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2021

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Articles 9091 - 9120 of 9975

Full-Text Articles in Engineering

A Fuzzy Expert System For Predicting The Mortality Of Covid'19, Monika Mangla, Nonita Sharma, Poonam Mittal Jan 2021

A Fuzzy Expert System For Predicting The Mortality Of Covid'19, Monika Mangla, Nonita Sharma, Poonam Mittal

Turkish Journal of Electrical Engineering and Computer Sciences

The COVID-19 pandemic has had a widespread impact on health and economy across the globe. It is leading to a huge number of deaths per day. Few researchers have been attracted to analyzing the mortality rate of COVID-19 from various perspectives. During the research, it has become evident that these fatalities are not only caused by COVID19, but they are also affected by some other factors. The authors of this paper aim to encompass three important types of factors viz. risk factors, clinical factors, and miscellaneous factors that influence the mortality of COVID-19. This manuscript presents a rule-based model under …

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Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar Jan 2021

Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar

Turkish Journal of Electrical Engineering and Computer Sciences

The cyclic prefix (CP) is a prefix technique widely used in orthogonal frequency division multiplexing (OFDM) systems in order to eliminate the intersymbol interference (ISI) caused by the dispersion of wireless channels. However, CP reduces the number of symbols that can be transmitted in one OFDM symbol. Therefore, CP is one of the bottlenecks of OFDM systems limiting their spectral efficiency (SE). This limitation on the SE of the classical CP-based OFDM system is the main motivation for this work to introduce a novel method. In this paper, the design of a new CP structure, which is based on the …

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New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan Jan 2021

New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, hyperchaotic system (HCSs) have been started to be used in engineering applications because they have complex dynamics, randomness, and high sensitivity. For this purpose, HCSs with different features have been introduced in the literature. In this work, a new HCS with a single discontinuous nonlinearity is introduced and analyzed. The proposed system has one saddle focus equilibrium. When the dynamic properties and bifurcation graphics of the system are analyzed, it is determined that the proposed system exhibits the complex phenomenon of multistability. Moreover, analog electronic circuit design of the proposed system is performed with positive second-generation current conveyor. In …

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Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut Jan 2021

Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that …

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Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga Jan 2021

Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga

Turkish Journal of Electrical Engineering and Computer Sciences

One of the major security challenges in cloud computing is distributed denial of service (DDoS) attacks. In these attacks, multiple nodes are used to attack the cloud by sending huge traffic. This results in the unavailability of cloud services to legitimate users. In this research paper, a hybrid machine learning-based technique has been proposed to detect these attacks. The proposed technique is implemented by combining the extreme learning machine (ELM) model and the blackhole optimization algorithm. Various experiments have been performed with the help of four benchmark datasets namely, NSL KDD, ISCX IDS 2012, CICIDS2017, and CICDDoS2019, to evaluate the …

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Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid Jan 2021

Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid

Turkish Journal of Electrical Engineering and Computer Sciences

The inclusion of renewable energy sources in a distribution system to form a dispersed or decentralized generation network has gained tremendous progress in recent years. The architecture of the distribution system has the potential to serve as a microgrid during an islanding operation connected directly to the load center while excited fully by renewable technologies. This paper deals with planning and designing of a medium voltage power distribution system in a rural area of Pakistan affluent with abundant reserves of renewable sources of electricity. Two types of distribution system architectures, namely radial and ring systems, are simulated using a power …

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Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta Jan 2021

Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta

Turkish Journal of Electrical Engineering and Computer Sciences

Image forgery detection is one of the key challenges in various real time applications, social media and online information platforms. The conventional methods of detection based on the traces of image manipulations are limited to the scope of predefined assumptions like hand-crafted features, size and contrast. In this paper, we propose a fusion based decision approach for image forgery detection. The fusion of decision is based on the lightweight deep learning models namely SqueezeNet, MobileNetV2 and ShuffleNet. The fusion decision system is implemented in two phases. First, the pretrained weights of the lightweight deep learning models are used to evaluate …

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Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena Jan 2021

Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena

Turkish Journal of Electrical Engineering and Computer Sciences

Booth multiplier is the key component in portable very large-scale integration (VSLI) systems enabled with signal and image processing applications. The area, delay, and energy are the major constraints in these systems. Therefore, in this paper, a detailed analysis of the state-of-the-art Booth multiplier architecture and its various internal units are presented to find the scope of optimization. Based on the finding of analysis, optimized new binary to 2's complement (B2C), Booth encoder-cum-selector type-1 and type-2, and partial product addition units are proposed. Furthermore, using these optimized units, an efficient parallel radix-4 8×8 Booth multiplier architecture is proposed. The simulation …

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Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz Jan 2021

Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz

Turkish Journal of Electrical Engineering and Computer Sciences

Transverse flux machines (TFM) can be designed with high pole numbers, so they are very useful in directdrive systems with high torque density. Although many TFM models have been proposed to date, no detailed classification and comparison has been made before. Conventional TFMs have a high power and torque density, but low power factors and high cogging torques have prevented them from being widely used. However, especially with the new disk type TFMs proposed in recent years and the methods developed, these drawbacks have been reduced. In this paper, the TFMs proposed in recent years have been classified and their …

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Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah Jan 2021

Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah

Turkish Journal of Electrical Engineering and Computer Sciences

The immense emergence of plug-in hybrid electric vehicles (PHEVs) is envisioned in the future. The rapid proliferation of PHEVs and their charging triggers intense surges in the load during load peak hours. A sophisticated controlled charging station is developed for PHEVs to alleviate grid load during peak demand hours. A novel feedback linearization embedded full recurrent adaptive NeuroFuzzy Legendre wavelet control (FBL-FRANF-Leg-WC) technique is employed to control the charging of PHEVs. The antecedent part of the NeuroFuzzy framework is based on recurrent Gaussian membership function while the consequent part comprises of recurrent Legendre wavelet. The charging station is integrated into …

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Combined System Identification And Robust Control Of A Gimbal Platform, Mehmet Baskin, Mehmet Kemal Leblebi̇ci̇oğlu Jan 2021

Combined System Identification And Robust Control Of A Gimbal Platform, Mehmet Baskin, Mehmet Kemal Leblebi̇ci̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Gimbaled imaging systems require very high performance inertial stabilization loops to achieve clear image acquisition, precise pointing, and tracking performance. Therefore, higher bandwidths become essential to meet recent increased performance demands. However, such systems often posses flexible dynamics around target bandwidth and time delay of gyroscope sensors which put certain limit to achievable bandwidths. For inertial stabilization loops, widely used design techniques have difficulty in achieving large bandwidth and satisfying required robustness simultaneously. Clearly, high performance control design hinges on accurate control-relevant model set. For that reason, combined system identification and robust control method is preferred. In the system identification …

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Analyzing Students' Experience In Programming With Computational Thinkingthrough Competitive, Physical, And Tactile Games: The Quadrilateral Methodapproach, M Ahsan Habib, Raja Jamilah Raja Yusof, Siti Salwah Salim, Asmiza Abdul Sani, Hazrina Sofian, Aishah Abu Bakar Jan 2021

Analyzing Students' Experience In Programming With Computational Thinkingthrough Competitive, Physical, And Tactile Games: The Quadrilateral Methodapproach, M Ahsan Habib, Raja Jamilah Raja Yusof, Siti Salwah Salim, Asmiza Abdul Sani, Hazrina Sofian, Aishah Abu Bakar

Turkish Journal of Electrical Engineering and Computer Sciences

The lack of computational thinking (CT) skills can be one of the reasons why students find themselves having difficulties in writing a good program. Therefore, understanding how CT skills can be developed is essential. This research explores how CT skills can be developed for programming through competitive, physical, and tactile games. The CT elements in this research focus on four major programming concepts, which are decomposition, pattern recognition, abstraction, and algorithmic thinking. We have conducted game activities through several algorithms that include sorting, swapping, and graph algorithms and analyzed how the game affects the student experience (SX) in understanding the …

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Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang Jan 2021

Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang

Turkish Journal of Electrical Engineering and Computer Sciences

This study develops the deep Q-network (DQN)-based noise suppression for robust speech recognition purposes under ambient noise. We thus design a reinforcement algorithm that combines DQN training with a deep neural networks (DNN) to let reinforcement learning (RL) work for complex and high dimensional environments like speech recognition. For this, we elaborate on the DQN training to choose the best action that is the quantized noise suppression gain by the observation of noisy speech signal with the rewards of DQN including both the word error rate (WER) and objective speech quality measure. Experiments demonstrate that the proposed algorithm improves speech …

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Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt Jan 2021

Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel ultrawide band (UWB) antipodal Vivaldi antenna with three pairs of slots was designed to be used as a sensor in microwave imaging systems for breast cancer detection. The proposed antenna operates in UWB frequency range of 3.05-12.2 GHz. FR4 was used as a dielectric material and as a substrate for forming the antenna that has a compact size of 36 mm x 36 mm x 1.6 mm. Frequency and time domain performance of the proposed antenna have been investigated and results show that it meets the requirements for UWB radar applications with linear phase response, …

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An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding Jan 2021

An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Edge computing is a new paradigm that provides data processing capabilities at the network edge. In view of the uneven data distribution and the constrained onboard resource, an edge device often needs to call for a number of neighboring devices as followers to cooperate on data analysis tasks. However, these followers may be rational and selfish, having their private optimization objectives such as energy efficiency. Therefore, the leader device needs to incentivize the followers to achieve a certain global objective, e.g., maximizing task accomplishment, rather than their own objectives. In this paper, we model the aforementioned challenges in edge computing …

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Ordered Physical Human Activity Recognition Based On Ordinal Classification, Duygu Bağci Daş, Derya Bi̇rant Jan 2021

Ordered Physical Human Activity Recognition Based On Ordinal Classification, Duygu Bağci Daş, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

Human activity recognition (HAR) is a critical process for applications that focus on the classification of human physical activities such as jogging, walking, downstairs, and upstairs. Ordinal classification (OC) is a special type of supervised multi-class classification in which an inherent ordering among the classes exists, such as low, medium, and high. This study combines these two concepts and introduces an approach to ?human activity recognition based on ordinal classification? (HAROC). In the proposed approach, ordinal classification is applied to human activity recognition where the physical activities can be ordered by using their signals? band power values. This is the …

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Line-Of-Sight Rate Construction For A Roll-Pitch Gimbal Via A Virtualpitch-Yaw Gimbal, Oğuzhan Çi̇fdalöz Jan 2021

Line-Of-Sight Rate Construction For A Roll-Pitch Gimbal Via A Virtualpitch-Yaw Gimbal, Oğuzhan Çi̇fdalöz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a method to construct the line of sight rate of a target with a roll-pitch gimbal and tracker is described. Construction of line-of-sight rate is performed via utilizing a virtual pitch-yaw gimbal. Kinematics of both the roll-pitch and pitch-yaw gimbals are described. A dynamical model for the roll-pitch gimbal is developed, and a nested control structure is designed to control the angular rates and line of sight angles. A kinematic model of the tracker is developed and a tracker controller is designed to keep the target in the field of view. Conversion equations between roll-pitch and pitch-yaw …

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Simultaneous Feedforward Online Command Rate Limiter Filters For Existingcontrollers, Gali̇p Serdar Tombul Jan 2021

Simultaneous Feedforward Online Command Rate Limiter Filters For Existingcontrollers, Gali̇p Serdar Tombul

Turkish Journal of Electrical Engineering and Computer Sciences

One of the biggest challenges in controller design for a mechatronics system is the actuator limitations. Either response time of the actuator or the input constraints creates limits for the controller performance and stability. In this study a novel feedforward online rate limiter scheme for arbitrary input signals is introduced by taking velocity, acceleration and jerk constraints into account, and it is investigated that how the control effort and system response is affected by the demand signal's rate of change limitations. A fin actuation system for a guided missile is given as an example where the demand signal comes from …

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Design And Analysis Of A Truncated Elliptical-Shaped Chipless Rfid Tag, Ameer Taimour Khan, Yassin Abdullah, Sidra Farhat, Wasim Nawaz, Usman Rauf Jan 2021

Design And Analysis Of A Truncated Elliptical-Shaped Chipless Rfid Tag, Ameer Taimour Khan, Yassin Abdullah, Sidra Farhat, Wasim Nawaz, Usman Rauf

Turkish Journal of Electrical Engineering and Computer Sciences

This article presents a novel polarization-insensitive chipless radio frequency identification tag having an encoding capacity of 11 bits. The proposed resonator design comprises discontinuous arc slots forming truncated elliptically shape offering 1:1 slot to bit correspondence with suppressed unwanted harmonic resonances. Electromagnetic performance analysis of the proposed tag design is done over an ungrounded Rogers RT duroid® 5880 laminate. The overall tag design covers a footprint of 15 × 15 × 0.508 mm3 offering convincingly appreciable bit density of 4.88 bits/cm2 . The realized tags are analyzed for real-world electromagnetic performance resulting in an agreement between measured and computed results. …

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An Mih-Enhanced Fully Distributed Mobility Management (Mf-Dmm) Solutionfor Real And Non-Real Time Cvbr Traffic Classes In Mobile Internet, Sankaranarayanan Parasuraman, Gayathri Rajaraman, Tamijetchelvy Ramachandiran Jan 2021

An Mih-Enhanced Fully Distributed Mobility Management (Mf-Dmm) Solutionfor Real And Non-Real Time Cvbr Traffic Classes In Mobile Internet, Sankaranarayanan Parasuraman, Gayathri Rajaraman, Tamijetchelvy Ramachandiran

Turkish Journal of Electrical Engineering and Computer Sciences

The integration of wireless access networks has progressed rapidly in recent years. Within the mobile communication environment, the operator provides multiple interface options for the mobile node (MN) to switch its connection to any access network during mobility to achieve the quality of service (QoS) for various traffic classes. The conventional centralised mobility management (CMM) scheme lacks reliability, dynamic anchoring and a single point of failure. This stimulates the distributed mobility management (DMM) scheme to handle mobility at the access network rather in a centralised manner. Therefore, in this paper, an IEEE 802.21 media independent handover (MIH) enhanced fully DMM …

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Deep Learning For Turkish Makam Music Composition, İsmai̇l Hakki Parlak, Yalçin Çebi̇, Ci̇han Işikhan, Derya Bi̇rant Jan 2021

Deep Learning For Turkish Makam Music Composition, İsmai̇l Hakki Parlak, Yalçin Çebi̇, Ci̇han Işikhan, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we introduce a new deep-learning-based system that can compose structured Turkish makam music (TMM) in the symbolic domain. Presented artificial TMM composer (ATMMC) takes eight initial notes from a human user and completes the rest of the piece. The backbone of the composer system consists of multilayered long short-term memory (LSTM) networks. ATMMC can create pieces in Hicaz and Nihavent makams in Şarkı form, which can be viewed and played with Mus2, a notation software for microtonal music. Statistical analysis shows that pieces composed by ATMMC are approximately 84% similar to training data. ATMMC is an open-source …

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Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇ Jan 2021

Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, hybrid methods are proposed for feature selection and classification of gene expression datasets. In the proposed genetic algorithm/support vector machine (GA-SVM) and genetic algorithm/k nearest neighbor (GA-KNN) hybrid methods, genetic algorithm is improved using Pearson's correlation coefficient, Relief-F, or mutual information. Crossover and selection operations of the genetic algorithm are specialized. Eight different gene expression datasets are used for classification process. The classification performances of the proposed methods are compared with the traditional GA-KNN and GA-SVM wrapper methods and other studies in the literature. Classification results demonstrate that higher accuracy rates are obtained with the proposed methods …

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Clustered Mobile Data Collection In Wsns: An Energy-Delay Trade-Of, İzzet Fati̇h Şentürk Jan 2021

Clustered Mobile Data Collection In Wsns: An Energy-Delay Trade-Of, İzzet Fati̇h Şentürk

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks enable monitoring remote areas with limited human intervention. However, the network connectivity between sensor nodes and the base station (BS) may not be always possible due to the limited transmission range of the nodes. In such a case, one or more mobile data collectors (MDCs) can be employed to visit nodes for data collection. If multiple MDCs are available, it is desirable to minimize the energy cost of mobility while distributing the cost among the MDCs in a fair manner. Despite availability of various clustering algorithms, there is no single fits all clustering solution when different requirements …

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Presentation Attack Detection For Face Recognition Using Remotephotoplethysmography And Cascaded Fusion, Mehmet Fati̇h Gündoğar, Çi̇ğdem Eroğlu Erdem Jan 2021

Presentation Attack Detection For Face Recognition Using Remotephotoplethysmography And Cascaded Fusion, Mehmet Fati̇h Gündoğar, Çi̇ğdem Eroğlu Erdem

Turkish Journal of Electrical Engineering and Computer Sciences

Spoofing (presentation) attacks are important threats for face recognition and authentication systems, which try to deceive them by presenting an image or video of a different subject, or by using a 3D mask. Remote (non-contact) photoplethysmography (rPPG) is useful for liveness detection using a facial video by estimating the heart-rate of the subject. In this paper, we first compare the presentation attack detection performance of three different rPPG-based heart rate estimation methods on four datasets (3DMAD, Replay-Attack, Replay-Mobile, and MSU-MFSD). We also present a cascaded fusion system, which utilizes a multistage ensemble of classifiers using rPPG, motion-based (including head-pose, eye-gaze …

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Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd Jan 2021

Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd

Turkish Journal of Electrical Engineering and Computer Sciences

Skin cancer is one of the most common cancers worldwide caused by excessive development of skin cells. Considering the rapid growth of the use of deep learning algorithms for skin cancer detection, selecting the optimal algorithm has become crucial to determining the efficiency of computer-aided diagnosis (CAD) systems developed for the healthcare sector. However, a sufficient number of criteria and parameters must be considered when selecting an ideal deep learning algorithm. A generally accepted method for benchmarking deep learning models for skin cancer classification is unavailable in the current literature. This paper presents a multi-criteria decision-making framework for evaluating and …

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Employing Deep Learning Architectures For Image-Based Automatic Cataractdiagnosis, Emrullah Acar, Ömer Türk, Ömer Faruk Ertuğrul, Erdoğan Aldemi̇r Jan 2021

Employing Deep Learning Architectures For Image-Based Automatic Cataractdiagnosis, Emrullah Acar, Ömer Türk, Ömer Faruk Ertuğrul, Erdoğan Aldemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Various eye diseases affect the quality of human life severely and ultimately may result in complete vision loss. Ocular diseases manifest themselves through mostly visual indicators in the early or mature stages of the disease by showing abnormalities in optics disc, fovea, or other descriptive anatomical structures of the eye. Cataract is among the most harmful diseases that affects millions of people and the leading cause of public vision impairment. It shows major visual symptoms that can be employed for early detection before the hypermature stage. Automatic diagnosis systems intend to assist ophthalmological experts by mitigating the burden of manual …

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New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin Jan 2021

New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

The spread of the novel coronavirus (COVID-19) has caused trillions of dollars of damages to the governments and health authorities by affecting the global economies. It is essential to identify, track and trace COVID-19 spread at its earliest detection. Timely action can not only reduce further spread but also help in providing an efficient medical response. Existing schemes rely on volunteer participation, and/or mobile traceability, which leads to delays in containing the spread. There is a need for an autonomous, connected, and centralized paradigm that can identify, trace and inform connected personals. We propose a novel connected Internet of Things …

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A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli Jan 2021

A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli

Turkish Journal of Electrical Engineering and Computer Sciences

The COVID-19 pandemic has caused millions of deaths and changed daily life globally. Countries have declared a half or full lockdown to prevent the spread of COVID-19. According to medical doctors, as many people as possible should be tested to identify their status, and corresponding actions then should be taken for COVID-19 positive cases. Despite the clear necessity of these medical tests, many countries are still struggling to acquire them. This fact clearly indicates the necessity of a large-scale, cheap, fast, and accurate alternative prescreening tool that can be used for the diagnosis of COVID-19 while waiting for the medical …

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A Case Study: Influence Of Circuit Impedance On The Performance Of Class-E² Resonant Power Converter For Capacitive Wireless Power Transfer, Yashwanth Bezawada, Yucheng Zhang Jan 2021

A Case Study: Influence Of Circuit Impedance On The Performance Of Class-E² Resonant Power Converter For Capacitive Wireless Power Transfer, Yashwanth Bezawada, Yucheng Zhang

Electrical & Computer Engineering Faculty Publications

The evolution of power electronics led to rapid development in wireless charging technology; as a result, a single active switch topology was introduced. The present market utilizes inductive wireless power transfer (IPT); because of the disadvantages of cost, size, and safety concerns, research on wireless power transfer was diverted towards capacitive wireless power transfer (CPT). This paper studies the optimal impedance tracking of the capacitive wireless power transfer system for maximum power transfer. Compared to prior methods developed for maximum power point tracking in power control, this paper proposes a new approach by means of finding impedance characteristics of the …

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Charge Transport, Conductivity And Seebeck Coefficient In Pristine And Tcnq Loaded Preferentially Grown Metal Organic Frameworks, Xin Chen, Kai Zhang, Zeinab Mohammed Hassan, Engelbert Redel, Helmut Baumgart Jan 2021

Charge Transport, Conductivity And Seebeck Coefficient In Pristine And Tcnq Loaded Preferentially Grown Metal Organic Frameworks, Xin Chen, Kai Zhang, Zeinab Mohammed Hassan, Engelbert Redel, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

This investigation on Metal-Organic Framework (MOF) HUKUST-1 films focuses on comparing the undoped pristine state and with the case of doping by TCNQ infiltration of the MOF pore structure. We have determined the temperature dependent charge transport and p-type conductivity for HKUST-1 films. Furthermore, the electrical conductivity and the current-voltage characteristics have been characterized in detail. Because the most common forms of MOFs, bulk MOF powders, do not lend themselves easily to electrical characterization investigations, here in this study the electrical measurements were performed on dense, compact surface-anchored metal-organic framework (SURMOF) films. These monolithic, well-defined, and (001) preferentially oriented MOF …

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