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Fiberblender: A Realistic Computer Model Of Nerve Bundles For Simulating And Validating The Acquisition Of Diffusion Tensor Imaging, Teddy Salan
Electronic Theses and Dissertations
Diffusion Tensor Imaging (DTI) is a powerful medical imaging technique that provides a unique method to investigate the structure and connectivity of neural pathways. DTI is a special magnetic resonance imaging (MRI) modality that combines the principles of magnetic resonance with molecular diffusion to trace the motion of water molecules. In the central nervous system, where nerve fibers are packed in highly-directional bundles, these molecules diffuse along the orientation of the fibers. Hence, characterizing the motion of water with DTI delivers a non-invasive in vivo technique to capture the connectivity of nerves themselves. Despite its promises and successful clinical applications …
Chaos And Time Series Analysis: Optimization Of The Poincaré Section And Distinguishing Between Deterministic And Stochastic Time Series, Jeremy George Cavers
Chaos And Time Series Analysis: Optimization Of The Poincaré Section And Distinguishing Between Deterministic And Stochastic Time Series, Jeremy George Cavers
Electronic Theses and Dissertations
This thesis is concerned with chaos theory and the analysis of time series using the Poincar e and Higuchi (P&H) method. The P&H method has been shown to qualitatively di erentiate between deterministic and stochastic time series. This thesis proposes that the P&H method can be extended to also quantitatively di erentiate between deterministic and stochastic time series. This extension of the P&H method was tested on twelve time series: six produced by deterministic chaotic systems and six produced by stochastic processes. Results show that, even with noise, the P&H method can quantitatively di erentiate between these two sets of …
Performance Evaluation Of Remanufacturing Systems, Ronak Savaliya
Performance Evaluation Of Remanufacturing Systems, Ronak Savaliya
Electronic Theses and Dissertations
Implementation of new environmental legislation and public awareness has increased the responsibility on manufacturers. These responsibilities have forced manufacturers to begin remanufacturing and recycling of their goods after they are disposed or returned by customers. Ever since the introduction of remanufacturing, it has been applied in many industries and sectors. The remanufacturing process involves many uncertainties like time, quantity, and quality of returned products. Returned products are time sensitive products and their value drops with time. Thus, the returned products need to be remanufactured quickly to generate the maximum revenue. Every year millions of electronic products return to the manufacturer. …
Sensitivity Based Multiobjective Finite Element Model Calibration With The Results Of Operational Modal Analysis, Mohammad Farshchin
Sensitivity Based Multiobjective Finite Element Model Calibration With The Results Of Operational Modal Analysis, Mohammad Farshchin
Electronic Theses and Dissertations
A new method is developed for finite element model calibration of structures with the results of modal testing. The proposed method applies multi-objective optimization to develop a set of calibrated models and employs sensitivity analysis to analyze and identify the most effective parameters for model calibration. The study consists of a full experimental study on modal identification of structures under ambient vibration conditions and an analytical study on finite element model calibration. The experimental study is focused on operational modal analysis of structures with covariance driven stochastic subspace identification in the time domain and frequency domain decomposition in the frequency …
Acceleration Of Deep Learning On Fpga, Huyuan Li
Acceleration Of Deep Learning On Fpga, Huyuan Li
Electronic Theses and Dissertations
In recent years, deep convolutional neural networks (ConvNet) have shown their popularity in various real world applications. To provide more accurate results, the state-of-the-art ConvNet requires millions of parameters and billions of operations to process a single image, which represents a computational challenge for general purpose processors. As a result, hardware accelerators such as Graphic Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), have been adopted to improve the performance of ConvNet. However, GPU-based solution consumes a considerable amount of power and a traditional RTL design on FPGA requires tedious development that is very time-consuming. In this work, we …
Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3d Indoor Monitoring, Tisha Lafaye Brown
Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3d Indoor Monitoring, Tisha Lafaye Brown
Electronic Theses and Dissertations
As a result of extensive research over the past decade or so, wireless sensor networks (wsns) have evolved into a well established technology for industry, environmental and medical applications. However, traditional wsns employ such sensors as thermal or photo light resistors that are often modeled with simple omni-directional sensing ranges, which focus only on scalar data within the sensing environment. In contrast, the sensing range of a wireless video sensor is directional and capable of providing more detailed video information about the sensing field. Additionally, with the introduction of modern features in non-fixed focus cameras such as the pan, tilt …
Knowledge Migration Strategies For Optimization Of Multi-Population Cultural Algorithm, Panth Parikh
Knowledge Migration Strategies For Optimization Of Multi-Population Cultural Algorithm, Panth Parikh
Electronic Theses and Dissertations
Evolutionary Algorithms (EAs) are meta-heuristic algorithms used for optimization of complex problems. Cultural Algorithm (CA) is one of the EA which incorporates knowledge for optimization. CA with multiple population spaces each incorporating culture and genetic evolution to obtain better solutions are known as Multi-Population Cultural Algorithm (MPCA). MPCA allows to introduce a diversity of knowledge in a dynamic and heterogeneous environment. In an MPCA each population represents a solution space. An individual belonging to a given population could migrate from one population to another for the purpose of introducing new knowledge that influences other individuals in the population. In this …
Genetic Algorithm For University Course Timetabling Problem, Achini Kumari Herath
Genetic Algorithm For University Course Timetabling Problem, Achini Kumari Herath
Electronic Theses and Dissertations
Creating timetables for institutes which deal with transport, sport, workforce, courses, examination schedules, and healthcare scheduling is a complex problem. It is difficult and time consuming to solve due to many constraints. Depending on whether the constraints are essential or desirable they are categorized as ‘hard’ and ‘soft’, respectively. Two types of timetables, namely, course and examination are designed for academic institutes. A feasible course timetable could be described as a plan for the movement of students and staff from one classroom to another, without conflicts. Being an NP-complete problem, many attempts have been made using varying computational methods to …