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Articles 811 - 840 of 3106
Full-Text Articles in Engineering
Channel And Carrier Frequency Offset Estimation Based On Projection Onto Abidimensional Basis, Roberto Carrasco Alvarez, Ramon Parra Michel, Aldo Gustavo Orozco Lugo, Marco Antonio Gurrola Navarro
Channel And Carrier Frequency Offset Estimation Based On Projection Onto Abidimensional Basis, Roberto Carrasco Alvarez, Ramon Parra Michel, Aldo Gustavo Orozco Lugo, Marco Antonio Gurrola Navarro
Turkish Journal of Electrical Engineering and Computer Sciences
Two of the most counterproductive effects that must be dealt with in communication systems in realistic environments are carrier frequency offset (CFO) and time-varying channels. These problems are usually addressed by using independent approaches for each one. This paper introduces an algorithm that attacks both of these effects in a joint fashion. It is based on a rough compensation of CFO, and after considering that the remaining CFO uncertainty can be seen as part of the time-varying channel a channel estimation that includes that composite channel is performed. Particularly, the channel estimation based on projection onto a bidimensional basis is …
Defect Detection Of Seals In Multilayer Aseptic Packages Using Deep Learning, Kemal Adem, Cemi̇l Közkurt
Defect Detection Of Seals In Multilayer Aseptic Packages Using Deep Learning, Kemal Adem, Cemi̇l Közkurt
Turkish Journal of Electrical Engineering and Computer Sciences
Sealing in aseptic packages, one of the healthiest and cheapest technologies to protect food from parasites in the liquid food industry, requires a detailed and careful control process. Since the controls are made manually and visually by expert machine operators, the human factor can lead to the failure to detect defects, resulting in high cost and food safety risks. Therefore, this study aims to perform a leak test in aseptic package seals by a system that makes decisions using independent deep learning methods. The proposed Faster R-CNN and the Updated Faster R-CNN deep learning models were subjected to training and …
On The Output Regulation For Linear Fractional Systems, Jesus Alberto Meda Campana, Elba Cinthya Garcia Estrada, Julio Cesar Gomez Mancilla, Jose De Jesus Rubio Avila, Mario Ricardo Cruz Deviana, Ricardo Tapia Herrera
On The Output Regulation For Linear Fractional Systems, Jesus Alberto Meda Campana, Elba Cinthya Garcia Estrada, Julio Cesar Gomez Mancilla, Jose De Jesus Rubio Avila, Mario Ricardo Cruz Deviana, Ricardo Tapia Herrera
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, the regulation problem is extended to the field of fractional-order linear systems considering the Caputo fractional derivative. The regulation equations are obtained on the basis of the Francis equations. It is also shown that the linear fractional regulator exists at $t=0$ only if the order of the plant is not greater than the order of the reference system.
Optimal Rescheduling Of Real Power To Mitigate Congestion Using Gravitational Search Algorithm, Kaushik Paul, Niranjan Kumar, Shaligram Agrawal, Kamalendu Paul
Optimal Rescheduling Of Real Power To Mitigate Congestion Using Gravitational Search Algorithm, Kaushik Paul, Niranjan Kumar, Shaligram Agrawal, Kamalendu Paul
Turkish Journal of Electrical Engineering and Computer Sciences
The initiative to manage congestion has gained interest in the current deregulated scenario. The principle commitment of the work in this article is to extend the gravitational search algorithm (GSA) as an efficient metaheuristic optimizing algorithm to diminish the rescheduling cost and efficiently attenuate the overloading of the line with the minimal deviation in the active power generation. The congestion management drive is accomplished by prioritizing the generators based on their sensitivity values. Thereafter, the GSA is introduced to optimally minimize the rescheduling cost along with the minimization of the total amount of active power output and system losses. The …
A New Approach For Parameter Estimation Of The Single-Diode Model Forphotovoltaic Cells/Modules, Bi̇lge Kaan Atay, Ulaş Emi̇noğlu
A New Approach For Parameter Estimation Of The Single-Diode Model Forphotovoltaic Cells/Modules, Bi̇lge Kaan Atay, Ulaş Emi̇noğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Solar energy has become a popular renewable energy source, leading to wide use of photovoltaic (PV) cells/modules in energy production. For this reason, realistic modeling of PVs and determining the equivalent circuit parameters is of great importance in terms of planning and operation. Hence, in this study, an analytical model for identifying the single-diode equivalent circuit parameters; series resistance (Rs ), shunt resistance (Rp ), diode ideality factor (a), diode reverse-saturation current (Io ), and photon current (Ipv ) for PV cells/modules is developed without neglecting any term. In order to test the accuracy of the model, a number of …
Lower Order Controller Design Using Weighted Singular Perturbation Approximation, Muhammad Raees Furquan Azhar, Umair Zulfiqar, Muwahida Liaquat
Lower Order Controller Design Using Weighted Singular Perturbation Approximation, Muhammad Raees Furquan Azhar, Umair Zulfiqar, Muwahida Liaquat
Turkish Journal of Electrical Engineering and Computer Sciences
Most of the analytical design procedures yield controllers of almost the same order as that of the plant. Resultantly, if the plant is of a high order, the controller obtained from these design procedures is also of a high order. The order of the controller should be practically acceptable for easy implementation. There are two indirect methods for designing a low order controller for high order plants: plant reduction and compensator reduction. In compensator reduction, the order of the controller designed for the original higher order plant is reduced. In plant reduction, the order of the plant is reduced for …
Enabling Space Time Division Multiple Access In Ietf 6tisch Protocol, Sedat Görmüş, Sercan Külcü
Enabling Space Time Division Multiple Access In Ietf 6tisch Protocol, Sedat Görmüş, Sercan Külcü
Turkish Journal of Electrical Engineering and Computer Sciences
IETF 6TiSCH standard aims to create reliable, deterministic, and low-power networks by scheduling bandwidth resources in time and frequency domains. The main emphasis of 6TiSCH protocol is that it creates Internet of things (IoT) networks with a deterministic and controllable delay. However, many of its benefits are tied to the ability of the 6TiSCH scheduler to optimally distribute radio resources among wireless nodes which may not be possible when the number of frequency resources are limited and several other wireless technologies share the same frequency band (e.g., WiFi, Bluetooth and IEEE 802.15.4). Here the integration of a low-complexity directional antenna …
Stegogis: A New Steganography Method Using The Geospatial Domain, Ömer Kurtuldu, Mehmet Demi̇rci̇
Stegogis: A New Steganography Method Using The Geospatial Domain, Ömer Kurtuldu, Mehmet Demi̇rci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Geographic data are used on a variety of computing devices for many different applications including navigation, tracking, location planning, and marketing. The prevalence of geographic data makes it possible to envision new useful applications. In this paper, we propose using geographic data as a medium for secret communication, or steganography. We develop a method called StegoGIS for hiding messages in geographic coordinates in the well-known binary of fast-moving objects and transmitting them secretly. We show that discovering this secret communication is practically impossible for third parties. We also show that a large amount of secret data can be transmitted this …
Improving Undersampling-Based Ensemble With Rotation Forest For Imbalanced Problem, Huaping Guo, Xiaoyu Diao, Hongbing Liu
Improving Undersampling-Based Ensemble With Rotation Forest For Imbalanced Problem, Huaping Guo, Xiaoyu Diao, Hongbing Liu
Turkish Journal of Electrical Engineering and Computer Sciences
As one of the most challenging and attractive issues in pattern recognition and machine learning, the imbalanced problem has attracted increasing attention. For two-class data, imbalanced data are characterized by the size of one class (majority class) being much larger than that of the other class (minority class), which makes the constructed models focus more on the majority class and ignore or even misclassify the examples of the minority class. The undersampling-based ensemble, which learns individual classifiers from undersampled balanced data, is an effective method to cope with the class-imbalance data. The problem in this method is that the size …
Pv-Based Off-Board Electric Vehicle Battery Charger Using Bidc, Ankita Paul, Krithiga Subramanian, Sujitha N
Pv-Based Off-Board Electric Vehicle Battery Charger Using Bidc, Ankita Paul, Krithiga Subramanian, Sujitha N
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the use of renewable energy sources is increasing drastically in several sectors, which leads to its role in the automobile industry to charge electric vehicle (EV) batteries. In this paper, a photovoltaic (PV) array-fed off-board battery charging system using a bidirectional interleaved DC-DC converter (BIDC) is proposed for light-weight EVs. This off-board charging system is capable of operating in dual mode, thereby supplying power to the EV battery from the PV array in standstill conditions and driving the DC load by the EV battery during running conditions. This dual mode operation is accomplished by the use of …
A Control Scheme For Maximizing The Delivered Power To The Load In A Standalonewind Energy Conversion System, Saeed Heshmatian, Davood A. Khaburi, Mahyar Khosravi, Ahad Kazemi
A Control Scheme For Maximizing The Delivered Power To The Load In A Standalonewind Energy Conversion System, Saeed Heshmatian, Davood A. Khaburi, Mahyar Khosravi, Ahad Kazemi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a control scheme is proposed for maximum power point tracking (MPPT) in a variable speed standalone wind energy conversion system (WECS) with permanent magnet synchronous generator. A MPPT algorithm is designed trying to eliminate the main deficiency of the conventional perturbation and observation (P&O) method, which is the challenge of choosing a proper step size and the unwanted trade-off between accuracy and speed. The designed algorithm properly addresses this drawback and significantly improves the MPPT performance. Another important issue is to ensure fast and accurate tracking of the optimal reference point obtained from the MPPT algorithm and …
Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony
Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, enormous progress has been made on power generation using photovoltaic (PV) system. Solar power is one of the most promising renewable energy sources that is providing its benefit specifically in rural areas. With the increasing need for solar energy, it becomes necessary to extract maximum power from the PV array. The output power of the solar cells varies directly with the ambient temperature and Irradiation. Therefore, the challenge is to track maximum power from the PV array when environmental factors change. This paper focuses on increasing the efficiency of a PV array by incorporating artificial intelligence techniques. …
Exploring Bigram Character Features For Arabic Text Clustering, Dia Eddin Abuzeina
Exploring Bigram Character Features For Arabic Text Clustering, Dia Eddin Abuzeina
Turkish Journal of Electrical Engineering and Computer Sciences
The vector space model (VSM) is an algebraic model that is widely used for data representation in text mining applications. However, the VSM poses a critical challenge, as it requires a high-dimensional feature space. Therefore, many feature selection techniques, such as employing roots or stems (i.e. words without infixes and prefixes, and/or suffixes) instead of using complete word forms, are proposed to tackle this space challenge problem. Recently, the literature shows that one more basic unit feature can be used to handle the textual features, which is the twoneighboring character form that we call microword. To evaluate this feature type, …
Design Of A Substrate Integrated Waveguide Matrix Amplifier, Shabnam Ahamadi Andevari, Gholamreza Moradi
Design Of A Substrate Integrated Waveguide Matrix Amplifier, Shabnam Ahamadi Andevari, Gholamreza Moradi
Turkish Journal of Electrical Engineering and Computer Sciences
Developments in microwave systems have increased the need for matrix amplifiers, which provide both high gain and wide frequency bands. The aim of this paper is to design a novel 2x4 matrix amplifier with a substrate integrated waveguide (SIW)-based power divider and combiner and a microstrip gain equalizer in the X and low Ku frequency bands. The proposed amplifier can be easily integrated with any microstrip, rectangular waveguide, or SIW-based circuits. The analysis and design of the amplifier is performed using two full wave simulators with different computational techniques (finite element method and finite integration technique) to verify the results. …
Symptom-Aware Hybrid Fault Diagnosis Algorithm In The Network Virtualization Environment, Yuze Su, Xiangru Meng, Xiaoyang Han, Qiaoyan Kang
Symptom-Aware Hybrid Fault Diagnosis Algorithm In The Network Virtualization Environment, Yuze Su, Xiangru Meng, Xiaoyang Han, Qiaoyan Kang
Turkish Journal of Electrical Engineering and Computer Sciences
As an important technology in next-generation networks, network virtualization has received more and more attention. Fault diagnosis is the crucial element for fault management and it is the process of inferring the exact failure in the network virtualization environment (NVE) from the set of observed symptoms. Although various traditional fault diagnosis algorithms have been proposed, the virtual network has some new characteristics, which include inaccessible fault information of the substrate network, inaccurate network observations, and a dynamic embedding relationship. To solve these challenges, a symptom-aware hybrid fault diagnosis (SAHFD) algorithm in the NVE is proposed in this paper. First, a …
Community Detection In Complex Networks Using A New Agglomerative Approach, Majid Arasteh, Somayeh Alizadeh
Community Detection In Complex Networks Using A New Agglomerative Approach, Majid Arasteh, Somayeh Alizadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Complex networks are used for the representation of complex systems such as social networks. Graph analysis comprises various tools such as community detection algorithms to uncover hidden data. Community detection aims to detect similar subgroups of networks that have tight interconnections with each other while, there is a sparse connection among different subgroups. In this paper, a greedy and agglomerative approach is proposed to detect communities. The proposed method is fast and often detects high-quality communities. The suggested method has several steps. In the first step, each node is assigned to a separated community. In the second step, a vertex …
A Robust Ensemble Feature Selector Based On Rank Aggregation For Developing New Vo\Textsubscript{2}Max Prediction Models Using Support Vector Machines, Fatih Abut, Mehmet Fati̇h Akay, James George
A Robust Ensemble Feature Selector Based On Rank Aggregation For Developing New Vo\Textsubscript{2}Max Prediction Models Using Support Vector Machines, Fatih Abut, Mehmet Fati̇h Akay, James George
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a new ensemble feature selector, called the majority voting feature selector (MVFS), for developing new maximal oxygen uptake (VO2max) prediction models using a support vector machine (SVM). The approach is based on rank aggregation, which meaningfully utilizes the correlation among the relevance ranks of predictor variables given by three state-of-the-art feature selectors: Relief-F, minimum redundancy maximum relevance (mRMR), and maximum likelihood feature selection (MLFS). By applying the SVM combined with MVFS on a self-created dataset containing maximal and submaximal exercise data from 185 college students, several new hybrid (VO2max) prediction models have been created. To compare the …
Speech Emotion Recognition Using Semi-Nmf Feature Optimization, Surekha Reddy Bandela, T Kishore Kumar
Speech Emotion Recognition Using Semi-Nmf Feature Optimization, Surekha Reddy Bandela, T Kishore Kumar
Turkish Journal of Electrical Engineering and Computer Sciences
In recent times, much research is progressing forward in the field of speech emotion recognition (SER). Many SER systems have been developed by combining different speech features to improve their performances. As a result, the complexity of the classifier increases to train this huge feature set. Additionally, some of the features could be irrelevant in emotion detection and this leads to a decrease in the emotion recognition accuracy. To overcome this drawback, feature optimization can be performed on the feature sets to obtain the most desirable emotional feature set before classifying the features. In this paper, semi-nonnegative matrix factorization (semi-NMF) …
Scale-Invariant Mfccs For Speech/Speaker Recognition, Zekeri̇ya Tüfekci̇, Gökay Di̇şken
Scale-Invariant Mfccs For Speech/Speaker Recognition, Zekeri̇ya Tüfekci̇, Gökay Di̇şken
Turkish Journal of Electrical Engineering and Computer Sciences
The feature extraction process is a fundamental part of speech processing. Mel frequency cepstral coefficients (MFCCs) are the most commonly used feature types in the speech/speaker recognition literature. However, the MFCC framework may face numerical issues or dynamic range problems, which decreases their performance. A practical solution to these problems is adding a constant to filter-bank magnitudes before log compression, thus violating the scale-invariant property. In this work, a magnitude normalization and a multiplication constant are introduced to make the MFCCs scale-invariant and to avoid dynamic range expansion of nonspeech frames. Speaker verification experiments are conducted to show the effectiveness …
Investigation Of Start-Up Conditions On Electric Submersible Pump Driven With Flux Switching Motor, Mohammadhossein Barzegari Bafghi, Abolfazl Vahedi
Investigation Of Start-Up Conditions On Electric Submersible Pump Driven With Flux Switching Motor, Mohammadhossein Barzegari Bafghi, Abolfazl Vahedi
Turkish Journal of Electrical Engineering and Computer Sciences
One of the motor types that is recently considered to be a candidate for electric submersible pumps (ESPs) is the flux switching motor. Therefore, it becomes crucial to verify that this type of motor can stand ESP conditions. The main subject of this paper is to investigate the start-up condition of ESP along with considering the long power supply cable to study the motor performance, where the real aspect of the ESP conditions is investigated. Since there is not any model of pump load that models the dynamic behavior of ESP correctly, first, a model for the pump is developed. …
A Hybrid Feature-Selection Approach For Finding The Digital Evidence Of Web Application Attacks, Mohammed Babiker, Eni̇s Karaarslan, Yaşar Hoşcan
A Hybrid Feature-Selection Approach For Finding The Digital Evidence Of Web Application Attacks, Mohammed Babiker, Eni̇s Karaarslan, Yaşar Hoşcan
Turkish Journal of Electrical Engineering and Computer Sciences
The most critical challenge of web attack forensic investigations is the sheer amount of data and level of complexity. Machine learning technology might be an efficient solution for web attack analysis and investigation. Consequently, machine learning applications have been applied in various areas of information security and digital forensics, and have improved over time. Moreover, feature selection is a crucial step in machine learning; in fact, selecting an optimal feature subset could enhance the accuracy and performance of the predictive model. To date, there has not been an adequate approach to select optimal features for the evidence of web attack. …
An Automated Snick Detection And Classification Scheme As A Cricket Decision Review System, Aftab Khan, Syed Qadir Hussain, Muhammad Waleed, Ashfaq Khan, Umair Khan
An Automated Snick Detection And Classification Scheme As A Cricket Decision Review System, Aftab Khan, Syed Qadir Hussain, Muhammad Waleed, Ashfaq Khan, Umair Khan
Turkish Journal of Electrical Engineering and Computer Sciences
Umpire decisions can greatly affect the outcome of a cricket game. When there is doubt about the umpire?s call for a decision, a decision review system (DRS) may be brought into play by a batsman or bowler to validate the decision. Recently, the latest technologies, including Hotspot, Hawk-eye, and Snickometer, have been employed when there is doubt among the on-field umpire, batsman, or bowlers. This research is a step forward in gaging the true class of a snick generated from the contact of the cricket ball with either (i) the bat, (ii) gloves, (iii) pad, or (iv) a combination of …
Decision-Making For Small Industrial Internet Of Things Using Decision Fusion, Tuğrul Çavdar, Nader Ebrahimpour
Decision-Making For Small Industrial Internet Of Things Using Decision Fusion, Tuğrul Çavdar, Nader Ebrahimpour
Turkish Journal of Electrical Engineering and Computer Sciences
The industrial Internet of Things (IIoT) is a new field of Internet of Things (IoT) that has gained more popularity recently in industrial units and makes it possible to access information anywhere and anytime. In other words, geographic coordinates cannot prevent obtaining equipment and its data. Today, it is possible to manage and control equipment simply without spending time in an operational area and just by using the IIoT. This system collects data from manufacturing and production units by using wireless sensor networks or other networks for classification of fault detection. These data are then used after analysis to allow …
A Novel Randomized Recurrent Artificial Neural Network Approach: Recurrent Random Vector Functional Link Network, Ömer Faruk Ertuğrul
A Novel Randomized Recurrent Artificial Neural Network Approach: Recurrent Random Vector Functional Link Network, Ömer Faruk Ertuğrul
Turkish Journal of Electrical Engineering and Computer Sciences
The random vector functional link (RVFL) has successfully been employed in many applications since 1989. RVFL has a single hidden layer feedforward structure that also has direct links between the input layer and the output layer. Although nonlinearity, high generalization capacity, and fast training ability can be provided in RVFL, it can be found from the literature that higher nonlinearity can be obtained by adding recurrent feedback to an artificial neural network. In this paper, the recurrent type of RVFL (R-RVFL), which has both outer feedbacks and also inner feedbacks, is proposed. In order to evaluate and validate the proposed …
A Fine-Grain And Scalable Set-Based Cache Partitioning Through Thread Classification, İsa Ahmet Güney, Gürhan Küçük
A Fine-Grain And Scalable Set-Based Cache Partitioning Through Thread Classification, İsa Ahmet Güney, Gürhan Küçük
Turkish Journal of Electrical Engineering and Computer Sciences
As contemporary processors utilize more and more cores, cache partitioning algorithms tend to preserve cache associativity with a finer-grain of control to achieve higher throughput and fairness goals. In this study, we propose a scalable set-based cache partitioning mechanism, which welds an allocation policy and an enforcement scheme together. We also propose a set-based classifier to better allocate partitions to more deserving threads, a fast set redirection logic to map accesses to dedicated cache sets, and a double access mechanism to overcome the performance penalty due to a repartitioning phase. We compare our work to the best line-grain cache partitioning …
An Optimized Harmonic Elimination Method Based On Synchronized Microcontroller Architecture, Vivek Gopinath, Meenu Nair, Jayanta Biswas, Mukti Barai
An Optimized Harmonic Elimination Method Based On Synchronized Microcontroller Architecture, Vivek Gopinath, Meenu Nair, Jayanta Biswas, Mukti Barai
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes an optimized synchronous PWM method for harmonic elimination in a quasi square wave inverter. The synchronized PWM method enables online harmonic computation and PWM pulse generation in a multitasking digital controller to eliminate lower order harmonics. The multitasking digital controller reduces the look-up table requirement and helps in realizing efficient implementation to eliminate dominant harmonics. This method offers a simple scalable solution for combined fifth and seventh harmonic elimination using two low-cost eight-bit PIC microcontrollers (PIC18F4550, PIC18F452). Experimental results are demonstrated for a single-phase three-level inverter. The proposed method achieves 90$\% $ reduction of fifth and seventh …
A Hybrid Multiband Printed Loop Antenna For Wlan/Wimax Bands For Applications In Mimo Systems, Ali Shahshahani, Mohammad Amin Honarvar
A Hybrid Multiband Printed Loop Antenna For Wlan/Wimax Bands For Applications In Mimo Systems, Ali Shahshahani, Mohammad Amin Honarvar
Turkish Journal of Electrical Engineering and Computer Sciences
In this article a thin hybrid multiband printed loop antenna is presented for application in multiple-input multiple-output (MIMO) systems. The proposed antenna has several advantages; for example, the pseudofilter feature of the proposed antenna is one of this antenna's advantages. Because of the antenna's width ($9.5$~mm), it can be used on the edges of the board. The first resonant frequency is generated by the original loop of the antenna. Incorporation of different embedded components, i.e. a subsidiary loop, extended ground-traces, parasitic patch, and the slits, results in the proposed antenna resonating as a multiband antenna. This antenna is adjusted in …
Line Independency-Based Network Modelling For Backward/Forward Load Flow Analysis Of Electrical Power Distribution Systems, Reyhaneh Taheri, Alimorad Khajezadeh, Mohammad Hossein Rezaeian Koochi, Abbas Sharifi Nasab Anari
Line Independency-Based Network Modelling For Backward/Forward Load Flow Analysis Of Electrical Power Distribution Systems, Reyhaneh Taheri, Alimorad Khajezadeh, Mohammad Hossein Rezaeian Koochi, Abbas Sharifi Nasab Anari
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a straightforward method for line independency-based modelling of electrical power distribution systems is proposed. The proposed method can determine the backward and forward sweeping routes of distribution systems for calculating line currents and bus voltages. To do that, the method identifies the independent lines in consecutive steps. An independent line is a line in the distribution system whose current does not depend on the current of other lines in the system. The proposed line independency-based network modelling is required to be performed only once and prior to the load flow analysis. The output of the proposed method, …
Quantification Of Resistive Wall Instability For Particle Accelerator Machines, Fati̇h Yaman
Quantification Of Resistive Wall Instability For Particle Accelerator Machines, Fati̇h Yaman
Turkish Journal of Electrical Engineering and Computer Sciences
The aim of this study is to quantify longitudinal resistive wall impedances, corresponding wake functions, and wake potentials for different accelerator machines of interest. Accurate calculations of wake potentials by particle-in-cell codes are extremely difficult for the investigated parameters; therefore, we use an analytical approach and consider large domains with fine discretization for the required numerical integrations. The semianalytical wake potential computations are benchmarked against numerical general purpose 2D/3D Maxwell solver software codes and a different analytical approach for a certain set of parameters. We report examples to illustrate limitations of wake potential estimations from coupling impedances, and computations for …
Predicting Co And Nox Emissions From Gas Turbines: Novel Data And A Benchmark Pems, Heysem Kaya, Pinar Tüfekci̇, Erdi̇nç Uzun
Predicting Co And Nox Emissions From Gas Turbines: Novel Data And A Benchmark Pems, Heysem Kaya, Pinar Tüfekci̇, Erdi̇nç Uzun
Turkish Journal of Electrical Engineering and Computer Sciences
Predictive emission monitoring systems (PEMS) are important tools for validation and backing up of costly continuous emission monitoring systems used in gas-turbine-based power plants. Their implementation relies on the availability of appropriate and ecologically valid data. In this paper, we introduce a novel PEMS dataset collected over five years from a gas turbine for the predictive modeling of the CO and NOx emissions. We analyze the data using a recent machine learning paradigm, and present useful insights about emission predictions. Furthermore, we present a benchmark experimental procedure for comparability of future works on the data