Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1926

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Now showing 1 - 20 of 211

Citation - Scopus: 5
18 - Acoustic and Mechanical Properties of Biofibers and Their Composites
(Elsevier, 2022) Koç, Büşra; Genç, Garip; Körük, Hasan
In this study, the acoustic and mechanical properties of many biofibers and their composites are presented. First, the sound absorption coefficients and transmission losses of commonly used natural fibers and their composites are presented, by clearly reporting the thickness of the samples, for three different frequency ranges (<500 Hz: low, 500–2000 Hz: medium, and >2000 Hz: high). In addition, the sound absorption coefficients (for low- and medium-frequency ranges) and noise reduction coefficients of some 40-cm-thick samples are overlaid in order to directly compare their performances. Second, the physical properties, such as the density, diameter, and length of biofibers, and mechanical properties, such as the damping (or loss factor) and Young’s modulus of biofibers and their composites, are presented in detail. For comparison purposes, the acoustic and mechanical properties of some conventional materials, such as carbon and glass fibers, are included in the tables and figures. Finally, the effects of some parameters, such as pretreatment, fiber diameter, fiber/matrix ratio, moisture content, manufacturing and machining parameters/techniques, and measurement conditions/methods, on the acoustic and mechanical properties of natural materials are presented. Furthermore, current applications and potential usage areas of natural fibers are briefly discussed.
Citation - Scopus: 3
19 - Identification of the Elastic and Damping Properties of Jute and Luffa Fiber-Reinforced Biocomposites
(Elsevier, 2022) Genç, Garip; Saygılı, Yusuf; Körük, Hasan; Şanlıtürk, Yusuf Kenan
Although there are many studies in the literature on the static mechanical properties of biomaterials such as tensile strength, the dynamic mechanical properties of biomaterials such as modal loss factors have not been investigated in detail. In this study, the Young’s moduli and damping (or loss factors) of some jute and luffa fiber-reinforced biocomposites are investigated. The effects of fiber/resin ratio and thickness on the mechanical properties of the jute and luffa composites are identified via an experimental approach. For this purpose, acoustic and structural frequency response functions of some homogeneous and hybrid jute and luffa composite plates with different fiber/resin ratios and thicknesses are measured. By analyzing the measured frequency response functions using the circle-fit method, the modal frequencies and loss factors of the homogeneous and hybrid composite plates are determined. By assuming that the homogeneous plates are isotropic, the same plates are modeled using the finite element method, and by comparing the experimental and theoretical natural frequencies, the elastic properties of the homogeneous plates are determined. In addition, the same homogeneous plates are modeled by considering an anisotropic material model, and the associated material properties are determined. By using the identified material properties, the finite element models of the hybrid composite plates are developed, and by comparing their experimental and theoretical natural frequencies, the identified elastic material properties are evaluated and validated.
Citation - WoS: 7
Citation - Scopus: 4
2D Modeling Temperature Development of Mass Concrete Structures at Early Age
(FIB. The International Federation for Structural Concrete, 2018) Yikici, T.A.; Chen, R.H.L.
In this paper, a 2D finite volume analysis methodology was used to predict temperature development within three different bridge pier caps. MATLAB® was employed to generate a program that solves the governing heat transfer equation where development of thermo-physical concrete properties was defined as a function of degree of hydration. The rate of heat generation was obtained experimentally via adiabatic calorimetry and the activation energy was determined following the ASTM C 1074 procedure to implement equivalent age concept. 2D finite volume analysis results were presented in comparison with the recorded concrete temperatures from the field. Accordingly, temperature time histories at the center and the side surface of the bridge pier caps were predicted reasonably well using the concrete mixture information and the measured concrete hydration properties. © 2022 Elsevier B.V., All rights reserved.
A Bi-Objective Traffic Signal Optimization Model for Mixed Traffic Concerning Pedestrian Delays
(Elsevier B.V., 2024) Akyol, Görkem; Çelikoğlu, Hilmi Berk; Silgu, Mehmet Ali; Goncu, Sadullah
Urban traffic networks suffer in numerous ways from traffic congestion. Some of these adverse effects are increased travel times of cars, buses, bicycle users, pedestrians etc., with the addition of excessive greenhouse gas emissions. Transportation engineers and policy makers try to improve the quality of urban transportation systems by developing projects to enhance the pedestrian experience, reduce private car usage, reduce total time spent in the network through different control strategies, and diminish the detrimental effects. In this context, this study takes Connected and Automated Vehicles (CAVs) and pedestrians into account at signal-controlled intersections. A novel intersection signal control optimization methodology that incorporates pedestrian delays and vehicular emissions from CAVs is presented. Non-dominated sorting genetic algorithm-II is utilized to solve the multiobjective optimization problem. For the emission calculations, the MOVES3 emission model is utilized. The proposed framework is tested on real-world case study. Simulation experiments showed major improvements in pedestrian delays and lower emissions. © 2024 The Authors. Published by ELSEVIER B.V.
Citation - Scopus: 2
A Decade of Discriminative Language Modeling for Automatic Speech Recognition
(2015) Arısoy, Ebru; Saraçlar, Murat; Dikici, Erinc
This paper summarizes the research on discriminative language modeling focusing on its application to automatic speech recognition (ASR). A discriminative language model (DLM) is typically a linear or log-linear model consisting of a weight vector associated with a feature vector representation of a sentence. This flexible representation can include linguistically and statistically motivated features that incorporate morphological and syntactic information. At test time, DLMs are used to rerank the output of an ASR system, represented as an N-best list or lattice. During training, both negative and positive examples are used with the aim of directly optimizing the error rate. Various machine learning methods, including the structured perceptron, large margin methods and maximum regularized conditional log-likelihood, have been used for estimating the parameters of DLMs. Typically positive examples for DLM training come from the manual transcriptions of acoustic data while the negative examples are obtained by processing the same acoustic data with an ASR system. Recent research generalizes DLM training by either using automatic transcriptions for the positive examples or simulating the negative examples.
Citation - Scopus: 4
A Framework for Automatic Generation of Spoken Question-Answering Data
(Association for Computational Linguistics (ACL), 2022) Manav, Y.; Menevşe, M.Ü.; Özgür, A.; Arısoy, Ebru
This paper describes a framework to automatically generate a spoken question answering (QA) dataset. The framework consists of a question generation (QG) module to generate questions automatically from given text documents, a text-to-speech (TTS) module to convert the text documents into spoken form and an automatic speech recognition (ASR) module to transcribe the spoken content. The final dataset contains question-answer pairs for both the reference text and ASR transcriptions as well as the audio files corresponding to each reference text. For QG and ASR systems we used pre-trained multilingual encoder-decoder transformer models and fine-tuned these models using a limited amount of manually generated QA data and TTS-based speech data, respectively. As a proof of concept, we investigated the proposed framework for Turkish and generated the Turkish Question Answering (TurQuAse) dataset using Wikipedia articles. Manual evaluation of the automatically generated question-answer pairs and QA performance evaluation with state-of-the-art models on TurQuAse show that the proposed framework is efficient for automatically generating spoken QA datasets. To the best of our knowledge, TurQuAse is the first publicly available spoken question answering dataset for Turkish. The proposed framework can be easily extended to other languages where a limited amount of QA data is available. © 2022 Association for Computational Linguistics.
A Historical Perspective To Fabrication in Architecture for Preserving Heritage
(Education and research in Computer Aided Architectural Design in Europe, 2019) Özgan, Sibel Yasemin; Özkar, Mine; Hamzaoğlu, Begüm
Digital technologies have recently been at the forefront of the causal link between making and design. A growing number of architecture programs of universities incorporates fabrication to the educational environment, and even to the curriculum. Fabrication technology is now considered among the set of tools students are expected to acquire a basic knowledge of and skills in. Nevertheless, the pedagogical potential of fabrication in communicating traditions of making is underused in an oversight of the continuity of the relevant know-how. Our position is that traditions of making can be the subject matter of fabrication with the objective to remedy the role of fabrication tools in architectural history, sustainable architectural production, and in the field of digital heritage. In this paper, we report on two comparative studies that illustrate how the instrumental factors of two historical crafts can be articulated using fabrication. © 2019, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.
Citation - WoS: 1
Citation - Scopus: 2
A Machine Learning Approach To Resolving Conflicts in Physical Human-Robot Interaction
(Association for Computing Machinery, 2025) Ulas Dincer, Enes; Al-Saadi, Zaid; Hamad, Y.M.; Aydın, Yusuf; Kucukyilmaz, A.; Basdogan, C.
As artificial intelligence techniques become more sophisticated, we anticipate that robots collaborating with humans will develop their own intentions, leading to potential conflicts in interaction. This development calls for advanced conflict resolution strategies in physical human-robot interaction (pHRI), a key focus of our research. We use a machine learning (ML) classifier to detect conflicts during co-manipulation tasks to adapt the robot's behavior accordingly using an admittance controller. In our approach, we focus on two groups of interactions, namely "harmonious"and "conflicting,"corresponding respectively to the cases of the human and the robot working in harmony to transport an object when they aim for the same target, and human and robot are in conflict when human changes the manipulation plan, e.g. due to a change in the direction of movement or parking location of the object.Co-manipulation scenarios were designed to investigate the efficacy of the proposed ML approach, involving 20 participants. Task performance achieved by the ML approach was compared against three alternative approaches: (a) a rule-based (RB) Approach, where interaction behaviors were rule-derived from statistical distributions of haptic features; (b) an unyielding robot that is proactive during harmonious interactions but does not resolve conflicts otherwise, and (c) a passive robot which always follows the human partner. This mode of cooperation is known as "hand guidance"in pHRI literature and is frequently used in industrial settings for so-called "teaching"a trajectory to a collaborative robot.The results show that the proposed ML approach is superior to the others in task performance. However, a detailed questionnaire administered after the experiments, which contains several metrics, covering a spectrum of dimensions to measure the subjective opinion of the participants, reveals that the most preferred mode of interaction with the robot is surprisingly passive. This preference indicates a strong inclination toward an interaction mode that gives more control to humans and offers less demanding interaction, even if it is not the most efficient in task performance. Hence, there is a clear trade-off between task performance and the preferred mode of interaction of humans with a robot, and a well-balanced approach is necessary for designing effective pHRI systems in the future. © 2025 Copyright held by the owner/author(s).
Citation - Scopus: 1
A Microwave Imaging Scheme for Detection of Pulmonary Edema and Hemorrhage
(IEEE, 2022) Ertek, Didem; Kucuk, Gokhan; Bilgin, Egemen
The microwave imaging systems have the potential to present a cost effective and less hazardous alternative to conventional medical imaging techniques. In this paper, a Contrast Source Inversion method based microwave imaging scheme is proposed and tested for the detection of pulmonary edema and hemorrhage. To this end, a realistic human torso phantom is used, and the electromagnetic parameters of the human tissues is determined via Cole-Cole model. The scattered field is simulated via Method of Moments at the operating frequency of 350 MHz, and a 50 dB white Gaussian noise is added to model a realistic measurement setup. The numerical tests performed with the proposed technique suggest that the method can be used to locate the pulmonary edema and hemorrhage, and it is capable of distinguishing these two medical conditions successfully.
A Practical PCB-Based Framework for Spiking Neural Networks with a Half-Adder Example
(IEEE, 2025) Cikikci, Sevde Vuslat; Orek, Eren; Aysoy, Ayhan; Ozgen, Ali Kagan; Yavuz, Arda; Ayhan, Tuba
This paper addresses the half-adder problem using Spiking Neural Networks (SNNs). In a previous study, the XOR operation was successfully realized on a breadboard and in this study it is integrated into the half-adder structure. The system uses input signals at frequencies of 50 Hz and 100 Hz and the neurons are generated by the Leaky Integrate and Fire (LIF) model. Unlike other neuron models, the LIF model is less complex. In addition, it was preferred because of its biological meaningfulness compared to the Integrate and Fire model. The network, consisting of 18 neurons in total, shows that basic arithmetic operations can be performed with SNN. Overall, this study demonstrates that basic logic operations can be implemented in neural networks, thus providing new perspectives for digital calculation. The successful solution of the Half Adder problem using SNNs not only proves the calculation capabilities of SNNs, but also opens new perspectives for the development of more complex logical circuits using these biologically inspired neural circuits.
Citation - Scopus: 1
A Ran/Sdn Controller Based Connectivity Management Platform for Mobile Service Providers
(Institute of Electrical and Electronics Engineers Inc., 2017) Ayhan, Gökhan; Koca, Melih; Zeydan, Engin; Tan, A. Serdar
In this demo, we demonstrate the integration of radio access network (RAN)/Software-Defined Networking (SDN) controller with a connectivity management platform designed for mobile wireless networks. This is an architecture designed throughout the EU Celtic-Plus project SIGMONA1. OpenDaylight based RAN/SDN controller and the application server are capable of collecting infrastructure and client related parameters from OpenFlow enabled switches and Android based phones respectively. The decision on the best access network selection is computed at the application server using a Multiple Attribute Decision Making (MADM) algorithm and instructed back to Android-based mobile client for execution of access network selection. © 2017 IFIP.
A Resonator Design For Mutual Coupling Reduction Between Microstrip Antennas In Mımo Applications At 28 Ghz
(Institute of Electrical and Electronics Engineers Inc., 2024) Gollu, A.A.; Polat, B.; Semerci, D.; Bilgin, E.
A simple resonator structure is proposed to reduce the mutual coupling between rectangular microstrip patch antennas positioned close to each other for MIMO applications at 28 GHz center frequency. Here, the frequency of 28 GHz is chosen because it is one of middle bands for 5G communication in USA. Two microstrip patch antennas with gaps using a common dielectric substrate and a ground plane are employed as antennas and the patches are closely placed with an edge-to-edge distance of 0.6 mm (approximately λ/18). In order to reduce the mutual coupling between these radiating elements and increase the isolation, a resonator is positioned between them and its parameters are optimized. In the simulations, it is observed that the proposed resonator reduces the coupling by approximately 10 dB. By this result, it can be concluded that the proposed structure may be suitable for tightly packed MIMO systems. © 2024 IEEE.
Citation - Scopus: 2
A Visualization Platfom for Disk Failure Analysis
(IEEE, 2018) Arslan, Şuayb Şefik; Yiğit, İbrahim Onuralp; Zeydan, Engin
It has become a norm rather than an exception to observe multiple disks malfunctioning or whole disk failures in places like big data centers where thousands of drives operate simultaneously. Data that resides on these devices is typically protected by replication or erasure coding for long-term durable storage. However, to be able to optimize data protection methods, real life disk failure trends need to be modeled. Modelling helps us build insights while in the design phase and properly optimize protection methods for a given application. In this study, we developed a visualization platform in light of disk failure data provided by BackBlaze, and extracted useful statistical information such as failure rate and model-based time to failure distributions. Finally, simple modeling is performed for disk failure predictions to alarm and take necessary system-wide precautions.
Citation - Scopus: 1
Adaptive Boosting of Dnn Ensembles for Brain-Computer Interface Spellers
(IEEE, 2021) Çatak, Yiğit; Aksoy, Can; Özkan, Hüseyin; Güney, Osman Berke; Koç, Emirhan; Arslan, Şuayb Şefik
Steady-state visual evoked potentials (SSVEP) are commonly used in brain computer interface (BCI) applications such as spelling systems, due to their advantages over other paradigms. In this study, we develop a method for SSVEP-based BCI speller systems, using a known deep neural network (DNN), which includes transfer and ensemble learning techniques. We test performance of our method on publicly available benchmark and BETA datasets with leave-one-subject-out procedure. Our method consists of two stages. In the first stage, a global DNN is trained using data from all subjects except one subject that is excluded for testing. In the second stage, the global model is fine-tuned to each subject whose data are used in the training. Combining the responses of trained DNNs with different weights for each test subject, rather than an equal weight, provide better performance as brain signals may differ significantly between individuals. To this end, weights of DNNs are learnt with SAMME algorithm with using data belonging to the test subject. Our method significantly outperforms canonical correlation analysis (CCA) and filter bank canonical correlation analysis (FBCCA) methods.
AI-Driven Digital Soil Mapping: Leveraging Generative AI, Ensemble Learning and Geospatial Technologies for Data-Scarce Regions
(Springer Science and Business Media Deutschland GmbH, 2025) Drias, Yassine; Drias, Habiba; Belkadi, Widad Hassina; Cakar, Tuna; Abdelhamid, Zakaria; Bensemmane, Riad Yacine
This study presents a methodology for generating highresolution digital soil maps by integrating artificial intelligence (AI) with geospatial technologies. The research begins with comprehensive data collection and the extraction of relevant soil properties with the help of generative AI. To improve predictive accuracy, ensemble learning algorithms were employed due to their ability to capture complex relationships within soil characteristics. Additionally, a structured preprocessing pipeline was developed to refine and standardize the collected soil data, ensuring its suitability for modeling. The model's performance was evaluated using spatial cross-validation techniques to identify the most effective predictive approach. To validate the proposed methodology, experiments were conducted in northern Algeria, a region characterized by diverse landscapes ranging from arid zones to fertile plains. The results demonstrate the potential of AI-driven approaches to enhance soil mapping, particularly in regions where high-quality and up-to-date soil data are limited. This study underscores the efficacy of AI and geospatial technologies in advancing precision agriculture and land management.
Citation - Scopus: 8
An Empirical Analysis of Financial Fair-Play: the Case of Russian Premier League
(Pensoft Publishers, 2020) Özaydın, Selçuk
The real impact of financial fair play (FFP) came along with the break-even rule which prevents clubs from over-spending through a variety of sanctions. As UEFA limited clubs’ expenses with their incomes, the transfer market took a hit. This paper demonstrates the impact of FFP on Russian Premier League teams’ transfer activity, examines how transfers’ demography and career profiles changed and investigates the changes in competitive balance after break-even. A regression discontinuity design is conducted in order to estimate the policy impact. The empirical results suggest that Russian clubs have been severely affected by break-even in terms of transfer expenditure and balance and started to transfer more U21 players and players from lesser leagues of the world. Furthermore, competitive balance in the Russian Premier League deteriorated in favor of the giants in the league as a result of break-even.
Citation - WoS: 2
Citation - Scopus: 10
An Fpga Implementation of a Risc-V Based Soc System for Image Processing Applications
(IEEE, 2021) Gholizadehazari, Erfan; Ayhan, Tuba; Ors, Berna
The Laplacian filter is one of the fundamental applications in image processing. In our work, the Laplacian filter has been applied to an image, and both hardware and software implementation of the filter has been studied. Our system consists of an OV7670 Camera module, Nexys 4 DDR FPGA board and VGA monitor to display the processed video stream. Mentioned process has forwarding tasks: camera module captures raw RGB data and writes to RAM, Laplacian filter IP processes raw image and the results written back to memory. VGA modules show output images to monitor. The Laplacian filter part considered in hardware and software implementation is compared in terms of time and area.
Citation - Scopus: 1
An Fpga Implementation of Givens Rotation Based Digital Architecture for Computing Eigenvalues of Asymmetric Matrix
(IEEE, 2022) Köseoğlu, İlayda; Yalçın, Mustak Erhan; Öztürk, Elif; Ayhan, Tuba
This paper proposes the digital circuit design that performs the eigenvalue calculation of asymmetric matrices with realvalued elements. Eigenvalues are computed iteratively through the QR algorithm. In the QR algorithm, the input matrix is factorized into orthogonal Q and upper triangular R matrix, then the RQ product is calculated to obtain an iterated matrix. For a time-efficient QR decomposition process, the Givens Rotation (GR) Principle is utilized to benefit from the parallelization feature. Parallelization is managed by the Systolic Array (SA) architecture that is created by placing Givens Generation (GG) and Row Updates (RU) blocks in a triangle array. In this paper, 4×4 input matrix is used to create a TSA architecture including n-1 diagonal (GG), and (n ∗ (n−1))/2 off-diagonal (RU) modules. In the results section, Givens Rotation is compared with the Gram Schmidt algorithm used in our previous study [1] in terms of error, and area usage.
Citation - WoS: 14
Citation - Scopus: 40
An Overview of Blockchain Technologies: Principles, Opportunities and Challenges
(IEEE, 2018) Arslan, Şuayb Şefik; Mermer, Gültekin Berahan; Zeydan, Engin
Blokzincir, toplumumuzun birbiriyle iletişim kurma ve ticaret yapma biçiminde devrim yapma potansiyeline sahip, yakın zamanda ortaya çıkmış olan bir teknolojidir. Bu teknolojinin sağladığı en önemli avantaj aracı gerektiren bir oluşumda güvenilir bir merkezi kuruma ihtiyaç duymadan değer taşıyan işlemleri değiş tokuş edebilmesidir. Ayrıca, veri bütünlüğü, dahili orijinallik ve kullanıcı şeffaflığı sağlayabilir. Blokzincir, birçok yenilikçi uygulamanın temel alınacağı yeni internet olarak görülebilir. Bu çalışmada, genel çalışma prensibi, oluşan fırsatlar ve ileride karşılaşılabilecek zorlukları içerecek şekilde güncel blokzincir teknolojilerinin genel bir görünümünü sunmaktayız.
An Overview on the Structural Monitoring, Assessment and Retrofitting of Historical Structures With a Focus on 13th Century Monuments
(Springer international Publishing Ag, 2024) Ilki, Alper; Inci, Pinar; Halici, Omer F.; Demir, Cem; Comert, Mustafa; Kuran, Fikret
Monumental historical structures affirm natural and cultural identity and hence they should be transmitted to future generations. The protection and preservation of these structures against aging and natural hazards, particularly seismic actions, requires a comprehensive approach including diagnosis of the present condition of the structure and enhancement of structural capacity for disaster mitigation, if necessary. It is obvious that due to their historical values, any attempt towards the preservation of the monumental historical structures must be carried out with respect to the principles of integrity and authenticity. In this study, the structural performance assessment procedures, implementation of structural health monitoring systems and seismic strengthening strategies are discussed and described with reference to 13th-century monumental historical structures in Turkiye. The structural engineering aspects of recent activities for the restoration and preservation of the Great Mosque and Hospital of Divrigi (a world heritage listed structure) and Sivas Ulu Cami (Mosque) Minaret are briefly presented. In light of the structural analysis and monitoring results, recommendations for interventions to these monumental structures are outlined.

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