WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Article Citation - WoS: 3Citation - Scopus: 5Block Size Analysis for Discrete Wavelet Watermarking and Embedding a Vector Image as a Watermark(Zarka Private Univ, 2019) Sever, Hayri; Sever, Hayri; Senol, Ahmet; Elbasi, Ersin; Bilgisayar MühendisliğiAs telecommunication and computer technologies proliferate, most data are stored and transferred in digital format. Content owners, therefore, are searching for new technologies to protect copyrighted products in digital form. Image watermarking emerged as a technique for protecting image copyrights. Early studies on image watermarking used the pixel domain whereas modern watermarking methods convert a pixel based image to another domain and embed a watermark in the transform domain. This study aims to use, Block Discrete Wavelet Transform (BDWT) as the transform domain for embedding and extracting watermarks. This study consists of 2 parts. The first part investigates the effect of dividing an image into non overlapping blocks and transforming each image block to a DWT domain, independently. Then, effect of block size on watermark success and, how it is related to block size, are analyzed. The second part investigates embedding a vector image logo as a watermark. Vector images consist of geometric objects such as lines, circles and splines. Unlike pixel-based images, vector images do not lose quality due to scaling. Vector watermarks deteriorate very easily if the watermarked image is processed, such as compression or filtering. Special care must be taken when the embedded watermark is a vector image, such as adjusting the watermark strength or distributing the watermark data into the image. The relative importance of watermark data must be taken into account. To the best of our knowledge this study is the first to use a vector image as a watermark embedded in a host image.Article Citation - WoS: 6Citation - Scopus: 7Illicit Material Detection Using Dual-Energy X-Ray Images(Zarka Private Univ, 2016) Hassanpour, Reza; Hassanpour, Reza; Yazılım MühendisliğiDual energy X-ray inspection systems are widely used in security and controlling systems. The performance of these systems however, degrades with the poor performance of human operators. Computer vision based systems are of vital importance in improving the detection rate of illicit materials, while keeping false alarms at a reasonably low level. In this study, a novel method is proposed for detecting material overlapping and reconstructing multiple images by alleviating these overlaps. Evaluation tests were conducted on images taken from luggage inspection X-ray screening devices used in shopping centres. The experimental results indicate that the reconstructed images are much easier to inspect by human operators than the unprocessed original images.Article Machine Learning-Based Efficiency Prediction of Francis Type Hydraulic Turbines Through Comprehensive Performance Testing(Sage Publications Ltd, 2025) Besni, Ferdi; Buyuksolak, Fevzi; Ayli, Ece; Celebioglu, Kutay; Aradag, Selin; Tascioglu, YigitIn this study, the rehabilitation works carried out for the KEPEZ HPP, which has been in operation for over 50 years in Antalya, Turkey, is discussed. Within this scope, the existing turbine components are optimized using the CFD method, and a design that provides higher performance at the required flow rate and head is obtained. Analyses are performed using numerical methods to examine the behavior of the new turbine at different flow rates and heads, and a hill chart is created. In the second stage, model tests are carried out at the TOBB ETU HYDRO Water Turbine Design and Test Center in accordance with IEC60193 standards. Different ML methods are examined for their ability to predict turbine performance, following the development of the hydrid CFD-Experimental methodology. According to the authors knowledge, there is no study in the literature that combines experimental, numerical, and ML methods for turbines, and ML methods have not been applied before for Francis-type turbine performance prediction. The outcomes of the study contribute to the advancement of turbine design and optimization processes, offering valuable insights for the successful implementation of rehabilitation projects in the hydropower sector.Article Citation - WoS: 2Citation - Scopus: 3The Entropy Method Integrated RSM Model to Evaluate Hole Geometries in Electrochemical Blind Hole Drilling(Taylor and Francis Ltd., 2025) Ayhan, Emre; Yurdakul, Mustafa; Çoǧun, Can; İç, Yusuf TanselThe electrochemical drilling (ECD) process enables the machining of conductive materials with a wide range of hardness, yield strength, and brittleness. In this study, the ECD experiments have been conducted on blind hole drilling in high-speed steel material using a tailor-made ECD machine. The hole geometries (cross-sectional profiles) at different machining parameters have been examined for the hole depth consistency (HDC), hole cross-sectional area (HCAC) and the hole profile length (HPLC) evaluation (response; output) metrics introduced. The relationships between the hole geometry evaluation metrics and machining parameters are obtained using the response surface method (RSM). Using the Entropy method, an optimisation model is also proposed to combine multiple responses into a single objective function. The effectiveness of the Entropy method is compared with the Analytical Hierarchical Process (AHP). The comparison showed that the Entropy model provides more robust and convenient results than the AHP approach. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 2Citation - Scopus: 5Comparative Performance Analysis of Filtering Methods for Removing Baseline Wander Noise From an Ecg Signal(World Scientific Publ Co Pte Ltd, 2024) Ozaydin, Selma; Ahmad, ImteyazECG signals play a vital role in the diagnosis of cardiovascular conditions. However, they often suffer from the effects of various noise sources, including baseline wandering, respiratory artifact noise, power line interference and electrode motion artifacts. To overcome these challenges, it is imperative to implement low-frequency signal noise reduction strategies. Such strategies aim to significantly improve the quality of ECG signals, thus promoting more accurate and reliable diagnosis of cardiovascular disorders. This paper conducts a comparative analysis to assess the effectiveness of commonly used filtering and wavelet techniques in reducing Baseline Wander (BW) noise within ECG signals generated by the influence of breathing or electrode movements. It is common to observe the selection and evaluation of only one particular technique in the existing literature. In contrast, this study aims to provide a comprehensive comparative analysis, providing insight into the performance and relative merits of different techniques. Our research uses both filtering and Discrete Wavelet Transform (DWT) techniques in baseline noise removal. In this context, a reference point is established utilizing noise-free signals and a meticulous investigation of the wavelet-based approach that most effectively eliminates the resulting noise is provided. Subsequently, we assess the reference input and output signal via Signal-to-Noise Ratio (SNR) and Kolmogorov-Smirnov statistical test measurements. The most important contribution of this work to the scientific community resides in the comprehensive examination of IIR/FIR-based and wavelet method-based filtering methods capable of yielding the highest SNR levels across various ECG signals with various types of BW noise. Additionally, the effectiveness of the Chebychev-II filter in BW noise removal is highlighted. Our study was conducted using the MATLAB platform and code command lines were shared to facilitate the reproduction of our study by other researchers. It is considered that this study will be an important reference in the selection of effective techniques for removing BW noise within ECG signals.Article Citation - WoS: 5Citation - Scopus: 3Optimum Bidding Strategy for Wind and Solar Power Plants in Day-Ahead Electricity Market(Springer Heidelberg, 2021) Keysan, Ozan; Satir, Benhur; Ozcan, MehmetThere are two possible strategies for wind power plants (WPPs) and solar power plants (SPPs) to maximize their income in day ahead markets (DAM) in the presence of imbalance cost: joint bidding (JB) via collaboration by participating to balancing groups and deployment of storage technologies. There are limited studies in the literature covering the comparative analysis of "JB strategy" with "battery deployment (BD) strategy". In the existence of balancing responsibility, the comparative analysis of these strategies is the main contribution of this study to the literature. Our Second contribution is the analysis of the impact of different regulatory regimes, which are set by the regulatory authority, on total income. JBM (joint bidding model), which is the model for joint bidding via different collaboration groups, is developed for the analysis of JB strategy, BDM (battery deployment model), which is the model covering the deployment of storage technology, is developed for the analysis of BD strategy. The impact of each strategy on total income is analyzed. According to the analysis of the results of the models, while JB strategy, which is sensitive to the regulatory regime, increases the total annual income of the collaboration groups up to 0.65%, BD strategy seems not feasible and financially viable. On the other hand, extra income values per MW of battery for SPP is between $218 and $400 /MW-year, while these values are between $2460 and $6795/MW-year for the group of 15 WPPs. Therefore, deployment of battery for WPPs creates extra income more than tenfold of that of SPP. BD strategy can be viable provided that the levelized cost of deployment of battery drops below the extra income values achieved per MW of battery.Article Citation - WoS: 5Citation - Scopus: 7An Adoptive Renewable Energy Resource Selection Using Hesitant Pythagorean Fuzzy Dematel and Vikor Methods(Ios Press, 2022) Narayanamoorthy, Samayan; Kang, Daekook; Baleanu, Dumitru; Geetha, SelvarajNowadays, energy from renewable energy resources (RERs) partially satisfies society's energy demands. Investment in the renewable energy system is an arduous task because of huge investments. Generally, RERs selection involves conflicting criteria. Hence there is necessary to evaluate the RERs alternatives in economic, technological, and environmental aspects. Here, DEMATEL (Decision Making Trial and Evaluation Laboratory) method has been utilized to assess the interrelationship among the criteria under hesitant Pythagorean fuzzy (HPF) information. The Pythagorean fuzzy set (PFS) has recently obtained enormous attention and is applied widely in decision-making. We have proposed an integrating model with DEMATEL and VIKOR (Vise Kriterijumska Optimizacija Kompromisno Resenje) methods to identify and evaluate the criteria and alternatives in RERs selection. Within the proposed model, the HPF-DEMATEL method is utilized for weighting the criteria, and the HPF-VIKOR method is utilized for ranking. Finally, an illustrative example demonstrates the proposed method.Editorial Challenges of the (Anti) Adaptive Urbanization in Multiple Scales(Emerald Group Publishing Ltd, 2023) Orhan, Ezgi; Lotfata, AynazArticle Citation - WoS: 1Mm-Food: a High-Dimensional Index Structure for Efficiently Querying Content and Concept of Multimedia Data(Ios Press, 2023) Yazici, Adnan; Arslan, SerdarThe semantic query problem is commonly called the semantic gap and is one of the significant problems in multimedia data retrieval. In this study, we focus on multimedia data retrieval by combining semantic information with data content to solve the semantic gap problem effectively. The main idea behind the combination of low-level content descriptors and the concept of multimedia data is to represent the content information with the semantic information by adding a low-level content descriptor as a new dimension to the index structure. This new dimension is represented by constructing an array index structure that uses a fuzzy clustering algorithm. Thus, a new high-dimensional index structure, named MM-FOOD, supporting querying of multimedia data, including fuzzy querying, is presented in this paper. This proposed index structures construction and query algorithms are explained throughout this paper. Our experiments show that our indexing mechanism is considerably efficient compared to the basic indexing approach, which stores low-level content and semantic concept descriptors in separate structures when the data size is large.Article A Partial Coverage Hierarchical Location Allocation Model for Health Services(inderscience Enterprises Ltd, 2023) Karasakal, Esra; Toreyen, Ozgun; Karasakal, OrhanWe consider a hierarchical maximal covering location problem (HMCLP) to locate health centres and hospitals so that the maximum demand is covered by two levels of services in a successively inclusive hierarchy. We extend the HMCLP by introducing the partial coverage and a new definition of the referral. The proposed model may enable an informed decision on the healthcare system when dynamic adaptation is required, such as a COVID-19 pandemic. We define the referral as coverage of health centres by hospitals. A hospital may also cover demand through referral. The proposed model is solved optimally for small problems. For large problems, we propose a customised genetic algorithm. Computational study shows that the GA performs well, and the partial coverage substantially affects the optimal solutions. [Submitted: 20 January 2021; Accepted: 15 January 2022]
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