determinism and performance, we made the following contributions: design space investigation and evaluation regarding VLIW processors, complete WCET analysis for the proposed design, complete VHDL design and timing characterization, detailed branch architecture, low-overhead full-predication system for VLIW processors

    Animal Welfare Assessment

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    This Special Issue provides a collection of recent research and reviews that investigate many areas of welfare assessment, such as novel approaches and technologies used to evaluate the welfare of farmed, captive, or wild animals. Research in this Special Issue includes welfare assessment related to pilot whales, finishing pigs, commercial turkey flocks, and dairy goats; the use of sensors or wearable technologies, such as heart rate monitors to assess sleep in dairy cows, ear tag sensors, and machine learning to assess commercial pig behaviour; non-invasive measures, such as video monitoring of behaviour, computer vision to analyse video footage of red foxes, remote camera traps of free-roaming wild horses, infrared thermography of effort and sport recovery in sport horses; telomere length and regulatory genes as novel biomarkers of stress in broiler chickens; the effect of environment on growth physiology and behaviour of laboratory rare minnows and housing system on anxiety, stress, fear, and immune function of laying hens; and discussions of natural behaviour in farm animal welfare and maintaining health, welfare, and productivity of commercial pig herds

    ECOHYDROLOGICAL MODELING OF BEAVER DAMS

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    Beavers (Castor canadensis and C. fiber) are expanding in their native range in North America and Eurasia and are expanding their range into urban environments and the Arctic tundra. Outside their natural range, they are also in Southern Patagonia because of historic releases in the fur industry. Given the broad geographical span of this expansion, it is critical to understand and predict the hydrology of beaver-dominated landscapes. Beavers build dams that modify the water balance and modulate streamflow through different flow states, which might result in drought and flood mitigation. To date, four published hydrological models have been developed to predict these impacts; however, these models were unable to represent dam variability and dynamics. In this study, a model specific to beaver dams was developed to predict the impacts of beaver dams on hydrology by including the flow state dynamics and the heterogeneity of dams and ponds. First, through the instrumentation of the montane peatland of Sibbald Fen in the Canadian Rocky Mountains, I determined that flow state changes of beaver dams are dynamic on a much shorter scale than previously documented. The shifts from one flow state to another happen regularly, have limited synchronicity within dam sequences, and can be predicted. In Sibbald, 66% to 80% of the flow state changes coincided with rainfall-runoff triggers and no changes were associated with biota using the dams. Following this flow state dynamic, I then developed an open-source model called BeaverPy in Python to simulate key features of dams and their impact on hydrology. Five single flow states and mixed combinations were included to identify their dynamics using a vector-based modeling approach, which accounted for changes in dam structures. Simulating individual and in-sequence dams from Sibbald Fen demonstrated that BeaverPy successfully models streamflow modulation by beaver dams, water storage in ponds, and flow state changes. Metrics for simulated vs. measured behavior for streamflow showed a good agreement in root mean squared error (g in beaver-dominated environments, thereby enhancing the understanding of how to incorporate beaver dams into flood mitigation and stream restoration projects and climate change initiatives

    Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009

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    Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence
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