01. Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed

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Citation - WoS: 7
Citation - Scopus: 4
2D Modeling Temperature Development of Mass Concrete Structures at Early Age
(FIB. The International Federation for Structural Concrete, 2017) Yikici, T.A.; Chen, R.H.L.; 02.04. Department of Civil Engineering; 02. Faculty of Engineering; 01. MEF University
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; 02.04. Department of Civil Engineering; 02. Faculty of Engineering; 01. MEF University
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.
A Comparative Analysis of the Health Care Utilization and Costs of Patients Diagnosed With and Without Liver Cancer in the Us Medicare Population
(2017) Ogbomo, A.; Lin, Y.; Keshishian, A; Xie, L; Yuce, H; Başer, Onur; 04. Faculty of Economics, Administrative and Social Sciences; 01. MEF University
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Citation - Scopus: 2
A Decade of Discriminative Language Modeling for Automatic Speech Recognition
(2015) Arısoy, Ebru; Saraçlar, Murat; Dikici, Erinc; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
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; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
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; 01. MEF University
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: 3
Citation - Scopus: 2
A Joint Dedupe-Fountain Coded Archival Storage
(2017) Arslan, Şuayb Şefik; Göker, Turguy; Wideman, Rod; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF University
An erasure-coded archival file storage system is presented using a chunk-based deduplication mechanism and fountain codes for space/time efficient operation. Unlike traditional archival storage, this proposal considers the deduplication operation together with correction coding in order to provide a reliable storage solution. The building blocks of deduplication and fountain coding processes are judiciously interleaved to present two novel ideas, reducing memory footprint with weaker hashing and dealing with the increased collisions using correction coding, and applying unequal error protection to deduplicated chunks for increased availability. The combination of these two novel ideas made the performance of the proposed system stand out. For example, it is shown to outperform one of the replication-based as well as RAID data protection schemes. The proposed system also addresses some of the fundamental challenges of today's low-cost deduplicated data storage systems such as hash collisions, disk bottleneck and RAM overflow problems, securing savings up to 90% regular RAM use.
Citation - Scopus: 1
A Microwave Imaging Scheme for Detection of Pulmonary Edema and Hemorrhage
(IEEE, 2022) Ertek, Didem; Kucuk, Gokhan; Bilgin, Egemen; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
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.
Citation - WoS: 1
A Modified Newton Method Formulation for Microwave Imaging
(IEEE, 2020) Coşğun, Sema; Çayören, Mehmet; Bilgin, Egemen; Doğu, Semih; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
A new variant of Newton type methods has been developed for quantitative microwave imaging. To deal with the ill-posedness of the inverse problems, standard Newton type methods involve a linearization of the so called data equation using the Fréchet derivative with respect to the contrast function. Here, the formulation is expanded to include the object equation, therefore, the formulation seeks to reduce the errors in both the data and the object equations. While this modification does not remove the need to solve forward problem at each step, it nevertheless significantly improves convergence rate and the performance. To assess the efficiency of the proposed technique, numerical simulations with synthetic and experimental data have been carried out. The results demonstrate that the proposed variant outperforms the standard Newton method, and shows comparable performance to the contrast source inversion (CSI) algorithm with fewer iterations.
A Multiobjective Evolutionary Algorithm Approach for Map Sketch Generation
(2018) Topcu, Şafak; Etaner-Uyar, A. Sima; 01. MEF University
In this paper, we present a method to generate map sketches for strategy games using a state of the art many-objective evolutionary algorithm, namely NSGAIII. The map sketch generator proposed in this study outputs a three objective Pareto-front in which all the points are fair and strong in different aspects. The generated map sketch can be used by level designers to create real time strategy maps effectively and/or help them see multiple aspects of a game map simultaneously. The algorithm can also be utilised as a benchmark generator to be used in tests for various cases such as shortest path algorithms and strategy game bots. The results reported in this paper are very promising and promote further study.
Citation - WoS: 1
Citation - Scopus: 1
A Novel Tunable Vortex-Induced Vibration Wind Energy Harvester
(Ieee, 2024) Dorantes Gonzalez, Dante Jorge; 02.03. Department of Mechanical Engineering; 02. Faculty of Engineering; 01. MEF University
This study presents a novel approach to enhancing the efficiency and robustness of vortex-induced vibration energy harvesters for wind energy conversion. Through the development and evaluation of alternative tunable stiffness mechanisms, particularly focusing on a discrete-tunable mechanism with three levels of torsional springs, significant improvements in energy capture and construction simplicity have been achieved. By optimizing dynamic models and conducting thorough structural analyses, potential weaknesses in the design have been identified and addressed. The innovative tunable mechanism, currently undergoing patent review, represents a substantial advancement in the field of renewable energy technologies, offering a promising solution for urban energy harvesting applications. This research underscores the importance of continuous innovation and optimization in energy harvesting systems to meet the evolving demands for sustainable energy production.
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; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
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 Randomized Clinical Trial Comparing the Effects of Mindfulness-Based and Cognitive Behavioral Therapy-Based Stress Reduction in Medical Students
(Cambridge Univ Press, 2024) Pence, A. Yay; Coldur, M.; Atalay, Z.; Aslan, S.; Beba, B.; Sayin, C. Coskun; Ertek, I. Ekmekci; 06.01. Department of Guidance and Psychological Counseling; 06. Faculty of Education; 01. MEF University
[No Abstract Available]
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.; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
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 - WoS: 1
Citation - Scopus: 1
A Simplified Approach for Site-Specific Design Spectrum
(2018) Tönük, Gökçe; Kurtuluş, Aslı; Ansal, Atilla; 02.04. Department of Civil Engineering; 02. Faculty of Engineering; 01. MEF University
The design acceleration spectrum requires site investigations and site-response analyses in accordance with the local seismic hazard. The variability in earthquake source and path effects may be considered using a large number of acceleration records compatible with the earthquake hazard. An important step is the selection and scaling of input acceleration records. Likewise, a large number of soil profiles need to be considered to account for the variability of site conditions. One option is to use Monte Carlo simulations with respect to layer thickness and shear wave velocity profiles to account for the variability of the site factors. The local seismic hazard analysis yields a uniform hazard acceleration spectrum on the bedrock outcrop. Site-specific response analyses also need to produce a uniform hazard acceleration spectrum on the ground surface. A simplified approach is proposed to define acceleration design spectrum on the ground surface that may be considered a uniform hazard spectrum.
Citation - WoS: 8
Citation - Scopus: 9
A Value-Adding Approach To Reliability Under Preventive Maintenance Costs and Its Applications
(2014) Dubey, Rameshwar; Kılıç, Erdem; Ali, Sadia Samar; Weber, Gerhard Wilhelm; 04.01. Department of Economics; 04. Faculty of Economics, Administrative and Social Sciences; 01. MEF University
No equipment (system) can be perfectly reliable in spite of the utmost care and best efforts on the part of the designer, decision-maker and manufacturer. The two sides of maintenance are corrective and preventive maintenance. It is generally assumed that a preventive maintenance action is less costly than a repair maintenance action. We examine this proposition in detail on the basis of a failure-time model that relates conformance quality to reliability. Illustratively, we present reliability in the context of contracts with asymmetric information. The model shows how to overcome information rents through price distortions and quantity rationing. The paper ends with a conclusion and an outlook to future studies.
Citation - Scopus: 2
A Visualization Platfom for Disk Failure Analysis
(IEEE, 2018) Arslan, Şuayb Şefik; Yiğit, İbrahim Onuralp; Zeydan, Engin; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF University
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; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF University
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 high-resolution 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. © 2025 Elsevier B.V., All rights reserved.

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