Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/7

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Citation - Scopus: 1
Cold Chain Logistics Firm Selection by Using Ahp-Vikor Integrated Method and a Case Study in Food Industry
(Springer Science and Business Media Deutschland GmbH, 2020) Buyukselcuk, E.C.; Endüstri Mühendisliği Bölümü
With the Industry 4.0, a new trend has started for all sectors and enterprises have entered into a period of intense working and investment to turn into intelligent systems. Cold chain logistics also has the same trend, and companies have pushed the button to be involved in this process. Due to changing lifestyles and generally decreasing prices, the world market for perishable products such as processed foods and cooled products is growing. Cold chain transportation is an important issue in basic food and health product logistics to prevent the growth of harmful microorganisms and to ensure that the products remain intact. In this study, it is aimed to determine the right cold chain logistics firm for company EDB that is a small and medium-sized enterprise (SME) operating in the food industry. Firstly, the selection criteria are defined according to the literature survey and expert views. AHP approach has been used to calculate the weight of them. After the determination of weight of criteria, VIKOR approach has been used to identify the best cold chain logistics firm for company EDB. The results were obtained by using Expert Choice 11.0 and Excel calculator finally the best one has been determined. © 2020, Springer Nature Switzerland AG.
Citation - WoS: 1
Citation - Scopus: 1
Design and Development of a New Tactile Stimulator
(Ieee, 2019) Kazma, Coskun; Levent, Vecdi Emre; Aydin, Nizamettin; Bilgisayar Mühendisliği Bölümü
We have designed and implement a tactile stimulator to obtain information from the central nervous system. Our system consists of two main components. The first one is tactile stimulator, which was designed to stimulate index and middle finger tips, stimulating mechanoreceptors according to the test protocol. Second one is a personal computer running a desktop software for the implementation of test protocols. The flow is as follows; the subjects are asked the question of the test protocol through the personal computer. The parameters are then transmitted to the embedded board on the machine. The embedded board drives step motors to apply the relevant test parameters. The desktop software expects the individual to answer the question using the right or the left mouse button of the computer mouse. After answering the relevant question, the test proceeds to the next step. According to the test protocol, the stimulation process of the mechanoreceptors located at the index and middle finger tips must start and terminate at the same time. From this perspective, the embedded board with 3 18F46K22 PIC microcontrollers produces 2 square wave signals with different frequencies and amplitudes at the same time. The embedded system card developed with the PIC microcontroller is also developed with FPGA. The system has also been tested on 24 blue and white collar employees and a significant result has been obtained.
Citation - Scopus: 2
Event Graphs: Syntax, Semantics, and Implementation
(Institute of Electrical and Electronics Engineers Inc., 2023) Gunal, M.M.; Ismail Osais, Y.; Wagner, G.
This tutorial aims to introduce Event Graphs (EGs), invented 40 years ago by Lee Schruben to allow eventbased modeling of discrete dynamic systems. Their simplicity and naturalness in causality modelling and simulation modelling made EGs popular in research and practice. In a simulation, an event causes state changes in a system as well as other events to happen in the future. EGs provide a parsimonious diagram representation for the Event Scheduling paradigm of Discrete Event Simulation. We first introduce their visual syntax and informal semantics, and then present a recent extension by adding objects to EGs. Our tutorial also includes an introduction to the formal semantics of EGs and a Python implementation for executing EGs. © 2023 IEEE.
Forty Years of Event Graphs in Research and Education
(Institute of Electrical and Electronics Engineers Inc., 2023) Gunal, M.M.; Osais, Y.I.; Schruben, L.; Wagner, G.; Yücesan, E.
Forty years ago, in 1983, Lee Schruben proposed the Event Graph formalism and modeling language, subsequently defining the paradigm of Event-Based Simulation, in a precise way, which had been pioneered 20 years before by SIMSCRIPT. The purpose of this panel is for a group of Event Graph researchers both from Operations Research and Computer Science, including the inventor of Event Graphs and one of his former PhD students who has made essential contributions to their theory, to discuss their views on the history and potential of Event Graph modeling and simulation. In particular, the adoption of Event Graphs as a discrete process modeling language in Discrete Event Simulation and in Computer Science, and their potential as a foundation for the entire field of Discrete Event Simulation and for the fields of process modeling and AI in Computer Science is debated. © 2023 IEEE.
Citation - Scopus: 3
Fpga Based Dco-Ofdm Phy Transceiver for Vlc Systems
(Institute of Electrical and Electronics Engineers Inc., 2019) Levent, V.E.; Uysal, M.; Saglam, G.; Ugurdag, H.F.; Fajar Rizqi Annafianto, N.; Aydin, F.; Kebapci, B.; Bilgisayar Mühendisliği Bölümü
Satisfying the demand for high bandwidth and low latency in Visible Light Communication (VLC) systems is a difficult challenge. VLC channels exhibit frequency-selectiveness at peak-speeds. This phenomenon generates a serious inter-symbol interference effect. A physical layer (PHY) design that can carry out physical layer communication tasks to overcome all these strains is required. In this study, an FPGA based PHY design that implements DCO-OFDM algorithm is described for VLC systems. A demo was performed with the developed PHY design using an LED transmitter and a photodetector receiver. © 2019 Chamber of Turkish Electrical Engineers.
Citation - WoS: 3
Citation - Scopus: 4
Inverse Problem for Euler-Bernoulli Equation With Periodic Boundary Condition
(Univ Nis, Fac Sci Math, 2018) Kanca, Fatma; Baglan, Irem; Bilgisayar Mühendisliği Bölümü
In this work the inverse coefficient problem for Euler-Bernoulli equation with periodic boundary and integral addition conditions is investigated. Under some natural regularity and consistency conditions on the input data the existence, uniqueness and continuously dependence upon the data of the solution are shown by using the generalized Fourier method. Numerical tests using the implicit finite difference scheme combined with an iterative method are presented and discussed. Also an example is presented with figures.
Reflection Coefficient Prediction in Triple-Layer Microwave Absorbers: A Machine Learning Perspective
(Institute of Electrical and Electronics Engineers Inc., 2025) Nas, Abdurrahim; Kankilic, Sueda; Karpat, Esin; Elektrik-elektronik Mühendisliği Bölümü
Electromagnetic absorbers prevent the reflection and transmission of electromagnetic waves. Electromagnetic absorbers have a wide range of applications from military to medical applications. In these areas, absorber designs have different importance in terms of parameters such as reflection coefficient, selected material and thickness. Many difficulties are encountered to achieve the optimal design. In this paper, we propose a machine learning regression method for three-layer microwave absorber architecture to obtain the optimum parameters, overcome the difficulties and speed up the process. The material and thickness of each layer are used as parameters to feed the models and the reflection coefficient is estimated using these parameters. Predictions are made with various regression algorithms. These algorithms are KNeighbors Regression, Random Forest Regressor, XGBoost Regression, CatBoost Regressor, AdaBoost Regressor which uses similarities between observations, Gradient Boosting Regressor which is tree based or boosted tree based algorithms, Linear Regression which uses a linear model, Partial Least Squares Regression which uses cross decomposition, Gaussian Process Regressor which uses statistical distribution, Stochastic Gradient Descent Regressor which uses a linear model to reduce empirical loss to predict an output. Mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), R-squared (R2) are used with the predictions of each model to obtain the metrics for the analysis of the results. The predicted values and actual values of the metrics are used to compare the regression algorithms used in the research. After the comparison, our observations show that in most cases CatBoost Regressor is better than other models used in the research. In general, it is observed that most of the machine learning regression algorithms used in this paper can be used to predict the reflection coefficient of three-layer microwave absorbers as output and input parameters used in the research. © 2025 Elsevier B.V., All rights reserved.
Safe Drug Administration in Pediatric Nursing Education: A Quasi-Experimental Design Study
(Ataturk Univ, 2023) Onturk, Zehra Kan; Sanci, Yagmur; Hemşirelik Bölümü
Objective: This study was carried out to determine the correlation between the performance of students who received simulation-based pediatric nursing education and their self-confidence regarding safe drug administrations during simulation.Methods: The study was conducted in pretest and posttest quasi-experimental design and carried out on a sample group (n =39) based on criteria established at the Nursing Department of a foundation university. Students were subjected to a simulation of "Drug Management in Children" within the scope of the pediatric nursing course. The researchers collected data through a check-list, a self-confidence scale, and tests (pretest and posttest) used in the simulation application on "Drug Management in Children."Results: The students obtained a mean score of 129.00 +/- 14.36 on the self-confidence scale. The posttest scores of the students were statistically significantly higher than the pretest scores (P = .011). The performance mean score of the students from the simulation checklist for safe drug administrations was 36.28 +/- 6.65. There was no statistically significant correlation between the scores from the self-confidence scale, the pretest, the posttest, and the checklist scores (P> .05).Conclusion: This study underlines the importance of having a suitable level of self-confidence for students' educational gains and also indicated that there was no correlation between self-confidence and performance.
STS: AI-Driven Smart Test Scenario Generation Tool
(Institute of Electrical and Electronics Engineers Inc., 2025) Bağlum, Cem; Yayan, Uǧur
One of the most critical steps in the software testing lifecycle, test scenario generation, reduces process efficiency due to its high time and resource requirements. As an innovative solution to this issue, the Smart Test Scenario Tool (STS) has been developed. Smart Test Scenario Tool (STS) enhances contextual accuracy and automation in test scenario generation by analyzing documents in xlsx, py, cpp, txt, and docx formats using large language models. This approach minimizes time loss, and the risk of errors encountered in traditional manual testing processes while transforming test procedures into a context-driven and systematic framework, offering an innovative contribution to the literature. Strengthened with a Streamlit interface, MongoDB-supported database management, and Ollama integration, the system enables the test scenario generation process, a critical component of the software testing cycle, to be conducted more efficiently and reliably. The validity of the study was confirmed through two distinct projects, the first implemented in Python and the second in C++. © 2025 Elsevier B.V., All rights reserved.
Transaction Types in Cryptocurrencies
(Institute of Electrical and Electronics Engineers Inc., 2024) Uysal, T.; Unozkan, H.
The cryptocurrency ecosystem has witnessed an explosive growth, and this study delves into the mechanisms that fuel this expansion. Focusing on airdrops, staking, farming, and coin burning, the research analyzes a vast dataset of transactions from the Ethereum and Binance Networks. This analysis sheds light on the strategic use of these tools by highlighting transactions that engage users and distribute rewards (e.g., airdrops, staking). Furthermore, the study investigates farming as a method to enhance market efficiency by providing liquidity, and coin burning as a strategy to manage token supply and potentially increase value through scarcity. While effective utilization of these mechanisms can bolster token value and project success, regulatory challenges remain. Ultimately, this study aims to raise public awareness of cryptocurrency transaction types and the associated risks. Although many researchers have studied illicit flows on cryptocurrency transactions, in literature we haven't confronted with any study regarding transaction types. By analyzing over 107 million transaction records, the research presents the distribution of these transaction types. With the analysis of the transaction types, the definitions of them, the statistical outputs from the more than 107 million transaction records from ERC20 and BEP20 blockchain systems and the analysis of some specific token types such as Pancake Swap and Shiba, this research is the first study to present an academic approach with statistical analysis. This study can provide investors with knowledge that safeguard them from the potential pitfalls of cryptocurrency transactions. Also, this study presents some basic statistics so as to understand main patterns of different types of transactions. © 2024 IEEE.
Citation - Scopus: 1
Unet3D Based Next Frame Prediction;
(Institute of Electrical and Electronics Engineers Inc., 2024) Akbacak, E.; Bilgisayar Mühendisliği Bölümü
The concept of next-frame prediction, which is predicting the subsequent frames using historical frames' spatial and temporal properties, is indispensable in computer vision. There are various application of frame prediction such as predicting a future event in autonomous vehicles, predicting patient falls in biomedical engineering, and reducing the amount of data transmitted in video transmission. Deep learning applications in this field are the focus of the most effective methods. Especially CNN-LSTM, Convolutional LSTMs, and GAN-supported deep learning methods are very common. This study proposes the inflated 3D Unet encoder-decoder model, which is not yet used for the next-frame prediction problem. The proposed model predicts both the next frame and the subsequent frames. Experimental results have shown that the proposed method gives better results than CNN-LSTM and Convolutional LSTMs. © 2024 IEEE.
A Unique Web 3 Product-NFT Usage in Healthcare
(IEEE, 2025) Unozkan, Huseyin; Endüstri Mühendisliği Bölümü
Non-fungible tokens (NFTs) have gained immense popularity and value in recent years. After the Web 3 revolution, many new products have been constructed based on smart contracts or powerful software agreements. One of the most exciting products of Web 3 is NFT, with their increasing popularity, high volatility, and significant price movements making them popular in trading activities. Although many people, investors and researchers perceive NFTs as a trading product, the smart contract and metadata, both of which make up of NFT structure, offer valuable support for the big data storage and processing fields. In recent years, researchers have proposed different uses of NFTs in healthcare systems to improve the quality of services by using NFTs' versatile data storage architecture. In this study, the capability of NFTs in the storage of health data is investigated, the usage and usage proposals of NFTs in health are examined, and probable usage areas in health sciences are evaluated. The uniqueness of this study is, using NFTs as the dead parental data storage in which the metadata does not need to be mitigated, but the stored data is very valuable for doctors to assess the genetic illnesses comes from parental DNAs.
Citation - Scopus: 5
Using Process Mining Approach for Machining Operations
(Springer Science and Business Media Deutschland GmbH, 2020) Altan, Z.; Birgün, S.; Endüstri Mühendisliği Bölümü
In the Industry 4.0 world, both service and manufacturing companies should review their systems and processes, remove any application that causes waste, ensure lean flow and change business models if necessary, in order to fulfill the requirements of this trend. Introducing Industry 4.0 on a problematic system or process might harm it enough to cause the company disappear instead of benefiting it. For applications correctly decided to be built upon a correct system, data flow must be accurate and timely. And at this stage, data amount that increases with process mining and complexity of the big data will be solved and more information will be obtained about real production processes and data. In this study, a prototype is developed using the data of a previously studied manufacturing research. This prototype handles only one phase of the manufacturing process and extracts all the initial possible pathways of this phase through process mining. © 2020, Springer Nature Switzerland AG.

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