Analytical Modeling And Study On Noise Characteristics Of Rotor Eccentric Spmsmwith Unequal Magnetic Poles Structure,
2021
TÜBİTAK
Analytical Modeling And Study On Noise Characteristics Of Rotor Eccentric Spmsmwith Unequal Magnetic Poles Structure, Pengpeng Xia, Shenbo Yu, Rutong Dou, Fengchen Zhai
Turkish Journal of Electrical Engineering and Computer Sciences
he establishment of the analytical model of the rotor eccentric surface-mounted permanent magnet syn-chronous motor (SPMSM) with unequal magnetic poles structure will be beneficial to calculating the magnetic field andstudying noise characteristics quickly. Based on the equivalent surface current (ESC) method and equivalent boundarymethod, the analytical model of the rotor eccentric SPMSM with unequal magnetic poles structure is proposed. Duringthe modeling process, the magnetic field produced by a permanent magnet (PM) is obtained using the ESC method, andthe effect on the air gap magnetic field, which arised from stator, is replaced with the concentric current sheet (CCS)magnetic field. And, the …
Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking,
2021
TÜBİTAK
Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li
Turkish Journal of Electrical Engineering and Computer Sciences
Named data networking (NDN), as a future Internet architecture that is a promising alternative to TCP/IPnetworks, has the new features of connectionless, in-network cache, and hop-by-hop forwarding, which makes thecongestion control algorithms of traditional TCP/IP networks unable to be directly applied to NDN. In addition, sincethe optimal size of the sending window cannot be determined, the existing window-based congestion control algorithmsgenerally use the AIMD-like window adjustment algorithm, which cannot achieve the optimal throughput. In thispaper, we propose a precise feedback-based, multipath-aware congestion control algorithm PFECC, which is inspiredby Accel-Brake Control algorithm. PFECC considers the influence of Interest flows, uses a …
On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi,
2021
TÜBİTAK
On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a nonorthogonal multiple access based cooperative relaying system (NOMA-CRS) is consideredto increase spectral efficiency. Besides, the simultaneous wireless information and power transfer (SWIPT) is proposedfor the relay in NOMA-CRS. In SWIPT-NOMA-CRS, three different energy harvesting (EH) protocols, power sharing(PS), time sharing (TS) and ideal protocols are implemented. The outage performances of the SWIPT-NOMA-CRSare studied for all three EH protocols. In the analysis, to represent practical/reasonable scenarios, imperfect successiveinterference canceler (SIC) and imperfect channel state information (CSI) are taken into consideration. The derivedoutage probability (OP) expressions are validated via computer simulations. Besides, the OP for the benchmark scheme,NOMA-CRS …
Turkish Sign Language Recognition Based On Multistream Data Fusion,
2021
TÜBİTAK
Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat
Turkish Journal of Electrical Engineering and Computer Sciences
Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …
An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d,
2021
TÜBİTAK
An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici
Turkish Journal of Electrical Engineering and Computer Sciences
An adaptive algorithm for evaluation of singular and near singular integrals in 3D is presented. The algorithmis based on successive adaptive/selective subdivisions of the element until a prescribed error criteria is met. For evaluatingthe integrals in each subdivision, Gauss quadrature is applied. The method is computationally simple, memory efficientand can be applied for both triangular and quadrilateral elements, including the elements with nonplanar and/or curvedsurfaces. To assess the method, several examples are discussed. It has shown that the algorithm performs well forsingular and near-singular integral examples presented in the paper and evaluates the integrals with very high accuracy.
Dual Bit Control Low-Power Dynamic Content Addressable Memory Design For Iotapplications,
2021
TÜBİTAK
Dual Bit Control Low-Power Dynamic Content Addressable Memory Design For Iotapplications, V V Satyanarayana Satti, Sridevi Sriadibhatla
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet of things (IoT) is an emerging area in the semiconductor industry for low-power and high-speedapplications. Many search engines of IoT applications require low power consumption and high-speed content addressablememory (CAM) devices for the transmission of data packets between servers and end devices. A CAM is a hardwaredevice used for transfer of packets in a network router with high speed at the cost of power consumption. In this paper,a new dual bit control precharge free (PF) dynamic content addressable memory (DCAM) has been introduced. Theproposed design uses a new charge control circuitry, which is used to control the dual …
Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction,
2021
TÜBİTAK
Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer
Turkish Journal of Electrical Engineering and Computer Sciences
Reinforcement learning (RL) agents are often designed specifically for a particular problem and they generallyhave uninterpretable working processes. Statistical methods-based agent algorithms can be improved in terms ofgeneralizability and interpretability using symbolic artificial intelligence (AI) tools such as logic programming. Inthis study, we present a model-free RL architecture that is supported with explicit relational representations of theenvironmental objects. For the first time, we use the PrediNet network architecture in a dynamic decision-making problemrather than image-based tasks, and multi-head dot-product attention network (MHDPA) as a baseline for performancecomparisons. We tested two networks in two environments -i.e., the baseline box-world environment and …
A Topological Overview Of Microgrids: From Maturity To The Future,
2021
TÜBİTAK
A Topological Overview Of Microgrids: From Maturity To The Future, Ayşe Kübra Erenoğlu, Semanur Sancar, Ozan Erdi̇nç, Mustafa Bağriyanik
Turkish Journal of Electrical Engineering and Computer Sciences
The concept of microgrid (MG) has attracted great attention from the system operators for increasing operational effectiveness as well as providing more reliable, sustainable and economic power system. In this paper, a comprehensive investigation is presented to shine new light on evaluating changes in MG operation from maturity to the future. A great deal of literature studies consisting of the traditional MG architecture, encountered challenges and proposed solutions for overcoming them are all examined in detail. Also, the impact of highly integrated renewable-based energy sources into the power system is analysed by current studies. Moreover, modern MG architecture is extensively …
Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review,
2021
TÜBİTAK
Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems- where chaos theory is widely employed is optimization problems. Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already …
Efficient Power Macromodeling Approach For An Ip-Based Soc System Usingdiscrete Water Cycle Algorithm,
2021
TÜBİTAK
Efficient Power Macromodeling Approach For An Ip-Based Soc System Usingdiscrete Water Cycle Algorithm, Faisal Siddiq, Yaseer Arafat Durrani
Turkish Journal of Electrical Engineering and Computer Sciences
Low-power consumption is becoming a crucial concern that cannot be neglected in system-on-chip (SoC) designs. Low-power solutions help designers to provide a powerful methodology to analyze, estimate, and optimize today's power concerns. Early estimation of power at a high level reduces the redesign cycle and turn-around time. Power dissipation is a function of input patterns and their characteristics. This paper describes a power estimation technique by using predefined statistical characteristics-based input patterns, which gives the average power dissipation of individual intellectual property (IP) blocks and interconnects/buses in an SoC system design. During the power estimation phase, the discrete water cycle …
The Effect Of Demand Response Control On Stability Delay Margins Of Loadfrequency Control Systems With Communication Time-Delays, Deni̇z Kati̇poğlu, Şahi̇n Sönmez, Saffet Ayasun, Ausnain Naveed
Turkish Journal of Electrical Engineering and Computer Sciences
This paper studies the effect of dynamic demand response (DR) control on stability delay margins of load frequency control (LFC) systems including communication time-delays. A DR control loop is included in each control area, called as LFC-DR system and Rekasius substitution is utilized to identify stability margins for various proportionalintegral (PI) gains and participation ratios of the secondary and DR control loops. The purpose of Rekasius substitution technique is to obtain purely complex roots on the imaginary axis of the time-delayed LFC-DR system. This substitution first converts the characteristic equation of the LFC-DR system including delay-dependent exponential terms into an …
Using Eeg To Detect Driving Fatigue Based On Common Spatial Pattern Andsupport Vector Machine,
2021
TÜBİTAK
Using Eeg To Detect Driving Fatigue Based On Common Spatial Pattern Andsupport Vector Machine, Li Wang, David Johnson, Yingzi Lin
Turkish Journal of Electrical Engineering and Computer Sciences
To investigate the correlation between electroencephalogram (EEG) and driving fatigue states, this study used machine learning algorithms to detect driving fatigue based on EEG. 14 channels of EEG data were collected from thirty-four healthy subjects in this research at Northeastern University. Each subject participated in two scenarios (baseline and fatigue scenarios). Subjective ratings of fatigue levels were also obtained from the subjects using the NASA-Task Load Index (TLX). The common spatial pattern (CSP) algorithm was used to extract features from the raw EEG data. The support vector machine (SVM) was used as the classifier in the design of the machine …
Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts,
2021
Edith Cowan University
Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau
Research outputs 2014 to 2021
The complex task of vision based fruit and vegetables classification at a supermarket self-checkout poses significant challenges. These challenges include the highly variable physical features of fruit and vegetables i.e. colour, texture shape and size which are dependent upon ripeness and storage conditions in a supermarket as well as general product variation. Supermarket environments are also significantly variable with respect to lighting conditions. Attempting to build an exhaustive dataset to capture all these variations, for example a dataset of a fruit consisting of all possible colour variations, is nearly impossible. Moreover, some fruit and vegetable classes have significant similar physical …
The Digitization Of Court Processes In African Regional And Subregional Judicial Institutions,
2021
Walden University
The Digitization Of Court Processes In African Regional And Subregional Judicial Institutions, Frederic Drabo
Walden Dissertations and Doctoral Studies
Despite information technology (IT) officers’ multiple efforts to develop reliable and efficient electronic justice (e-justice) systems, digitizing court processes still presents several quality challenges associated with IT infrastructure and literacy issues. Grounded in the principles of total quality management, the purpose of this qualitative multiple case study was to identify strategies and best practices IT officers in African regional economic communities (REC) use for digitizing regional and subregional court processes to improve African e-justice systems. The participants included four IT officers working as assistant computer system analysts (ACSA), computer system analysts (CSA), and heads of IT (HIT) in regional and …
A Meta-Gradient Approach To Learning Cooperative Multi-Agent Communication Topology,
2021
University of South Carolina - Columbia
A Meta-Gradient Approach To Learning Cooperative Multi-Agent Communication Topology, Qi Zhang, Dingyang Chen
Publications
In cooperative multi-agent reinforcement learning (MARL), agents often can only partially observe the environment state, and thus communication is crucial to achieving coordination. Communicating agents must simultaneously learn to whom to communicate (i.e., communication topology) and how to interpret the received message for decision-making. Although agents can efficiently learn communication interpretation by end-to-end backpropagation, learning communication topology is much trickier since the binary decisions of whether to communicate impede end-to-end differentiation. As evidenced in our experiments, existing solutions, such as reparameterization tricks and reformulating topology learning as reinforcement learning, often fall short. This paper introduces a meta-learning framework that aims …
Parallel Computation,
2021
Minnesota State University Moorhead
Parallel Computation, Mahesh Wosti
Student Academic Conference
Parallel computing has always fascinated me since I became aware of it. I think it is the only path forward if we are to build and make a super-fast computer in days to come. For my senior seminar, I want to build a simple framework of the parallel system and dig deeper into potential benefits and drawbacks of using a parallel system compared to the serial computing that is still pervasive in today’s modern technology.
Intrusion Detection For Industrial Control Systems,
2021
Eastern Washington University
Intrusion Detection For Industrial Control Systems, Kurt Lamon
EWU Masters Thesis Collection
Industrial Control Systems (ICS) are rapidly shifting from closed local networks, to remotely accessible networks. This shift has created a need for strong cybersecurity anomaly and intrusion detection for these systems; however, due to the complexity and diversity of ICSs, well defined and reliable anomaly and intrusion detection systems are still being developed. Machine learning approaches for anomaly and intrusion detection on the network level may provide general protection that can be applied to any ICS. This paper explores two machine learning applications for classifying the attack label of the UNSW-NB15 dataset. The UNSW-NB15 is a benchmark dataset that was …
Arkhe - Unmanned Detection Robot,
2021
Eastern Michigan University
Arkhe - Unmanned Detection Robot, Hannah Klooster
Senior Honors Theses and Projects
Our project is an Unmanned Thermal Detection Robot. Our robot contains a visual camera, a sonar sensor, and a thermal sensor. This project involves hardware building and coding of the sensors and robot itself. The purpose of this project is to create an accessible and affordable unmanned robot with sensors capable of being able to detect human life forms in disaster areas, or areas inaccessible to humans, and to protect the lives of rescuers, find people in disaster areas quicker, and to help save lives. Our project has successfully created an affordable robot that uses sensors to detect and avoid …
Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems,
2021
Missouri University of Science and Technology
Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems, Natasha Amelia Jarus
Doctoral Dissertations
Many of our critical infrastructures, from power grids to water distribution networks, are complex hybrid systems that use software to control their non-trivial physical dynamics. These systems must be able to capably serve their purpose, while also being reliable, dependable, safe, secure, and efficient. Representation and analysis of these features requires the creation of several distinct models. These models may encode design goals or be derived from collected instrumentation data, reflecting both how a system ought to operate and how it does operate. It is essential to ensure that all of these models consistently and accurately describe the same system. …
Topological Biclustering Artmap,
2021
Missouri University of Science and Technology
Topological Biclustering Artmap, Raghu Yelugam
Masters Theses
”Detection of gene mutations is central for assessing genetic factors affecting disease predisposition, genetic causes of a particular disease, and gene-targeted treatment. DNA microarray methods are widely used to detect mutations by contrasting the expression levels of thousands of genes together under varying experimental conditions. The experimental conditions could be diseased cell states compared with the normal cell states. Biclustering, a robust exploratory data analysis tool, can be applied to microarray data to detect subsets of genes that co-express highly only for a subset of experimental conditions. Such detection is crucial for gaining insights into gene regulatory networks, differential gene …
