Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Research Project Yenilenebilir Enerji İçin Ödeme İstekliliği Ve Bu İstekliliği Etkileyen Faktörlerin Analiz Edilmesi(TUBİTAK, 2018) Doğan, EyüpBu projede, Türkiye?de ikamet eden hanehalkının yenilenebilir enerji için ödeme istekliliği (YÖİS) ve bu istekliliği etkileyen faktörler analiz edilecektir. İlgili literatür kapsamında, gelişmiş ve gelişmekte olan birçok ülke için YÖİS ve bu istekliliğe etki eden faktörler incelenmesine rağmen, daha önce bu alanda Türkiye üzerine bir çalışma yapılmamıştır. Bu projenin amacı, Türkiye?deki vatandaşların YÖİS ve bu istekliliği etkileyen değişkenleri inceleyerek literatürdeki bu boşluğu doldurmaktır. Ayrıca, Sundt ve Rehdanz (2015) ?ın meta-analiz çalışması, ilgili literatürdeki çoğu makalenin yaş, eğitim seviyesi, gelir düzeyi ve çevresel duyarlılık gibi faktörlerin olası etkisini analiz etmesine rağmen sadece bir kaç makalenin hanehalkı sayısını ekonometrik modele dahil ettiğini göstermiştir. Bu proje, coğunlukla kullanılan demografik faktörlerin yanısıra hanehalkı sayısınında YÖİS?i etkileyip etkilemediğini araştıracaktır. Bu projeyi gerçekleştirebilmek için koşullu değer yöntemiyle hazırlanan toplam 2 bölüm ve 26 sorudan oluşan bir anket kullanılacaktır. Yüzyüze görüşme yöntemiyle Türkiye?nin 12 farklı İBBS bölgesinden toplam 2,500 kişiyle yüzyüze görüşme yöntemiyle doldurulacak anketlerden elde edilecek bilgiler sayesinde, Türkiye?de ikamet eden hanehalkının ortalama YÖİS miktarı ve hangi faktörlerin bu istekliliği anlamlı yada anlamsız etkilediği çeşitli yöntemler kullanılarak analiz edilecektir. Türkiye, Avrupa Birliğine aday bir ülke, G-20 ekonomilerinden birisi ve NATO?ya dahil bir ülke olmasının yanısıra, Dünya ve Avrupa enerji piyasasında da önemli bir konuma sahiptir. Ayrıca, yenilenebilir enerji alanında kısa ve orta vadede yapılması hedeflenen yatırımlarda göz önüne alındığında, Türkiye bu literatür içerisinde araştırılması gereken ülkelerin arasındadır. Bununla birlikte, son zamanlarda küresel ısınma, gaz emisyonu ve çevresel kirlilik gibi faktörler global bir sorun haline gelmiştir. Yenilenebilir enerjinin kullanımı daha temiz bir çevre için önemli bir unsurdur. Türkiye enerjide dışa bağımlı bir ülkedir. Ayrıca, Türkiye'nin elektrik enerjisinin %48'inin doğal gazdan üretiliyor olmasının yarattığı kırılganlığın son dönem Rusya krizi ile görülmüş olması sonrasında enerji karmasında çeşitlendirme çok daha hassasiyet kazanmıştır. Yenilenebilir enerjinin artırılması bağımlılığı azaltacak önemli bir araçtır. Hanehalklarının katılımı, hedeflenen yenilenebilir enerji projelerinin hayata geçirilmesini kolaylaştıracaktır. Bu proje dört ana hedefe ulaşmak üzerine odaklanmıştır: i) Türkiye?de ikamet eden hanehalklarının yenilenebilir kaynalardan üretilen elektrik enerjisi almak için ödemeye razı oldukları ortalama miktarı bulmak, ii) YÖİS?i etkileyebilecek yaş, cinsiyet, gelir düzeyi, egitim seviyesi, çevreye olan duyarlılık ve hanehalkı sayısı gibi faktörleri analiz etmek, iii) yenilenebilir enerji yatırımlarının hanehalkları tarafından desteklenmesine olanak sağlayacak bir politikanın Türkiye?de uygulanabilirliğini ortaya koymak, iv) bu proje çıktılarını uluslararası indekslerce taranan bir dergide yayınlatmak.Research Project Bor Zengini Amorf Malzemeler(TUBİTAK, 2020) Durandurdu, MuratBu TÜBİTAK 1001 projesi kapsamında, bor zengini farklı amorf malzemeler [B1-xSix, B1-xCx, B1-_x000D_ xOx, ve B1-xLix (0, 5 ≥ � ≥ 0,05)] ab initio moleküler dinamik tekniği kullanılarak sıvı hallerin hızlıca_x000D_ soğutulması sonucu modellenmiş ve bu malzemelerin atomik yapıları, elektronik yapıları ve_x000D_ mekanik özellikleri ayrıntı olarak araştırılmıştır. Bunlara ek olarak, bu malzemelerin bazı_x000D_ oranlarının yüksek basınçtaki davranışları incelenmiştir. Bazı malzemelerde, örneğin BC ve BO_x000D_ malzemelerinde, bor oranının artmasıyla iki boyutlu yapıdan üç boyutlu yapıya geçiş_x000D_ gözlemlenmiştir. Ayrıca yüksek bor oranlarında, B12 icosahedralların oluştuğu bulunmuştur. B12_x000D_ molekülüne ek olarak nano boyutunda B7, B10, B14, B16 kafes moleküllerinin oluşumu bazı_x000D_ malzemelerde gözlemlenmiştir. Modellenen malzemelerin her birinin yarıiletken özelliği gösterdiği_x000D_ fakat yasak band aralığında bor oranına bağlı genel bir eğilim olmayıp dalgalanmaların olduğu_x000D_ bulunmuştur. B12 moleküllerinin oluşumunun malzemelerin mekanik özelliğini dikkate değer bir_x000D_ şekilde etkilediği ve bor oranı yüksek olan malzemelerin daha sert bir özellik gösterdiği_x000D_ bulunmuştur. Yüksek basınç uygulamasıyla, malzemelerin daha yoğun bir amorf yapıya faz_x000D_ geçişişi yaptığı ve malzemeye bağlı olarak, faz geçişlerinin tersinir ya da tersinir olmayan faz_x000D_ geçişleri olduğu gözlemlenmiştir.Article Citation - Scopus: 2Zeolite Synthesis by Alkali Fusion Method Using Two Different Fly Ashes Derived From Turkish Thermal Power Plants(Chamber of Mining Engineers of Turkey, 2020-03-01) Top, S.; Vapur, HüseyinIn this study, Faujasite (Na-LSX) (3.5(Ca0.3)3.5(Na0.6)3.5(Mg0.1)Al7Si17O48 32(H2O)) type zeolites and Ca-Filipsite (CaK0.6Na0.4Si5.2Al2.8O16 6(H2O)) type zeolites were produced from Sugözü Thermal Power Plant and Çatalaǧzi Thermal Power Plant fly ashes by alkali fusion method followed by water leaching, respectively. In these methods, fly ashes and sodium hydroxide (NaOH) were mixed in certain proportions and sintered at 600°C in ash furnace. Then, zeolites were obtained from the ground materials after water leaching and solid/liquid separation, respectively. Cation Exchange Capacity (CEC), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier-Transform Infrared Spectroscopy (FTIR), X-Ray Fluorescence (XRF) and Atomic Absorption Spectrometer (AAS) analyses were used to characterize the synthesized zeolites. The zeolites synthesized with Sugözü fly ashes in a ratio of 1:2 had 136.93 meq/100 g CEC, whereas the CEC of synthesized zeolite from Çatalaǧzi fly ashes was found to be 247.88 meq/100 g. As a result, zeolites, which can be used as wastewater treatment agent, energy storage material, catalyst and separator, were synthesized by using 2 different Class F fly ash. © 2023 Elsevier B.V., All rights reserved.Article Citation - WoS: 7Citation - Scopus: 8Using Students' Performance to Improve Ontologies for Intelligent E-Learning System(Edam, 2015) Icoz, Kutay; Sanalan, Vehbi A.; Cakar, Mehmet Akif; Ozdemir, Esra Benli; Kaya, SukruOntologies have often been recommended for E-learning systems, but few efforts have successfully incorporated student data to represent knowledge conceptualizations. Defining key concepts and their relations between each other establishes the backbone of our E-learning system. The system guides an individual student through his/her course by evaluating their progress and suggesting instructional material to review based upon their answers. Three main tasks are performed within this framework: building ontologies for the course, measuring a student's understanding level for the concepts, and making personal suggestions to create an individualized learning environment. This paper presents: the integration of ontologies, assisted with student data, together with an intelligent Recommendation Module for the development of an E-learning system; the comparison and correction adaption of ontology from students' mind maps; and the assessment of students' actual weaknesses in comparison to what Recommendation Module suggests. The sample of 127 students, five classrooms, was conveniently selected among seventh grade students of a demographically average school in a major city in Turkey. The students' achievement was assessed and the scores for different questions were investigated for associations with concepts made in the students' minds. The results provided significant correlations among scores, and a fit model for the concepts represented by questions. The student suggested model slightly differed from the ontology map from the experts. Based on the data-supported model, the Recommendation Module more accurately determined the students' learning deficiencies and suggested concepts to be reviewed.Article Citation - WoS: 2Citation - Scopus: 2The Nexus of Leadership, Political Empowerment, and Social Mobilization: The Case of the July 15 Coup Attempt in Turkey(Seta Foundation, 2020-06-30) Donmez, Rasim Ozgur; Timur, Kasim; Lloyd, Fatma Armagan TekeThis study analyzes the mutually empowering relations between Turkish President Recep Tayyip Erdogan and his followers, and how Erdogan's charismatic leadership and image functioned to galvanize his followers on the night of July 15, 2016, when large numbers of them mobilized against the attempted coup. The article has three sections. The first is a theoretical discussion which sheds light on the concept and the underlying mechanisms of political empowerment and its effects on the relationships between leaders and followers. The second section evaluates Erdogan's characteristics and ruling style, which was instrumental in motivating resistance to the abortive coup. Finally, the third section analyzes the various means by which Erdogan was able to inspire the masses to mobilize against the armed junta through interviews and observations.Article Solutions to Nonlinear Second-Order Three-Point Boundary Value Problems of Dynamic Equations on Time Scales(Tubitak Scientific & Technological Research Council Turkey, 2019-05-29) Dogan, AbdulkadirIn this paper, we consider existence criteria of three positive solutions of three-point boundary value problems for p-Laplacian dynamic equations on time scales. To show our main results, we apply the well-known Leggett-Williams fixed point theorem. Moreover, we present some results for the existence of single and multiple positive solutions for boundary value problems on time scales, by applying fixed point theorems in cones. The conditions we used in the paper are different from those in [Dogan A. On the existence of positive solutions for the one-dimensional p-Laplacian boundary value problems on time scales. Dynam Syst Appl 2015; 24: 295-304].Article Citation - WoS: 6Citation - Scopus: 6Sex Effect on the Correlation of Immunoglobulin G Glycosylation With Rheumatoid Arthritis Disease Activity(Tubitak Scientific & Technological Research Council Turkey, 2020-12-14) Ercan, AltanRheumatoid arthritis (RA) is a chronic autoimmune disease which affects females more than males with a presence of autoantibodies. Immunoglobulin G (IgG) produced by adaptive arm has 2 functional domains, Fc and Fab. The Fc domain binds Fc gamma receptors and C1q proteins of the innate arm. Therefore, the IgG Fc domain serves as a bridge between the innate and adaptive arms and is regulated by an evolutionarily conserved N-glycosylation with variable structures. These glycans are classified as agalactosylated G0, monogalactosylated G1, and digalactosylated G2, which are further modified by core-fucosylation (F) and bisecting N-acetylglucosamine (B) moieties such as G0F and G0FB. Interestingly, proinflammatory G0F is shown to be regulated by estrogen in vivo. Here, it is hypothesized that the regulation of G0F by estrogen contributes to sex dichotomy in RA by setting up the level of IgG-dependent inflammation and therefore, RA disease activity (Das28-CRP3). To investigate this hypothesis, IgG glycosylation was characterized in serum samples from active RA patients (n = 232) and healthy controls (n = 232) by serum N-glycan analysis using the high performance liquid chromatography. According to the results, the IgG Fc glycan phenotype originates predominantly from the structure of G0F, and both G0F and G0FB correlate with Das28-CRP3 in females, but not in males. In conclusion, IgG G0F-dependent inflammation differs in males and females, and these differences point to the differential regulation of inflammation by sex hormone estrogen via IgG glycosylation.Article Citation - WoS: 2Citation - Scopus: 2Prediction of Preference and Effect of Music on Preference: A Preliminary Study on Electroencephalography from Young Women(Tubitak Scientific & Technological Research Council Turkey, 2019-03-01) Yilmaz, Bulent; Gazeloglu, Cengiz; Altindis, FatihNeuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated. The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19-channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic, loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density (PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect of music was investigated by comparing the mean differences between music and no music groups using independent two-sample t-test. In the preference prediction part sequential forward selection, k-nearest neighbors (k-NN) and the support vector machines (SVM), and 5-fold cross-validation approaches were used. It is found that music did not affect like decision in any of the power bands, on the contrary, music affected dislike decisions for all bands with no exceptions. Furthermore, the accuracies obtained in preference prediction study were between 77.5 and 82.5% for k-NN and SVM techniques. The results of the study showed the feasibility of using EEG signals in the investigation of the music effect on purchasing behavior and the prediction of preference of an individual.Article Citation - WoS: 5Citation - Scopus: 6Performance Analysis of Hamming Code for WSN-Based Smart Grid Applications(Tubitak Scientific & Technological Research Council Turkey, 2018) Yigit, Melike; Gungor, Vehbi Cagri; Boluk, PinarMany methods have been employed to detect, compare, and correct errors to increase communication reliability and efficiency in wireless sensor networks (WSNs). However, to the best of our knowledge, no existing study has compared the performance of error control codes by using different modulation techniques in a smart grid communication environment when multichannel scheduling is used. This paper presents a detailed performance evaluation and makes a comparison of different modulation techniques, such as frequency shift keying (FSK), differential phase shift keying (DPSK), binary phase shift keying (BPSK), and offset quadrature phase-shift keying (OQPSK), using Hamming codes in a 500-kV line-of-sight substation smart grid environment with multichannel scheduling. A link-quality-aware routing algorithm is used as a routing protocol and a log-normal shadowing channel is employed as a channel model. Simulations are performed in MATLAB and the performance of the Hamming code with various modulation techniques is compared with the results obtained without using any error correction codes for throughput, delay, and bit error rate. The results show that the performance of the Hamming code with OQPSK modulation is better than its performance with other modulation techniques. Moreover, the results show that the performance of Hamming code improves with multichannel scheduling for all modulation techniques.Article Citation - WoS: 4Citation - Scopus: 5Noise-Assisted Multivariate Empirical Mode Decomposition Based Emotion Recognition(Istanbul Univ-Cerrahapasa, 2018-08-03) Ozel, Pinar; Akan, Aydin; Yilmaz, BulentEmotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms. Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD). Despite its various benefits, EMD has several drawbacks: it is intended for univariate data; it is prone to mode mixing; and the number of local extrema must be enough before the EMD process can begin. To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals. Emotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms. Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD). Despite its various benefits, EMD has several drawbacks: it is intended for univariate data; it is prone to mode mixing; and the number of local extrema must be enough before the EMD process can begin. To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals.
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