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Articles 1681 - 1710 of 8897

Full-Text Articles in Physical Sciences and Mathematics

An Electrothermal Current Prediction Method For Overload Protection Of Miniaturecircuit Breakers, Sen Lyu, Ming Zong Jan 2020

An Electrothermal Current Prediction Method For Overload Protection Of Miniaturecircuit Breakers, Sen Lyu, Ming Zong

Turkish Journal of Electrical Engineering and Computer Sciences

Traditional miniature circuit breakers (MCBs) cannot meet the requirement for the intelligence of distributing apparatuses in a smart grid. The intellectualization of MCBs is restricted due to the lack of appropriate current measurement methods. Thus, an electrothermal current prediction method is proposed based on the derived relationship between root-mean-square (RMS) current and steady-state temperature rise. A fast acquisition algorithm is used to obtain the required temperature rise before thermal equilibrium to highly reduce the total time consumption. The presented prediction method is found immunized against the ambient temperature. The theory is validated with experiments using a thermostat. The tested steady-state …

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Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar Jan 2020

Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar

Turkish Journal of Electrical Engineering and Computer Sciences

The performance of cross-correlation functions can decrease computational complexity under optimal fingerprint feature selection. In this paper, a technique is proposed to perform alignment of fingerprints followed by their matching in fewer computations. Minutiae points are extracted and alignment is performed on the basis of their spatial locations and orientation fields. Unlike traditional cross-correlation based matching algorithms, ridges are not included in the matching process to avoid redundant computations. However, optimal cross-correlation is chosen by correlating feature vectors accompanying x-y locations of minutiae points and their aligned orientation fields. As a result, matching time is significantly reduced with much improved …

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Low-Profile Folded Dipole Uhf Rfid Tag Antenna With Outer Strip Lines Formetal Mounting Application, Fuad Erman, Effariza Hanafi, Eng-Hock Lim, Wan Amirul Wan Mohd Mahyiddin, Sulaiman Wadi Harun, Mohamad Sofian Abu Talip, Rawan Soboh, Hassan Umair Jan 2020

Low-Profile Folded Dipole Uhf Rfid Tag Antenna With Outer Strip Lines Formetal Mounting Application, Fuad Erman, Effariza Hanafi, Eng-Hock Lim, Wan Amirul Wan Mohd Mahyiddin, Sulaiman Wadi Harun, Mohamad Sofian Abu Talip, Rawan Soboh, Hassan Umair

Turkish Journal of Electrical Engineering and Computer Sciences

A metal mountable UHF RFID tag antenna with a low-profile folded dipole structure is proposed. It is fabricated on a single layer of polytetrafluoroethylene (PTFE) dielectric laminate. It is composed of two symmetrical C-shape resonators integrated with the outer strip lines. The IC chip's terminals are connected directly to the center of the C-shaped resonators. The outer strip lines are integrated with the C-shaped resonators, which function to lower the reflection coefficient so as to match the IC chip impedance. In particular, the outer strip lines increase the inductive reactance of the antenna impedance in order to realize IC chip …

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Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun Jan 2020

Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun

Turkish Journal of Electrical Engineering and Computer Sciences

JPEG is the most widely used image compression standard for sensing, medical, and security applications. JPEG provides a high degree of compression but field devices relying on battery power must further economize on data transmissions to prolong deployment duration with particular use cases in wireless sensor networks. Transmitting a subset of image data could potentially enhance the battery life of power-constrained devices and also meet the application requirements to identify the objects within an image. Depending on an application's needs, after the first selected subset is received at the base station, further transmissions of the image data for successive refinements …

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Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk Jan 2020

Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk

Turkish Journal of Electrical Engineering and Computer Sciences

In supervised classification, obtaining nonlinear separating functions from an algorithm is crucial for prediction accuracy. This paper analyzes the polyhedral conic functions (PCF) algorithm that generates nonlinear separating functions by only solving simple subproblems. Then, a revised version of the algorithm is developed that achieves better generalization and fast training while maintaining the simplicity and high prediction accuracy of the original PCF algorithm. This is accomplished by making the following modifications to the subproblem: extension of the objective function with a regularization term, relaxation of a hard constraint set and introduction of a new error term. Experimental results show that …

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A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le Jan 2020

A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le

Turkish Journal of Electrical Engineering and Computer Sciences

Quality of service (QoS) differentiation is an integral component of any networking system, particularly, with the current and future great diversity of users? applications and their manifold requirements. In optical burst switching (OBS) networks, there are two approaches for QoS differentiation: one is based on offset time and the other is based on burst length. This paper presents a mechanism of QoS differentiation based on both offset time and burst length, in which the offset times are calculated to achieve a complete isolation of data loss between priority classes and the burst length is adaptively adjusted according to the feedbacked …

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An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi Jan 2020

An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi

Turkish Journal of Electrical Engineering and Computer Sciences

A genetic algorithm (GA) is not a good option for finding solutions around in neighborhoods. The current study applies a memetic algorithm (MA) with a proposed local search to the mutation operator of a genetic algorithm in order to solve the traveling salesman problem (TSP). The proposed memetic algorithm uses swap, reversion and insertion operations to make changes in the solution. In the basic GA, unlike in the real world, the relationship between generations has not been considered. This gap is resolved using the proposed complex network to allow selection among possible solutions. The degree measure has been used for …

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Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri Jan 2020

Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a power-speed (P-V) model of the wind turbine by assuming three different functions for the first performance region; cubic, quadratic and uncorrected cubic. These three functions have been compared with the manufacturer models of five different wind turbines which were installed in five different locations in Jordan; Tafila, Hofa, Fujeij, Al Rajef, and Deahan. The wind turbine of these wind farms are considered as large scale HAWT in the range of Mw. The generated P-V models are developed by applying a new method described in this paper which is basically based on generating a multiplier factor x. …

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Gabor Filter-Based Localization Of Straight And Curved Needlesin 2d Ultrasound Images, Mert Kaya, Abdurrahman Enes Şenel, Özkan Bebek Jan 2020

Gabor Filter-Based Localization Of Straight And Curved Needlesin 2d Ultrasound Images, Mert Kaya, Abdurrahman Enes Şenel, Özkan Bebek

Turkish Journal of Electrical Engineering and Computer Sciences

2D ultrasound (US) is one of the most commonly used medical imaging devices for needle localization in biopsies. However, the produced images are low-resolution and contain an excessive number of artifacts, which makes the needle localization challenging. Image processing techniques can help resolve this issue. This paper presents a novel Gabor filter-based method for needle localization in 2D US images, which enhances the needle outline in the images while suppressing other structures. The scheme works in two stages: First, the Gabor filter is applied to the image, the needle insertion angle is estimated, and the needle trajectory is found using …

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Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor Jan 2020

Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor

Turkish Journal of Electrical Engineering and Computer Sciences

Network reconfiguration is a process to change the open-switches in distribution system for a minimum power loss. In the past, metaheuristic techniques were applied widely for network reconfiguration with consideration of a fixed loading profile. When the loading changes, the current configuration may not be the optimal one. Thus, the technique needs to be executed to find a new optimal configuration based on the latest loading. The process is time-consuming since metaheuristic techniques commonly require high computational times and produces inconsistent results. Therefore, this paper proposes a network reconfiguration technique based on artificial neural network (ANN) for variable loading conditions. …

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Performance Optimisation Of A Sensing Chamber Using Fluid Dynamics Simulationfor Electronic Nose Applications, Punjan Dohare, Sudeshna Bagchi, Amol P. Bhondekar Jan 2020

Performance Optimisation Of A Sensing Chamber Using Fluid Dynamics Simulationfor Electronic Nose Applications, Punjan Dohare, Sudeshna Bagchi, Amol P. Bhondekar

Turkish Journal of Electrical Engineering and Computer Sciences

The sensor chamber plays a significant role in order to improve the performance of an electronic nose in terms of stability, repeatability, reproducibility, and sensitivity. Fluid dynamics simulations of six different configurations of 3D sensing chambers are presented to facilitate the efficient design of an electronic nose system comprising 64 sensor arrays. Numerical simulations were carried out to investigate the gas (zero air) flow behaviour inside these chambers under steady-state conditions for velocities ranging from 0.1 to 2 m/s using ANSYS software. Design optimisation was performed in terms of area coverage, velocity, and mass fraction. The results show that the …

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Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan Jan 2020

Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan

Turkish Journal of Electrical Engineering and Computer Sciences

Person reidentification (Re-ID) is an important task in computer vision and has many applications in videobased surveillance. Recently, the triplet loss has been popular in the deep learning framework for person Re-ID. It is particularly important to note that the selection of hard triplets has significant influence on the performance of the learned deep model. However, the existing triplet losses only focus on some specific forms of hard triplets, thus leading to weaker generalization capability. To address this issue, we propose a novel variant of the triplet loss, named exhaustive hard triplet mining loss (EHTM), which is able to deal …

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Effects Of Sliding Mode Control Antiretroviral Drug On Hiv-1 Viral Load, Musharif Ahmed, Saad Zafar, Muhammad Aamer Saleem, Muhammad Zubair, Ijaz Mansoor Qureshi Jan 2020

Effects Of Sliding Mode Control Antiretroviral Drug On Hiv-1 Viral Load, Musharif Ahmed, Saad Zafar, Muhammad Aamer Saleem, Muhammad Zubair, Ijaz Mansoor Qureshi

Turkish Journal of Electrical Engineering and Computer Sciences

Human immunodeficiency virus (HIV) has devastating effects on human society. Researchers have proposed many models for the decay of CD4+T cells, the growth of infected cells, and viral load. In this paper, four first-order nonlinear coupled differential equations have been considered. Four variables are CD4+T cells, which are healthy, less infected cells,more infected cells capable of producing virus,and finally the viralload. Apart from the two drug therapies, protease inhibitor (PI) and reverse transcriptase inhibitor (RTI), which have already been considered in the literature, we have proposed antiretroviral drug (ARD) that works as sliding mode controller. We have used numerical methods …

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Design Of A Miniaturized Planar Microstrip Wilkinson Power Divider With Harmonic Cancellation, Saeedeh Lotfi, Saeed Roshani, Sobhan Roshani Jan 2020

Design Of A Miniaturized Planar Microstrip Wilkinson Power Divider With Harmonic Cancellation, Saeedeh Lotfi, Saeed Roshani, Sobhan Roshani

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a compact microstrip Wilkinson power divider is designed and proposed using rectangularshaped resonator cells. The presented resonator cells are used instead of quarter-wave length branches in the traditional structure to reduce the circuit size, increase the bandwidth, and eliminate the unwanted harmonics. The designed resonator behavior is studied analytically and the locations of transmission zeros are investigated using transfer function andLCequivalentcircuitmethods. The proposed power divider(PD)operates at 2GHz frequency and suppresses the 2nd to 14th unwanted harmonics. The proposed PD achieves approximately 50% size reduction and 40%fractional bandwidth (FBW). The abilities of desirable size reduction and harmonic suppression …

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Sdma-Based Distributed Device Discovery For D2d Communication, Muddasir Rahim, Muhammad Awais Javed, Ahmad Naseem Alvi Jan 2020

Sdma-Based Distributed Device Discovery For D2d Communication, Muddasir Rahim, Muhammad Awais Javed, Ahmad Naseem Alvi

Turkish Journal of Electrical Engineering and Computer Sciences

Device-to-device (D2D) communication is an important technique to improve capacity of future wireless networks. Cellular communications, internet of things and intelligent transport systems are key areas that could benefit from reduced end-to-end delay provided by D2D communication. Efficient device discovery is an important precondition to enable D2D communication. In this paper, we propose a space division multiple access (SDMA)-based distributed device discovery protocol in which user equipments (UEs) periodically transmit discovery beacons to each other. The proposed protocol reduces contention in the discovery beacons by allocating resource blocks to the UEs based on their location. Simulations results show that the …

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A Detailed Survey Of Turkish Automatic Speech Recognition, Recep Si̇nan Arslan, Necaatti̇n Barişçi Jan 2020

A Detailed Survey Of Turkish Automatic Speech Recognition, Recep Si̇nan Arslan, Necaatti̇n Barişçi

Turkish Journal of Electrical Engineering and Computer Sciences

Significant improvements have been made in automatic speech recognition(ASR)systems in terms of both the general technology and the software used. Despite these advancements, however, there is still an important difference between the recognition performance of humans and machines. This work focuses on the studies conducted in the field of Turkish speech recognition, the progress made in such studies in recent years, the language-specific constraints, the performance results achieved in the applications developed to date, and the development of a general scheme for researchers wishing to develop an ASR system for the Turkish language. A comprehensive study on the Turkish language, …

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Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r Jan 2020

Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Minimization or elimination of cogging torque is a significant issue in permanent magnet (PM) motor design process. There are some design techniques to reduce or eliminate this unwanted torque components in PM motors. This paper focuses on two different design techniques, varying magnet pole-arc and step-skew, to reduce cogging torque component in radial flux PM synchronous motors. Different design points which consider pulsating torque components and back-EMF harmonics are obtained via finite element analysis (FEA) for a low power industrial PM motor. A prototype motor is manufactured for one of the desired designs and is tested experimentally. Good agreement is …

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Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu Jan 2020

Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents the application of deep learning algorithms towards demand response management. Demand limit violation and voltage stability are the major problems associated with a secondary distribution system. These problems are solved using demand response models by day ahead scheduling loads at every 15 min interval through linear integer programming and based on short term forecasting of load (kW). A new architecture for short term load forecasting is presented namely gated recurrent unit in which statistical analysis is carried out to get the optimal architecture of the neural network model. Reliability indices such as loss of load probability (LOLP) …

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A New Configuration For Four-Switch Three-Phase Inverters Based On A Switched-Capacitor Step-Up Cell For Electric Vehicles Application, Alireza Lahooti Eshkevari, Ali Mosallanejad, Mohammad Sadegh Sepasian Jan 2020

A New Configuration For Four-Switch Three-Phase Inverters Based On A Switched-Capacitor Step-Up Cell For Electric Vehicles Application, Alireza Lahooti Eshkevari, Ali Mosallanejad, Mohammad Sadegh Sepasian

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new configuration for four-switch three-phase inverters based on a step-up switchedcapacitor cell, which is called switched-capacitor four-switch three-phase inverter (SCFSTPI). This converter includes eight power switches and two DC-link capacitors. Voltage step-up feature, high efficiency, integrated structure, and bidirectional power flow are the main contribution of this new configuration. A modified space vector modulation (SVM) strategy is presented to generate appropriate pulses for the converter. This modulation method also eliminates the effect of capacitors voltage imbalance problem on the inverter output voltage and current. Simulation and experimental results are presented and investigated to confirm the performance …

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Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb Jan 2020

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …

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Reference Governors For Time-Varying Systems And Constraints, Collin Freiheit Jan 2020

Reference Governors For Time-Varying Systems And Constraints, Collin Freiheit

Graduate College Dissertations and Theses

Control systems are often subject to constraints imposed by physical limitations or safety considerations, and require means of constraint management to ensure the stability and safety of the system. For real-time implementation, constraint management schemes must not carry a heavy computational burden; however many of the current solutions are computationally unattractive, especially those with robust formulations. Thus, the design of constraint management schemes with low computational loads is an important and practical problem for control engineers. Reference Governor (RG) is an efficient constraint management scheme that is attractive for real-time implementation due to its low computational complexity and ease of …

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Computational Assessment Of Aortic Valve Function And Mechanics Under Hypertension, Saurav Kadel Jan 2020

Computational Assessment Of Aortic Valve Function And Mechanics Under Hypertension, Saurav Kadel

Browse all Theses and Dissertations

Calcific aortic valve disease (CAVD), the most common valvular heart disorder, is associated with complications such as stroke, heart attack, aortic aneurysm, left ventricular hypertrophy, and ultimately death. While hypertension has been identified as a major risk factor for CAVD, the mechanisms by which it may promote calcification are still unknown. Given the sensitivity of valvular tissue to mechanical stress alterations, the hemodynamic abnormalities linked to hypertension may play a role in the development of CAVD. Further, the effects of hypertension on the left ventricular functionality and coronary flow resistance remain largely uninvestigated. Hence, the objectives of this thesis were …

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Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik Jan 2020

Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a convolutional neural networks Turkish tweet classification system for crisis response. This system has the ability to classify the present information before or during any crisis. In addition, a preprocessing model was also implemented and integrated as a part of the developed system. This paper presents the first ever Turkish tweet dataset for crisis response, which can be widely used and improve similar studies. This dataset has been carefully preprocessed, annotated, and well organized. It is suitable to be used by all the well-known natural language processing tools. Extensive experimental work, using our produced Turkish tweet dataset …

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A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal Jan 2020

A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal

Theses and Dissertations--Electrical and Computer Engineering

Advances in computing power in recent years have facilitated developments in autonomous robotic systems. These robotic systems can be used in prosthetic limbs, wearhouse packaging and sorting, assembly line production, as well as many other applications. Designing these autonomous systems typically requires robotic system and world models (for classical control based strategies) or time consuming and computationally expensive training (for learning based strategies). Often these requirements are difficult to fulfill. There are ways to combine classical control and learning based strategies that can mitigate both requirements. One of these ways is to use a gravity compensated torque control with reinforcement …

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Resource Efficient Design Of Quantum Circuits For Cryptanalysis And Scientific Computing Applications, Edgard Munoz-Coreas Jan 2020

Resource Efficient Design Of Quantum Circuits For Cryptanalysis And Scientific Computing Applications, Edgard Munoz-Coreas

Theses and Dissertations--Electrical and Computer Engineering

Quantum computers offer the potential to extend our abilities to tackle computational problems in fields such as number theory, encryption, search and scientific computation. Up to a superpolynomial speedup has been reported for quantum algorithms in these areas. Motivated by the promise of faster computations, the development of quantum machines has caught the attention of both academics and industry researchers. Quantum machines are now at sizes where implementations of quantum algorithms or their components are now becoming possible. In order to implement quantum algorithms on quantum machines, resource efficient circuits and functional blocks must be designed. In this work, we …

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Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale Jan 2020

Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale

Electronic Theses and Dissertations

The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …

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Optimization Study Of A Combined Wind-Solar Farm For A Specified Demand, Venkat Siddhartha Rama Jan 2020

Optimization Study Of A Combined Wind-Solar Farm For A Specified Demand, Venkat Siddhartha Rama

Browse all Theses and Dissertations

At the present time, using wind and solar energy for producing electricity in the United States is becoming cost competitive. According to Lazard’s 2019 [36] levelized cost of energy (LCOE) analysis of a number of energy sources used for producing electricity in the United States, wind and solar are cheaper than natural gas and coal. While capital, maintenance, operation, and fuel costs are included in LCOE numbers, energy source intermittency is not. Intermittency is an important issue with wind and solar energy sources, but not with natural gas or coal energy sources. Combining wind and solar energy sources into one …

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Flux Expulsion In Niobium Superconducting Radio-Frequency Cavities Of Different Purity And Essential Contributions To The Flux Sensitivity, P. Dhakal, Gianluigi Ciovati, Alex Gurevich Jan 2020

Flux Expulsion In Niobium Superconducting Radio-Frequency Cavities Of Different Purity And Essential Contributions To The Flux Sensitivity, P. Dhakal, Gianluigi Ciovati, Alex Gurevich

Physics Faculty Publications

Magnetic flux trapped during the cooldown of superconducting radio-frequency cavities through the transition temperature due to incomplete Meissner state is known to be a significant source of radio-frequency losses. The sensitivity of flux trapping depends on the distribution and the type of defects and impurities which pin vortices, as well as the cooldown dynamics when the cavity transitions from a normal to superconducting state. Here we present the results of measurements of the flux trapping sensitivity on 1.3 GHz elliptical cavities made from large-grain niobium with different purity for different cooldown dynamics and surface treatments. The results show that lower …

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Iterative Optical Diffraction Tomography For Reconstruction Of Multiply-Scattering Objects, Shengli Fan Jan 2020

Iterative Optical Diffraction Tomography For Reconstruction Of Multiply-Scattering Objects, Shengli Fan

Electronic Theses and Dissertations, 2020-2023

As a label-free, non-destructive, high-resolution, and quantitative imaging technique, optical diffraction tomography (ODT) has been widely used to image biological samples and microstructures, such as cells, tissues, and optical fibers. The refractive-index (RI) distribution of an object is reconstructed from multi-view measurements of diffracted fields emerging from the object. Typical ODT setups include the object rotating configuration (ORC) and the illumination scanning configuration (ISC). One major limitation of ODT is that it is only applicable to weakly-scattering objects. In this dissertation, novel methods have been developed to overcome the reconstruction difficulty caused by multiple scattering, so as to extend ODT …

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Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath Jan 2020

Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath

Turkish Journal of Electrical Engineering and Computer Sciences

Recent developments in deep networks allow us to train networks with more parameters by yielding better performance given sufficient amount of data. However, we are still restricted with the availability of labelled data in medical image segmentation, where the problem is exacerbated with high intra- and intervariability of anatomical structures. In order to bypass this problem without compromising network performance, this study introduces a PERINet, which promises to achieve higher performance while being with smaller parameter count such as on the order of 0.8 million than its counterparts. The network benefits from rich features generated by our versions of inception …

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