Physical Sciences and Mathematics Commons^™

A Bidirectional Wireless Power Transfer System For An Electric Vehicle With A Relay Circuit, Chenyang Xia, Wei Wang, Yuling Liu, Kezhang Lin, Yanhe Wang, Xiaojie Wu

Turkish Journal of Electrical Engineering and Computer Sciences

In order to extend the transfer distance, enhance the tolerance for coil misalignment, and improve the capability of energy feedback and power transfer efficiency of conventional wireless power transfer (WPT) systems for electric vehicles, this paper presents a bidirectional WPT topology with a relay circuit. In the proposed topology, the primary and pickup circuits are implemented with virtually identical structures, which can operate in both magnetic field excitation and magnetic field receiving modes to facilitate bidirectional power flow between the primary side and the pickup side. A relay circuit is introduced to achieve high transfer efficiency under special conditions such …

A New Segmentation Method Of Cerebral Mri Images Based On The Fuzzy C-Means Algorithm, Mohamed Zaki Abderrezak, Mouatez Billah Chibane, Karim Mansour

Turkish Journal of Electrical Engineering and Computer Sciences

The aim of this work is to present a new method for cerebral MRI image segmentation based on modification of the fuzzy c-means (FCM) algorithm. We used local and nonlocal information distance in the initial function of the robust FCM model. The obtained results of the classification of MRI images showed the effectiveness of the suggested model. Calculation of the similarity index confirms that our method is well adapted to MRI images even in the presence of noise.

Heuristic Algorithm-Based Estimation Of Rotor Resistance Of An Induction Machine By Slot Parameters With Experimental Verification, Mehmet Çelebi̇, Murat Tören

Turkish Journal of Electrical Engineering and Computer Sciences

The estimations of induction machine equivalent circuit parameters are still being widely used in the analysis and in determining the characteristics of the machine. Since the most important part of the machine is the rotor where torque is produced, the calculation of rotor resistance correctly will directly affect all other data. Almost all parameters belonging to the stator side can easily be determined through external measurements. However, due to the formulation of the rotor as a closed box, estimating rotor resistance and the rotor's slot shape by heuristic algorithms, without damaging the rotor physically, and comparing it with its actual …

Median Filtering Detection Based On Variations And Residuals In Image Forensics, Kang Hyeon Rhee

Turkish Journal of Electrical Engineering and Computer Sciences

To attain a robust feature vector for median filtering detection (MFD) in digital forgery images, this paper presents a short feature vector that is made up of three types of feature sets. The first set is defined by the variation to be the 3-D length in the gradient difference of the intensity values of the adjacent row and column line pairs in the image, respectively. The second set is defined by the variation in the coefficient difference of the Fourier transform to be the 3-D length in the adjacent line pairs. The last set is defined by the residual image …

A Novel Optical Flow-Based Representation For Temporal Video Segmentation, Samet Akpinar, Ferdanur Alpaslan

Turkish Journal of Electrical Engineering and Computer Sciences

Temporal video segmentation is a field of multimedia research enabling us to temporally split video data into semantically coherent scenes. In order to develop methods challenging temporal video segmentation, detecting scene boundaries is one of the more widely used approaches. As a result, representation of temporal information becomes important. We propose a new temporal video segment representation to formalize video scenes as a sequence of temporal motion change information. The idea here is that some sort of change in the optical flow character determines motion change and cuts between consecutive scenes. The problem is eventually reduced to an optical flow-based …

Ekf-Based Self-Regulation Of An Adaptive Nonlinear Pi Speed Controller For A Dc Motor, Omer Saleem, Urwa Omer

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a robust adaptive nonlinear proportional--integral (ANPI) scheme to control the speed of a direct-current (DC) motor. Unlike proportional--integral--derivative (PID) controllers, PI controllers have a simpler structure and they deliver effective control effort. However, due to inadequate controller gains, they are often unable to simultaneously improve the transient as well as the steady-state response of the system. A nonlinear PI (NPI) controller alleviates these issues and delivers a good response. In this research, the proportional and integral gains of the NPI controller are dynamically modulated via a nonlinear sigmoidal function (SiF) of the error dynamics of the motor's …

Time-Jerk Optimal Trajectory Planning Of A 7-Dof Redundant Robot, Shaotian Lu, Jingdong Zhao, Li Jiang, Hong Liu

Turkish Journal of Electrical Engineering and Computer Sciences

In order to improve the efficiency and smoothness of a robot and reduce its vibration, an algorithm called the augmented Lagrange constrained particle swarm optimization (ALCPSO), which combines constrained particle swarm optimization with the augmented Lagrange multiplier method to realize time-jerk (defined as the derivative of the acceleration) optimal trajectory planning is proposed. Kinematic constraints such as joint velocities, accelerations, jerks, and traveling time are considered. The ALCPSO algorithm is used to avoid local optimization because a new particle swarm is newly produced at each initial time process. Additionally, the best value obtained from the former generation is saved and …

Indirect Adaptive Neurofuzzy Hermite Wavelet Based Control Of Pv In A Grid-Connected Hybrid Power System, Sidra Mumtaz, Laiq Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Owing to the evolution of the smart grid, the emergence of hybrid power systems (HPSs), and the proliferation of plug-in-hybrid electric vehicles, the development of efficient and robust maximum power point tracking (MPPT) algorithms for renewable energy sources due to their inherent intermittent nature has overwhelmed the power industry. In this paper, an incremental conductance (IC) based Hermite wavelet incorporated neurofuzzy indirect adaptive MPPT control paradigm for a photovoltaic (PV) system in a grid-connected HPS is proposed. The performance of the proposed adaptive Hermite wavelet incorporated neurofuzzy MPPT control paradigm is validated through a comprehensive grid-connected HPS test-bed developed in …

Koch Fractal-Based Hexagonal Patch Antenna For Circular Polarization, Manisha Gupta, Vinita Mathur

Turkish Journal of Electrical Engineering and Computer Sciences

The design and performance of an inset feed modified hexagonal patch antenna for possible applications in ultrawideband communication systems is reported. The inset feed hexagonal patch antenna is modified by introducing a fractal up to the second iteration. A right-angled isosceles triangular microstrip antenna is used in the Koch fractal structure on the edges. The proposed antenna is a combination of two standard fractal structures, i.e. Sierpinski and Koch. A rectangular defect in the ground has also been done. The antenna is simulated by applying CST Microwave Studio simulation software. The results are verified by fabricating the antenna and tested …

Data Clustering Using Seed Disperser Ant Algorithm, Wen Liang Chang, Jeevan Kanesan, Anand Jayant Kulkarni, Harikrishnan Ramiah

Turkish Journal of Electrical Engineering and Computer Sciences

Nature-inspired optimization algorithms have become popular in the past decade. They have been applied to solve various kinds of problems. Among these would be data clustering, which has become popular in data mining in recent times due to the data explosion. In the last decade, many metaheuristic algorithms have been used to obtain improved data clustering optimization for solving data mining problems. In this paper, we applied the seed disperser ant algorithm (SDAA), which mimics the evolution of an Aphaenogaster senilis ant colony, and we introduced a modified SDAA that is a hybrid of K-means and SDAA for solving data …

Breast-Region Segmentation In Mri Using Chest Region Atlas And Svm, Aida Fooladivanda, Shahriar Baradaran Shokouhi, Nasrin Ahmadinejad

Turkish Journal of Electrical Engineering and Computer Sciences

An important step for computerized analysis of breast magnetic resonance imaging (MRI) is segmentation of the breast region. Due to the similar signal intensity of fibroglandular tissue and the chest wall, the segmentation process is difficult for breasts with fibroglandular tissue connected to the chest wall. In order to overcome this challenge, a new framework is presented that relies on a chest region atlas. The proposed method first detects the approximated breast-chest wall boundary using an intensity-based operation. A support vector machine (SVM) then determines the connectivity of fibroglandular tissue to the chest wall by the extracted features from the …

Improving Peptide Identification By Considering Ordered Amino Acid Usage, Ahmed Al-Qurri

Theses and Dissertations

Proteomics has made major progress in recent years after the sequencing of the genomes of a substantial number of organisms. A typical method for identifying peptides uses a database of peptides identified using tandem mass spectrometry (MS/MS). The profile of accurate mass and elution time (AMT) for peptides that need to be identified will be compared with this database. Restricting the search to those peptides detectable by MS will reduce processing time and more importantly increase accuracy. In addition, there are significant impacts for clinical studies. Proteotypic peptides are those peptides in a protein sequence that are most likely to …

Metabolic Investigations Of The Molecular Mechanisms Associated With Parkinson’S Disease, Robert Powers, Shulei Lei, Annadurai Anandhan, Darrell D. Marshall, Bradley Worley, Ronald Cerny, Eric D. Dodds, Yuting Huang, Mihalis I. Panayiotidis, Aglaia Pappa, Rodrigo Franco

Robert Powers Publications

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by fibrillar cytoplasmic aggregates of α-synuclein (i.e., Lewy bodies) and the associated loss of dopaminergic cells in the substantia nigra. Mutations in genes such as α -synuclein (SNCA) account for only 10% of PD occurrences. Exposure to environmental toxicants including pesticides and metals (e.g., paraquat (PQ) and manganese (Mn)) is also recognized as an important PD risk factor. Thus, aging, genetic alterations, and environmental factors all contribute to the etiology of PD. In fact, both genetic and environmental factors are thought to interact in the promotion of idiopathic PD, but the mechanisms …

K-Mer Analysis Pipeline For Classification Of Dna Sequences From Metagenomic Samples, Russell Kaehler

Graduate Student Theses, Dissertations, & Professional Papers

Biological sequence datasets are increasing at a prodigious rate. The volume of data in these datasets surpasses what is observed in many other fields of science. New developments wherein metagenomic DNA from complex bacterial communities is recovered and sequenced are producing a new kind of data known as metagenomic data, which is comprised of DNA fragments from many genomes. Developing a utility to analyze such metagenomic data and predict the sample class from which it originated has many possible implications for ecological and medical applications. Within this document is a description of a series of analytical techniques used to process …

An Online Approach For Feature Selection For Classification In Big Data, Nasrin Banu Nazar, Radha Senthilkumar

Turkish Journal of Electrical Engineering and Computer Sciences

Feature selection (FS), also known as attribute selection, is a process of selection of a subset of relevant features used in model construction. This process or method improves the classification accuracy by removing irrelevant and noisy features. FS is implemented using either batch learning or online learning. Currently, the FS methods are executed in batch learning. Nevertheless, these techniques take longer execution time and require larger storage space to process the entire dataset. Due to the lack of scalability, the batch learning process cannot be used for large data. In the present study, a scalable efficient Online Feature Selection (OFS) …

A New Approach For Digital Image Watermarking To Predict Optimal Blocks Using Artificial Neural Networks, Raheleh Khorsand Movaghar, Hossein Khaleghi Bizaki

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel nonblind digital image watermarking based on discrete wavelet transform and singular value decomposition. This robust scheme takes advantage of artificial neural networks for selecting suitable image blocks in which the watermark signal can be embedded. Local characteristics of the blocks such as luminance and texture sensitivity are the main criteria that the selections are based on. Generally, selection is based on a prediction of the results with the objective of transparency and watermark resilience. In other words, before embedding the water mark signal, it is estimated which blocks would be the best for …

Comparative Study For Identification Of Multiple Alarms In Telecommunication Networks, Ati̇la Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

Telecommunication networks consist of communication units interconnected physically or by means of protocols in order to provide basic services like data, voice, or image transfers. In this study, a modeling frame for network units and their links in a topological frame is presented based on a real mobile communication network named TASMUS (TAktik Saha MUharebe Sistemi - Tactical Field Combat System). Alarm handling is one of the most critical features required in communication networks. Based on simulated single alarm and multiple (double) alarm scenarios, known powerful alarm estimation approaches, namely the coding method, neural networks, and knowledge-based systems, have been …

Erp: An Efficient Reactive Routing Protocol For Dense Vehicular Ad Hoc Networks, Thandapany Sivakumar, Rajendiran Manoharan

Turkish Journal of Electrical Engineering and Computer Sciences

A vehicular ad hoc network (VANET) is a type of mobile ad hoc network (MANET) that provides an exchange of messages between vehicles. VANETs encourage researchers to create safety and comfort applications that will lead to intelligent transport systems. Conventional ad hoc routing methods may cause flooding of packets to find routes in a VANET. Hence, finding a route from the source to the destination vehicle by local broadcast techniques in densely populated urban areas may create a broadcast storm and network bandwidth is unnecessarily wasted to discover routes between source and destination vehicles. In this paper, an efficient routing …

Short-Period Mesospheric Gravity Waves And Their Sources At The South Pole, Dhvanit Mehta, Andrew J. Gerrard, Yusuke Ebihara, Allan T. Weatherwax, Louis J. Lanzerotti

Physics Faculty Publications

The sourcing locations and mechanisms for short-period, upward-propagating gravity waves at high polar latitudes remain largely unknown. Using all-sky imager data from the Amundsen–Scott South Pole Station, we determine the spatial and temporal characteristics of 94 observed small-scale waves in 3 austral winter months in 2003 and 2004. These data, together with background atmospheres from synoptic and/or climatological empirical models, are used to model gravity wave propagation from the polar mesosphere to each wave's source using a ray-tracing model. Our results provide a compelling case that a significant proportion of the observed waves are launched in several discrete layers in …

Natural Recession Of The Eastern Margin Of The Leofnard Salt In Western Canada, Neil Lennart Anderson, Robert James Sidford Brown, Dale A. Cederwall

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The Lloydminster area (T35-65, R15W3M-10W4M) of east-central Alberta and west-central Saskatchewan, Canada, is dissected by the north-northwest trending updip active dissolution margin, of the Devonian Leofnard Member rock salt. West of this margin, up to 150 m of rock salt is preserved; updip and to the east, the salt has mostly been leached from the rock record. The margin is up to 40 km wide and characterized by extreme local variations in net salt thickness. The dissolution of the Leofnard rock salt in the Lloydminster area has resulted in the entrapment of significant hydrocarbon accumulation. Stratigraphic traps, for example, have …

Multiple Drivers Of Seasonal Change In Pri: Implications For Photosynthesis 2. Stand Level, Anatoly A. Gitelson, John A. Gamon, Alexei E. Solovchenko

Department of Biological Systems Engineering: Papers and Publications

The goal of this study was to explore the relationships between stand-level photochemical reflectance index (PRI) and canopy structure/ pigment pools, as well as light use efficiency (LUE) of photosynthetically active vegetation focusing on seasonal or ontogenetic time frames. PRI was originally designed as a means of assessing the xanthophyll cycle and LUE over short (e.g. diurnal) time frames, and few studies have explored the drivers of PRI over longer, seasonal time frames, particularly in crops having different photosynthetic pathways or canopy structures. Consequently, our purpose was to understand and quantify the drivers of PRI responses over seasonal time scales …

Spatially Biased Dispersal Of Acorns By A Scatter-Hoarding Corvid May Accelerate Passive Restoration Of Oak Habitat On California’S Largest Island, Mario B. Pesendorfer, T. Scott Sillett, Scott A. Morrison

School of Biological Sciences: Faculty Publications

Scatter hoarding by corvids (crows, jays, magpies, and nutcrackers) provides seed dispersal for many large-seeded plants, including oaks and pines. When hoarding seeds, corvids often choose nonrandom locations throughout the landscape, resulting in differential survival of seeds. In the context of habitat restoration, such disproportional storing of seeds in areas suitable for germination and establishment can accelerate expansion and recovery of large-seeded tree populations and their associated ecosystems. Here, we investigate the spatial preferences of island scrub jays Aphelocoma insularis during scatter hoarding of acorns (Quercus spp.) on Santa Cruz Island. We use a large behavioral data set on …

A Comparison Of Decision Tree With Logistic Regression Model For Prediction Of Worst Non-Financial Payment Status In Commercial Credit, Jessica M. Rudd Mph, Gstat, Jennifer L. Priestley

Published and Grey Literature from PhD Candidates

Credit risk prediction is an important problem in the financial services domain. While machine learning techniques such as Support Vector Machines and Neural Networks have been used for improved predictive modeling, the outcomes of such models are not readily explainable and, therefore, difficult to apply within financial regulations. In contrast, Decision Trees are easy to explain, and provide an easy to interpret visualization of model decisions. The aim of this paper is to predict worst non-financial payment status among businesses, and evaluate decision tree model performance against traditional Logistic Regression model for this task. The dataset for analysis is provided …

Faculty Assessment: Outside Evaluators, John Pratte, Matthew Laposata

Assessment and Feedback

A questionnaire was also developed to solicit faculty perceptions of the laboratory programs. The primary focus of the questions for the faculty was on the efficacy of the laboratory program, their perceptions of its effectiveness, and their satisfaction with the laboratory report format. This questionnaire was given to several scientists from outside institutions, and an outside evaluator reviewed the activity modules and visited the campus to perform a holistic external assessment of the project. Responses from these evaluators were very positive. For example, the outside evaluators were asked to assess the activities on 12 factors such as clarity of writing, …

Adaptive Orthonormal Systems For Matrix-Valued Functions, Daniel Alpay, Fabrizio Colombo, Tao Qian, Irene Sabadini, Tao Qian

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this paper we consider functions in the Hardy space Hp×q2 defined in the unit disc of matrix-valued. We show that it is possible, as in the scalar case, to decompose those functions as linear combinations of suitably modified matrix-valued Blaschke product, in an adaptive way. The procedure is based on a generalization to the matrix-valued case of the maximum selection principle which involves not only selections of suitable points in the unit disc but also suitable orthogonal projections. We show that the maximum selection principle gives rise to a convergent algorithm. Finally, we discuss the case of real-valued signals.

Functions Of The Infinitesimal Generator Of A Strongly Continuous Quaternionic Group, Daniel Alpay, Fabrizio Colombo, Jonathan Gantner, David P. Kimsey

Mathematics, Physics, and Computer Science Faculty Articles and Research

The analogue of the Riesz-Dunford functional calculus has been introduced and studied recently as well as the theory of semigroups and groups of linear quaternionic operators. In this paper we suppose that T is the infinitesimal generator of a strongly continuous group of operators (ZT (t))t2R and we show how we can define bounded operators f(T ), where f belongs to a class of functions which is larger than the class of slice regular functions, using the quaternionic Laplace-Stieltjes transform. This class will include functions that are slice regular on the S-spectrum of T but not necessarily at infinity. Moreover, …

Janus Sequences Of Quantum Measurements And The Arrow Of Time, Andrew N. Jordan, Areeya Chantasri, Kater Murch, Justin Dressel, Alexander N. Korotkov

Mathematics, Physics, and Computer Science Faculty Articles and Research

We examine the time reversal symmetry of quantum measurement sequences by introducing a forward and backward Janus sequence of measurements. If the forward sequence of measurements creates a sequence of quantum states in time, starting from an initial state and ending in a final state, then the backward sequence begins with the time-reversed final state, exactly retraces the intermediate states, and ends with the time-reversed initial state. We prove that such a sequence can always be constructed, showing that unless the measurements are ideal projections, it is impossible to tell if a given sequence of measurements is progressing forward or …

On-Road Remote Sensing Of Automobile Emissions In The Chicago Area: Fall 2016, Gary A. Bishop, Molly J. Haugen

Fuel Efficiency Automobile Test Publications

No abstract provided.

United States Light And Heavy -Duty Fuel Specific On -Road No And No X Emission Factor Trends And Their Importance In Inventory Calculations (Presentation), Gary A. Bishop

Fuel Efficiency Automobile Test Publications

No abstract provided.

Assessment Of Rockfall Rollout Risk Along Varying Slope Geometries Using The Rocfall And Crsp Software, Mariam S. Al E'Bayat

Masters Theses

"Most routes in mountainous areas suffer from rock falling, rolling and bouncing risk. There are many computer programs concerned with simulating the rockfall problem, and whereas they have the same purpose, they however differ in the input data that's needed to simulate the problem, and they also differ in the way of processing and kind of output.

This study used Rocfall® and the Colorado Rockfall Simulation Program (CRSP®) to simulate sixty-three models of varying slope geometry, where only the slope geometry is changed with the same material properties for both the slope and the rocks.

Both programs were fast and …