WoS İndeksli Yayınlar Koleksiyonu
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Article Citation Count: 82D Materials (WS2, MoS2, MoSe2) Enhanced Polyacrylamide Gels for Multifunctional Applications(Mdpi, 2022) Uysal, Bengu Ozugur; Nayir, Seyma; Acba, Melike; Citir, Betul; Durmaz, Sumeyye; Kocoglu, Sevval; Yildiz, EkremMultifunctional polymer composite gels have attracted attention because of their high thermal stability, conductivity, mechanical properties, and fast optical response. To enable the simultaneous incorporation of all these different functions into composite gels, the best doping material alternatives are two-dimensional (2D) materials, especially transition metal dichalcogenides (TMD), which have been used in so many applications recently, such as energy storage units, opto-electronic devices and catalysis. They have the capacity to regulate optical, electronic and mechanical properties of basic molecular hydrogels when incorporated into them. In this study, 2D materials (WS2, MoS2 and MoSe2)-doped polyacrylamide (PAAm) gels were prepared via the free radical crosslinking copolymerization technique at room temperature. The gelation process and amount of the gels were investigated depending on the optical properties and band gap energies. Band gap energies of composite gels containing different amounts of TMD were calculated and found to be in the range of 2.48-2.84 eV, which is the characteristic band gap energy range of promising semiconductors. Our results revealed that the microgel growth mechanism and gel point of PAAm composite incorporated with 2D materials can be significantly tailored by the amount of 2D materials. Furthermore, tunable band gap energies of these composite gels are crucial for many applications such as biosensors, cartilage repair, drug delivery, tissue regeneration, wound dressing. Therefore, our study will contribute to the understanding of the correlation between the optical and electronic properties of such composite gels and will help to increase the usage areas so as to obtain multifunctional composite gels.Article Citation Count: 43D indoor positioning with spatial modulation for visible light communications(Elsevier, 2023) Arsan, Taner; Yesilirmak, Yalin Evrim; Bayman, Irem Ozgur; Arsan, Taner; Panayırcı, Erdal; Stevens, NobbyIn this paper, a novel three-dimensional (3D) indoor visible light positioning (VLP) algorithm is proposed based on the spatial modulation (SM) and its error performance assessed as compared to the conventional received signal strength (RSS)-based 3D VLP systems. As contrasted to the traditional VLP system, the proposed SM-based 3D VLP system first estimates the optical channel gain between the transmitting light-emitting diodes (LEDs) and the two photo detectors (PDs) attached to the user by a pilot-based channel estimation technique. Then, unknown 3D positions of the receiver are determined by the trilateration algorithm with distances computed from the estimates of the channel gains. Consequently, the 3D VLP system achieves an interference -free transmission with increased spectral efficiency and without the need for a demultiplexing process at the receiving end. The algorithm's performance is evaluated regarding positioning error by applying the SM over four LEDs and the number of pilots selected as a function of the environmental signal-to-noise ratios (SNRs). The computer simulation results show that the positioning errors are obtained in an order of magnitude smaller than RSS-based techniques in an indoor industrial environment. This is mainly because the distances involved in determining the 3D positions can be determined more precisely by the pilot-aided channel estimation method without creating any data rate problem in transmission due to the higher spectral efficiency of the SM.Article Citation Count: 23D Printer Selection for the Sustainable Manufacturing Industry Using an Integrated Decision-Making Model Based on Dombi Operators in the Fermatean Fuzzy Environment(Mdpi, 2024) Görçün, Ömer Faruk; Zolfani, Sarfaraz Hashemkhani; Kucukonder, Hande; Antucheviciene, Jurgita; Pavlovskis, MiroslavasThree-dimensional printers (3DPs), as critical parts of additive manufacturing (AM), are state-of-the-art technologies that can help practitioners with digital transformation in production processes. Three-dimensional printer performance mostly depends on good integration with artificial intelligence (AI) to outperform humans in overcoming complex tasks using 3DPs equipped with AI technology, particularly in producing an object with no smooth surface and a standard geometric shape. Hence, 3DPs also provide an opportunity to improve engineering applications in manufacturing processes. As a result, AM can create more sustainable production systems, protect the environment, and reduce external costs arising from industries' production activities. Nonetheless, practitioners do not have sufficient willingness since this kind of transformation in production processes is a crucial and irrevocable decision requiring vast knowledge and experience. Thus, presenting a methodological frame and a roadmap may help decision-makers take more responsibility for accelerating the digital transformation of production processes. The current study aims to fill the literature's critical theoretical and managerial gaps. Therefore, it suggests a powerful and efficient decision model for solving 3DP selection problems for industries. The suggested hybrid FF model combines the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF-SWARA) and the Fermatean Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (FF-RAFSI) approaches. The novel FF framework is employed to solve a critical problem encountered in the automobile manufacturing industry with the help of two related case studies. In addition, the criteria are identified and categorized regarding their influence degrees using a group decision approach based on an extended form of the Delphi with the aid of the Fermatean fuzzy sets. According to the conclusions of the analysis, the criteria "Accuracy" and "Quality" are the most effective measures. Also, the suggested hybrid model and its outcomes were tested by executing robustness and validation checks. The results of the analyses prove that the suggested integrated framework is a robust and practical decision-making tool.Article Citation Count: 23D self-assemble formation of molybdenum disulfide (MoS2)-doped polyacrylamide (PAAm) composite hydrogels(Tubitak Scientific & Technological Research Council Turkey, 2022) Durmaz, Sumeyye; Yildiz, Ekrem; Uysal, Bengu Ozugur; Pekcan, OnderPolyacrylamide (PAAm), a renowned member of the hydrogel class, has many uses throughout a wide range of industrial processes, including water absorbed diapers, contact lenses, wastewater treatment, biomedical applications such as drug delivery vehicles and tissue engineering because of its physical stability, durability, flexibility easier shaping, and so on. PAAm also provides new functionalities after the incorporation of inorganic structures such as molybdenum disulfide (MoS2). During the copolymerization process, the transmittance of all samples reduced significantly after a particular time, referred to as the gel point. Microgels form a tree above the gel point as projected by Flory-Stockmayer classical theory. Because of microgels positioned at the junction points of the Cayley tree, the addition of MoS2 results in strong intramolecular crosslinking and looser composites. Moreover, fractal geometry provides a quantitative measure of randomness and thus permits characterization of random systems such as polymers. Fractal dimension of these polymer composites is calculated from power-law-dependent scattered intensity. It was also confirmed that a hydrogel rapidly formed within a few seconds, indicating a 3D network formation inside the gel. These materials may have a great potential for application in wearable and implantable electronics due to this highly desired 3D self-assemble feature.Article Citation Count: 13D-printed actuator-based beam-steering approach for improved physical layer security in visible light communication(Optica Publishing Group, 2022) Erdem, Mehmet Can; Gurcuoglu, Oguz; Panayırcı, Erdal; Kurt, Gunes Karabulut; Ferhanoglu, OnurIn this study, we present the design, manufacture, and implementation of a 3D-printed lens scanner-based beam steering for use in visible light communication (VLC) applications. The 5 cm x 5 cm scanner is designed for low-cost 3D printing with fused deposition modeling using polylactic acid. Scanning is facilitated through electromagnetic actuation of the lens frame, carrying a conventional 25 mm lens, from two nearly orthogonal directions. The serpentine spring that connects the lens frame to the external frame is tailored to offer similar spring constants in the directions of actuation and has minimal (<1.5 mm) sag due to the mass of the lens. The manufactured actuator was integrated on a miniaturized VLC test bed (70 cm x 40 cm x 40 cm). Using the test bed, we characterized the applied voltage versus beam displacement behavior of the actuator in the lateral plane and demonstrated beam steering on amoving target with face-recognition feedback. The proposed scheme was targeted to offer an improved security measure in VLC through tracking the legitimate receiver (i.e., via face recognition) and uses the feedback to steer the focused light onto the targeted device. The joint use of focusing and steering features allows for the legitimate receiver to roam within the room while enjoying the improved secrecy due to the focused light. We calculate the secrecy capacity for the demonstrated approach, which compares favorably with a number of jamming, spatial modulation, and beam-forming counterparts. The presented actuator can be used with larger room dimensions, yet upscaling to larger illumination units will require the use of a lens having smaller focus to address a larger total steering angle. (C) 2022 Optica Publishing GroupArticle Citation Count: 05403 Sayılı Kanun Çerçevesinde Terekedeki Tarım Arazilerinin Devredilmesi Karşısında Muris Muvazaası(Istanbul Univ, 2020) Senol, A. Nilay; Kazmacı, Özge UzunThe Law on Protection of Soil and Land Use, numbered 5403, aims to protect the unity of agricultural lands, and to prevent the division of the soil with inheritance. This law stipulates first, the possibility regarding the giving over of the agricultural land in succession to one or more heirs, to a family partnership, to a limited liability company or to a third person with the consensus of the heirs and second, in case of disagreement, the judge shall decide whether to leave the agricultural land to a competent heir or to sell the land. Furthermore, according to this law, the competent heir to whom the agricultural land will be left can be determined by means of testamentary disposition. It is possible and also valid within the legal constraints that the testator can also transfer the agricultural land to one of the heirs while he is alive. It is arguable whether this transaction can be considered as the testator’s simulation or not, if this transaction has also been made with a simulated transaction. Some principles are set out by the Supreme Court in terms of the simulation of the testator, and although these principles and decisions are criticized by the doctrine, such cases are held by these principles. The purpose and the regulations of the Law numbered 5403 shall be taken into consideration in determining testator’s simulationArticle Citation Count: 18Absolute configuration and biological profile of pyrazoline enantiomers as MAO inhibitory activity(Wiley, 2019) Yelekçi, Kemal; Sarıgül, Sevgi; Bultinck, Patrick; Herrebout, Wouter; Doğan, İlknur; Yelekçi, Kemal; Uçar, Gülberk; Kelekçi, Nesrin GökhanA new racemic pyrazoline derivative was synthesized and resolved to its enantiomers using analytic and semipreparative high-pressure liquid chromatography. The absolute configuration of both fractions was established using vibrational circular dichroism. The in vitro monoamine oxidase (MAO) inhibitory profiles were evaluated for the racemate and both enantiomers separately for the two isoforms of the enzyme. The racemic compound and both enantiomers were found to inhibit hMAO-A selectively and competitively. In particular the R enantiomer was detected as an exceptionally potent and a selective MAO-A inhibitor (K-i = 0.85 x 10(-3) +/- 0.05 x 10(-3) mu M and SI: 2.35 x 10(-5)) whereas S was determined as poorer compound than R in terms of K-i and SI (0.184 +/- 0.007 and 0.001). The selectivity of the enantiomers was explained by molecular modeling docking studies based on the PDB enzymatic models of MAO isoforms.Conference Object Citation Count: 0Abstraction in FPGA implementation of neural networks(World Scientific and Engineering Academy and Society, 2008) Öğrenci, Arif SelçukA model for FPGA implementation of multilayer perceptron neural networks is presented. The model tries to incorporate object oriented design principles in the analysis training and design of components using hardware description languages. The synthesis will be based on the tools supplied by the FPGA vendors. The results indicate that the method can be utilized and it can be further improved to create a general methodology that bridges the gap between hardware and software in embedded system design.Conference Object Citation Count: 1Accelerating Brain Simulations on Graphical Processing Units(IEEE, 2015) Bozkuş, Zeki; El-Ghazawi, Tarek A.; Bozkuş, ZekiNEural Simulation Tool(NEST) is a large scale spiking neuronal network simulator of the brain. In this work we present a CUDA(R) implementation of NEST. We were able to gain a speedup of factor 20 for the computational parts of NEST execution using a different data structure than NEST's default. Our partial implementation shows the potential gains and limitations of such possible port. We discuss possible novel approaches to be able to adapt generic spiking neural network simulators such as NEST to run on commodity or high-end GPGPUs.Article Citation Count: 11Accurate Refinement Of Docked Protein Complexes Using Evolutionary Information And Deep Learning(Imperıal College Press, 2016) Akbal-Delibas, Bahar; Farhoodi, Roshanak; Pomplun, Marc; Haspel, NuritOne of the major challenges for protein docking methods is to accurately discriminate native-like structures from false positives. Docking methods are often inaccurate and the results have to be refined and re-ranked to obtain native-like complexes and remove outliers. In a previous work we introduced AccuRefiner a machine learning based tool for refining protein-protein complexes. Given a docked complex the refinement tool produces a small set of refined versions of the input complex with lower root-mean-square-deviation (RMSD) of atomic positions with respect to the native structure. The method employs a unique ranking tool that accurately predicts the RMSD of docked complexes with respect to the native structure. In this work we use a deep learning network with a similar set of features and five layers. We show that a properly trained deep learning network can accurately predict the RMSD of a docked complex with 1.40 angstrom error margin on average by approximating the complex relationship between a wide set of scoring function terms and the RMSD of a docked structure. The network was trained on 35000 unbound docking complexes generated by RosettaDock. We tested our method on 25 different putative docked complexes produced also by RosettaDock for five proteins that were not included in the training data. The results demonstrate that the high accuracy of the ranking tool enables AccuRefiner to consistently choose the refinement candidates with lower RMSD values compared to the coarsely docked input structures.Conference Object Citation Count: 6Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing(IEEE, 2014) Erküçük, Serhat; Erküçük, Serhat; Çırpan, Hakan AliIn wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately it is indeed more important to analyze the presence or absence of the signal correctly. Furthermore these studies do not consider the achievable lower bounds of reconstruction error and how well the selected method performs correspondingly. Motivated by these issues we investigate in detail the primary user detection performance of Bayesian compressive sensing (BCS) approach in this paper. Accordingly we (i) determine the BCS signal reconstruction performance in terms of mean-square error (MSE) compression ratio and signal-to-noise ratio (SNR) and compare it with the conventionally used basis pursuit approach (ii) determine how well BCS performs compared with the Bayesian Cramer-Rao lower bound (BCRLB) of the signal reconstruction error and (iii) assess the probability of detection performance of BCS for various SNR and compression ratio values. The results of this study are important for determining the achievable performance of BCS based spectrum sensing.Article Citation Count: 1Achieving Sustainability in Solar Energy Firms in Turkey through Adopting Lean Principles(Mdpi, 2022) Ayağ, Zeki; Ayag, ZekiLean principles and sustainability are considered important terms in business. Solar firms are witnessing great competition to fulfill energy requirements, suffering from a huge amount of waste, negatively affecting the sustainability dimensions. Thus, the aim of the study is to build a framework for solar energy firms to achieve sustainability through adopting lean principles, which will help to fix many problems as waste and costs. The method included reviewing the literature to explore the founding of the relation between the two terms, and using a questionnaire that was directed to the responsible people in Turkish solar energy firms. The results of the survey were analyzed to: (1) Find out what the responsible people think about the two terms lean and sustainability; (2) Measure the probable relationship between lean principles and sustainability dimensions by applying a linear regression test; (3) Use the results of point number two to build the framework. The result showed there was a high level of relative importance about the two terms from the point of view of managers and experts in solar firms. In addition, the study found a relationship between adopting pull and flow principles of lean, and achieving economic and social dimensions of sustainability, this finding is represented in a framework.Article Citation Count: 5The acquisition and use of relative clauses in Turkish-learning children's conversational interactions: a cross-linguistic approach(Cambridge University Press, 2019) Uzundağ, Berna A.; Küntay, Aylin C.Using a cross-linguistic approach, we investigated Turkish-speaking children's acquisition and use of relative clauses (RCs) by examining longitudinal child-caregiver interactions and cross-sectional peer conversations. Longitudinal data were collected from 8 children between the ages of 8 and 36 months. Peer conversational corpus came from 78 children aged between 43 and 64 months. Children produced RCs later than in English (Diessel, 2004) and Mandarin (Chen & Shirai, 2015), and demonstrated increasing semantic and structural complexity with age. Despite the morphosyntactic difficulty of object RCs, and prior experimental findings showing a subject RC advantage, preschool-aged children produced object RCs, which were highly frequent in child-directed speech, as frequently as subject RCs. Object RCs in spontaneous speech were semantically less demanding (with pronominal subjects and inanimate head nouns) than the stimuli used in prior experiments. Results suggest that multiple factors such as input frequency and morphosyntactic and semantic difficulty affect the acquisition patterns.Article Citation Count: 1Across dimensions: Two- and three-dimensional phase transitions from the iterative renormalization-group theory of chains(2020) Keçoğlu, İbrahim; Berker, A. NihatSharp two- and three-dimensional phase transitional magnetization curves are obtained by an iterative renormalization-group coupling of Ising chains, which are solved exactly. The chains by themselves do not have a phase transition or nonzero magnetization, but the method reflects crossover from temperaturelike to fieldlike renormalization-group flows as the mechanism for the higher-dimensional phase transitions. The magnetization of each chain acts, via the interaction constant, as a magnetic field on its neighboring chains, thus entering its renormalization-group calculation. The method is highly flexible for wide application.Editorial Citation Count: 7The Act of Killing An Interview with Joshua Oppenheimer(CINEASTE, 2013) Behlil, Melis; Oppenheimer, Joshua[Abstract Not Available]Conference Object Citation Count: 4Action Recognition Using Random Forest Prediction with Combined Pose-based and Motion-based Features(IEEE, 2013) Ar, İlktan; Akgül, Yusuf SinanIn this paper we propose a novel human action recognition system that uses random forest prediction with statistically combined pose-based and motion-based features. Given a set of training and test image sequences (videos) we first adopt recent techniques that extract low-level features: motion and pose features. Motion-based features which represent motion patterns in the consecutive images are formed by 3D Haar-like features. Pose-based features are obtained by the calculation of scale invariant contour-based features. Then using statistical methods we combine these low-level features to a novel compact representation which describes the global motion and the global pose information in the whole image sequence. Finally Random Forest classification is employed to recognize actions in the test sequences by using this novel representation. Our experimental results on KTH and Weizmann datasets have shown that the combination of pose-based and motion-based features increased the system recognition accuracy. The proposed system also achieved classification rates comparable to the state-of-the-art approaches.Conference Object Citation Count: 1Active and Reactive Power Load Profiling Using Dimensionality Reduction Techniques and Clustering(Institute of Electrical and Electronics Engineers Inc., 2019) Ceylan, Oğuzhan; Ceylan, Oğuzhan; Papadopoulos, Theofilos A.; Kazaki, Anastasia G.; Barzegkar-Ntovom, Georgios A.This paper proposes a methodology to characterize active and reactive power load profiles. Specifically, the approach makes use of fast Fourier Transform for conversion into frequency domain, principle component analysis to reduce the dimension and K-means++ to determine the representative load profiles. The data set consists of five-year measurements taken from the Democritus University of Thrace Campus. Test days were also classified as working and non-working. From the results it is observed that the proposed methodology determines representative load profiles effectively both regarding active and reactive power.Book Part Citation Count: 0Book Part Citation Count: 0Active Citizenship in Europe Practices and Demands in the EU, Italy, Turkey, and the UK Conclusion(Palgrave, 2017) Bee, Cristiano[Abstract Not Available]Book Part Citation Count: 0Active Citizenship in Europe Practices and Demands in the EU, Italy, Turkey, and the UK Preamble and Introduction(Palgrave, 2017) Bee, Cristiano[Abstract Not Available]
