Browsing by Author "Maraş, H. Hakan"

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A New Robust Binary Image Embedding Algorithm in Discrete Wavelet Domain
(IEEE, 2014) Mohammed, Ahmed; Maraş, H. Hakan; Elbaşı, Ersin; 34410
Digital watermarks have recently emerged as a possible solution for protecting the copyright of digital materials, the work presented in this paper is concerned with the Discrete Wavelet Transform (DWT) based non-blind digital watermarking, and how the DWT is an efficient transform in the field of digital watermarking. In this work we used an optimum criteria that embeds four watermarks in more than one level of DWT in the same algorithm. The aim of this work is to keep the Correlation Coefficient (CC) between the original and the extracted watermark around the value of 0.9.
Analysing Iraqi Railways Network by Applying Specific Criteria Using the GIS Techniques
(Coll Science Women, Univ Baghdad, 2019) Naji, Hayder Faris; Maraş, H. Hakan; 34410
The railways network is one of the huge infrastructure projects. Therefore, dealing with these projects such as analyzing and developing should be done using appropriate tools, i.e. GIS tools. Because, traditional methods will consume resources, time, money and the results maybe not accurate. In this research, the train stations in all of Iraq's provinces were studied and analyzed using network analysis, which is one of the most powerful techniques within GIS. A free trial copy of ArcGIS (R) 10.2 software was used in this research in order to achieve the aim of this study. The analysis of current train stations has been done depending on the road network, because people used roads to reach those train stations. The data layers for this study were collected and prepared to meet the requirements of network analyses within GIS. In this study, the current train stations in Iraq were analyzed and studied depending on accessibility value for those stations. Also, to know the numbers of people who can reach those stations within a walking time of 20 minutes. So, this study aims to analyze the current train stations according to multiple criteria by using network analysis in order to find the serviced areas around those stations. Results will be presented as digital maps layers with their attribute tables that show the beneficiaries from those train stations and serviced areas around those stations depending on specific criteria, with a view to determine the size of this problem and to support the decision makers in case of locating new train stations within the best locations for it.
Detection of Rheumatoid Arthritis From Hand Radiographs Using A Convolutional Neural Network
(Springer, 2020) Üreten, K.; Erbay, H.; Maraş, H. Hakan
Introduction: Plain hand radiographs are the first-line and most commonly used imaging methods for diagnosis or differential diagnosis of rheumatoid arthritis (RA) and for monitoring disease activity. In this study, we used plain hand radiographs and tried to develop an automated diagnostic method using the convolutional neural networks to help physicians while diagnosing rheumatoid arthritis. Methods: A convolutional neural network (CNN) is a deep learning method based on a multilayer neural network structure. The network was trained on a dataset containing 135 radiographs of the right hands, of which 61 were normal and 74 RA, and tested it on 45 radiographs, of which 20 were normal and 25 RA. Results: The accuracy of the network was 73.33% and the error rate 0.0167. The sensitivity of the network was 0.6818; the specificity was 0.7826 and the precision 0.7500. Conclusion: Using only pixel information on hand radiographs, a multi-layer CNN architecture with online data augmentation was designed. The performance metrics such as accuracy, error rate, sensitivity, specificity, and precision state shows that the network is promising in diagnosing rheumatoid arthritis.
Finding the most suitable existing irrigation dams for small hydropower development in Turkey: A GIS-Fuzzy logic tool
(2021) Küçükali, Serhat; Al Bayatı, Omar; Maraş, H. Hakan; 20413
This paper enables a screening of existing irrigation dams in order to assess and rank potential sites for small hydropower development by using a Geographic Information System (GIS)-fuzzy logic multi-criteria scoring technique. The following criteria are evaluated: dam characteristics (reservoir normal level, reservoir capacity, dam purpose, dam ageing), and grid connection spatial characteristics. The proposed method estimates the suitability degree of each criterion separately and then aggregates them into a Site Suitability Index (SSI). Existing irrigation dams in Turkey are assessed in order to be utilized for hydropower development. The overall score of each candidate site is obtained and, their performance is compared for different strategies. One of the most suitable dams, Karadere, was chosen as a case study. By using the daily continuous monitored data, we showed that flow and head is highly variable during the irrigation season. Accordingly, we evaluated an innovative compact medium-head hydro turbine that can capture those fluctuations with its operational flexibility and minimal civil works. Moreover, an optimal path methodology was applied to find the best grid connection route from the dam to its nearest substation considering the site land use characteristics in order to minimize land expropriation. © 2021 Elsevier Ltd
Measurement of Edge Detection Algorithms in Clean and Noisy Environment
(IEEE, 2014) Mahmood, Alaa Mohammed; Maraş, H. Hakan; Elbaşı, Ersin; 34410
The subject of identification edge in images has a wide application in various fields for that it's considered one of the important topics in a digital image processing. There are many algorithms to detect the edge in images, but the performance of these algorithms depends on the type of image, the environment of the image and the threshold value of the edge algorithm. The objective of this paper is to evaluate five algorithms of edge detection which are Roberts, Sobel, Prewitt, LOG, and Canny in multi environments clean and noisy by using several types of original images (binary image, graphic image, high frequency image, low frequency image, median frequency image, and texture image) and then determine the best algorithm. In noisy environment the following noises was used Gaussian, salt and pepper and speckle. It's known that each edge detection algorithm has a threshold value, if the current pixel value is less than the defined threshold in strength, it will be considered an edge pixel. The change rate of the threshold value in all environments is also explained through this study.
Multimodal Interaction Flow Representation for Ubiquitous Environments - MIF: A Case Study in Surgical Navigation Interface Design
(2015) Tokdemir, Gül; Altun, Gamze; E. Çağıltay, Nergiz; Maraş, H. Hakan; Börcek, Alp Özgün; 17411
With the advent of technology, new interaction modalities became available which augmented the system interaction. Even though there are vast amount of applications for the ubiquitous devices like mobile agents, smart glasses and wearable technologies, many of them are hardly preferred by users. The success of those systems is highly dependent on the quality of the interaction design. Moreover, domain specific applications developed for these ubiquitous devices involve detailed domain knowledge which normally IT professionals do not have, which may involve a substantial lack of quality in the services provided. Hence, effective and high quality domain specific applications developed for these ubiquitous devices require significant collaboration of domain experts and IT professionals during the development process. Accordingly, tools to provide common communication medium between domain experts and IT professionals would provide necessary medium for communication. In this study, a new modelling tool for interaction design of ubiquitous devices like mobile agents, wearable devices is proposed which includes different interaction modalities. In order to better understand the effectiveness of this newly proposed design tool, an experimental study is conducted with 11 undergraduate students (novices) and 15 graduate students (experienced) of Computer Engineering Department for evaluating defect detection performance for the defects seeded into the interface design of a neuronavigation device. Results show that the defects were realized as more difficult for the novices and their performance was lower compared to experienced ones. Considering the defect types, wrong information and wrong button type of defects were recognized as more difficult. The results of this study aimed to provide insights for the system designers to better represent the interaction design details and to improve the communication level of IT professionals and the domain experts.
Neuronavigation Systems and Passive Usage Problem
(IEEE, 2015) Çağıltay, Nergiz; Tokdemir, Gül; Aydın, Elif; Tokdemir, Gül; Maraş, H. Hakan; Tonbul, Gökçen; Aydın, Elif; 17411
Nowadays, neuronavigation systems are used in brain surgery procedures, known as a technology to help the surgeon during the operational period. However, the surgeons have faced several problems with the existing systems. Some of these problems are related to the systems software and user interfaces. In this study, such problems are examined and the "Passive Usage" term is added to the literature by establishing a connection between the problems of endoscopic surgical procedures and similar issues occurred in other domains. The passive usage problem is generalized on different domains for the first time with this study. The results of the study expected to gather up the similar passive usage problems experienced in different domains. Accordingly, the methodologies and studies that are conducted in different research areas may lead to eliminate the Passive Usage problems efficiently.
Simulation-based environments for surgical practice
(IEEE, 2017) Özçelik, Erol; Çağıltay, Nergiz Ercil; Özçelik, Erol; Maraş, H. Hakan; 115500
Modeling and simulation environments provide several insights about the real situations such as endoscopic surgery. Endoscopic surgery requires both hand skills, so, understanding the effect of using dominant or non dominant hand on mental workload is important to better design, develop and implement modeling and simulation environments to support real-life implementations of surgical procedures. This experimental study presents a simulation application of eye-tracking approach to understand mental workload in different hand conditions: dominant hand, non-dominant hand and both hand. The results of the study show that, performing simulated surgical tasks by both hands compared to dominant hand, increases mental workload which is evident by higher pupil size. Accordingly, to manage the mental-load problems of surgeons while performing complex tasks that require both hand usage simulation-based environments can be used. Consequently, collection of detailed information such as eye-data, can give several insights about the behaviors of the surgeons. Also, their required skills can be improved by development of simulation and training environments.