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Title: DEPTH MAP ENHANCEMENT FOR REAL-TIME 3D RECONSTRUCTION
Creator: Lee, Kitae
Date: 2015, 2015-07
Description: In this paper, we present a novel depth map enhancement for real-time 3D reconstruction by the Microsoft Kinect. The Kinect sensor is...
Show moreIn this paper, we present a novel depth map enhancement for real-time 3D reconstruction by the Microsoft Kinect. The Kinect sensor is relatively affordable and capable of generating high-resolution color image and depth maps of the scene at realtime rates. However, owning the low- cost, there are several artifacts. Generated depth map contains lots of holes, which they are missing information around object boundaries and mis-alignment with color image. The objective of 3D reconstruction is to recreate a real scene, as accurate as possible within a virtual three-dimensional space using a computer. The algorithm of 3D-recosntrution is highly based on the quality of the depth map. This poor depth map could not be applied in potential real-time 3D reconstruction. We present novel multi-step upsampling-based our novel anisotropic diffusion algorithms with generated depth map and color image by Kinect. This method has better performance than existed bilateral filtering and original anisotropic filtering in terms of filling holes, sharpening the boundaries of objects and alignment between depth map and color image. We compare the performance of these filters. It is difficult to do a meaningful comparison of two algorithms with using output of Kinect sensor directly; as for each observation of the same scene, we will get different sensed value. In order to circumvent this problem and to achieve an accurate comparison process, we used dataset from Computer Vision Group at Munchen Technology Universty(TUM). This dataset and the scripts is related to quantitative error metrics are avail at http://vision.in.tum.de/data/datasets/rgbd-‐dataset. We also contribute making our project parallel and GPU computing to satisfy real-time system condition.
M.S. in Electrical Engineering, July 2015
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Title: THERMAL ANALYSIS OF PM MACHINES FOR HIGH PERFORMANCE ELECTRIC VEHICLES
Creator: La Marca, Frank
Date: 2016, 2016-07
Description: As demand grows for electrification of the automotive industry, the need for a traction motor becomes imperative. There has been considerable...
Show moreAs demand grows for electrification of the automotive industry, the need for a traction motor becomes imperative. There has been considerable effort by electric machine manufacturers to develop and build a traction motor that meets the speci- fications of the automobile industry. One of the limiting factors in the design of an electric automobile is the thermal performance of a traction motor. This thesis focuses on thermal analysis of an electric machine with a major focus on a machine that operates in an automotive environment. Thermal analysis of the electric machine will be focus on the analysis of an electric machine that is used in a FSAE electric racecar. Theory behind various thermal extraction methods are reviewed, including heat transfer and the fluid dynamics of an electric machine. Thermal modeling methods are also investigated, including analytical methods and numerical methods such as finite element analysis and computational fluid dynamics. The importance of thermal modeling of an electric machine is to understand the heat transfer occurring in the machine. In high performance electric machines the limiting factor of the machine the temperature rise when torque is applied. In- vestigation of the heat transfer of a machine can identify the hot spot of the machine and methods of reduction. This will allow for more current applied and more torque which will give a higher density machine.
M.S. in Electrical Engineering, July 2016
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Title: The methods used by public utility commissions in arriving at the proper depreciation and valuation of electric light, power, and railway companies and their effect on rate regulation
Creator: Schmidt, Emil J., Detar, Delos
Date: 2009, 1911
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/methodsusedbypub00schm
Thesis (B.S.)--Armour Institute of Technology

Title: PEDESTRIAN DETECTION AND TRACKING FOR ADVANCED DRIVER ASSISTANCE SYSTEMS
Creator: Mesmakhosroshahi, Maral
Date: 2017, 2017-05
Description: In an effort to reduce driver errors in being the major cause of traffic accidents, there is a lot of research being conducted into the...
Show moreIn an effort to reduce driver errors in being the major cause of traffic accidents, there is a lot of research being conducted into the development of advanced driver assistance systems (ADAS). ADAS is a system aimed at helping the driver in tasks such as pedestrian and vehicle detection, traffic sign recognition and lane detection. Pedestrian detection is one of the major tasks in advanced driver assistance systems (ADAS). Most of the stereo based pedestrian detection algorithms include three major steps: 1. Ground plane estimation 2. Region of interest (ROI) generation 3. Pedestrian classification In this thesis, we present a stereo-based pedestrian detection framework for advanced driver assistance systems by exploiting both color and depth information obtained from a stereo camera installed in a vehicle. In our proposed framework, we first use the vertical gradient of the dense depth map to estimate and discard the ground plane. The boundaries of the ground plane are then searched to detect the pedestrians and the depth values of the boundaries are used to compute the size of the detection windows for detecting pedestrians at different scales. In addition, a depth-based multi-scale ROI extraction method has been proposed to reduce the computation time of ROI extraction. For classifying ROIs to pedestrian and non-pedestrian classes, Histogram of Oriented Gradients (HOG)/Linear support vector machine (SVM) and Integral Channel Features (ICF)/Adaboost are used. To recover the missed pedestrians and improve the detection rate, an ROI tracking algorithm is proposed which incorporates the ROIs extracted from the current frame with theROIs tracked from a reference frame. For additional reduction in search space, we propose a novel algorithm to reduce the number of candidate windows extracted as ROI by taking advantage of the temporal correlation between the adjacent frames. We also propose a method to improve the accuracy of the pedestrian classifi- cation using the aggregated channel features. In this approach, we use the aggregated channel features as our baseline detector and improve it's accuracy using the tanh normalization and Gabor filter. After classification using Adaboost, we use a posi- tive subset of the bounding boxes to classify them again using Convlutional Neural Network to finalize the detection.
Ph.D. in Electrical Engineering, May 2017
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Title: Investigation of high-tension switching equipments
Creator: Clarke, Fred, Sturgess, Fred M.
Date: 2009, 1907
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/investigationofh00clar
Thesis (B.S.)--Armour Institute of Technology; Bibliography: leaves 80-90

Title: Investigation of the mercury arc rectifier by means of the oscillograph
Creator: Hail, J. C., Campbell, E. E.
Date: 2009, 1907
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/investigationofm00hail
Thesis (B.S.)--Armour Institute of Technology

Title: An investigation of the effects of iron conduits on line drop
Creator: Putt, F. A., Beamer, B. E.
Date: 2009, 1905
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/investigationofe00putt
Thesis (B.S.)--Armour Institute of Technology

Title: Investigation of the properties of chilled cast iron as a material for permanent magnets
Creator: Harrington, Philip, Smith, G. W.
Date: 2009, 1906
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/investigationofp00smit
Thesis (B.S.)--Armour Institute of Technology

Title: STEREO-BASED DEPTH MAP PROCESSING: ESTIMATION AND REFINEMENT
Creator: Loghman, Maziar
Date: 2016, 2016-12
Description: During the past decade, research in 3D video has become a hot topic owing to advancements in both hardware and software. Amongst different...
Show moreDuring the past decade, research in 3D video has become a hot topic owing to advancements in both hardware and software. Amongst different methods proposed for representing 3D data, multi-view video plus depth (MVD) format has gained a lot of attention. Most of such 3D algorithms rely on a per-pixel depth representation of the scene called a depth map. Depth maps are very useful for rendering virtual views and have lead to advancements in 3D compression algorithms. Generating an accurate and dense depth map is one of the important prerequisite for many 3D video applications. In this thesis, we highlight the following major problems in MVD. * Depth map estimation * Depth map refinement * Depth map coding In order to generate an accurate depth map, we propose a method based on Census transform with adaptive window patterns and semi-global optimization. A modified cross-based cost aggregation technique is proposed which helps to calculate a more reliable depth map. In order to further enhance the quality of the generated depth map, a novel multi-resolution anisotropic diffusion based algorithm is presented. The proposed depth refinement algorithm computes a dense depth map in which the holes have been filled and the object boundaries are sharpened. The next part of the research is based on depth map coding. In depth map coding, a considerable amount of time is required to investigate the mode decision pro- cess for every block of depth pixels. However, in real-time purposes, we can partially skip the mode selection step. In this thesis, we propose a novel depth intra-coding scheme for 3D video coding based on HEVC standard. The core idea of the proposed method is motivated by the fact that depth maps have specific characteristics that distinguish them from those of color images. By analyzing the reference depth maps based on homogeneousness of different regions, for some particular blocks, the DMM full-RD search is skipped and the mode is selected based on the previous similar tree- blocks. By this means, the time complexity of the encoding process is significantly reduced.
Ph.D. in Electrical Engineering, December 2016
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Title: JOINT UFH AND POWER CONTROL FOR EFFECTIVE WIRELESS ANTI-JAMMING COMMUNICATION
Creator: Xu, Kaihe
Date: 2012-04-27, 2012-05
Description: Jamming-resistant communication without pre-shared secrets has received extensive attention recently and is commonly tackled by utilizing the...
Show moreJamming-resistant communication without pre-shared secrets has received extensive attention recently and is commonly tackled by utilizing the technique of uncoordinated frequency hopping (UFH). However, existing approaches exhibit signi cant performance constraints due to the use of UFH at both the sender and the receiver sides. To improve the state of the art, in this paper we aim to signi cantly improve the performance of the anti-jamming system in the presence of a power-limited jammer. Speci cally, we for the rst time jointly consider UFH and power control and pose these two techniques into a uniform framework. The proposed approach utilizes online learning theory to determine both the hopping channels and the transmitting powers based on the history of channel status. By dividing the transmission power into multiple levels, the sender with a limited power budget is able to choose both the sending channels and the corresponding transmission power. The sender keeps re ning its knowledge of channel status to improve future channel selection and power allocation based on the feedback information from the receiver. We analytically show that, in presence of a power-limited jammer, the average transmission delay of our system is bounded by a xed value with high probability. Extensive simulations are conducted to demonstrate the e ectiveness of our scheme against various jamming attacks.
M.S. in Electrical Engineering, May 2012e
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Title: Measurement of capacity in transmission lines and cables
Creator: Heim, Richard M, Dumke, William
Date: 2009, 1914
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/measurementofcap00heim
Thesis (B.S.)--Armour Institute of Technology

Title: Investigation of an air cooling process for static transformers
Creator: Carroll, E. J., Payne, J. H.
Date: 2009, 1905
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/investigationofa00carr
Thesis (B.S.)--Armour Institute of Technology

Title: NON-INTRUSIVE LOAD MONITORING AND DEMAND RESPONSE FOR RESIDENTIAL ENERGY MANAGEMENT
Creator: Iwayemi, Abiodun
Date: 2016, 2016-05
Description: Compared to cellphone bills which itemize billing into local, international, text messaging, and data, todays electricity bills are opaque....
Show moreCompared to cellphone bills which itemize billing into local, international, text messaging, and data, todays electricity bills are opaque. Residential electricity customers receive a monthly bill detailing their aggregate energy usage, without any insight into which appliances are responsible for what proportions of their bill. We therefore created a Non-intrusive load monitoring framework that uses only data available from smart meters and the price signals from the Electric utility, and combine it with Optimal Stopping Rule-based schedulers to create a framework to equip residents with the information they need to be more energy efficient while balancing their costs and comfort. Non-intrusive load monitoring provides homeowners with detailed feedback on their electricity usage, but an open area is automated appliance labeling and the creation of generalizable appliance models that can be trained in one home, and deployed in another. Manually labeling such events to use them for disaggregating residential appliances is a costly and tedious task, and we developed two approaches for semisupervised learning of appliance signatures. The first approach uses 1-Nearest neighbor semi-supervised learning, and we developed a stopping criterion which reduces the likelihood of mislabeling appliance instances. This approach was extended to a cluster-then-label semi-supervised learning approach which can use only 3 labeled samples of each appliance to label and classify similar appliances within the home. Our approach enables the comparison of unequal length time series, and incorporates additional features extracted from the appliance time series. Finally, we develop a hybrid framework that combines detailed appliance models learned via Non-intrusive load monitoring with optimal stopping rule schedulers. We evaluated the performance of these models in terms of cost and delay, and explored the effect that errors in the real-time price and appliance models have on appliance running costs to demonstrate how our approach outperforms scheduling using only day head prices.
Ph.D. in Electrical Engineering, May 2016
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Title: SECURE AND RESILIENT OPERATION OF CYBER-PHYSICAL POWER SYSTEMS
Creator: Li, Zhiyi
Date: 2017, 2017-07
Description: For economic reasons, modern power systems are commonly operated close to their secure limits so that they are vulnerable to unexpected severe...
Show moreFor economic reasons, modern power systems are commonly operated close to their secure limits so that they are vulnerable to unexpected severe disruptions such as disastrous cyberattacks and extreme weather events. This thesis is aimed at enhancing the security and resilience of power supplies for facilitating the development of a Smart Grid, when power systems in various parts of the world have been undergoing transitions toward cyber-physical systems. First, this thesis discusses common cybersecurity vulnerabilities in modern power systems and presents physical implications of cyberattacks on power system operations. In particular, this thesis analyzes a specifc type of coordinated cyberphysical attacks that could lead to undetectable line outages. Coordinated with physical attacks causing line outages, cyberattacks comprising topology preserving and load redistribution attacks could mask and potentially exasperate the outages to trigger cascading failures. Such coordinated cyber-physical attacks are analyzed in a bi-level optimization model which is then transformed into a mixed-integer linear programming problem. The proposed model and the two-stage solution algorithm are examined by case studies based on the IEEE 14-bus and 118-bus test systems. Second, this thesis offers the pertinent studies on quantifying the risk of cybersecurity vulnerabilities in power system operations. A type of locally coordinated cyber-physical attacks is analyzed in detail, which would cause undetectable line outages in local areas without the need for complete network information. A risk-based optimization model in the mixed-integer linear programming form is presented for analyzing physical implications resulting from the power ow redistribution. An efficient greedy search-based heuristic method is then developed to offer satisfactory solutions for real-time applications, which are verified by case studies based on a six-bus system and the two-area IEEE RTS-96 system. Third, this thesis studies security measures for mitigating the cybersecurity risk in power system operations. A game-theoretic framework is built for determining the optimal combination of security measures based on the minimax-regret decision rule. The resulting multi-level optimization model is reformulated as a bilevel mixed-integer linear programming problem. An implicit enumeration algorithm is then developed to achieve an exact solution to this complex problem. Acceleration techniques are also provided to improve the computation efficiency for large-scale power system applications. The proposed model and solution methods are validated by case studies based on a six-bus test system and the two-area RTS-96 system. Fourth, this thesis extends the discussion of cybersecurity vulnerabilities to the operation of distributed power systems like microgrids. Since microgrids are regarded as building blocks of a Smart Grid, they strive for cyber-secure operations for sustaining power services to local customers. The assessment and mitigation of the cybersecurity risk in microgrid operations is then presented in depth. Additional opportunities provided by software-defined networking technologies to enhance the microgrid cybersecurity are also realized by the proposed defense-in-depth framework that comprises three lines of defense against cyberattacks. Last, this thesis investigates the role of networked microgrids in enhancing the power system resilience against extreme events. Since resilience is an intrinsically complex property which requires deep understanding of power system operations, a generic simulation-based framework is developed for power system operators to analyze the resilience comprehensively and respond effectively in emergency conditions. The notion that the deployment of networked microgrids catalyzes the resilience enhancement in a Smart Grid is discussed in detail. Besides, the management of networked microgrids for achieving a higher degree of resilience, reliability, and efficiency of power supplies is discussed based on the proposed hierarchical control framework.
Ph.D. in Electrical Engineering, July 2017
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Title: Heat resistance of inner arc lamp globes
Creator: Enzler, L. J., Hammer, G. O.
Date: 2009, 1916
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/heatresistanceof00enzl
Thesis (B.S.)--Armour Institute of Technology

Title: FPGA IMPLEMENTATION OF ULTRASONIC FLAW DETECTION ALGORITHM BASED ON SUPPORT VECTOR MACHINE CLASSIFICATION
Creator: Jiang, Yiyue
Date: 2016, 2016-12
Description: In this study, a Support Vector Machine (SVM) classification method used for analyzing Ultrasound signals is implemented by FPGAs based on...
Show moreIn this study, a Support Vector Machine (SVM) classification method used for analyzing Ultrasound signals is implemented by FPGAs based on Xilinx Zynq SoC. The SVM processor aims at classifying A-scan data obtained by an ultrasonic sensor. For reducing development time, hardware software co-design tools such as Xilinx System Generator and Vivado have been used. SVM kernel function is implemented by DSP slices and block RAMs. Advanced Extensible Interface bridges the ARM core and FPGAs for more convenient communication. The main objective of this study is to achieve robust detection of ultrasonic flaw echoes in real-time using an SVM algorithm. The implementation on the FPGA shows that the architecture can be realized with a Xilinx Zedboard FPGA. It runs at 100MHz clock frequency and can calculate the SVM classification for 1024 feature space points under 0.02ms.
M.S. in Electrical Engineering, December 2016
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Title: INVESTIGATION INTO USE OF GEARLESS PMSG-BASED WIND FARM FOR GRID SUPPORT
Creator: Cui, Yinan
Date: 2011-12-05, 2011-12
Description: Wind energy has become the world’s fastest growing energy source，as environmental concerns have focused attention on the generation of...
Show moreWind energy has become the world’s fastest growing energy source，as environmental concerns have focused attention on the generation of electricity from clean and renewable sources. New capacity from wind turbines has been growing fast since 2004. Installed capacity reached 196630 Megawatt in 2010 worldwide. 2011 will also see good growth. Reliability and quality of the electrical power supply is of great importance for all grids. A well designed wind-turbine power source can help balancing the unpredictable power changes caused by the Load-side of the grid (Due to the meteorological nature of long-lasting wind at the sea, the offshore wind turbines are more stable in their power production aspect). Alone more and more R&D efforts, PMSG-based direct drive wind turbine generator has become a trend in the industry, its full scale back-to-back converters can achieve fast response of power factor tuning, which directly offers an option of generating a certain amount of reactive supporting power in solving short-term voltage stability problem in the local grid and a desired quantity of active power for mitigating the frequency oscillation in the system. Topics in this thesis includes: (1) analysis of the wind turbine generator model equipped with full scale back-to-back converters and their control schemes are proposed; (2) the low voltage ride-through test of a wind farm with the modeled wind turbine generator integrated into a finite 3-bus system is provided for further short term voltage stability studies; (3) the comparison is rendered between an offshore wind farm with no support on reactive power and the one with automatically reactive power support on voltage drop response in an 8-bus system connected with HVAC submarine cable; (4) study on dynamic active power compensation from wind farm for improving the frequency stability when large disturbance introduced. Keywords: PMSG, full scale converters, reactive power, short term voltage stability, active power, dynamic compensation
M.S. in Electrical Engineering, December 2011
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Title: DESIGN AND IMPLEMENTATION OF A POWER ASSISTED DRIVETRAIN FOR A WHEELCHAIR
Creator: Hou, Ruoyu
Date: 2012-04-06, 2012-05
Description: Over the last two decades, the number of people who have difficulty walking and need wheelchairs has been found to be increasing due to an...
Show moreOver the last two decades, the number of people who have difficulty walking and need wheelchairs has been found to be increasing due to an aging population caused by a low birth rate and advances in medical treatment. Based on a recent survey, a power assisted wheelchair is the latest one in the commercial wheelcair market. The power assisted wheelchair offers users an opportunity for physical activity, but it is often too expensive for customers. This has led to the design of more advanced and economical power assisted drivetrain systems for wheelchairs. In this thesis, a novel controller has been designed. Instead of using a torque sensor for measuring and amplifying human force, the proposed controller uses two infrared sensors to trigger two motors. Using this information in addition to the information from a motion sensor that detects the road angle variation, appropriate torque command is generated. The drivetrain requires the embedded controller has a strong I/O control function, but also high speed signal processing ability for realizing real time control. Therefore, a DSP (Digital Signal Processor) which integrates flexbile multiple PWM signal generator to drive two motors, two Hall sensors for motor position and speed feedback is considered as one of the strongest controllers for power assisted drivetrain implementation. This thesis has two main contributions: a) it presents a novel power assisted motor control strategy, including six-step motor control, Environmental Adaptive control and Push-Go control method; and b) it develops an embedded controller not only on the testbench, also on the wheelchair to realize this control strategy. The designed controller is low cost and compact.
M.S. in Electrical Engineering, May 2012
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Title: The Morkrum system of printing telegraphy
Creator: Earle, Ralph H.
Date: 2009, 1917
Publisher: Armour Institute of Technology
Description: http://www.archive.org/details/morkrumsystemofp00earl
Thesis (B.S.)--Armour Institute of Technology, 1917 B.S. in Electrical Engineering, 1917

Title: A Practical Network Coding Scheme Over GF (2q) for Multi-User Cooperative Wireless Networks
Creator: Chang, Peiqiang
Date: 2011-04-21, 2011-05
Description: In this work, I present a non-binary Decode-and-Forward Network Coded (DFNC) protocol over GF(2q) for reliable communication in multi-user...
Show moreIn this work, I present a non-binary Decode-and-Forward Network Coded (DFNC) protocol over GF(2q) for reliable communication in multi-user cooperative wireless networks. There are two time phases in DFNC protocol: each user transmits its own data in the first time phase and serves as a relay in the second time phase to transmit the network coded information combining its own and others. In particular, a non-binary coding matrix construction method is proposed so as to reduce the transmission overhead and to provide independence for decoding. Moreover, we design a creative joint decoding algorithm: Credit-based Updating Algorithm (CUA), which works on symbol-level coupling network-decoding and channel-decoding together. By fully exploiting the spatial diversity and redundancy residing in network coding, CUA improves the solvability of decoding set at the destination, and therefore achieves better performance than traditional decoding algorithms, such as Gaussian Elimination. From the analysis and simulation results, we demonstrate that the proposed protocol achieves higher diversity order and outperforms other traditional transmission schemes in terms of Symbol Error Rate (SER).
M.S. in Computer Engineering, May 2011
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