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2019

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Articles 13321 - 13350 of 15654

Full-Text Articles in Physical Sciences and Mathematics

Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci Jan 2019

Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci

Turkish Journal of Electrical Engineering and Computer Sciences

Collaborative filtering is one of the widely adopted approaches in recommender systems used for e-commerce applications, stating that users having similar tastes will have similar preferences in the future. The literature presents a number of similarity metrics such as the extended Jaccard coefficient to quantify these preference similarities. This paper aims to improve prediction accuracy by optimizing the similarity values computed using these metrics by adopting two biologically inspired approaches, namely artificial bee colony and genetic algorithms, with a bottom-up approach, suggesting that any improvement on a single-user basis will reflect on the overall prediction accuracy. Detailed statistical analysis was …

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Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba Jan 2019

Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba

Turkish Journal of Electrical Engineering and Computer Sciences

Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy …

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Task Graph Scheduling In The Presence Of Performance Fluctuations Of Computational Resources, Najmeh Malakoutifar, Hassan Motallebi Jan 2019

Task Graph Scheduling In The Presence Of Performance Fluctuations Of Computational Resources, Najmeh Malakoutifar, Hassan Motallebi

Turkish Journal of Electrical Engineering and Computer Sciences

Most of the existing work in the area of task graph scheduling considers resources with fixed processing capacity. The algorithms in these works rely on an estimation of the execution times of tasks on different resources. However, in practice, due to fluctuations in performance of cloud resources, these algorithms have challenges in these environments. In this paper, we focus on the problem of fault-tolerant scheduling of task graphs in the presence of performance fluctuations of computational resources. With the aim of reducing the adverse impacts of both soft errors and resource performance degradations, we propose an opportunistic task replication scheme …

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Energy And Economic Assessment Of Major Free Cooling Retrofits For Data Centers In Turkey, Ozan Gözcü, Hamza Sali̇h Erden Jan 2019

Energy And Economic Assessment Of Major Free Cooling Retrofits For Data Centers In Turkey, Ozan Gözcü, Hamza Sali̇h Erden

Turkish Journal of Electrical Engineering and Computer Sciences

Mechanical cooling is responsible for a significant fraction of the energy consumption of data centers (DCs). Free cooling systems take advantage of ambient conditions to reduce the need for compressor-based cooling. This study utilizes thermodynamic models of major free cooling systems such as the direct air-side economizer (ASE), indirect air-side economizer (IASE), indirect evaporative cooler (IEC), and indirect water-side economizer (WSE) integrated with the existing cooling infrastructure of a typical 1 MW IT load DC. Proposed models utilize hourly weather data of various cities in Turkey to compute annual energy consumption and cost-saving potentials of each free cooling method with …

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Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents, Indhumathi Chellaswamy, Joy Vasantha Rani Sp Jan 2019

Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents, Indhumathi Chellaswamy, Joy Vasantha Rani Sp

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a solution for automatic service restoration along with automatic fault location and isolation of the faulty sections in feeder in a power distribution system. A Java agent development environment-based multiagent system (MAS) is proposed to solve the problem of automatic service restoration in smart grid distribution systems. The agent-based solution development is discussed in detail and the MAS application to solve power restoration problem is elaborated in this paper. A study is done on a modified IEEE 33 bus system and the solution is implemented in the Velachery substation of the Tamilnadu electricity board. The results prove …

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Investigation Of Control Of Power Flow By Using Phase Shifting Transformers: Turkey Case Study, Erdi̇ Doğan, Nuran Yörükeren Jan 2019

Investigation Of Control Of Power Flow By Using Phase Shifting Transformers: Turkey Case Study, Erdi̇ Doğan, Nuran Yörükeren

Turkish Journal of Electrical Engineering and Computer Sciences

Transmission systems are needed to be upgraded based on expected/unexpected load growth factor by years. However, it is not so easy to install and upgrade the transmission system, which requires transmission planning calculation ahead of time. Traditionally, transmission companies built extra transmission lines to meet that load growth, but it is not easy and cost-effective to upgrade the system every time loads increase. Some unexpected load growth may occur for some load points that is not in the part of planning calculation. For those situations, the transmission system may face serious congestion problems. Transmission companies have been looking for a …

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Web Personalization Issues In Big Data And Semantic Web: Challenges Andopportunities, Bujar Raufi, Florije Ismaili, Jaumin Ajdari, Xhemal Zenuni Jan 2019

Web Personalization Issues In Big Data And Semantic Web: Challenges Andopportunities, Bujar Raufi, Florije Ismaili, Jaumin Ajdari, Xhemal Zenuni

Turkish Journal of Electrical Engineering and Computer Sciences

Web personalization is a process that utilizes a set of methods, techniques, and actions for adapting the linking structure of an information space or its content or both to user interaction preferences. The aim of personalization is to enhance the user experience by retrieving relevant resources and presenting them in a meaningful fashion. The advent of big data introduced new challenges that locate user modeling and personalization community in a new research setting. In this paper, we introduce the research challenges related to Web personalization analyzed in the context of big data and the Semantic Web. This paper also introduces …

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All-Polymer Ultrasonic Transducer Design For An Intravascular Ultrasonographyapplication, Dooyoung Hah Jan 2019

All-Polymer Ultrasonic Transducer Design For An Intravascular Ultrasonographyapplication, Dooyoung Hah

Turkish Journal of Electrical Engineering and Computer Sciences

Intravascular ultrasonography (IVUS), a medical imaging modality, is used to obtain cross-sectional views of blood vessels from inside. In IVUS, transducers are brought to the proximity of the imaging targets so that highresolution images can be obtained at high frequency without much concern of signal attenuation. To eliminate mechanical rotation rendered in conventional IVUS, it is proposed to manufacture a transducer array on a flexible substrate and wrap it around a cylindrical frame. The transducer of consideration is a capacitive micromachined ultrasonic transducer (CMUT). The whole device needs to be made out of polymers to be able to endure a …

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Qpsk-Dual Carrier Modulation For Ultra-Wideband Communication In Body Areanetwork Channels, Yasi̇n Karan, Sali̇m Kahveci̇ Jan 2019

Qpsk-Dual Carrier Modulation For Ultra-Wideband Communication In Body Areanetwork Channels, Yasi̇n Karan, Sali̇m Kahveci̇

Turkish Journal of Electrical Engineering and Computer Sciences

Dual carrier modulation (DCM) using orthogonal frequency-division multiplexing (OFDM) improves the performance in multipath fading channels. In the literature DCM is proposed with 16-quadrature amplitude modulation (16QAM) for ultra-wideband (UWB) communication, with four bits per symbol to keep reliable high date transmission over longer distances. Body area network (BAN) standards address transmission reliability more than data rate. UWB is one of the physical layers proposed in BAN standards. In this study, DCM is used with quadrature phase shift keying (QPSK) instead of 16QAM to have better performance in reliable transmission. The performance of QPSK-DCM is analyzed and compared with 16QAM-DCM, …

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A Light-Weight Solution For Blackhole Attacks In Wireless Sensor Networks, Bi̇lal Erman Bi̇lgi̇n, Selçuk Baktir Jan 2019

A Light-Weight Solution For Blackhole Attacks In Wireless Sensor Networks, Bi̇lal Erman Bi̇lgi̇n, Selçuk Baktir

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensors, which are smaller and cheaper, have started being used in many different applications. Military applications, health care and industrial monitoring, environmental applications, smart grids, and vehicular ad-hoc networks are some of the best known applications of wireless sensors. In some applications, especially military, environmental, and health care applications, it is required that the communication between sensor nodes be encrypted to achieve privacy and confidentiality. In this work, some modifications have been made to the ad-hoc on-demand distance vector routing protocol, mostly preferred in wireless sensor networks, to make data communications more reliable. The proposed routing protocol is shown …

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Verifiable Dynamic Searchable Encryption, Mohammad Etemad, Alpteki̇n Küpcü Jan 2019

Verifiable Dynamic Searchable Encryption, Mohammad Etemad, Alpteki̇n Küpcü

Turkish Journal of Electrical Engineering and Computer Sciences

Using regular encryption schemes to protect the privacy of the outsourced data implies that the client should sacrifice functionality for security. Searchable symmetric encryption (SSE) schemes encrypt the data in a way that the client can later search and selectively retrieve the required data. Many SSE schemes have been proposed, starting with static constructions, and then dynamic and adaptively secure constructions but usually in the honest-but-curious model. We propose a verifiable dynamic SSE scheme that is adaptively secure against malicious adversaries. Our scheme supports file modification, which is essential for efficiently working with large files, in addition to the ability …

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A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu Jan 2019

A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The single-source shortest path problem arises in many applications, such as roads, social applications, and computer networks. Finding the shortest path is challenging, especially for graphs that contain a large number of vertices and edges. In this work, we propose a novel hybrid method that first sparsifies a given graph by removing most edges that cannot form the shortest path tree and then applies a classical shortest path algorithm to the sparser graph. Removing all the edges that cannot form the shortest path tree would be expensive since it is equivalent to solving the original problem. Therefore, we propose an …

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Modified Self-Adaptive Local Search Algorithm For A Biobjective Permutation Flowshop Scheduling Problem, Çi̇ğdem Alabaş Uslu, Berna Dengi̇z, Canan Ağlan, İhsan Sabuncuoğlu Jan 2019

Modified Self-Adaptive Local Search Algorithm For A Biobjective Permutation Flowshop Scheduling Problem, Çi̇ğdem Alabaş Uslu, Berna Dengi̇z, Canan Ağlan, İhsan Sabuncuoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Interest in multiobjective permutation flow shop scheduling (PFSS) has increased in the last decade to ensure effective resource utilization. This study presents a modified self-adaptive local search (MSALS) algorithm for the biobjective permutation flow shop scheduling problem where both makespan and total flow time objectives are minimized. Compared to existing sophisticated heuristic algorithms, MSALS is quite simple to apply to different biobjective PFSS instances without requiring effort or time for parameter tuning. Computational experiments showed that MSALS is either superior to current heuristics for Pareto sets or is incomparable due to other performance indicators of multiobjective problems.

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Dop: Discover Objects And Paths, A Model For Automated Navigation Andselection In Virtual Environments, Muhammad Raees, Sehat Ullah Jan 2019

Dop: Discover Objects And Paths, A Model For Automated Navigation Andselection In Virtual Environments, Muhammad Raees, Sehat Ullah

Turkish Journal of Electrical Engineering and Computer Sciences

Navigation and selection are the two interaction tasks often needed for the manipulation of an object in a synthetic world. An interface that supports automatic navigation and selection may increase the realism of a virtual reality (VR) system. Such an engrossing interface of a VR system is possible by incorporating machine learning (ML) into the realm of the virtual environment (VE). The use of intelligence in VR systems, however, is a milestone yet to be achieved to make seamless realism in a VE possible. To improve the believability of an intelligent virtual agent (IVA), this research work presents DOP (Discover …

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Patient Comfort Level Prediction During Transport Using Artificial Neural Network, Zeljko Jovanovic, Marija Blagojevic, Dragan Jankovic, Aleksandar Peulic Jan 2019

Patient Comfort Level Prediction During Transport Using Artificial Neural Network, Zeljko Jovanovic, Marija Blagojevic, Dragan Jankovic, Aleksandar Peulic

Turkish Journal of Electrical Engineering and Computer Sciences

Since patient comfort during transport is a matter of paramount importance, this paper aims to determine the possibilities of applying neural networks for its prediction and monitoring. Specific objectives of the research include monitoring and predicting patient transport comfort, with subjective assessment of comfort by medical personnel. An original Android application that collects signals from an accelerometer and a GPS sensor was used with the aim of achieving the research goals. The collected signals were processed and a total of twelve parameters were calculated. A multilayer perceptron was created in the proposed research. The evaluation results indicate acceptable accuracy and …

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Design Of Energy Recovery Systems: Thermoelectric Combi Boiler Generator Andpower Analysis, Abdullah Hakan Yavuz Jan 2019

Design Of Energy Recovery Systems: Thermoelectric Combi Boiler Generator Andpower Analysis, Abdullah Hakan Yavuz

Turkish Journal of Electrical Engineering and Computer Sciences

Gas-fired combi boilers are commonly used to meet the need for heating and general-purpose hot water in developing countries. In this study, a thermoelectric combi boiler generator (TECBG) was developed. When the boiler is operated, cold water flows through the cold surface of TECBG and enters the boiler. In the same way, it is used by flows through the hot surface of TECBG in heated water. Thus, temperature difference occurrs between the surfaces of TECBG. The temperature difference is converted into electrical energy by Seebeck effect. The proposed system was implemented on a domestic combi boiler. The maximum temperature difference …

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Optimal Dg Allocation For Enhancing Voltage Stability And Minimizing Power Loss Using Hybrid Gray Wolf Optimizer, Salah Kamel, Ayman Awad, Hussein Abdel-Mawgoud, Francisco Jurado Jan 2019

Optimal Dg Allocation For Enhancing Voltage Stability And Minimizing Power Loss Using Hybrid Gray Wolf Optimizer, Salah Kamel, Ayman Awad, Hussein Abdel-Mawgoud, Francisco Jurado

Turkish Journal of Electrical Engineering and Computer Sciences

High penetration of photovoltaic and wind turbine-based distributed generators (DGs) can help reduce carbon emissions which is an important goal for the whole world. DG can be used to improve the voltage stability, present generation reserve/emergency, and consequently, the system power quality can be improved. However, it is very important to select the right size and location of a DG so that the power system can increase the gained benefits of such an installation to the maximum. In this paper, a hybrid optimization technique is proposed to determine the optimal allocation of DG in the standard IEEE 33-bus radial distribution …

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Extraction And Selection Of Statistical Harmonics Features For Electrical Appliancesidentification Using K-Nn Classifier Combined With Voting Rules Method, Fateh Ghazali, Abdenour Hacine-Gharbi, Philippe Ravier, Tayeb Mohamadi Jan 2019

Extraction And Selection Of Statistical Harmonics Features For Electrical Appliancesidentification Using K-Nn Classifier Combined With Voting Rules Method, Fateh Ghazali, Abdenour Hacine-Gharbi, Philippe Ravier, Tayeb Mohamadi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel framework for electrical appliances identification using statistical harmonic features of current signals and the use of the k-NN classifier combined with a voting rule strategy. Harmonic coefficients are computed over time using short-time Fourier series of the current signals. From these sequences of coefficients, the mean, standard deviation, skewness, and kurtosis are computed, which provide the statistical harmonic features. This framework has three novelties: (i) selecting the best combination of statistical measures in the sense of classification rate (CR); (ii) combining the k-NN classifier with the voting rule method in order to search …

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A New Hybrid Gravitational Search-Teaching-Learning-Based Optimization Methodfor The Solution Of Economic Dispatch Of Power Systems, Mehmet Fati̇h Tefek, Harun Uğuz Jan 2019

A New Hybrid Gravitational Search-Teaching-Learning-Based Optimization Methodfor The Solution Of Economic Dispatch Of Power Systems, Mehmet Fati̇h Tefek, Harun Uğuz

Turkish Journal of Electrical Engineering and Computer Sciences

The economic dispatch problem (EDP) is a complex, constrained, and nonlinear optimization problem. In the EDP, the active power bus should operate between the minimum and maximum bus limits to minimize the fuel cost. In this study, a fast, efficient, and reliable hybrid gravitational search algorithm-teaching learning based optimization (GSA-TLBO) method was proposed for the purpose of solving the EDP in power systems. The proposed method separates the search space into two sections as global and local searching. In the first part, searching was carried out by GSA method effectively to form the second search space. In the second part, …

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Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony Jan 2019

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. …

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Unsupervised Deep Feature Embeddings For Speaker Diarization, Rehan Ahmad, Syed Zubair Jan 2019

Unsupervised Deep Feature Embeddings For Speaker Diarization, Rehan Ahmad, Syed Zubair

Turkish Journal of Electrical Engineering and Computer Sciences

Speaker diarization aims to determine ?who spoke when?? from multispeaker recording environments. In this paper, we propose to learn a set of high-level feature representations, referred to as feature embeddings, from an unsupervised deep architecture for speaker diarization. These sets of embeddings are learned through a deep autoencoder model when trained on mel-frequency cepstral coefficients (MFCCs) of input speech frames. Learned embeddings are then used in Gaussian mixture model based hierarchical clustering for diarization. The results show that these unsupervised embeddings are better compared to MFCCs in reducing the diarization error rate. Experiments conducted on the popular subset of the …

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A Comparative Study On Handwritten Bangla Character Recognition, Md. Atiqul Islam Rizvi, Kaushik Deb, Md. Ibrahim Khan, Mir Md. Saki Kowsar, Tahmina Khanam Jan 2019

A Comparative Study On Handwritten Bangla Character Recognition, Md. Atiqul Islam Rizvi, Kaushik Deb, Md. Ibrahim Khan, Mir Md. Saki Kowsar, Tahmina Khanam

Turkish Journal of Electrical Engineering and Computer Sciences

Recognition of handwritten Bangla characters has drawn considerable attention recently. The Bangla language is rich with characters of various styles such as numerals, basic characters, and compound and modifier characters. The inherent variation in individual writing styles, along with the complex, cursive nature of characters, makes the recognition task more challenging. To compare the outcomes of handwritten Bangla character recognition, this study considers two different approaches. The first one is classifier-based, where a hybrid model of the feature extraction technique extracts the features and a multiclass support vector machine (SVM) performs the recognition. The second one is based on a …

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Symptom-Aware Hybrid Fault Diagnosis Algorithm In The Network Virtualization Environment, Yuze Su, Xiangru Meng, Xiaoyang Han, Qiaoyan Kang Jan 2019

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 …

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Atomic-Shaped Efficient Delay And Data Gathering Routing Protocol For Underwater Wireless Sensor Networks, Wajiha Farooq, Tariq Ali, Ahmad Shaf, Muhammad Umar, Sana Yasin Jan 2019

Atomic-Shaped Efficient Delay And Data Gathering Routing Protocol For Underwater Wireless Sensor Networks, Wajiha Farooq, Tariq Ali, Ahmad Shaf, Muhammad Umar, Sana Yasin

Turkish Journal of Electrical Engineering and Computer Sciences

High end-to-end delay is a major challenge in autonomous underwater vehicle (AUV)-aided routing protocols for underwater monitoring applications. In this paper, a new routing protocol called atomic-shaped efficient delay and data gathering (ASEDG) has been introduced for underwater wireless sensor networks. The ASEDG is divided into two phases; in the first phase, the atomic-shaped trajectory model with horizontal and vertical ellipticals was designed for the movement of the AUV. In the second phase, two types of delay models were considered to make our protocol more delay efficient: member nodes (MNs) to MNs and MNs to gateway nodes (GNs). The MNs-to-MNs …

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Increasing Bluetooth Low Energy Communication Efficiency By Presetting Protocol Parameters, Dusan Hatvani, Dominik Macko Jan 2019

Increasing Bluetooth Low Energy Communication Efficiency By Presetting Protocol Parameters, Dusan Hatvani, Dominik Macko

Turkish Journal of Electrical Engineering and Computer Sciences

Standard protocols are important regarding the compatibility of devices provided by different vendors. However, specific applications have various requirements and do not always need all features offered by standard protocols, making them inefficient. This paper focuses on standard Bluetooth Low Energy modifications, reducing control overhead for the intended healthcare application. Specifically, the connection establishment, device pairing, and connection parameter negotiations have been targeted. The simulation-based experiments showed over 20 times reduction of control-overhead time preceding a data transmission. It does not just directly increase the energy efficiency of communication; it also prolongs the time for sensor-based end devices to spend …

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Lightweight Signature Scheme To Protect Intellectual Properties Of Internet Of Things Applications In System On Chip Field-Programmable Gate Arrays, Kokila Jagadeesh, Ramasubramanian Natarajan Jan 2019

Lightweight Signature Scheme To Protect Intellectual Properties Of Internet Of Things Applications In System On Chip Field-Programmable Gate Arrays, Kokila Jagadeesh, Ramasubramanian Natarajan

Turkish Journal of Electrical Engineering and Computer Sciences

Billions of smart objects in the edge devices offer advanced connectivity to networks which increase the security and complexity of the Internet of things (IoT) applications. To make such entities smarter heterogeneous intellectual property (IP) cores from multiple service providers are reused in system on chip platform. Enabling both chip and IP protection at post fabrication level is imperative. The IoT-based IP cores are signed with the hybrid physical unclonable function and finite state machine model to protect from cloning, misuse, unauthorized user access, and physical attacks. The extended finite-state machine is used to verify the signature, which reduces the …

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Solving Vehicle Routing Problem For Multistorey Buildings Using Iterated Local Search, Osman Gökalp, Aybars Uğur Jan 2019

Solving Vehicle Routing Problem For Multistorey Buildings Using Iterated Local Search, Osman Gökalp, Aybars Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicle routing problem (VRP) which is a well-known combinatorial optimisation problem that has many applications used in industry is also a generalised form of the travelling salesman problem. In this study, we defined and formulated the VRP in multistorey buildings (Multistorey VRP) for the first time and proposed a solving method employing iterated local search metaheuristic algorithm. This variant of VRP has a great potential for turning the direction of optimisation research and applications to the vertical cities area as well as the horizontal ones. Routes of part picking or placing vehicles/humans in multistorey plants can be minimised by this …

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Parallel Brute-Force Algorithm For Deriving Reset Sequences From Deterministic Incomplete Finite Automata, Uraz Cengi̇z Türker Jan 2019

Parallel Brute-Force Algorithm For Deriving Reset Sequences From Deterministic Incomplete Finite Automata, Uraz Cengi̇z Türker

Turkish Journal of Electrical Engineering and Computer Sciences

A reset sequence (RS) for a deterministic finite automaton $\mathscr{A}$ is an input sequence that brings $\mathscr{A}$ to a particular state regardless of the initial state of $\mathscr{A}$. Incomplete finite automata (FA) are strong in modeling reactive systems, but despite their importance, there are no works published for deriving RSs from FA. This paper proposes a massively parallel algorithm to derive short RSs from FA. Experimental results reveal that the proposed parallel algorithm can construct RSs from FA with 16,000,000 states. When multiple GPUs are added to the system the approach can handle larger FA.

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Hgab3c: A New Hybrid Global Optimization Algorithm, Kamaljeet Kaur, Shakti Kumar, Jyoti Saxena Jan 2019

Hgab3c: A New Hybrid Global Optimization Algorithm, Kamaljeet Kaur, Shakti Kumar, Jyoti Saxena

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new optimization algorithm, namely HGAB3C, and presents its performance on the CEC-2014 test suite. In HGAB3C, simple genetic algorithms (GAs) and big bang-big crunch (BB-BC) are hybridized. The algorithm carries out global searches using a simple GA. In every generation the BB-BC algorithm is used to carry out local searches. The addition of local search has improved the capability of simple GAs significantly. The performance of the proposed algorithm is compared with 17 other optimization algorithms on all 30 functions of the CEC-2014 benchmark suite. It is observed that HGAB3C outperforms all other algorithms on 4 …

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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 Jan 2019

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 …

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