Development Of A Supervised Classification Method To Construct 2d Mineral Mapson Backscattered Electron Images,
2020
TÜBİTAK
Development Of A Supervised Classification Method To Construct 2d Mineral Mapson Backscattered Electron Images, Mahmut Camalan, Mahmut Çavur
Turkish Journal of Electrical Engineering and Computer Sciences
The Mineral Liberation Analyzer (MLA) can be used to obtain mineral maps from backscattered electron (BSE) images of particles. This paper proposes an alternative methodology that includes random forest classification, a prospective machine learning algorithm, to develop mineral maps from BSE images. The results show that the overall accuracy and kappa statistic of the proposed method are 97% and 0.94, respectively, proving that random forest classification is accurate. The accuracy indicators also suggest that the proposed method may be applied to classify minerals with similar appearances under BSE imaging. Meanwhile, random forest predicts fewer middling particles with binary and ternary …
A Viable Snore Detection System: Hardware And Software Implementations,
2020
TÜBİTAK
A Viable Snore Detection System: Hardware And Software Implementations, Ahmet Turgut Tuncer, Mehmet Bi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
A stand-alone, custom-made biomedical system was introduced for long-term monitoring of sleep and detection of snoring events. Commercially available electronic components were assembled for recording audio, pulse, and respiration signals. Its software was implemented for off-line processing of the acquired signals in C++ and MATLAB environments. The linear and nonlinear features of the signals were extracted and characterized using spectral energy distribution, entropy, and largest Lyapunov exponent (LLE). The performance of the system was evaluated with real physiological data gathered from 14 chronic snorers. Analysis of the cases indicated that the system identified the snoring events with an accuracy of …
Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods,
2020
TÜBİTAK
Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, railway transport has been preferred intensively in local and intercity freight and passenger transport. For this reason, it is of utmost importance that railway lines are operated in an uninterrupted and safe manner. In order to carry out continuous operation, all systems must continue to operate with maximum availability. In this study, data were collected from switch motors, which are the important equipment of railways, and the related equipment and these data were evaluated with sector experience and the results related to the failure status of the switch points were revealed. The obtained results were processed with …
Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi,
2020
TÜBİTAK
Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi, Damla Yaşar, Selma Teki̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Many text documents are spatiotemporal in nature, i.e. contents of a document can be mapped to a specific time period or location. For example, a news article about the French Revolution can be mapped to year 1789 as time and France as place. Identifying this time period and location associated with the document can be useful for various downstream applications such as document reasoning or spatiotemporal information retrieval. In this paper, temporal entropy with pointwise mutual information (PMI) is proposed to estimate the temporal focus of a document. PMI is used to measure the association of words with time expressions. …
Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers,
2020
TÜBİTAK
Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Social media and microblogging platforms generally contain elements of figurative and nonliteral language, including satire. The identification of figurative language is a fundamental task for sentiment analysis. It will not be possible to obtain sentiment analysis methods with high classification accuracy if elements of figurative language have not been properly identified. Satirical text is a kind of figurative language, in which irony and humor have been utilized to ridicule or criticize an event or entity. Satirical news is a pervasive issue on social media platforms, which can be deceptive and harmful. This paper presents an ensemble scheme for satirical news …
Convolutional Auto Encoders For Sentence Representation Generation,
2020
TÜBİTAK
Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give rise to the difficulty of selecting the answer. The deep learning field has recently achieved a pivotal success in semantic analysis, machine translation, and text summaries. The essence of this work, inspired by the human orthographic processing mechanism and using multiple convolution filters with pre-rendered 2-Dimension (2D) representations of sentences, input or output size is to learn the basic features of the language without concerns. For …
Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes and implements a self-supervised simulation-driven approach to data collection used for training of perception-based shallow neural networks for mobile robot obstacle avoidance. In the approach, a 2D LiDAR sensor was used as an information source for training neural networks. The paper analyzes neural network performance in terms of numbers of layers and neurons, as well as the amount of data needed for reliable robot operation. Once the best architecture is identified, it is trained using only data obtained in simulation and then implemented and tested on a real robot (Turtlebot 2) in several simulations and real-world scenarios. …
Measurement Based Threat Aware Drone Base Station Deployment,
2020
TÜBİTAK
Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Unmanned aerial vehicles are gaining importance with many civilian and military applications. Especially the surveillance, search/rescue, and military operations may have to be carried out in extremely constrained environments. In such scenarios, drone base stations (DBSs) have to provide communication services to the people at the ground. The ground users may have no access to the global positioning system (GPS); therefore, their locations have to be estimated using alternative techniques. Besides there may be threats in the environment, such as shooters. In this work, we address the problem of optimal DBS deployment under the aforementioned constraints. We propose a novel …
Fast Adaptive Reclosing In Double-Circuit Transmission Lines For Improving Powersystem Stability Based On Harmonic Analysis Scheme, Mohsen Jannati, Ali Akbar Akbari
Turkish Journal of Electrical Engineering and Computer Sciences
An appropriate method is proposed for identifying permanent faults from transient faults in double-circuit transmission lines. This method could be used in adaptive single phase auto-reclosures in order to diagnose between permanent and transient faults, determine extinguishing time of the secondary arc, and calculate issuing time of reclosing commands during the occurrence of transient single phase to ground faults. The proposed method is based on harmonic analysis of the adjacent healthy circuit and could be an effective solution for blocking permanent disconnection of the power flow, improving stability, and maintaining the power network synchronism. In this paper, transient and permanent …
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission,
2020
TÜBİTAK
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao
Turkish Journal of Electrical Engineering and Computer Sciences
Multiple-symbol differential detection (MSDD) algorithms are proposed in two-way relay transmission (TWRT). Firstly, generalized likelihood ratio test based MSDD (GLRT-MSDD) is proposed in TWRT. Unfortunately, as the number of observation windows increases, the computational complexity of GLRT-MSDD increases exponentially. Hence, this detection in TWRT constitutes a challenging problem. Moreover, we find a way to reformulate the GLRTMSDD model and additionally propose a lattice-reduction aided MSDD (LR-MSDD) model. Performance analysis and simulations show that the proposed LR-MSDD provides bit-error rate performance close to that of GLRT-MSDD with lower complexity in TWRT.
A Population Based Simulated Annealing Algorithm For Capacitated Vehicle Routing Problem,
2020
TÜBİTAK
A Population Based Simulated Annealing Algorithm For Capacitated Vehicle Routing Problem, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The Vehicle Routing Problem (VRP) is one of the most discussed and researched topics nowadays. The VRP is briefly defined as the problem of identifying the best route to reduce distribution costs and improve the quality of service provided to customers. The Capacitated VRP (CVRP) is one of the most commonly researched among the VRP types. Therefore, the CVRP was studied in this paper and a new population based simulated annealing algorithm was proposed. In the algorithm, three different route development operators were used, which are exchange, insertion and reversion operators. It was tested on 63 well-known benchmark instances in …
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification,
2020
TÜBİTAK
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Turkish Journal of Electrical Engineering and Computer Sciences
The extreme learning machine (ELM) is one of the machine learning applications used for regression and classification systems. In this paper, an extended comparison between an ELM and the backpropagation neural network (BPNN)-based i-vector is given in terms of a closed-set speaker identification task using 120 speakers from the TIMIT database. The system is composed of the mel frequency cepstal coefficient (MFCC) and power normalized cepstal coefficient (PNCC) approaches to form the feature extraction stage, while the cepstral mean variance normalization (CMVN) and feature warping are applied in order to mitigate the linear channel effect. The system is utilized with …
Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking,
2020
TÜBİTAK
Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D
Turkish Journal of Electrical Engineering and Computer Sciences
In recent times, energy consumption in communication media has been increasing drastically. In the literature, energy-saving techniques that enable network devices to enter sleep state or limit the data rate have been proposed to reduce energy costs. In our earlier work, we proposed an energy-saving technique called burst-based adaptive link rate (BBALR), the simulation of which assures increased energy savings. In this paper, we have emulated the hardware implementation of BBALR and compared its performance with the outputs of other prominent energy-saving policies based on dynamic link rate adaption. The energy savings are mapped from the measured sleep time and …
Design Of A Spurious-Free Rf Frequency Synthesizer For Fast-Settling Receivers,
2020
TÜBİTAK
Design Of A Spurious-Free Rf Frequency Synthesizer For Fast-Settling Receivers, Hi̇lmi̇ Kayhan Yilmaz, Serkan Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
A tunable reference clock frequency topology is presented as a spur reduction application for frequency synthesizers of fast frequency hopping spread spectrum systems. The method was verified by measurements on a designed hardware operating at L-band frequencies. This spur reduction method is based on optimizing the reference clock frequency of synthesizers to mitigate spurs. By using the spur reduction method, the power of spurious signals was reduced up to 57 dB. The performance of the spur reduction method was also analyzed at different loop-filter configurations. Smaller lock time was obtained by enlarging the bandwidth of the loop filter up to …
Optimization Of Real-World Outdoor Campaign Allocations,
2020
TÜBİTAK
Optimization Of Real-World Outdoor Campaign Allocations, Fatmanur Akdoğan Uzun, Doğan Altan, Ercan Peker, Mahmut Altuğ Üstün, Sanem Sariel
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we investigate the outdoor campaign allocation problem (OCAP), which asks for the distribution of campaign items to billboards considering a number of constraints. In particular, for a metropolitan city with a large number of billboards, the problem becomes challenging. We propose a genetic algorithm-based method to allocate campaign items effectively, and we compare our results with those of nonlinear integer programming and greedy approaches. Real-world data sets are collected with the given constraints of the price class ratios of billboards located in İstanbul and the budgets of the given campaigns. The methods are evaluated in terms of …
Analysis Of Acoustic Sensor Placement For Pd Location In Power Transformer,
2020
TÜBİTAK
Analysis Of Acoustic Sensor Placement For Pd Location In Power Transformer, Khairul Nadiah Khalid, Muhammad Nur Khairul Hafizi Rohani, Baharuddin Ismail, Muzamir Isa, Chang Yii Chai, Wan Nurul Auni Wan Muhammad
Turkish Journal of Electrical Engineering and Computer Sciences
Partial discharge (PD) is an abnormal activity that occurs in high-voltage components, such as power cables, switchgear, machines, and power transformers. Such activity needs to be diagnosed for the equipment to last longer as PD could harm the insulation and potentially lead to asset destruction from time to time. Moving one or more externally mounted acoustic sensors to different locations on the transformer tank is commonly used in order to detect and locate PD signal occurring in the power transformer. However, this procedure may lead to less accuracy in PD identification. Therefore, this research paper presents an analysis of acoustic …
Adjustable Testing Setup For A Single-Loop Optoelectronic Oscillator With Anelectrical Bandpass Filter,
2020
TÜBİTAK
Adjustable Testing Setup For A Single-Loop Optoelectronic Oscillator With Anelectrical Bandpass Filter, Mehmet Alp Ilgaz, Andrej Lavric, Temitope Odedeyi, Izzat Darwazeh, Bostjan Batagelj
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper we present a novel method to measure the free spectral range (FSR) and side-mode suppression ratio (SMSR) of an optoelectronic oscillator (OEO) by adjusting the optical fiber length using an optical path selector and signal source analyzer. We have designed a setup for a single-loop OEO operating around 5 GHz and 10 GHz that features electrical bandpass filters for side-mode suppression. The proposed approach makes it possible to evaluate the FSR and SMSR of OEOs with different optical fiber paths without requiring the changing of fiber spools or optical connectors. This approach could be useful for testbeds …
Combined Analytic Hierarchy Process And Binary Particle Swarm Optimization Formultiobjective Plug-In Electric Vehicles Charging Coordination With Time-Of-Usetariff, Junaid Bin Fakhrul Islam, Mir Toufikur Rahman, Hazlie Mokhlis, Mohamadariff Othman, Tengku Fiaz Tengku Mohmed Noor Izam, Hasmaini Mohamad
Turkish Journal of Electrical Engineering and Computer Sciences
Plug-in electric vehicles (PEVs) are gaining popularity as an alternative vehicle in the past few years. The charging activities of PEVs impose extra electrical load on residential distribution system as well as increasing operational cost. There are multiple conflicting requirements and constraints during the charging activities. Therefore, this paper presents multiobjective PEV charging coordination based on weighted sum technique to provide simultaneous benefits to the power utilities and PEV users. The optimization problem of the proposed coordination is solved using binary particle swam optimization. The objectives of the coordination are to (i) minimize daily power loss, (ii) maximize power delivery …
A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture,
2020
TÜBİTAK
A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture, Ridvan Umaz
Turkish Journal of Electrical Engineering and Computer Sciences
Conventional energy architectures that utilize multiple ambient energy sources are initiated either by an external power supply or through the addition of an extra power source (e.g., battery) to the architecture. However, these interventions compromise the goal of a self-sustainable energy harvesting system. Moreover, conventional architectures are not effective in situations where space is limited (e.g., an artificial heart) or when access to this space is difficult (e.g., human implantable devices), due to their large battery size. Thus, conventional energy combiner circuits that use multiple energy sources are not well suited for supplying power to most applications. This paper presents …
An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil,
2020
TÜBİTAK
An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top
Turkish Journal of Electrical Engineering and Computer Sciences
Magnetic nanoparticles (MNPs) have a wide range of clinical applications for imaging, therapy, and biosensing. Superparamagnetic MNPs can be directly visualized with high spatiotemporal resolution using the magnetic particle imaging (MPI) modality. The image resolution of MPI depends on the relaxation properties of the MNPs. Therefore, characterization of MNP response under alternating magnetic field excitation is necessary to predict MPI imaging performance and develop optimized MNPs. Biosensing applications also make use of the change in the relaxation response of MNPs after binding to a target agent. As MNP relaxation properties change with temperature and viscosity, noninvasive probing of these microenvironmental …
