WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 11Citation - Scopus: 13Wireless Sensor Network-Based Communication for Cooperative Simultaneous Localization and Mapping(Pergamon-Elsevier Science Ltd, 2015-01) Tuna, Gurkan; Gungor, Vehbi Cagri; Potirakis, Stelios M.; Zeadally, SheraliThis paper presents a novel approach of using a Wireless Sensor Network (WSN) as the communication means for Multi-Robot, Cooperative, Simultaneous Localization and Mapping (CSLAM) applications investigating the associated design challenges and suggesting corresponding solutions. Although the proposed approach brings several benefits including an increased coverage and communication range, self-organization capabilities, quick deployment, and flexible architecture, the realization is interrelated with performance in terms of energy efficiency and reliability. In this respect, the applicability of the WSNs for the presented approach is investigated. Centralized and distributed map merging methods in WSN-based CSLAM are evaluated in detail and the impacts of packet delays and losses on the performance of CSLAM algorithms are shown. Additionally, the involved network congestion and contention dynamics are presented, while the effects of observation range, speed, time intervals between observations, and odometry readings on the SLAM accuracy are shown based on an extensive set of simulation studies. (C) 2014 Elsevier Ltd. All rights reserved.Article Citation - WoS: 30Citation - Scopus: 31Three Dimensional Stress Analysis of Solid Oxide Fuel Cell Anode Micro Structure(Pergamon-Elsevier Science Ltd, 2014-11) Celik, Selahattin; Ibrahimoglu, Beycan; Toros, Serkan; Mat, Mahmut D.One of the most common problems in solid oxide fuel cells (SOFCs) is the delamination and thus the degradation of electrode/electrolyte interface which occurs in the consequences of the stresses generated within the different layers of the cell. Nowadays, the modeling of this problem under certain conditions is one of the main issues for the researchers. The structural and thermo-physical properties of the cell materials (i.e. porosity, density, Young's modulus etc.) are usually assumed to be homogenous in the mathematical modeling of solid oxide fuel cells at macro-scale. However, during the real operation, the stresses created in the multiphase porous layers might be very different than those at macro-scale. Therefore, micro-level modeling is required for an accurate estimation of the real stresses and the performance of SOFCs. This study presents a microstructural characterization and a finite element analysis of the delamination and the degradation of porous solid oxide fuel cell anode and electrode/electrolyte interface under various operating temperatures, compressing forces and material compositions by using the synthetically generated microstructures. A multi physics computational package (COMSOL) is employed to calculate the Von Misses stresses in the anode microstructures. The maximum thermal stress in the electrode/electrolyte interface and three phase boundaries is found to exceed the yield strength at 900 degrees C while 800 degrees C is estimated as a critical temperature for the delamination and micro cracks due to thermal stress generated. The thermal stress decreases in the grain boundaries with increasing content of one of the phases (either Ni or YSZ) and the porosity of the electrode. A clamping load higher than 5 kg cm(-2) is also found to exceed the shear stress limit. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.Article Citation - WoS: 479Citation - Scopus: 548The Role of Renewable Versus Non-Renewable Energy to the Level of Co2 Emissions a Panel Analysis of Sub-Saharan Africa's Big 10 Electricity Generators(Pergamon-Elsevier Science Ltd, 2018-08) Inglesi-Lotz, Roula; Dogan, EyupUndoubtedly, the increasing rates of CO2 emissions contribute highly to climate change. Studies stress the importance of understanding the determinants of emissions, in order to implement appropriate policies. In the past, literature only looked at the effect of aggregate energy to emissions; while nowadays, with the increasing role of renewables, they aim at evaluating the impacts of renewable and nonrenewable energies separately. Also, studies ignored possible cross-dependence among countries; concept particularly important for countries linked by trade or geographical position. Also, only lately, studies focused on developing economies. In this study, we aim to address these gaps of the literature by estimating the determinants (renewable and non-renewable energy, income and trade openness) of CO2 emissions for the ten biggest electricity generators in Sub-Saharan Africa for the period 1980 to 2011 by employing panel estimation techniques robust to cross dependence. A long-run relationship between the main variables is confirmed. Increases in non-renewable energy consumption intensify pollution while the opposite holds for renewable energy. With regards to direction of causal relationships, we observe a unidirectional causality running from emissions, income, trade and non-renewable energies towards renewable energies; from nonrenewable energy to emissions; and from emissions and non-renewable energies to trade. (C) 2018 Elsevier Ltd. All rights reserved.Article Citation - WoS: 204Citation - Scopus: 234The Relationship Between Economic Growth and Electricity Consumption From Renewable and Non-Renewable Sources: A Study of Turkey(Pergamon-Elsevier Science Ltd, 2015-12) Dogan, EyupThe main objective of this study is to analyze the short and long run estimates as well as the causality relationships between economic growth (GR), electricity consumption from renewable sources (RELC) and electricity consumption from non-renewable sources (NRELC) for Turkey in a multivariate model wherein capital (K) and labor (L) are included as additional variables. Using the autoregressive distributed lag (ARDL) approach to cointegration, the Johansen cointegration test and the Gregory-Hansen cointegration test with structural break, we show that GR, RELC, NRELC, K and L are cointegrated. Although NRELC has a long run positive effect on GR, the long run estimate of RELC is negative but insignificant at 5% level of significance. The Granger causality test based on the vector error correction model reveals the evidence of neutrality hypothesis between RELC and GR, and between NRELC and GR in Turkey in the short run. In addition, the Granger causality runs from RELC, NRELC, K and L to GR as well as from GR, RELC, K and L to NRELC in the long run, which supports the existence of growth hypothesis between RELC and GR, and feedback hypothesis between NRELC and GR in the long run. It is advised that policy makers in the Turkish government should continue to reduce the share of electricity consumption from renewable sources and encourage the usage of electricity from non-renewable sources to have sustainable long run growth rates. It is also essential to promote the investment projects to increase the efficiency of electricity generation from non-renewable sources. (C) 2015 Elsevier Ltd. All rights reserved.Article Citation - WoS: 810Citation - Scopus: 926The Influence of Real Output, Renewable and Non-Renewable Energy, Trade and Financial Development on Carbon Emissions in the Top Renewable Energy Countries(Pergamon-Elsevier Science Ltd, 2016-07) Dogan, Eyup; Seker, FahriDue to tremendous increase in the level of carbon dioxide (CO2) emissions in the last several decades, a number of studies in the energy-growth-environment literature have attempted to identify the determinants of CO2 emissions. A major criticism related to the existing studies, we realize, is the selection of panel estimation techniques. Almost all studies use panel methods that ignore the issue of cross-sectional dependence even though countries in the panel are most likely heterogeneous and cross-sectionally dependent In addition, the majority of existing studies use aggregate energy consumption, and thus fail to identify the impacts of energy consumption by sources on the environment In order to fulfill the mentioned gaps in the literature, this empirical study analyzes the influence of the real income, renewable energy consumption, non-renewable energy consumption, trade openness and financial development on CO2 emissions in the EKC model for the top countries listed in the Renewable Energy Country Attractiveness Index by employing heterogeneous panel estimation techniques with cross-section dependence. We find that the analyzed variables become stationary at their first-differences by using the CADF and the CIPS unit root tests, and the analyzed variables are cointegrated by employing the LM bootstrap cointegration test By using the FMOLS and the DOLS, we also find that increases in renewable energy consumption, trade openness and financial development decrease carbon emissions while increases in non-renewable energy consumption contribute to the level of emissions, and the EKC hypothesis is supported for the top renewable energy countries. (C) 2016 Elsevier Ltd. All rights reserved.Article Citation - WoS: 5Citation - Scopus: 5Taking Advantage of a Diverse Set of Efficient Production Schedules: A Two-Step Approach for Scheduling With Side Concerns(Pergamon-Elsevier Science Ltd, 2013-08) Goren, Selcuk; Pierreval, HenriIn many practical scheduling problems, the concerns of the decision-maker may not be all known in advance and therefore may not be included in the initial problem definition as an objective function and/or as constraints. In such a case, the usual techniques of multi-objective optimization become inapplicable. To cope with this problem and to facilitate handling the concerns of the decision-maker, which can be implicit or qualitative, a dedicated methodological framework is needed. In this paper we propose a new two-step framework. First, we aim at obtaining a set of schedules that can be considered efficient with respect to a performance measure and at the same time different enough from one another to enable flexibility in the final choice. We formalize this new problem and suggest to address it with a multimodal optimization approach. Niching considerations are discussed for common scheduling problems. Through the flexibility induced with this approach, the additional considerations can be taken into account in a second step, which allows decision-makers to select an appropriate schedule among a set of sound schedules (in contrast to common optimization approaches, where usually a single solution is obtained and it is final). The proposed two-step approach can be used to handle a wide range of underlying scheduling problems. To show its potential and benefits we illustrate the framework on a set of hybrid flow shop instances that have been previously studied in the literature. We develop a multimodal genetic algorithm that employs an adapted version of the restricted tournament selection for niching purposes in the first step. The second step takes into account additional concerns of the decision-maker related to the ability of the schedules to absorb the negative effects due to random machine breakdowns. Our computational experiments indicate that the proposed framework is capable of generating numerous high-performance (mostly optimal) schedules. Additionally, our computational results demonstrate that the proposed framework provides the decision-maker a high flexibility in dealing with subsequent side concerns, since there are drastic differences in the capabilities of the efficient solutions found in Step 1 to absorb the negative impacts of machine breakdowns. (C) 2013 Elsevier Ltd. All rights reserved.Article Citation - WoS: 102Citation - Scopus: 119Risk Based Facility Location by Using Fault Tree Analysis in Disaster Management(Pergamon-Elsevier Science Ltd, 2015-04) Akgun, Ibrahim; Gumusbuga, Ferhat; Tansel, BarbarosDetermining the locations of facilities for prepositioning supplies to be used during a disaster is a strategic decision that directly affects the success of disaster response operations. Locating such facilities close to the disaster-prone areas is of utmost importance to minimize response time. However, this is also risky because the facility may be disrupted and hence may not support the demand point(s). In this study, we develop an optimization model that minimizes the risk that a demand point may be exposed to because it is not supported by the located facilities. The purpose is to choose the locations such that a reliable facility network to support the demand points is constructed. The risk for a demand point is calculated as the multiplication of the (probability of the) threat (e.g., earthquake), the vulnerability of the demand point (the probability that it is not supported by the facilities), and consequence (value or possible loss at the demand point due to threat). The vulnerability of a demand point is computed by using fault tree analysis and incorporated into the optimization model innovatively. To our knowledge, this paper is the first to use such an approach. The resulting non-linear integer program is linearized and solved as a linear integer program. The locations produced by the proposed model are compared to those produced by the p-center model with respect to risk value, coverage distance, and covered population by using several test problems. The model is also applied in a real problem. The results indicate that taking the risk into account explicitly may create significant differences in the risk levels. (C) 2014 Elsevier Ltd. All rights reserved.Article Citation - WoS: 2Citation - Scopus: 5Radio Communications Interdiction Problem Under Deterministic and Probabilistic Jamming(Pergamon-Elsevier Science Ltd, 2019-07) Tanerguclu, Turker; Karasan, Oya Ekin; Akgun, Ibrahim; Karasan, EzhanThe Radio Communications Interdiction Problem (RCIP) seeks to identify the locations of transmitters on the battlefield that will lead to a robust radio communications network by anticipating the effects of intentional radio jamming attacks used by an adversary during electronic warfare. RCIP is a sequential game defined between two opponents that target each other's military units in a conventional warfare. First, a defender locates a limited number of transmitters on the defender's side of the battlefield to optimize the relay of information among its units. After observing the locations of radio transmitters, an attacker locates a limited number of radio jammers on the attacker's side to disrupt the communication network of the defender. We formulate RCIP as a binary bilevel (max-min) programming problem, present the equivalent single level formulation, and propose an exact solution method using a decomposition scheme. We enhance the performance of the algorithm by utilizing dominance relations, preprocessing, and initial starting heuristics. To reflect a more realistic jamming representation, we also introduce the probabilistic version of RCIP where a jamming probability is associated at each receiver site as a function of the prevalent jamming to signal ratios leading to an expected coverage of receivers as an objective function. We approximate the nonlinearity in the jamming probability function using a piecewise linear convex function and solve this version by adapting the decomposition algorithm constructed for RCIP. Our extensive computational results on realistic scenarios show the efficacy of the solution approaches and provide valuable tactical insights. (C) 2019 Elsevier Ltd. All rights reserved.Article Citation - WoS: 37Citation - Scopus: 35Performance Prediction and Adaptation for Database Management System Workload Using Case-Based Reasoning Approach(Pergamon-Elsevier Science Ltd, 2018-07) Raza, Basit; Kumar, Yogan Jaya; Malik, Ahmad Kamran; Anjum, Adeel; Faheem, MuhammadWorkload management in a Database Management System (DBMS) has become difficult and challenging because of workload complexity and heterogeneity. During and after execution of the workload, it is hard to control and handle the workload. Before executing the workload, predicting its performance can help us in workload management. By knowing the type of workload in advance, we can predict its performance in an adaptive way that will enable us to monitor and control the workload, which ultimately leads to performance tuning of the DBMS. This study proposes a predictive and adaptive framework named as the Autonomic Workload Performance Prediction (AWPP) framework. The proposed AWPP framework predicts and adapts the DBMS workload performance on the basis of information available in advance before executing the workload. The Case-Based Reasoning (CBR) approach is used to solve the workload management problem. The proposed CBR approach is compared with other machine learning techniques. To validate the AWPP framework, a number of benchmark workloads of the Decision Support System (DSS) and the Online Transaction Processing (OLTP) are executed on the MySQL DBMS. For preparation of training and testing data, we executed more than 1000 TPC-H and TPC-C like workloads on a standard data set. The results show that our proposed AWPP framework through CBR modeling performs better in predicting and adapting the DBMS workload. DBMSs algorithms can be optimized for this prediction and workload can be controlled and managed in a better way. In the end, the results are validated by performing post-hoc tests. (C) 2018 Elsevier Ltd. All rights reserved.Article Citation - WoS: 21Citation - Scopus: 24Performance Evaluation of Cloud Computing Platforms Using Statistical Methods(Pergamon-Elsevier Science Ltd, 2014-07) Atas, Gultekin; Gungor, Vehbi CagriCloud computing is a very attractive research topic. Many studies have examined the infrastructure as a service and software as a service aspects of cloud computing; however, few studies have focused on platform as a service (PaaS). According to recent reports, demand for enterprise PaaS solutions will increase continuously. However, different sectors require different types of PaaS applications and computing resources. Therefore, an evaluation and ranking framework for PaaS solutions according to application needs is required. To address this need, this study presents the most essential aspects of PaaS solutions and provides a framework for evaluating the performance of PaaS providers. It also proposes a suitable set of benchmarking algorithms that can help determine the most appropriate PaaS provider based on different resource needs and application requirements. Performance evaluations of three well-known cloud computing PaaS providers were conducted using the analytic hierarchy process and the logic scoring of preference methods. (C) 2014 Elsevier Ltd. All rights reserved.