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Bilgisayar Mühendisliği Bölümü

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Citation Count: Ozyer, Sibel T. untranslated, Kayaalp, M., "A Collaborative and Content Based Event Recommendation System Integrated With Data Collection Scrapers and Services At A Social Networking Site", Proceedings of the 2009 International Conference On Advances in Social Network Analysis and Mining, Asonam 2009, pp. 113-118, (2009).
A Collaborative and Content Based Event Recommendation System Integrated With Data Collection Scrapers and Services At A Social Networking Site
(IEEE Computer Society, 2009) Kayaalp, Mehmet; Özyer, T.; Özyer, Sibel T.; 18980
There are many activities that people prefer/opt out attending and these events are announced for attracting people. An intelligent recommendation system can be used in a social networking site in order to recommend people according to content and collaboration assessment. This study is an effort to recommend events to users within a social networking site. It can be any networking environment. We have used social environment that has been designed as a facebook1 application. Our application has also been integrated with several web sites. System collects event data from several related web sites either by using web services or web scraping. It also permits users rating events they have attended or planned. Given the social network between people, system tries to recommend upcoming events to users. For this purpose a combination of content based and collaborative filtering has been used. We have also taken geographical location info and social concept of an event. © 2009 IEEE.
Citation Count: Al-Mihrab, Mohammed A.; Salim, Ali J.; Ali, Jawad K. (2020). "A Compact Multiband Printed Monopole Antenna With Hybrid Polarization Radiation for GPS, LTE, and Satellite Applications", IEEE Access, Vol. 8, pp. 110371-110380.
A Compact Multiband Printed Monopole Antenna With Hybrid Polarization Radiation for GPS, LTE, and Satellite Applications
(2020) Al-Mihrab, Mohammed A.; Salim, Ali J.; Ali, Jawad K.
A new compact printed monopole antenna is presented in this paper. An open-loop hexagonal radiator excited by a microstrip feed line, which is printed on top of the substrate, which is FR4 type, while on another side, a partial ground plane is fixed and embedded with two pairs of slits as well as a pair of rectangular strips. Triple operating bands with two different polarization types are obtained. The lower band has right-hand circular polarization (RHCP) characteristic, whereas the upper band has left-hand circular polarization (LHCP) characteristic means that a dual-band dual-sense circular polarization (CP). Concerning the middle band, a linear polarization (LP) has been gotten in this antenna. Numerical analysis and experimental validation of the proposed antenna structure have been performed, and results are demonstrated. The measured impedance bandwidths (IBWs) are 14.7% (1.478-1.714 GHz), 6.8% (2.54-2.72 GHz), and 13.1% (4.29-4.89 GHz), respectively. The measured 3-dB axial ratio bandwidths (ARBWs) are 6.2% (1.510-1.606 GHz), and 22.7% (4.035-5.07 GHz) for the lower and the upper band, respectively. So, it's suitable for covering modern wireless applications such as GPS (Global Positioning System), LTE (Long Term Evaluation), and Satellite.
Citation Count: Sezer, Omer Berat; Ozbayoglu, Murat; Dogdu, Erdogan (2017). A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters, Conference: Complex Adaptive Systems Conference on Engineering Cyber Physical Systems (CAS) Location: Chicago, IL Date: OCT 30-NOV 01, 2017, Complex Adaptive Systems Conference With Theme: Engineering Cyber Physical Systems, Cas, 114, 473-480.
A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters
(Elsevier Science BV, 2017) Sezer, Ömer Berat; Özbayoğlu, Murat; Doğdu, Erdoğan; 142876
In this study, we propose a stock trading system based on optimized technical analysis parameters for creating buy-sell points using genetic algorithms. The model is developed utilizing Apache Spark big data platform. The optimized parameters are then passed to a deep MLP neural network for buy-sell-hold predictions. Dow 30 stocks are chosen for model validation. Each Dow stock is trained separately using daily close prices between 1996-2016 and tested between 2007-2016. The results indicate that optimizing the technical indicator parameters not only enhances the stock trading performance but also provides a model that might be used as an alternative to Buy and Hold and other standard technical analysis models. (c) 2017 The Authors. Published by Elsevier B.V.
Citation Count: Yumuşak, Semih...et al (2018). "A Discovery and Analysis Engine for Semantic Web", Companıon Proceedıngs Of The World Wıde Web Conference 2018 , pp. 1497-1505.
A Discovery and Analysis Engine for Semantic Web
(2018) Yumuşak, Semih; Kamilaris, Andreas; Doğdu, Erdoğan; Kodaz, Halife; Uysal, Elif; Aras, Riza Emre
The Semantic Web promotes common data formats and exchange protocols on the web towards better interoperability among systems and machines. Although Semantic Web technologies are being used to semantically annotate data and resources for easier reuse, the ad hoc discovery of these data sources remains an open issue. Popular Semantic Web endpoint repositories such as SPARQLES, Linking Open Data Project (LOD Cloud), and LODStats do not include recently published datasets and are not updated frequently by the publishers. Hence, there is a need for a web-based dynamic search engine that discovers these endpoints and datasets at frequent intervals. To address this need, a novel web meta-crawling method is proposed for discovering Linked Data sources on the Web. We implemented the method in a prototype system named SPARQL Endpoints Discovery (SpEnD). In this paper, we describe the design and implementation of SpEnD, together with an analysis and evaluation of its operation, in comparison to the aforementioned static endpoint repositories in terms of time performance, availability, and size. Findings indicate that SpEnD outperforms existing Linked Data resource discovery methods.
Citation Count: Arslan, S. (2022). "A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data", PeerJ Computer Science, Vol.8.
A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data
(2022) Arslan, Serdar; 325411
For decades, time series forecasting had many applications in various industries such as weather, financial, healthcare, business, retail, and energy consumption forecasting. An accurate prediction in these applications is a very important and also difficult task because of high sampling rates leading to monthly, daily, or even hourly data. This high-frequency property of time series data results in complexity and seasonality. Moreover, the time series data can have irregular fluctuations caused by various factors. Thus, using a single model does not result in good accuracy results. In this study, we propose an efficient forecasting framework by hybridizing the recurrent neural network model with Facebook’s Prophet to improve the forecasting performance. Seasonal-trend decomposition based on the Loess (STL) algorithm is applied to the original time series and these decomposed components are used to train our recurrent neural network for reducing the impact of these irregular patterns on final predictions. Moreover, to preserve seasonality, the original time series data is modeled with Prophet, and the output of both sub-models are merged as final prediction values. In experiments, we compared our model with state-of-art methods for real-world energy consumption data of seven countries and the proposed hybrid method demonstrates competitive results to these state-of-art methods.
Citation Count: Yumuşak, Semih;...et.al. (2022). "A Novel Hypercube-based Approach to Overlay Design Algorithms on Topic Distribution Networks", Politeknik Dergisi, Vol.25, No.4, pp.1535-1552.
A Novel Hypercube-based Approach to Overlay Design Algorithms on Topic Distribution Networks
(2022) Yumuşak, Semih; Layazali, Sina; Öztoprak, Kasım; Hassanpour, Reza
Data communication in peer-to-peer (P2P) network requires a fine-grained optimization for memory and processing to lower the total energy consumption. When the concept of Publish/subscribe (Pub/Sub) systems were used as a communication tool in a P2P network, the network required additional optimization algorithms to reduce the complexity. The major difficulty for such networks was creating an overlay design algorithm (ODA) to define the communication patterns. Although some ODAs may perform worse on a high-scale, some may have better average/maximum node degrees. Based on the experimentation and previous works, this study designed an algorithm called the Hypercube-ODA, which reduces the average/maximum node degree for a topic connected Pub/Sub network. The Hypercube-ODA algorithm creates the overlay network by creating random cubes within the network and arranging the nodes with the cubes they belong to. In this paper, the details of the proposed Hypercube algorithm were presented and its performance was compared with the existing ODAs. Results from the experiments indicate that the proposed method outperforms other ODA methods in terms of lower average node degree (lowering the average node degree by up to 60%).
Citation Count: Çiftci, Efe; Sümer, E. (2022). "A novel steganography method for binary and color halftone images", PeerJ Computer Science, Vol.8.
A novel steganography method for binary and color halftone images
(2022) Çiftci, Efe; Sümer, Emre; 20150
Digital steganography is the science of establishing hidden communication on electronics; the aim is to transmit a secret message to a particular recipient using unsuspicious carriers such as digital images, documents, and audio files with the help of specific hiding methods. This article proposes a novel steganography method that can hide plaintext payloads on digital halftone images. The proposed method distributes the secret message over multiple output copies and scatters parts of the message randomly within each output copy for increased security. A payload extraction algorithm, where plain carrier is not required, is implemented and presented as well. Results gained from conducted objective and subjective tests prove that the proposed steganography method is secure and can hide large payloads.
Citation Count: Oǧul, Burçin Buket; Özdemir, S. (2022). "A Pairwise Deep Ranking Model for Relative Assessment of Parkinson's Disease Patients from Gait Signals", IEEE Access, Vol.10, pp.6676-6683.
A Pairwise Deep Ranking Model for Relative Assessment of Parkinson's Disease Patients from Gait Signals
(2022) Oǧul, Burçin Buket; Özdemir, Suat
Continuous monitoring of the symptoms is crucial to improve the quality of life for patients with Parkinson's Disease (PD). Thus, it is necessary to objectively assess the PD symptoms. Since manual assessment is subjective and prone to misinterpretation, computer-aided methods that use sensory measurements have recently been used to make objective PD assessment. Current methods follow an absolute assessment strategy, where the symptoms are classified into known categories or quantified with exact values. These methods are usually difficult to generalize and considered to be unreliable in practice. In this paper, we formulate the PD assessment problem as a relative assessment of one patient compared to another. For this assessment, we propose a new approach to the comparative analysis of gait signals obtained via foot-worn sensors. We introduce a novel pairwise deep-ranking model that is fed by data from a pair of patients, where the data is obtained from multiple ground reaction force sensors. The proposed model, called Ranking by Siamese Recurrent Network with Attention, takes two multivariate time-series as inputs and produces a probability of the first signal having a higher continuous attribute than the second one. In ten-fold cross-validation, the accuracy of pairwise ranking predictions can reach up to 82% with an AUROC of 0.89. The model outperforms the previous methods for PD monitoring when run in the same experimental setup. To the best of our knowledge, this is the first study that attempts to relatively assess PD patients using a pairwise ranking measure on sensory data. The model can serve as a complementary model to computer-aided prognosis tools by monitoring the progress of the patient during the applied treatment.
Citation Count: Yilmaz, M.; O’Connor, R.V.,"A Scrumban Integrated Gamification Approach to Guide Software Process İmprovement: A Turkish Case Study [Gamifikacijski Pristup S İntegriranom Scrumban Metodologijom U Poboljšanju Razvoja Softvera: Turska Analiza Slučaja]", Tehnicki Vjesnik, Vol. 23, No. 1, (2016).
A Scrumban Integrated Gamification Approach to Guide Software Process İmprovement: A Turkish Case Study [Gamifikacijski Pristup S İntegriranom Scrumban Metodologijom U Poboljšanju Razvoja Softvera: Turska Analiza Slučaja]
(Strojarski Facultet, 2016) Yılmaz, Murat; O'Connor, Rory V.
In recent years, there has been an increasing interest in tailoring agile development methodologies by combining different agile practices. The adoption of such a balancing approach requires a systematic customization of best practices among agile methodologies. This paper presents an empirical case study for adopting a hybrid Scrumban methodology with an integrated gamification approach, which was conducted in the context of a small-medium enterprise (SME). First, we conducted a focus group to better understand the potential inquiries that might have been useful to improve the development process. Secondly, we employed a cross-sectional survey approach to explore the company personnel’s opinions regarding the changes in the process. The survey data was collected from 30 practitioners who were working for the same project in a software development organization in a technology research centre. The descriptive statistics were calculated with paired sample t-tests being used to compare for integration process that contains three stages (i) initial stage, (ii) Scrumban stage, (iii) Scrumban with integrated Gamification stage. The preliminary results of this research support the idea that a set of game elements can be integrated with a hybrid software development methodology to enhance individual and organizational productivity.
Citation Count: Gulec, Ulas; Yilmaz, Murat, "A serious game for improving the decision making skills and knowledge levels of Turkish football referees according to the laws of the game", Vol. 5, (2016).
A serious game for improving the decision making skills and knowledge levels of Turkish football referees according to the laws of the game
(Springer, 2016) Güleç, Ulaş; Yılmaz, Murat; 47439
Digital game-based learning environments provide emerging opportunities to overcome learning barriers by combining newly developed technologies and traditional game design. This study proposes a quantitative research approach supported by expert validation interviews to designing a game-based learning framework. The goal is to improve the learning experience and decision-making skills of soccer referees in Turkey. A serious game was developed and tested on a group of referees (N = 54). The assessment results of these referees were compared with two sample t-test and the Wilcoxon signed-ranked test for both the experimental group and the control group. The findings of the current study confirmed that a game-based learning environment has greater merit over the paper-based alternatives.
Citation Count: Dündar, Naz...et asl. (2024). "A shallow 3D convolutional neural network for violence detection in videos", Egyptian Informatics Journal, Vol. 26.
A shallow 3D convolutional neural network for violence detection in videos
(2024) Dündar, Naz; Keçeli, Ali Seydi; Kaya, Aydın; Sever, Hayri; 366608; 11916
With the recent worldwide statistical rise in the amount of public violence, automated violence detection in surveillance cameras has become a matter of high importance. This work introduces an end-to-end, trainable 3D Convolutional Neural Network (3D CNN) for detecting violence in video footage. The proposed network is inherently capable of processing both spatial and temporal information, thereby obviating the need for additional models that would introduce higher computational requirements and complexity. This work has two main contributions: 1) developing a lightweight 3D CNN suitable for inference on edge devices as mobile systems, and 2) a comprehensive explanation of all components comprising a CNN model, thereby enhances model interpretability. Experiments were conducted to assess the performance of the proposed model using a consolidated dataset combining four benchmark datasets. The results of the experiments support the asserted contributions, which are discussed in detail.
Citation Count: Darvish, Hamid R. "A study of the Information Services on Turkish High Schools", World Conference On Educatıonal Technology Researches-2011, Vol. 28, (2011)
A Study of the Information Services On Turkish High Schools
(Elsevier Science BV, 2011) Darvish, Hamid R.
The World Wide Web went public in 1989. Since then, every organization has come to utilize web-based technologies for their various purposes. Educational institutions have implemented web technology in their contemporary curriculums. The aim of this study is to investigate five private schools in Ankara, Turkey and to unravel the impact of information technology (internet usage, information services) in their programs. The five high schools were: Ari College, TED Ankara College, Tevfik Fikret High School, METU (Middle East Technical University) College and Bilkent High School. We conducted a qualitative research on the selected high schools by observing and collecting data. Research was done from March-May 2009. We found out that internet services in high schools are not utilized to their full capacity. (C) 2011 Published by Elsevier Ltd.
Citation Count: Erdoğan, Özgün; Saran, Nurdan Ayşe (2021). "A survey on server-based electronic identification and signature schemes to improve eIDAS: with a new proposal for Turkey", Peerj Computer Science, Vol. 7.
A survey on server-based electronic identification and signature schemes to improve eIDAS: with a new proposal for Turkey
(2021) Erdoğan, Özgün; Saran, Nurdan Ayşe; 20868
The design, development, and implementation of e-Government applications aim to improve the quality of daily life and facilitate the mobility of citizens by reducing the constraints imposed by existing borders. This study examines previous research in the literature on electronic identification (eID) credentials technologies and the projects carried out in Europe. This study focuses especially on server-based e-signing methods. In the light of these reviews, the applicability of a server-based mobile electronic signature model without disrupting local initiatives has been examined as a case study. As an exemplary case, Turkey's eID structure is examined from a technical and legal perspective. When creating the proposed server-based eID model, it was especially inspired by Austria's server-based approach in use. In this process, the suitability of the existing structure with the server-based e-signing method was examined. In addition, some suggestions were made to eliminate the problems that may prevent the use of the proposed server-based e-signing method. This study revealed that a server-based electronic signature approach would develop a more user-friendly and flexible solution in identity management. It was concluded that using a server-based signature approach would help achieve international standards for cross-border online identification methods.
Citation Count: Özcan, Eda...et al (2021). "A user task design notation for improved software design", Peerj Computer Science.
A user task design notation for improved software design
(2021) Özcan, Eda; Topallı, Damla; Tokdemir, Gül; Çağıltay, Nergiz Ercil; 17411
System design is recognized as one of the most critical components of a software system that bridges system requirements and coding. System design also has a significant impact on testing and maintenance activities, and on further improvements during the lifespan of the software system. Software design should reflect all necessary components of the requirements in a clear and understandable manner by all stakeholders of the software system. To distinguish system elements, separation of concerns in software design is suggested. In this respect, identification of the user tasks, i.e., the tasks that need to be performed by the user, is not currently reflected explicitly in system design documents. Our main assumption in this study is that software quality can be improved significantly by clearly identifying the user tasks from those that need to be performed by the computer system itself. Additionally, what we propose has the potential to better reflect the user requirements and main objectives of the system on the software design and thereby to improve software quality. The main aim of this study is to introduce a novel notation for software developers in the frame of UML Activity Diagram (UML-AD) that enables designers to identify the user tasks and define them separately from the system tasks. For this purpose, an extension of UML-AD, named UML-ADE (UML-Activity Diagram Extended) was proposed. Afterwards, it was implemented in a serious game case for which the specification of user tasks is extremely important. Finally, its effectiveness was analyzed and compared to UML-AD experimentally with 72 participants. The defect detection performance of the participants on both diagrams with two real-life serious game scenarios was evaluated. Results show a higher level of understandability for those using UML-ADE, which in turn may indicate a better design and higher software quality. The results encourage researchers to develop specific design representations dedicated to task design to improve system quality and to conduct further evaluations of the impact of these design on each of the above mentioned potential benefits for the software systems.
Citation Count: Tasel, Serdar F...et al., "A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria", Journal of Structural Biology, Vol. 194, No. 3, pp. 253-271, (2016).
A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria
(Academic Press INC Elsevier Science, 2016) Taşel, Faris Serdar; Mumcuoğlu, Erkan U.; Hassanpour, Reza; Perkins, Guy
Recent studies reveal that mitochondria take substantial responsibility in cellular functions that are closely related to aging diseases caused by degeneration of neurons. These studies emphasize that the membrane and crista morphology of a mitochondrion should receive attention in order to investigate the link between mitochondria] function and its physical structure. Electron microscope tomography (EMT) allows analysis of the inner structures of mitochondria by providing highly detailed visual data from large volumes. Computerized segmentation of mitochondria with minimum manual effort is essential to accelerate the study of mitochondrial structure/function relationships. In this work, we improved and extended our previous attempts to detect and segment mitochondria from transmission electron microcopy (TEM) images. A parabolic arc model was utilized to extract membrane structures. Then, curve energy based active contours were employed to obtain roughly outlined candidate mitochondrial regions. Finally, a validation process was applied to obtain the final segmentation data. 3D extension of the algorithm is also presented in this paper. Our method achieved an average F-score performance of 0.84. Average Dice Similarity Coefficient and boundary error were measured as 0.87 and 14 nm respectively. (C) 2016 Elsevier Inc. All rights reserved.
Citation Count: Sezer, O.B.; Ozbayoglu, A.M.; Dogdu, E., "An Artificial Neural Network-Based Stock Trading System Using Technical Analysis And Big Data Framework",Proceedings of the Southeast Conference, Acmse 2017, pp. 223-226, (2017).
An Artificial Neural Network-Based Stock Trading System Using Technical Analysis And Big Data Framework
(Association for Computing Machinery, 2017) Sezer, Ömer Berat; Özbayoğlu, Ahmet Murat; Doğdu, Erdoğan
In this paper, a neural network-based stock price prediction and trading system using technical analysis indicators is presented. The model developed first converts the financial time series data into a series of buy-sell-hold trigger signals using the most commonly preferred technical analysis indicators. Then, a Multilayer Perceptron (MLP) artificial neural network (ANN) model is trained in the learning stage on the daily stock prices between 1997 and 2007 for all of the Dow30 stocks. Apache Spark big data framework is used in the training stage. The trained model is then tested with data from 2007 to 2017. The results indicate that by choosing the most appropriate technical indicators, the neural net- work model can achieve comparable results against the Buy and Hold strategy in most of the cases. Furthermore, fine tuning the technical indicators and/or optimization strategy can enhance the overall trading performance.
Citation Count: Yilmaz, Murat...et al. (2017). An examination of personality traits and how they impact on software development teams, Information And Software Technology, 86, 101-122.
An examination of personality traits and how they impact on software development teams
(Elsevier Science BV, 2017) Yılmaz, Murat; O'Connor, Rory V.; Colomo-Palacios, Ricardo; Clarke, Paul; 55248
Context Research has shown that a significant number of software projects fail due to social issues such as team or personality conflicts. However, only a limited number of empirical studies have been undertaken to understand the impact of individuals' personalities on software team configurations. These studies suffer from an important limitation as they lack a systematic and rigorous method to relate personality traits of software practitioners and software team structures. Objective: Based on an interactive personality profiling approach, the goal of this study is to reveal the personality traits of software practitioners with an aim to explore effective software team structures. Method: To explore the importance of individuals' personalities on software teams, we employed a two-step empirical approach. Firstly, to assess the personality traits of software practitioners, we developed a context-specific survey instrument, which was conducted on 216 participants from a middle-sized soft ware company. Secondly, we propose a novel team personality illustration method to visualize team structures. Results: Study results indicated that effective team structures support teams with higher emotional stability, agreeableness, extroversion, and conscientiousness personality traits. Conclusion: Furthermore, empirical results of the current study show that extroversion trait was more predominant than previously suggested in the literature, which was especially more observable among agile software development teams. (C) 2017 Elsevier B.V. All rights reserved.
Citation Count: Kılınç, İsmail; Yılmaz, M. (2018). "An Exploratory Study to Assess Digital Map Zoom/Pan/Rotate Methods with HoloLens", Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Vol.22, No.2, pp.458-463.
An Exploratory Study to Assess Digital Map Zoom/Pan/Rotate Methods with HoloLens
(2018) Kılınç, İsmail; Yılmaz, Murat
Geographical map display plays an important part of a GIS (GeographicalInformation System). The usability of a map display is certainly depends on how easilyuser navigates through spatial data and selects features on it. Currently, desktop computerbased GIS applications uses mouse movements, buttons and scroll for a set of functionssuch as zoom, pan and rotate. However currently Hololens supports only gaze, air tapgesture and voice commands as an input. Although the functionality looks simple, it ischallenging to find optimal solution by using input devices for those functions even whilecreating in a desktop application. This study aims to assess an optimal way to enable thesefunctions on hologram maps by investigating its validity and usability.
Citation Count: Clarke, Paul...et al., "An Investigation of Software Development Process Terminology", 16th International Conference on Software Process Improvement and Capability Determination (SPICE), Vol. 609, pp. 351-361, (2016).
An Investigation of Software Development Process Terminology
(2016) Mesquida, Antoni-Lluis; Ekert, Damjan; Ekstrom, J. J.; Gornostaja, Tatjana; Jovanovic, Milos; Johansen, Jorn; Mas, Antonia; Messnarz, Richard; Villar, Blanca Najera; O'Connor, Alexander; O'Connor, Rory V.; Reiner, Michael; Sauberer, Gabriele; Schmitz, Klaus-Dirk; Yılmaz, Murat; Clarke, Paul
The practice of software development has evolved considerably in recent decades, with new programming technologies, the affordability of hardware, pervasive internet access and mobile computing all contributing to the emergence of new software development processes. The newer process initiatives, which include those which are sometimes referred to as agile or lean methods, have brought with them new terms, which sometimes reflect the introduction of novel concepts. Other times, new terms correspond to long established concepts that have been repackaged. The net position is that we have a proliferation of language and term usage in the software development process domain, a problem which has implications for assessors and assessment frameworks, and for the broader community. In this paper, we explore this problem, finding that it is worthy of further research. Plus, we identify a technique suited to addressing this concern: the establishment of a canonical software process ontological model.
Citation Count: Naji, Hayder Fans; Maras, H. Hakan, "Analysing Iraqi Railways Network by Applying Specific Criteria Using the GIS Techniques", Baghdad Science Journal, Vol. 16, No. 1, pp. 121-129, (2019).
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.