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Articles 961 - 990 of 7169
Full-Text Articles in Computer Engineering
Low Communication Parallel Distributed Adaptive Signal Processing (Lc-Pdasp)Architecture For Processing-Inefficient Platforms, Hasan Raza, Ghalib Hussain, Noor Khan
Low Communication Parallel Distributed Adaptive Signal Processing (Lc-Pdasp)Architecture For Processing-Inefficient Platforms, Hasan Raza, Ghalib Hussain, Noor Khan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a low communication parallel distributed adaptive signal processing (LC-PDASP) architecturefor a group of computationally incapable and inexpensive small platforms is introduced. The proposed architectureis capable of running computationally high adaptive filtering algorithms parallely with minimally low communicationoverhead. A recursive least square (RLS) adaptive algorithm based on the application of multiple-input multiple-output(MIMO) channel estimation is implemented on the proposed LC-PDASP architecture. Complexity and Communicationburden of proposed LC-PDASP architecture are compared with that of conventional PDASP architecture. The compar-ative analysis shows that the proposed LC-PDASP architecture exhibits low computational complexity and provides animprovement more than of85%reduced communication burden than …
Long Term Stability Of 1.3 Ghz High Power Rf Amplifier, Özlem Karsli, İ.Evri̇m Çolak
Long Term Stability Of 1.3 Ghz High Power Rf Amplifier, Özlem Karsli, İ.Evri̇m Çolak
Turkish Journal of Electrical Engineering and Computer Sciences
Turkish accelerator and radiation laboratory (TARLA) is an accelerator based oscillator mode free electronlaser (FEL) facility under construction. The acceleration beamline includes a fundamental buncher (FB) in order to confine the electron beam into a compressed bunch. In this study, we demonstrate the commissioning tests of 500 W RF amplifier powering FB and present the phase stability dependence on the pressure and temperature of the water cooling line under long time run conditions.As the disturbing effects break down the synchronization between the particle and RF power during acceleration, the reasons disquieting the stability of the RF amplifier are investigated. One …
Design Of A Compact Wearable Ultrawideband Mimo Antenna With Improved Portisolation, Amit Baran Dey, Utkarsh Bhatt, Wasim Arif
Design Of A Compact Wearable Ultrawideband Mimo Antenna With Improved Portisolation, Amit Baran Dey, Utkarsh Bhatt, Wasim Arif
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a compact dual element wearable ultrawideband (UWB) multi-in multi-out (MIMO)antenna with increased port isolation. The suggested design consists of a jeans substrate in which a tree-fashioned stubcomprising of eight branches is introduced in the middle position of the partially etched antenna ground for improvingthe characteristics of port isolation. The proposed design occupies the frequency spectrum operating from 1.71 to12.63 GHz (impedance bandwidth of around 152.3%) and satisfies the bandwidth demands for WiMAX (3.2-3.8 GHz),WLAN (5.15-5.35/5.72-4.85 GHz), the C Downlink-uplink bands (3.7-4.2/5.9-6.425GHz), ITU bands (8-8.5GHz) andthe downlink defense band (7.2-7.5GHz). The antenna is able to maintain isolation between …
The Nearest Polyhedral Convex Conic Regions For High-Dimensional Classification, Hakan Çevi̇kalp, Emre Çi̇men, Gürkan Öztürk
The Nearest Polyhedral Convex Conic Regions For High-Dimensional Classification, Hakan Çevi̇kalp, Emre Çi̇men, Gürkan Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
In the nearest-convex-model type classifiers, each class in the training set is approximated with a convexclass model, and a test sample is assigned to a class based on the shortest distance from the test sample to these classmodels. In this paper, we propose new methods for approximating the distances from test samples to the convex regionsspanned by training samples of classes. To this end, we approximate each class region with a polyhedral convex conicregion by utilizing polyhedral conic functions (PCFs) and its extension, extended PCFs. Then, we derive the necessary formulations for computing the distances from test samples to these …
Analysis Of Shielding Effectiveness By Optimizing Aperture Dimensions Of Arectangular Enclosure With Genetic Algorithm, Sunay Güler, Si̇bel Yeni̇kaya
Analysis Of Shielding Effectiveness By Optimizing Aperture Dimensions Of Arectangular Enclosure With Genetic Algorithm, Sunay Güler, Si̇bel Yeni̇kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Electromagnetic compatibility (EMC) has now become a substantial challenge more than any other time sincethe number of electric vehicles (EV) increased rapidly. The electric driving system in an EV consists of power electroniccomponents supplied by high voltage battery source. They are both source and victim of potential electromagneticinterference (EMI) since fast switching process occurs inside them. Electromagnetic shielding provides a significantprotection against EMI for any electrical and electronic components inside the vehicle. In this paper, analysis of shieldingeffectiveness (SE) by optimizing aperture dimensions of a rectangular enclosure is investigated. Realistic dimensions of theshielding enclosure of an inverter component are employed. …
A Nonlinear Disturbance Observer Scheme For Discrete Time Control Systems, Mehmet Önder Efe, Coşku Kasnakoğlu
A Nonlinear Disturbance Observer Scheme For Discrete Time Control Systems, Mehmet Önder Efe, Coşku Kasnakoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a modification to the original disturbance observer based control (DOBC) scheme byredefining the lowpass filter using a nonlinear element. The proposed technique improves the disturbance predictionperformance for both small and large magnitude disturbance signals. The contribution of the current work is to unfoldthe stability and performance conditions under the proposed modification. A comparative set of simulation studies arediscussed and it is seen that the proposed modification results in smaller disturbance prediction error energy and smallertracking error energy when the plant model is discrete time and uncertain.
Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat
Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat
Turkish Journal of Electrical Engineering and Computer Sciences
Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …
Design Of The Fractional Order Internal Model Controller Using The Swarmintelligence Techniques For The Coupled Tank System, Sateesh Kumar Vavilala, Vinopraba Thirumavalavan, Radhakrishnan Thota, Sivakumaran Natarajan
Design Of The Fractional Order Internal Model Controller Using The Swarmintelligence Techniques For The Coupled Tank System, Sateesh Kumar Vavilala, Vinopraba Thirumavalavan, Radhakrishnan Thota, Sivakumaran Natarajan
Turkish Journal of Electrical Engineering and Computer Sciences
The coupled tank system (comprising two tanks) is used in the chemical industries, water treatment plantsetc. Level control of the coupled tank system is a common problem in the process control industry. This work proposes afractional order internal model controller (FOIMC) with a higher order fractional filter for the level control of the coupledtank system. A first order plus delay time (FOPDT) model of the system is used in the controller design. FOIMC hasadvantages like robustness to changes in the system gain and extended stability margins. The proposed higher orderfractional filter makes the controller physically realizable and quickly roll off …
An Efficient Deep Learning Based Fog Removal Model For Multimedia Applications, Gaurav Saxena, Sarita Singh Bhadauria
An Efficient Deep Learning Based Fog Removal Model For Multimedia Applications, Gaurav Saxena, Sarita Singh Bhadauria
Turkish Journal of Electrical Engineering and Computer Sciences
In the present era of technology, several applications such as surveillances systems, security and object recognitions mainly depend on the contents of an image. In this context, the hazy/foggy environment and/or other adverse climatic conditions degrade the image contents that severely influences the result of related applications. The effective haze removal from a single image decides the reliability of these systems. The convolutional neural network (CNN) based techniques are widely used among the available image dehazing methods. However, in CNN based image dehazing techniques, the robustness and accuracy of the learning models are based on the improvement of transmission estimation …
Model-Based Control For Second-Order Piezo Actuator System With Hysteresis Intime-Delay Environment, Saikat Kumar Shome, Sandip Jana, Arpita Mukherjee, Partha Bhattacharjee
Model-Based Control For Second-Order Piezo Actuator System With Hysteresis Intime-Delay Environment, Saikat Kumar Shome, Sandip Jana, Arpita Mukherjee, Partha Bhattacharjee
Turkish Journal of Electrical Engineering and Computer Sciences
Piezo actuated systems are promising solutions for precision positioning applications. In this paper, a piezoelectric actuator is modeled as a second-order system using the Dahl hysteresis model and the system parameters have been identified from experimental data. The modified internal model control (M-IMC) approach is presented, which not only improves control performance but also reduces associated controller hardware resources. System dead time is approximated using first-order Padé expansion and the proposed Smith predictor-based M-IMC for piezoelectric actuators is seen to offer satisfactory stable control response even for plants with large dead time. The control performance of the M-IMC has been …
Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken
Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken
Turkish Journal of Electrical Engineering and Computer Sciences
Generative adversarial networks (GANs) can be used in a wide range of applications where drawing samples from a data probability distribution without explicitly representing it is essential. Unlike the deep convolutional neural networks (CNNs) trained for mapping an input to one of the multiple outputs, monitoring the overfitting and underfitting in GANs is not trivial since they are not classifying but generating a data. While training set and validation set accuracy give a direct sense of success in terms of overfitting and underfitting for CNNs during the training process, evaluating the GANs mainly depends on the visual inspection of the …
Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali
Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali
Turkish Journal of Electrical Engineering and Computer Sciences
Robot motion planning & control is one of the most critical and prevalent problems in the robotics community. Even though original motion planning algorithms had relied on "open-loop" strategies and policies, researchers and engineers have been focusing on feedback motion planning and control algorithms due to the uncertainties, such as process and sensor noise of autonomous robotic applications. Recently, several studies proposed some robust feedback motion planning strategies based on sparsely connected safe zones. In this class of planning and control policies, local control policy inside a single zone computes and feeds the control actions that can drive the robot …
Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar
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 …
Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl
Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl
Turkish Journal of Electrical Engineering and Computer Sciences
Timed automata is a fundamental modeling formalism for real-time systems. During the design of such real-time systems, often the system information is incomplete, and design choices can vary. These uncertainties can be integrated to the model via parameters and labelled transitions. Then, the design can be completed by tuning the parameters and restricting the transitions via controller synthesis. These problems, namely parameter synthesis and controller synthesis, are studied separately in the literature. Herein, these are combined to generate an automaton satisfying the given specification by both parameter tuning and controller synthesis, thus exploring all design choices. First, it is shown …
A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker
A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
Semisupervised learning is a type of machine learning technique that constructs a classifier by learning from a small collection of labeled samples and a large collection of unlabeled ones. Although some progress has been made in this research area, the existing semisupervised methods provide a nominal classification task. However, semisupervised learning for ordinal classification is yet to be explored. To bridge the gap, this study combines two concepts ?semisupervised learning? and "ordinal classification" for the categorical class labels for the first time and introduces a new concept of "semisupervised ordinal classification". This paper proposes a new algorithm for semisupervised learning …
Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding
Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding
Turkish Journal of Electrical Engineering and Computer Sciences
Under the noncascade structure, the balance between q-axis current constraint and dynamic performance in permanent-magnet synchronous motor system has become a critical problem. On the one hand, large transient current is required to provide high torque to achieve fast dynamic performance. On the other hand, current constraint becomes a state constraint problem, instead of governing q-axis reference current in the cascade structure directly. Aiming at this issue, a novel fast terminal sliding mode control (FTSMC)-based controller with current constraint is developed in this paper. The novelty of this scheme is related to the proposed penalty function based on interior point …
Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga
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 …
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …
Shapeshifter: A Morphable Microprocessor For Low Power, Nazli Tokatli, İsa Ahmet Güney, Sercan Sari, Merve Güney, Uğur Nezi̇r, Gürhan Küçük
Shapeshifter: A Morphable Microprocessor For Low Power, Nazli Tokatli, İsa Ahmet Güney, Sercan Sari, Merve Güney, Uğur Nezi̇r, Gürhan Küçük
Turkish Journal of Electrical Engineering and Computer Sciences
A composite core contains large and small heterogeneous microengines. The most important property of composite cores is their ability to select the most proper microengine for running applications to save power without sacrificing too much performance. To achieve this, a composite core tries to predict the performance of the passive microengine by collecting various processor statistics from the active microengine at runtime. In the method proposed in the literature, the microengine, which is more ideal for running the rest of the application, is determined by a migrationdecision circuitry that is bound to collected statistics and complex functions, which are run …
Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari
Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari
Turkish Journal of Electrical Engineering and Computer Sciences
Clustering ensemble selection has shown high efficiency in the improvement of the quality of clustering solutions. This technique comprises two important metrics: diversity and quality. It has been empirically proved that ensembles of higher effectiveness can be achieved through taking into consideration the diversity and quality simultaneously. However, the relationships between these two metrics in base clusterings have remained uncertain. This paper suggests a new hierarchical selection algorithm using a diversity/quality measure based on the Jaccard similarity measure. In the proposed algorithm, the selection of the subsets of the clustering partitions is done based on their diversity measures. The proposed …
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Research outputs 2014 to 2021
Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …
Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau
Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau
Research outputs 2014 to 2021
The complex task of vision based fruit and vegetables classification at a supermarket self-checkout poses significant challenges. These challenges include the highly variable physical features of fruit and vegetables i.e. colour, texture shape and size which are dependent upon ripeness and storage conditions in a supermarket as well as general product variation. Supermarket environments are also significantly variable with respect to lighting conditions. Attempting to build an exhaustive dataset to capture all these variations, for example a dataset of a fruit consisting of all possible colour variations, is nearly impossible. Moreover, some fruit and vegetable classes have significant similar physical …
Human Activity Recognition Based On Wearable Flex Sensor And Pulse Sensor, Xiaozhu Jin
Human Activity Recognition Based On Wearable Flex Sensor And Pulse Sensor, Xiaozhu Jin
Electronic Theses and Dissertations
In order to fulfill the needs of everyday monitoring for healthcare and emergency advice, many HAR systems have been designed [1]. Based on the healthcare purpose, these systems can be implanted into an astronaut’s spacesuit to provide necessary life movement monitoring and healthcare suggestions. Most of these systems use acceleration data-based data record as human activity representation [2,3]. But this data attribute approach has a limitation that makes it impossible to be used as an activity monitoring system for astronavigation. Because an accelerometer senses acceleration by distinguishing acceleration data based on the earth’s gravity offset [4], the accelerometer cannot read …
Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar
Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar
UNF Graduate Theses and Dissertations
Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the …
A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz
A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz
Electrical and Computer Engineering Publications
With recent advances in non-contact sensing technology such as cameras, unmanned aerial and ground vehicles, the structural health monitoring (SHM) community has witnessed a prominent growth in deep learning-based condition assessment techniques of structural systems. These deep learning methods rely primarily on convolutional neural networks (CNNs). The CNN networks are trained using a large number of datasets for various types of damage and anomaly detection and post-disaster reconnaissance. The trained networks are then utilized to analyze newer data to detect the type and severity of the damage, enhancing the capabilities of non-contact sensors in developing autonomous SHM systems. In recent …
On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge
On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge
Articles
We consider the consequence of breaking with a fundamental result in complex analysisby lettingi2=±1wherei=√−1is the basic unit of all imaginary numbers. An analysis of theMandelbrot set for this case shows that a demarcation between a Fractal and a Euclidean object ispossible based oni2=−1andi2= +1, respectively. Further, we consider the transient behaviourassociated with the two cases to produce a range of non-standard sets in which a Fractal geometricstructure is transformed into a Euclidean object. In the case of the Mandelbrot set, the Euclideanobject is a square whose properties are investigate. Coupled with the associated Julia sets and othercomplex plane mappings, this …
Efficient Hybrid Passive Method For The Detection And Localization Of Copy-Moveand Spliced Images, Navneet Kaur, Neeru Jindal, Kulbir Singh
Efficient Hybrid Passive Method For The Detection And Localization Of Copy-Moveand Spliced Images, Navneet Kaur, Neeru Jindal, Kulbir Singh
Turkish Journal of Electrical Engineering and Computer Sciences
Digital passive image forgery methods are extensively used to verify the authenticity and integrity of images.Splicing and copy-move are the most common types of passive digital image forgeries. Several approaches have beenproposed to detect these forgeries separately, but very few approaches are available that can detect them simultaneously.However, a more e?icient method is still in demand to meet the day-to-day challenges to detect these forgeries at thesame time. So, a passive hybrid approach based on discrete fractional cosine transform (DFrCT) and local binarypattern (LBP) is proposed to detect copy-move and splicing forgeries simultaneously. The extra parameter i.e. fractionalparameter of DFrCT …
Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker
Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems- where chaos theory is widely employed is optimization problems. Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already …
Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz
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 …
Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman
Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman
Turkish Journal of Electrical Engineering and Computer Sciences
We present a bagging ensemble of convolutional networks in combination with the test-time augmentation technique to improve performance on the cross-dataset gender recognition problem. The bagging ensemble combines the predictions from multiple homogeneous models into the ensemble prediction. Augmentation techniques are often used in the learning phase of the CNNs to improve the generalization ability. On the other hand, test-time augmentation is not a common method used in the testing phase of the learned model. We conducted experiments on models trained using different hyperparameters. We augmented the test data and combine the predictive outputs from these network models. Experiments performed …