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Articles 601 - 630 of 3106
Full-Text Articles in Computer Sciences
Multitask-Based Association Rule Mining, Peli̇n Yildirim Taşer, Kökten Ulaş Bi̇rant, Derya Bi̇rant
Multitask-Based Association Rule Mining, Peli̇n Yildirim Taşer, Kökten Ulaş Bi̇rant, Derya Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, there has been a growing interest in association rule mining (ARM) in various fields. However, standard ARM algorithms fail to discover rules for multitask problems as they do not consider task-oriented investigation and, therefore, they ignore the correlation among the tasks. Considering this situation, this paper proposes a novel algorithm, named multitask association rule miner (MTARM), that tends to jointly discover rules by considering multiple tasks. This paper also introduces two novel concepts: single-task rule and multiple-task rule. In the first phase of the proposed approach, highly frequent local rules (single-task rules) are explored for each task separately and …
Adaptive Prescribed Performance Servo Control Of An Automotive Electronicthrottle System With Actuator Constraint, Zitao Sun, Xiaohong Jiao
Adaptive Prescribed Performance Servo Control Of An Automotive Electronicthrottle System With Actuator Constraint, Zitao Sun, Xiaohong Jiao
Turkish Journal of Electrical Engineering and Computer Sciences
To further improve the transient and steady-state performance of automotive electronic throttle position tracking, in this paper an adaptive prescribed performance servo control strategy is designed and applied to a real electronic throttle control system. In view of the possible high gain of the prescribed performance controller in practice, the actuator constraint is also considered in the controller design. The designed servo controller can ensure the transient and steady-state responses of tracking error are limited in the range prescribed by the performance function, and converge with the prescribed convergence rate and have no overshoot. The incorporated adaptive updating law can …
Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi, Damla Yaşar, Selma Teki̇r
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, Aytuğ Onan, Mansur Alp Toçoğlu
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 …
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
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. …
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao
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.
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
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, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D
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 …
A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture, Ridvan Umaz
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, Can Bariş Top
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 …
On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya
On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya
Turkish Journal of Electrical Engineering and Computer Sciences
In game-theoretic settings the key notion of analysis is an equilibrium, which is a profile of agent strategies such that no viable coalition of agents can improve upon their coalitional welfare by jointly changing their strategies. A Nash equilibrium, where viable coalitions are only singletons, and a super strong equilibrium, where every coalition is deemed viable, are two extreme scenarios in regard to coalition formation. A recent trend in the literature is to consider equilibrium notions that allow for coalition formation in between these two extremes and which are suitable to model social coalition structures that arise in various real-life …
Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan
Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance strategies based on predefined rules have been introduced in the automated negotiation literature. Those rules mostly rely on some heuristics, which take time and/or utility into account. For some negotiation settings, an acceptance strategy solely based on a negotiation deadline might perform well; however, it might fail in another setting. Instead of following predefined acceptance rules, this paper presents an acceptance strategy that aims to learn whether to accept its opponent's …
Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez
Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez
Turkish Journal of Electrical Engineering and Computer Sciences
Currently, many systems depend on software, and software reliability as such has become one of the key challenges. Several studies have been carried out that focus on the impact of external environmental factors that impact software reliability. These studies, however, were all carried out in the same geographical context. Given the rapid developments in software engineering, this study aims to identify and reinvestigate the environmental factors that impact software reliability by also considering a different context. The environmental factors that have an impact on software reliability as reported in earlier studies have been analyzed and synthesized. Subsequently, a survey study …
Dynamic Optimal Management Of A Hybrid Microgrid Based On Weather Forecasts, Hamadi Bouaicha, Emily Craparo, Habib Dallagi, Samir Nejim
Dynamic Optimal Management Of A Hybrid Microgrid Based On Weather Forecasts, Hamadi Bouaicha, Emily Craparo, Habib Dallagi, Samir Nejim
Turkish Journal of Electrical Engineering and Computer Sciences
Hybrid microgrids containing both renewable and conventional power sources are becoming increasingly attractive for a variety of reasons. However, intermittency of renewable power production and uncertainty in future load prediction increase risks of electric grid instability and, by consequence, restrict the portion of renewable power production in microgrids. In order, to prefigure the upcoming renewable power production, particularly, wind power and photovoltaic power, we suggest using weather forecasts. In addition to illustrating short term renewable power prediction based on ensemble weather forecasts, this paper focuses on optimizing the management of distributed power generation, power storage, and power exchange with the …
Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi
Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate indoor localization technologies are currently in high demand in wireless sensor networks, which strongly drive the development of various wireless applications including healthcare monitoring, patient tracking and endoscopic capsule localization. The precise position determination requires exact estimation of the time varying characteristics of wireless channels. In this paper, we address this issue and propose a three-phased scheme, which employs an optimal single stage TDOA/FDOA/AOA indoor localization based on spatial sparsity. The first contribution is to formulate the received unknown signals from the emitter as a compressive sensing problem. Then, we solve an $\ell_1$ minimization problem to localize the emitter's …
Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath
Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath
Turkish Journal of Electrical Engineering and Computer Sciences
Recent developments in deep networks allow us to train networks with more parameters by yielding better performance given sufficient amount of data. However, we are still restricted with the availability of labelled data in medical image segmentation, where the problem is exacerbated with high intra- and intervariability of anatomical structures. In order to bypass this problem without compromising network performance, this study introduces a PERINet, which promises to achieve higher performance while being with smaller parameter count such as on the order of 0.8 million than its counterparts. The network benefits from rich features generated by our versions of inception …
Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado
Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado
Turkish Journal of Electrical Engineering and Computer Sciences
Flexible AC transmission systems (FACTS) technology is widely adopted and utilized to maintain the performance of power systems. However, the improvements of power system performance achieved by FACTS devices depend on the right sizing and allocation of such devices. For technical and economic considerations, a FACTS device's location and size should be selected very carefully in order to maximize its benefits to the power system. In this paper, the sizing and location of a static VAR compensator (SVC) are optimally determined using a new optimization technique called lightning attachment procedure optimization (LAPO). The optimal allocation of the SVC is determined …
Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya
Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Real-time response, low cost, sensitive and easy setup fiber optic chemical sensors were fabricated by etching a part of single mode fiber in hydrofluoric (HF) acid solution and tested in different water samples such as tap water, DI water, salty and sugar water with different concentrations to record ringdown time (RDT) differences between media due to refractive index differences by employing the fiber loop ringdown (FLRD) spectroscopy technique. Baseline stability of 0.63 % and the minimum detectable RDT of $5.05$ $\mu$s for this kind of fiber optic chemical sensors were obtained. Fabricated sensors were coated with N,N-Diethyl-p-phenylenediamine for the first …
Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel
Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel
Turkish Journal of Electrical Engineering and Computer Sciences
This work presents the field of view (FOV) maximization of a magnetically actuated two-dimensional (2D) gimballed scanner. The process of maximization is completed in two steps. (1) Optimization of the electrocoil providing the magnetic force that moves the scanner and (2) precise choice of optimum respective locations of both the scanner and the electrocoil. We first derived a formula relating the generated magnetic flux density, coil design parameters and driving voltage. Subsequently, we discussed the design trade-offs of an actuating electrocoil. We also conducted several experiments on a stainless steel 430 scanner having a footprint of 15 mm × 15 …
Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes
Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes
Turkish Journal of Electrical Engineering and Computer Sciences
Surface plasmon resonance (SPR) is a charge-density oscillation that occurs when a beam of p-polarized monochromatic light impinges with a greater angle than the critical angle in a dielectric-metal interface. Because of the high losses related to metals, the generated surface plasmon waves propagate with high attenuation in the visible and near-infrared spectral regions in most of the dielectric-metal interfaces. An alternative to reduce such losses is to use a transparent indium tin oxide (ITO) film. In this paper, we compared theoretical calculations and experimental measurements of the SPR angle $\theta_{SPR}$ on the interfaces of a borosilicate prism (Bp) and …
Low Power And Low Phase Noise Vco With Dual Current Shaping For Iotapplications, Sajad Nejadhasan, Narges Moazenian, Ebrahim Abiri, Mohammah Reza Salehi
Low Power And Low Phase Noise Vco With Dual Current Shaping For Iotapplications, Sajad Nejadhasan, Narges Moazenian, Ebrahim Abiri, Mohammah Reza Salehi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, two low phase noise and power consumption VCO circuits, which are suitable for Internet of things (IoT) applications, are proposed. In the first structure, in order to have more control of the current consumption, the current shaping technique is used in the PMOS and NMOS biasing circuit. In the second structure, for increasing the oscillation amplitude and reducing the phase noise, independent biasing for the NMOS section is used. In both structures, to increase the frequency tuning range (FTR), without using a capacitor bank, the varactor is used in the biasing structure. In the first structure the …
Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin
Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Developing software systems to meet user-demanded functionality is critical. Achieving the design goals by providing the needed functionality is a necessary task, and it is about figuring out a proper set of quality attributes and implementing each one by reflecting a complete set of quality attributes. This study presents popular quality attributes of crisis software systems by conducting a literature review. Each crisis software system has been studied by concentrating on crisis management phases where the system is used, design purposes, and the data processing style. The findings of this research shed light on the crisis software development process by …
A Fuzzy Neural Network For Web Service Selection Aimed At Dynamic Software Rejuvenation, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni
A Fuzzy Neural Network For Web Service Selection Aimed At Dynamic Software Rejuvenation, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni
Turkish Journal of Electrical Engineering and Computer Sciences
Software rejuvenation is an effective technique to counteract software aging in continuously running applications such as web service-based systems. In these systems, web services are allocated based on the requirements of receivers and the facilities of servers. One of the challenges while assigning web services is how to select appropriate server to reduce faults. In this paper, we propose dynamic software rejuvenation as a proactive fault-tolerance technique based on the neural fuzzy system. While considering a threshold for the rejuvenation of each web service, we completed the training based on the features of the service providers as well as the …
A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le
A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le
Turkish Journal of Electrical Engineering and Computer Sciences
Quality of service (QoS) differentiation is an integral component of any networking system, particularly, with the current and future great diversity of users? applications and their manifold requirements. In optical burst switching (OBS) networks, there are two approaches for QoS differentiation: one is based on offset time and the other is based on burst length. This paper presents a mechanism of QoS differentiation based on both offset time and burst length, in which the offset times are calculated to achieve a complete isolation of data loss between priority classes and the burst length is adaptively adjusted according to the feedbacked …
Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune
Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune
Turkish Journal of Electrical Engineering and Computer Sciences
The present paper aims to determine a robust sensor fault-tolerant controller based on fuzzy logic using a robust adaptive super-twisting observer for the control of an induction machine and an inverter set by a state estimation method. The speed sensor is considered in the present case. The modular structure of the fault-tolerant control (FTC) scheme allows integrating this sensor within the existing closed-loop system, and the observer can therefore be designed independently. This article presents a new method to develop a fuzzy decision system that provides faulttolerant control. This paper also aims at detecting the mechanical speed sensor faults. The …
Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez
Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez
Turkish Journal of Electrical Engineering and Computer Sciences
Shortening the periods of compaction tests can be possible by analyzing the data obtained from previous laboratory tests with regression methods. The regression analysis applied to current data reduces the cost of experiments, saves time, and gives estimated outputs. In this study, the MLS-SVR, KB-SVR, and DTR algorithms were employed for the first time for the estimation of soil compaction parameters. The performances of these regression algorithms in estimating maximum dry unit weight (MDD) and optimum water content (OMC) were compared. Furthermore, the soil properties (fine-grained soil, sand, gravel, specific gravity, liquid limit, and plastic limit) were employed as inputs …
Optimum Reference Distance Based Path Loss Exponent Determination Forvehicle-To-Vehicle Communication, Kenan Kuzulugi̇l, Zeynep Hasirci, İsmai̇l Hakki Çavdar
Optimum Reference Distance Based Path Loss Exponent Determination Forvehicle-To-Vehicle Communication, Kenan Kuzulugi̇l, Zeynep Hasirci, İsmai̇l Hakki Çavdar
Turkish Journal of Electrical Engineering and Computer Sciences
Vehicle-to-vehicle (V2V) communication environment differs from classical wireless communication with respect to low antenna heights and high mobility. Therefore, V2V channel modeling based on real measurements is still crucial to get the channel parameters for the various road environments. One of the most extracted parameters from measurements is path loss exponent and selecting a fixed reference distance value in obtaining this parameter may also cause remarkable fitting errors. Thus, in this study, least square method-based approach for the best-fitted path loss exponent calculation was proposed by determining the optimum reference distance value from the V2V channel measurements. First, V2V channel …
Sdma-Based Distributed Device Discovery For D2d Communication, Muddasir Rahim, Muhammad Awais Javed, Ahmad Naseem Alvi
Sdma-Based Distributed Device Discovery For D2d Communication, Muddasir Rahim, Muhammad Awais Javed, Ahmad Naseem Alvi
Turkish Journal of Electrical Engineering and Computer Sciences
Device-to-device (D2D) communication is an important technique to improve capacity of future wireless networks. Cellular communications, internet of things and intelligent transport systems are key areas that could benefit from reduced end-to-end delay provided by D2D communication. Efficient device discovery is an important precondition to enable D2D communication. In this paper, we propose a space division multiple access (SDMA)-based distributed device discovery protocol in which user equipments (UEs) periodically transmit discovery beacons to each other. The proposed protocol reduces contention in the discovery beacons by allocating resource blocks to the UEs based on their location. Simulations results show that the …
An Energy-Efficient Lightweight Security Protocol For Optimal Resource Provenance In Wireless Sensor Networks, Sujesh Lal, Joe Prathap P M
An Energy-Efficient Lightweight Security Protocol For Optimal Resource Provenance In Wireless Sensor Networks, Sujesh Lal, Joe Prathap P M
Turkish Journal of Electrical Engineering and Computer Sciences
Security of resource sharing and provenance is a major concern in wireless sensor networks(WSNs),wherethe intruders can easily inject malicious intermediate nodes for various personal gains. This selective forwarding attack may reduce the flow of resource sharing and throughput in the network. Most of the existing techniques are complex and do not provide sufficient security to sensor nodes with low energy. This paper proposes an energy-efficient and lightweight security protocol for optimal resource provenance in multihop WSNs and the Internet of things (IoT) network. The sharing of the resources between the sensor nodes indicates the strength of the mutual cooperation between …
A New Grid Partitioning Technology For Location Privacy Protection, Yue Sun, Lei Zhang, Jing Li, Zhen Zhang
A New Grid Partitioning Technology For Location Privacy Protection, Yue Sun, Lei Zhang, Jing Li, Zhen Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, the location-based service (LBS) has become an essential part of convenient service in people's daily life. However, the untrusted LBS servers can store lots of information about the user, such as the user's identity, location, and destination. Then the information can be used as background knowledge and combined with the query frequency of the user to launch the inference attack to obtain user's privacy. In most of the existing schemes, the author considers the algorithm of virtual location selection from the historical location of the user. However, the LBS server can infer the user's location information on the historical …