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Articles 661 - 690 of 10317
Full-Text Articles in Physical Sciences and Mathematics
A Novel Crimping Technique Approach For High Power White Good Plugs, Ömer Ci̇han Kivanç, Okan Özgönenel, Ömer Bostan, Şahi̇n Güzel, Mert Demi̇rsoy
A Novel Crimping Technique Approach For High Power White Good Plugs, Ömer Ci̇han Kivanç, Okan Özgönenel, Ömer Bostan, Şahi̇n Güzel, Mert Demi̇rsoy
Turkish Journal of Electrical Engineering and Computer Sciences
The crimping process is essential to human health and the durability of devices, especially in domestic appliances. Moreover, terminal crimping is critical to the safe transmission of electricity; incorrect crimping leads to problems including overheating of the plug, power loss, arc, and failure of the mechanical connection. In recent years, analysis has been performed by the finite element method (FEM) to prevent the incorrect design of crimping and to develop higher performance crimping techniques. A novel crimping technique for domestic appliances requiring high powered plugs is proposed in this study. After defining the crimp parameters and the materials that are …
A Hybrid Acoustic-Rf Communication Framework For Networked Control Of Autonomous Underwater Vehicles: Design And Cosimulation, Saeed Nourizadeh Azar, Oytun Erdemi̇r, Mehrullah Soomro, Özgür Gürbüz Ünlüyurt, Ahmet Onat
A Hybrid Acoustic-Rf Communication Framework For Networked Control Of Autonomous Underwater Vehicles: Design And Cosimulation, Saeed Nourizadeh Azar, Oytun Erdemi̇r, Mehrullah Soomro, Özgür Gürbüz Ünlüyurt, Ahmet Onat
Turkish Journal of Electrical Engineering and Computer Sciences
Underwater control applications, especially ones using autonomous underwater vehicles (AUVs) have become very popular for industrial and military underwater exploration missions. This has led to the requirement of establishing a high data rate communication link between base stations and AUVs, while underwater systems mostly rely on acoustic communications. However, limited data rate and considerable propagation delay are the major challenges for employing acoustic communication in missions requiring high control gains. In this paper, we propose a hybrid acoustic and RF communication framework for establishing a networked control system, in which, for long distance communication and control the acoustic link is …
Learning Target Class Eigen Subspace (Ltc-Es) Via Eigen Knowledge Grid, Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan
Learning Target Class Eigen Subspace (Ltc-Es) Via Eigen Knowledge Grid, Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan
Turkish Journal of Electrical Engineering and Computer Sciences
In one-class classification (OCC) tasks, only the target class (class-of-interest (CoI)) samples are well defined during training, whereas the other class samples are totally absent. In OCC algorithms, the high dimensional data adds computational overhead apart from its intrinsic property of curse of dimensionality. For target class learning, conventional dimensionality reduction (DR) techniques are not suitable due to negligence of the unique statistical properties of CoI samples. In this context, the present research proposes a novel target class guided DR technique to extract the eigen knowledge grid that contains the most promising eigenvectors of variance-covariance matrix of CoI samples. In …
A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan
A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan
Turkish Journal of Electrical Engineering and Computer Sciences
Today, thanks to the rapid development of technology, the importance of digital images is increasing. However, sensor errors that may occur during the acquisition, interruptions in the transmission of images and errors in storage cause noise that degrades data quality. Salt and pepper noise, a common impulse noise, is one of the most well-known types of noise in digital images. This noise negatively affects the detailed analysis of the image. It is very important that pixels affected by noise are restored without loss of image fine details, especially at high level of noise density. Although many filtering algorithms have been …
Blmdp: A New Bi-Level Markov Decision Process Approach To Joint Bidding Andtask-Scheduling In Cloud Spot Market, Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi
Blmdp: A New Bi-Level Markov Decision Process Approach To Joint Bidding Andtask-Scheduling In Cloud Spot Market, Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi
Turkish Journal of Electrical Engineering and Computer Sciences
In the cloud computing market (CCM), computing services are traded between cloud providers and consumers in the form of the computing capacity of virtual machines (VMs). The Amazon spot market is one of the most well-known markets in which the surplus capacity of data centers is auctioned off in the form of VMs at relatively low prices. For each submitted task, the user can offer a price that is higher than the current price. However, uncertainty in the market environment confronts the user with challenges such as the variable price of VMs and the variable number of users. An appropriate …
Priority Enabled Content Based Forwarding In Fog Computing Via Sdn, Yasi̇n İnağ, Metehan Güzel, Feyza Yildirim Okay, Mehmet Demi̇rci̇, Suat Özdemi̇r
Priority Enabled Content Based Forwarding In Fog Computing Via Sdn, Yasi̇n İnağ, Metehan Güzel, Feyza Yildirim Okay, Mehmet Demi̇rci̇, Suat Özdemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
As the number of Internet of Things (IoT) applications increases, an efficient transmitting of the data generated by these applications to a centralized cloud server can be a challenging issue. This paper aims to facilitate transmission by utilizing fog computing (FC) and software defined networking (SDN) technologies. To this end, it proposes two novel content based forwarding (CBF) models for IoT networks. The first model takes advantage of FC to reduce transmission and computational delay. Based on the first model, the second model makes use of the prioritization concept to address the timely delivery of critical data while ensuring the …
Estimation Of Mode Shape In Power Systems Under Ambient Conditions Using Advanced Signal Processing Approach, Rahul S, Sunitha R
Estimation Of Mode Shape In Power Systems Under Ambient Conditions Using Advanced Signal Processing Approach, Rahul S, Sunitha R
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a dynamic approach for the monitoring and estimation of electromechanical oscillatory modes in the power system in real time with less computational burden. Extensive implementation of phasor measurement units (PMU) and the utilization of advanced signal processing techniques help in identifying the dynamic behaviors of oscillatory modes. Conventional nonstationary analysis techniques are computationally weak to handle a larger quantity of data in real-time. This research utilizes the variational mode decomposition (VMD) for signal decomposition, which is highly tolerant to noise and computationally more robust. The predefined parameters of the VMD process are assigned using FFT analysis of …
Evaluating The Role Of Carbon Quantum Dots Covered Silica Nanofillers On The Partial Discharge Performance Of Transformer Insulation, Kasi Viswanathan Palanisamy, Chandrasekar Subramaniam, Balaji Sakthivel
Evaluating The Role Of Carbon Quantum Dots Covered Silica Nanofillers On The Partial Discharge Performance Of Transformer Insulation, Kasi Viswanathan Palanisamy, Chandrasekar Subramaniam, Balaji Sakthivel
Turkish Journal of Electrical Engineering and Computer Sciences
The article presents the experimental results on the role of carbon quantum dots (CQD) covered silica nanofillers on the partial discharge (PD) properties of transformer oil insulation. The improvement in PD performance of nanofiller blend oil is tested with increased voltage gradient and nanofiller concentration. PD of nanoblend oils for various concentrations of modified silica ranging from 0 to 0.1%wt was measured. PD activity of the test samples is simulated in the laboratory with needle, rod and plane electrode geometry combinations. The facets of PD signals such as PD magnitude, PD inception and time duration of PD extracted from phase-resolved …
A Novel Deep Reinforcement Learning Based Stock Price Prediction Using Knowledge Graph And Community Aware Sentiments, Anil Berk Altuner, Zeynep Hi̇lal Ki̇li̇mci̇
A Novel Deep Reinforcement Learning Based Stock Price Prediction Using Knowledge Graph And Community Aware Sentiments, Anil Berk Altuner, Zeynep Hi̇lal Ki̇li̇mci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Stock market prediction has been an important topic for investors, researchers, and analysts. Because it is affected by too many factors, stock market prediction is a difficult task to handle. In this study, we propose a novel method that is based on deep reinforcement learning methodologies for the prediction of stock prices using sentiments of community and knowledge graph. For this purpose, we firstly construct a social knowledge graph of users by analyzing relations between connections. After that, time series analysis of related stock and sentiment analysis is blended with deep reinforcement methodology. Turkish version of Bidirectional Encoder Representations from …
A New Speed Planning Method Based On Predictive Curvature Calculation For Autonomous Driving, Beki̇r Öztürk, Volkan Sezer
A New Speed Planning Method Based On Predictive Curvature Calculation For Autonomous Driving, Beki̇r Öztürk, Volkan Sezer
Turkish Journal of Electrical Engineering and Computer Sciences
As the number of vehicles in traffic is increasing day by day, the accident rates and driving effort are significantly raising. For this reason, ensuring safety and driving comfort is becoming more and more important. Driver assistance systems are the most common systems that are adopted for this purpose. With the development of technology, lane tracking support and adaptive cruise control systems are now being sold as standard equipment. More advanced research is being done for fully autonomous driving. One of the most critical parts of autonomous driving is speed profile planning. In this paper, a curvature-based predictive speed planner …
Lightweight Distributed Computing Framework For Orchestrating High Performance Computing And Big Data, Muhammed Numan İnce, Meli̇h Günay, Joseph Ledet
Lightweight Distributed Computing Framework For Orchestrating High Performance Computing And Big Data, Muhammed Numan İnce, Meli̇h Günay, Joseph Ledet
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the need for the ability to work remotely and subsequently the need for the availability of remote computer-based systems has increased substantially. This trend has seen a dramatic increase with the onset of the 2020 pandemic. Often local data is produced, stored, and processed in the cloud to remedy this flood of computation and storage needs. Historically, HPC (high performance computing) and the concept of big data have been utilized for the storage and processing of large data. However, both HPC and Hadoop can be utilized as solutions for analytical work, though the differences between these may …
Strategic Integration Of Battery Energy Storage And Photovoltaic At Low Voltage Level Considering Multiobjective Cost-Benefit, Samarjit Patnaik, Manas Nayak, Meera Viswavandya
Strategic Integration Of Battery Energy Storage And Photovoltaic At Low Voltage Level Considering Multiobjective Cost-Benefit, Samarjit Patnaik, Manas Nayak, Meera Viswavandya
Turkish Journal of Electrical Engineering and Computer Sciences
Renewable energy sources, such as solar photovoltaic (PV) systems and battery energy storage systems (BESS), help reduce greenhouse gas emissions while fulfilling the world?s growing energy demand. The inclusion of BESS reduces the peak hour demand, and control of charging and discharging of BESS can be economical for distributors facing time-based energy pricing. This paper discusses a novel multiobjective Horse herd optimisation algorithm (MOHHOA) approach, which is inspired by the social behaviour of horses in herds for PV and BESS optimal allocation in the radial distribution system. The proposed algorithm combines multiple benefits like benefits from economic gain per day, …
Offline Tuning Mechanism Of Joint Angular Controller For Lower-Limb Exoskeleton With Adaptive Biogeographical-Based Optimization, Mohammad Soleimani Amiri, Rizauddin Ramli
Offline Tuning Mechanism Of Joint Angular Controller For Lower-Limb Exoskeleton With Adaptive Biogeographical-Based Optimization, Mohammad Soleimani Amiri, Rizauddin Ramli
Turkish Journal of Electrical Engineering and Computer Sciences
Designing an accurate controller to overcome the nonlinearity of dynamic systems is a technical matter in control engineering, particularly for tuning the parameters of the controller precisely. In this paper, a tuning mechanism for a proportional-integral-derivative (PID) controller of lower limb exoskeleton (LLE) joints by adaptive biogeographical based-optimization (ABBO) is presented. The tuning of the controller is defined as an optimization problem and solved by ABBO, which is an iterative algorithm inspired by a blending crossover operator (BLX-?). The parameters of the migration change proportionally to the growth of iteration that conveys the error to rapid convergence by narrowing the …
Software Security Management In Critical Infrastructures: A Systematic Literature Review, Gülsüm Ece Ekşi̇, Bedi̇r Teki̇nerdoğan, Cagatay Catal
Software Security Management In Critical Infrastructures: A Systematic Literature Review, Gülsüm Ece Ekşi̇, Bedi̇r Teki̇nerdoğan, Cagatay Catal
Turkish Journal of Electrical Engineering and Computer Sciences
Critical infrastructure (CI) is an integrated set of systems and assets that are essential to ensure the functioning of a nation, including its economy, the public's health and/or safety. Hence, protecting critical infrastructures (CI) is vital because of the potential severe consequences that may emerge at the national level. Many CIs are now controlled by software, and likewise, software is often the major source of many security problems in critical infrastructures. Software security management in CIs has been addressed in the literature and several useful approaches have been provided. Yet, these approaches are fragmented over multiple different studies, often do …
A Survey On Organizational Choices For Microservice-Based Software Architectures, Hüseyi̇n Ünlü, Burak Bi̇lgi̇n, Onur Demi̇rörs
A Survey On Organizational Choices For Microservice-Based Software Architectures, Hüseyi̇n Ünlü, Burak Bi̇lgi̇n, Onur Demi̇rörs
Turkish Journal of Electrical Engineering and Computer Sciences
During the last decade, the demand for more flexible, responsive, and reliable software applications increased exponentially. The availability of internet infrastructure and new software technologies to respond to this demand led to a new generation of applications. As a result, cloud-based, distributed, independently deployable web applications working together in a microservice-based software architecture style have gained popularity. The style has been a common practice in the industry and successfully utilized by companies. Adopting this style demands software organizations to transform their culture. However, there is a lack of research studies that explores common practices for microservices. Thus, we performed a …
An Efficient End-To-End Deep Neural Network For Interstitial Lung Disease Recognition And Classification, Masum Shah Junayed, Afsana Ahsan Jeny, Md Baharul Islam, Ikhtiar Ahmed, Afm Shahen Shah
An Efficient End-To-End Deep Neural Network For Interstitial Lung Disease Recognition And Classification, Masum Shah Junayed, Afsana Ahsan Jeny, Md Baharul Islam, Ikhtiar Ahmed, Afm Shahen Shah
Turkish Journal of Electrical Engineering and Computer Sciences
The automated Interstitial Lung Diseases (ILDs) classification technique is essential for assisting clinicians during the diagnosis process. Detecting and classifying ILDs patterns is a challenging problem. This paper introduces an end-to-end deep convolution neural network (CNN) for classifying ILDs patterns. The proposed model comprises four convolutional layers with different kernel sizes and Rectified Linear Unit (ReLU) activation function, followed by batch normalization and max-pooling with a size equal to the final feature map size well as four dense layers. We used the ADAM optimizer to minimize categorical cross-entropy. A dataset consisting of 21328 image patches of 128 CT scans with …
An Adaptive Search Equation-Based Artificial Bee Colony Algorithm For Transportation Energy Demand Forecasting, Durmuş Özdemi̇r, Safa Dörterler
An Adaptive Search Equation-Based Artificial Bee Colony Algorithm For Transportation Energy Demand Forecasting, Durmuş Özdemi̇r, Safa Dörterler
Turkish Journal of Electrical Engineering and Computer Sciences
This study aimed to develop a new adaptive artificial bee colony (A-ABC) algorithm that can adaptively select an appropriate search equation to more accurately estimate transport energy demand (TED). Also, A-ABC and canonical artificial bee colony (C-ABC) algorithms were compared in terms of efficiency and performance. The input parameters used in the proposed TED model were the official economic indicators of Turkey, including gross domestic product (GDP), population, and total vehicle kilometer per year (TKM). Three mathematical models, linear (A-ABCL), exponential (A-ABCE), and quadratic (A-ABCQ) were developed and tested. Also, economic variables were generated using the "curve fitting" technique to …
Dual-Polarized Elliptic-H Slot-Coupled Patch Antenna For 5g Applications, Emre Alp Mi̇ran, Mehmet Çi̇ydem
Dual-Polarized Elliptic-H Slot-Coupled Patch Antenna For 5g Applications, Emre Alp Mi̇ran, Mehmet Çi̇ydem
Turkish Journal of Electrical Engineering and Computer Sciences
A dual-polarized, slot-coupled dielectric patch antenna design is presented in sub-6 GHz for 5G base stations. Proposed antenna is implemented using two dielectric patch layers (main patch and parasitic patch) above a feeding line layer. Excitation is realized by crossed elliptic-H slots in order to create orthogonal ± 45$^{\circ}$ polarizations. Through the use of patches at proper heights together with elliptic-H slots, significant improvement in impedance bandwidth, matching level, isolation and front-to-back ratio is acquired. Prototype antenna has an impedance bandwidth of 18.5\% (3.23--3.85 GHz) for $ S_{11} $, $ S_{22} $ $
Missing Samples Reconstruction Using An Efficient And Robust Instantaneous Frequency Estimation Algorithm, Sadiq Ali, Nabeel Ali Khan
Missing Samples Reconstruction Using An Efficient And Robust Instantaneous Frequency Estimation Algorithm, Sadiq Ali, Nabeel Ali Khan
Turkish Journal of Electrical Engineering and Computer Sciences
In order to recover missing samples in a nonstationary signal, this paper employs a time-signal analysis and filtering method. The instantaneous frequency of a multicomponent signal is first estimated by employing a robust and computationally efficient method. Then the time-frequency filtering is performed using a dechirping operation to recover missing samples. These steps are repeated until convergence. The proposed method achieves better performance than the state of art methods both in terms of the accuracy of the recovered signal and computational efficiency.
Classification And Phenological Staging Of Crops From In Situ Image Sequences By Deep Learning, Uluğ Bayazit, Deni̇z Turgay Altilar, Ni̇lgün Güler Bayazit
Classification And Phenological Staging Of Crops From In Situ Image Sequences By Deep Learning, Uluğ Bayazit, Deni̇z Turgay Altilar, Ni̇lgün Güler Bayazit
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate knowledge of crop type information is not only valuable for verifying the declaration of farmers to obtain subsidy or insurance for the grown crop, but also for generating crop type maps that serve a variety of purposes in land monitoring and policy. On the other hand, accurate knowledge of crop phenological stage can help farm personnel apply fertilization and irrigation regimes on a timely basis. Although deep learning based networks have been applied in the past to classify the type and predict the phenological stage of crops from in situ images of fields, more advanced deep learning based networks, …
Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz
Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
TV rating is a numeric estimate of the popularity of television programs. Forecasting TV ratings is considered an important asset for investment planning of media due to its potential of reducing the risks of future ventures. The aim of this study is to develop a machine learning model capable of efficiently forecasting the TV ratings of Turkish TV series in a practical manner. To this end, two prediction models were proposed for forecasting the TV ratings of television series, facilitating an extensive set of features. A contribution of this study is the inclusion of social media-based features using search trends …
Long-Term Traffic Flow Estimation: A Hybrid Approach Using Location-Basedtraffic Characteristic, Tuğberk Ayar, Ferhat Atli̇nar, Mehmet Amaç Güvensan, Hafi̇za İrem Türkmen
Long-Term Traffic Flow Estimation: A Hybrid Approach Using Location-Basedtraffic Characteristic, Tuğberk Ayar, Ferhat Atli̇nar, Mehmet Amaç Güvensan, Hafi̇za İrem Türkmen
Turkish Journal of Electrical Engineering and Computer Sciences
Traffic speed estimation plays a key role in various situations, ranging from individual's trip planning to urban traffic management. Despite many studies on short-term prediction, there is only a limited number of studies focusing on long-term prediction and only a couple of them does go beyond 24 h. On the contrary, this study presents a novel hybrid architecture using location-based traffic characteristic for traffic speed estimation up to 7 days. In this architecture, the introduced mean filtering estimation (MFE) model and long short-term memory (LSTM) neural network are jointly utilized for minimizing the error for traffic flow estimation. Both MFE …
Privacy Preserving Scheme For Document Similarity Detection, Ayad Abdulsada, Salah Al-Darraji, Dhafer Honi
Privacy Preserving Scheme For Document Similarity Detection, Ayad Abdulsada, Salah Al-Darraji, Dhafer Honi
Turkish Journal of Electrical Engineering and Computer Sciences
The problem of detecting similar documents plays an essential role for many real-world applications, such as copyright protection and plagiarism detection. To protect data privacy, the new version of such a problem becomes more challenging, where the matched documents are distributed among two or more parties and their privacy should be preserved. In this paper, we propose new privacy-preserving document similarity detection schemes by utilizing the locality-sensitive hashing technique, which can handle the misspelled mistakes. Furthermore, the keywords' occurrences of a given document are integrated into its underlying representation to support a better ranking for the returned results. We introduced …
Critical Speed Calculation Of A Refurbishment Of 11mw Hydro Power Plant Unit, Ahmet Seli̇m Pehli̇van, Dario Kraljevic, Ivan Triplat, Beste Bahçeci̇
Critical Speed Calculation Of A Refurbishment Of 11mw Hydro Power Plant Unit, Ahmet Seli̇m Pehli̇van, Dario Kraljevic, Ivan Triplat, Beste Bahçeci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Hydro generator design is a significant issue in terms of safety, efficiency, and energy production sustainability. One of the most crucial issues about design criteria is to satisfy the needs of the project?s critical speed. In this work, the critical speed calculation of an 11 MW hydro power plant was investigated with several design steps. Numerical solution methodologies were implemented using ARMD?. A generator design was developed, and the implementation of the rotor was carried out in Antalya, Turkey. Vibration and displacements of the hydro generator are adequate. The generator unit is active for 3 years and have never encountered …
Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş
Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş
Turkish Journal of Electrical Engineering and Computer Sciences
The aerodynamic design and analysis of an Unmanned Air Vehicle, capable of vertical take-off and landing by employing fixed four rotors on the tilt-wing and two rotors on the tilt-tail, will be presented in this study. Both main wing and the horizontal tail can be tilted 90°. During VTOL, transition and forward flight, aerodynamic and thrust forces have been employed. Different flight conditions, including the effects of angle of attack, side slip, wing tilt angle and control surfaces deflection angle changes, have been studied with CFD analysis. For a Tilt-Wing UAV, there are challenges like high non-linearity, vulnerability to disturbances …
Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft
Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft
Turkish Journal of Electrical Engineering and Computer Sciences
The massive use of social media causes rapid information dissemination that amplifies harmful messages such as fake news. Fake-news is misleading information presented as factual news that is generally used to manipulate public opinion. In particular, fake news related to COVID-19 is defined as 'infodemic' by World Health Organization. An infodemic is a misleading information that causes confusion which may harm health. There is a high volume of misinformation about COVID-19 that causes panic and high stress. Therefore, the importance of development of COVID-19 related fake news identification model is clear and it is particularly important for Turkish language from …
The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan
The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan
Turkish Journal of Electrical Engineering and Computer Sciences
The meaningful performance of convolutional neural network (CNN) has enabled the solution of various state-of-the-art problems. Although CNNs achieve satisfactory results in computer-vision problems, they still have some difficulties. As the designed CNN models are deepened to achieve much better accuracy, computational cost and complexity increase. It is significant to train CNNs with suitable topology and training hyperparameters that include initial learning rate, minibatch size, epoch number, filter size, number of filters, etc. because the initialization of hyperparameters affects classification results. On the other hand, it is not possible to make a definite inference for the hyperparameter initialization and there …
A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani
A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani
Turkish Journal of Electrical Engineering and Computer Sciences
A new design of current mode instrumentation amplifier (CMIA) with tunable gain and low voltage operation capability is proposed in this paper, which is suitable for biomedical signals processing, especially in electrocardiogram (ECG). It consists of a new design of current differencing transconductance amplifier (CDTA) and dual z copy CDTA (DZC-CDTA). The gain of the proposed CMIA is controlled by a MOS-based tunable resistor. The main advantage of the proposed CMIA is its high gain that can be tuned over a significant range with the help of two resistances. The performance of the proposed instrumentation amplifier is evaluated through simulation …
A Factor Graph Optimization Mapping Based On Normaldistributions Transform, Kedi Zhong, Yuansheng Liu, Jiansuo Yang, Ming Lu, Jun Zhang
A Factor Graph Optimization Mapping Based On Normaldistributions Transform, Kedi Zhong, Yuansheng Liu, Jiansuo Yang, Ming Lu, Jun Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
This paper aims to achieve highly accurate mapping results and real time pose estimation of autonomous vehicle by using the normal distribution transform (NDT) algoritm. A factor graph optimization algorithm (FGO-NDT) is proposed to address the poor real-time performance and pose drift errors of the NDT algorithm. Smooth point cloud data are obtained by multisensor calibration and data preprocessing. NDT registration is then used for lidar odometry and feature matching. The global navigation satellite system (GNSS) data and loop detection results are added to the factor graph framework as the pose constraint factors to optimize the pose trajectory and eliminate …
Investigations On Cogging Torque Mitigation Techniques Of Transverse Flux Motorfor Direct Drive Low-Speed Spacecraft Applications, Ravichandran Mh, Venkatakirthiga Murali, Haridas Tr
Investigations On Cogging Torque Mitigation Techniques Of Transverse Flux Motorfor Direct Drive Low-Speed Spacecraft Applications, Ravichandran Mh, Venkatakirthiga Murali, Haridas Tr
Turkish Journal of Electrical Engineering and Computer Sciences
The transverse flux motor (TFM) is an ideal choice for direct drive high torque applications owing to its proven higher torque density compared to the radial flux and axial flux motors. TFM motors have several merits to be used for spacecraft applications, considering the everlasting demand of the industry for reduction in power and mass. This paper investigates the various cogging torque mitigation techniques for transverse flux motor to be effectively used as the drive motor for precise position control spacecraft requirement. The paper discusses the basic design variables of surface mounted TFM (SM-TFM) that are to be considered for …