Bilgisayar Mühendisliği Bölümü

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Citation - WoS: 0
Citation - Scopus: 0
A case study on web-based information system evaluation
(Acad Conferences Ltd, 2014) Tokdemir, Gul; Tokdemir, Gül; Bilgen, Semih; Ercil, Yavuz; 17411; Bilgisayar Mühendisliği
A new framework is proposed to assess web-based information systems (WISs) which is domain-independent, that is, can be applied for profit seeking as well as service oriented or non-profit seeking organizations. Assessment starts from an identification of the critical success factors (CSF) that outline organizational strategies, and proceeds to determine the measures of three categories of relationships: User-WIS, Other systems-WIS, Organization-WIS. These measures and CSF's are evaluated collectively to arrive at an effectiveness measure. A case study illustrating the applicability of the assessment framework in the e-business domain is presented.
Citation - Scopus: 33
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, M.; Ozyer, T.; Ozyer, S.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 - Scopus: 0
A Data Fusion Approach In Protein Homology Detection
(2008) Oğul, Hasan; Polatkan, A.C.; Oǧul, H.; Sever, Hayri; Sever, H.; 11916; Bilgisayar Mühendisliği
The discriminative framework for protein remote homology detection based on support vector machines (SVMs) is reconstructed by the fusion of sequence based features. In this respect, n-peptide compositions are partitioned and fed into separate SVMs. The SVM outputs are evaluated with different techniques and tested to discern their ability for SCOP protein super family classification on a common benchmarking set. It reveals that the fusion approach leads to an improvement in prediction accuracy with a remarkable gain on computer memory usage. © 2008 IEEE.
Citation - WoS: 0
Citation - Scopus: 2
A Discovery and Analysis Engine for Semantic Web
(Assoc Computing Machinery, 2018) Yumusak, Semih; Doğdu, Erdoğan; Kamilaris, Andreas; Dogdu, Erdogan; Kodaz, Halife; Uysal, Elif; Aras, Riza Emre; Bilgisayar Mühendisliği
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 - WoS: 0
Citation - Scopus: 4
A drift-reduced scheme for hierarchical wavelet coding scalable video transmissions
(Ieee, 2009) Choupani, Roya; Wong, Stephan; Tolun, Mehmet R.
Scalable video coding allows for the capability of (partially) decoding a video bitstream when faced with communication deficiencies such as low handwidth or loss of data resulting in lower video quality. As the encoding is usually based on perfectly reconstructed frames, such deficiencies result in differently decoded frames at the decoder than the ones used in the encoder and, therefore, leading to errors being accumulated in the decoder. This is commonly referred to as the drift error. Drift-free scalable video coding methods also suffer from the low performance problem as they do not combine the residue encoding scheme of the current standards such as MPEG-4 and H.264 with scalability characteristics. We propose a scalable video coding method which is based on the motion compensation and residue encoding methods found in current video standards combined with the scalability property of discrete wavelet transform. Our proposed method aims to reduce the drift error while preserving the compression efficiency. Our results show that the drift error has been greatly reduced when a hierarchical structure for frame encoding is introduced.
Citation - Scopus: 1
A Knowledge Visualization Model for Evaluating Internet News Agencies On Conflicting News
(2011) Medeni, I.T.; Medeni, İhsan Tolga; Peker, S.; Uyar, M.E.; 181215; Bilgisayar Mühendisliği
With the advent of the Internet, the news agencies have published news on their websites for the internet readers. This improvement enables Internet readers to access news easily and also to gain information and knowledge in real time manner. Since there are many online news agencies and online newspapers, readers generally have difficulty to decide which newspaper or agency provides the most reliable news. The reliability can be defined as using consistent and proper source of news especially on conflicting news but this increases news' source complexity. As a knowledge management technique, knowledge visualization is one of the ways for readers to decrease this complexity level. In this study, we propose a knowledge visualization model to identify success rates of the online news agencies and online newspapers regarding how consistent they are with the concluded actual news content. This model will be a baseline to indicate knowledge management capabilities of the agencies based on conflicted news categories. © 2011 MIPRO.
Citation - WoS: 0
A Novel Hypercube-based Approach to Overlay Design Algorithms on Topic Distribution Networks
(Gazi Univ, 2022) Yumusak, Semih; Hassanpour, Reza; Layazali, Sina; Oztoprak, Kasim; Hassanpour, Reza; Yazılım Mühendisliği
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 - WoS: 9
Citation - Scopus: 15
A serious game for improving the decision making skills and knowledge levels of Turkish football referees according to the laws of the game
(Springer international Publishing Ag, 2016) Güleç, Ulaş; Gulec, Ulas; Yilmaz, Murat; Yılmaz, Murat; 47439; Bilgisayar Mühendisliği; Yazılım Mühendisliği
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 - Scopus: 24
A Serious Game for Speech Disorder Children Therapy
(2012) Tokdemir, Gül; Cagatay, M.; Ege, P.; Çağıltay, Nergiz; Tokdemir, G.; Cagiltay, N.E.; 17411; Bilgisayar Mühendisliği; Yazılım Mühendisliği
Today meaning of games is much more serious than just considering them as an entertainment and free-time activity. Games have begun to be used in many different areas such as education, healthcare, military, corporate management and public policy for different purposes. Several benefits of serious games have been reported in the literature. Studies also show that with a combination of entertainment and education (edutainment) several benefits could be achieved in the rehabilitation process of the disordered individuals. This study reports the advantages of 3D game environments for speech and language therapy of children and benefits of making the treatment process accessible from anywhere and anytime are demonstrated. © 2012 IEEE.
Citation - WoS: 0
Citation - Scopus: 0
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 - Scopus: 4
Abstract Conceptual Database Model Approach
(2013) Çağıltay, Nergiz; Çaĝiltay, N.E.; Topalli, D.; Tokdemir, Gül; Aykaç, Y.E.; Tokdemir, G.; 17411; Yazılım Mühendisliği; Bilgisayar Mühendisliği
One of the main objectives of the software engineers is to provide software related solutions for social problems and to increase the availability of social welfare. In that sense, the quality of the software is directly related to address the users' needs and their level of satisfaction. To reflect user requirements to the software processes, the correct design of the database model provides a critical stage during software development. Database design is a fundamental tool for modeling all the requirements related to users' data. The possible faulty conditions in database design have adverse effects on all of the software development processes. The possible faulty conditions can also cause continuous changes in the software and the desired functionality of the targeted system which may result in user dissatisfaction. In this context, reflecting the user requirements accurately in the database model and understanding of the database model correctly by every person involved in the software development process is the factor that directly affects the success of software systems' development. In this study, a two-stage conceptual data modeling approach is proposed to reduce the level of complexity, to improve the understandability of database models and to improve the quality of the software. This study first describes the proposed two-stage conceptual data modeling. Than the proposed method's impact on software engineers' comprehension is also investigated and the results are compared with the degree of complexity of the related conceptual data models. Results of this study show that, the proposed two-stage conceptual modeling approach improves the understanding levels of software engineers and eliminated possible defects in this stage. © 2013 The Science and Information Organization.
Citation - WoS: 0
Citation - Scopus: 1
Adaptive Embedded Zero Tree For Scalable Video Coding
(int Assoc Engineers-iaeng, 2011) Choupani, Roya; Wong, Stephan; Tolun, Mehmet R.; 1863
Video streaming over the Internet has gained popularity during recent years mainly due to the revival of video-conferencing and video-telephony applications and the proliferation of (video) content providers. However, the heterogeneous, dynamic, and best-effort nature of the Internet cannot always guarantee a certain bandwidth for an application utilizing the Internet. Scalability has been introduced to deal with such issues (up to a certain point) by adapting the video quality with the available bandwidth. In addition, wavelet based scalability combined with representation methods such as embedded zero trees (EZWs) provides the possibility of reconstructing the video even when only the initial part of the streams have been received. EZW prioritizes the wavelet coefficients based on their energy content. Our experiments however, indicate that giving more priority to low frequency content improves the video quality at a specific bit rate. In this paper, we propose a method to improve on the compression rate of the EZW by prioritizing the coefficients by combining each frequency sub-band with its energy content. Initial experimental show that the first two layers of the generated EZW are about 22.6% more concise.
Citation - WoS: 10
Citation - Scopus: 12
Adopting Virtual Reality as a Medium for Software Development Process Education
(Assoc Computing Machinery, 2018) Güleç, Ulaş; Gulec, Ulas; Yilmaz, Murat; Yılmaz, Murat; Isler, Veysi; O'Connor, Rory, V; Clarke, Paul; 47439; Bilgisayar Mühendisliği; Yazılım Mühendisliği
Software development is a complex process of collaborative endeavour which requires hands-on experience starting from requirement analysis through to software testing and ultimately demands continuous maintenance so as to mitigate risks and uncertainty. Therefore, training experienced software practitioners is a challenging task. To address this gap, we propose an interactive virtual reality training environment for software practitioners to gain virtual experience based on the tasks of software development. The goal is to transport participants to a virtual software development organization where they experience simulated development process problems and conflicting situations, where they will interact virtually with distinctive personalities, roles and characters borrowed from real software development organizations. This PhD in progress paper investigates the literature and proposes a novel approach where participants can acquire important new process knowledge. Our preliminary observations suggest that a complementary VR-based training tool is likely to improve the experience of novice software developers and ultimately it has a great potential for training activities in software development organizations.
Citation - WoS: 2
Citation - Scopus: 2
ADS-B Attack Classification using Machine Learning Techniques
(Ieee, 2021) Kacem, Thabet; Kaya, Aydin; Keceli, Ali Seydi; Catal, Cagatay; Wijsekera, Duminda; Costa, Paulo; 35304
Automatic Dependent Surveillance Broadcast (ADS-B) is one of the most prominent protocols in Air Traffic Control (ATC). Its key advantages derive from using GPS as a location provider, resulting in better location accuracy while offering substantially lower deployment and operational costs when compared to traditional radar technologies. ADS-B not only can enhance radar coverage but also is a standalone solution to areas without radar coverage. Despite these advantages, a wider adoption of the technology is limited due to security vulnerabilities, which are rooted in the protocol's open broadcast of clear-text messages. In spite of the seriousness of such concerns, very few researchers attempted to propose viable approaches to address such vulnerabilities. In addition to the importance of detecting ADS-B attacks, classifying these attacks is as important since it will enable the security experts and ATC controllers to better understand the attack vector thus enhancing the future protection mechanisms. Unfortunately, there have been very little research on automatically classifying ADS-B attacks. Even the few approaches that attempted to do so considered just two classification categories, i.e. malicious message vs not malicious message. In this paper, we propose a new module to our ADS-Bsec framework capable of classifying ADS-B attacks using advanced machine learning techniques including Support Vector Machines (SVM), Decision Tree, and Random Forest (RF). Our module has the advantage that it adopts a multi-class classification approach based on the nature of the ADS-B attacks not just the traditional 2-category classifiers. To illustrate and evaluate our ideas, we designed several experiments using a flight dataset from Lisbon to Paris that includes ADS-B attacks from three categories. Our experimental results demonstrated that machine learning-based models provide high performance in terms of accuracy, sensitivity, and specificity metrics.
Citation - WoS: 29
Citation - Scopus: 50
An Artificial Neural Network-Based Stock Trading System Using Technical Analysis And Big Data Framework
(Assoc Computing Machinery, 2017) Sezer, Omer Berat; Doğdu, Erdoğan; Ozbayoglu, A. Murat; Dogdu, Erdogan; Bilgisayar Mühendisliği
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 network 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 - WoS: 5
Citation - Scopus: 5
An evaluation of the relationship between physical/mechanical properties and mineralogy of landscape rocks as determined by hyperspectral reflectance
(Springer Heidelberg, 2016) Maras, Erdem Emin; Maraş, Hadi Hakan; Caniberk, Mustafa; Odabas, Mehmet Serhat; Degerli, Burcu; Maras, Suleyman Sirri; Maras, Hadi Hakan; 34410; Bilgisayar Mühendisliği
We investigated the relationships between mineral content and the physical and mechanical properties of landscape rock using a non-destructive remote sensing method applied in the laboratory. Using this technique, the spectral properties of the landscape rock could be collected at different wavelengths without harming the samples. Differences in spectral reflectance were compared with the physical and mechanical properties of the stone. Significant correlations were observed between reflectance values and the rocks' mechanical and physical properties, with correlation coefficients of 95 to 99 %. However, establishing a correlation between two variables is not a sufficient condition to establish a causal relationship. Mineral densities and mineral content are characteristics used for the classification of landscape rock. We have concluded that although spectral signatures from landscape rock can be used for predicting which stones might have similar features when comparing two batches of stone, the high correlations we discovered cannot confirm a cause and effect relationship that would allow for the prediction of a rock's physical and mechanical properties. Although this conclusion is disappointing, the mineral content and the significant correlations discovered by hyperspectral reflectance scanning can be used as supplementary information when comparing two samples of landscape rock.
Citation - WoS: 23
Citation - Scopus: 24
An investigation of hydrogen bonded neutral B4Hn (n=1-11) and anionic B4H11(-1) clusters: Density functional study
(Elsevier Science Bv, 2007) Boyukata, Mustafa; Özdoğan, Cem; Ozdogan, Cem; Guvenc, Ziya B.; 120207; Ortak Dersler Bölümü
In this study, detailed analysis of the structural stability of hydrogen bonded four-atom boron clusters within the framework of density functional theory (DFT) is presented. Effects of the number of hydrogen atoms on the structural stability of 134, binding energy of the clusters, and also on the boron-hydrogen binding energy are investigated. Attention is also paid to the determination of energetically the most stable geometries of B4Hn (n = 1-11) boron hydrides, and to their isomers. The lower-lying electronic states of the B4Hn structures are investigated. In addition natural electron configurations of the most stable clusters and charge transfer between the atoms in the cluster are also analyzed. Furthermore, the stability of anionic form of B4H11(-1) cluster is examined. (c) 2006 Elsevier B.V. All rights reserved.
Citation - Scopus: 0
An Rsvp Model for Opnet Simulator With An Integrated Qos Architecture
(Caltek s.r.l., 2009) Özyer, S.T.; Hassanpour, Reza; Hassanpour, R.; 18980; Yazılım Mühendisliği
Resource Reservation Protocol (RSVP) allows Internet real-time applications to request a specific end-to-end Quality of service (QoS) for data stream before they start transmitting data. In this paper firstly an overview of RSVP is presented. After that the different quality of services available and the relation between QoS and RSVP have been explained. The fundamentals of RSVP as a protocol is discussed. The performance issues and benchmarking for planned portion architecture at the department of Computer Engineering, Çankaya University has been given next. The experimental results and discussions conclude this paper. In this paper, OPNET network simulation tool has been used. Under given architecture and protocol, performance of quality of service implications has been carried out.
Citation - WoS: 0
Citation - Scopus: 0
Analysis of Neurooncological Data to Predict Success of operation Through Classification
(Assoc Computing Machinery, 2016) Tokdemir, Gül; Bagherzadi, Negin; Borcek, Alp Ozgun; Çağıltay, Nergiz; Tokdemir, Gul; Cagiltay, Nergiz; Maras, H. Hakan; 17411; Bilgisayar Mühendisliği; Yazılım Mühendisliği
Data mining algorithms have been applied in various fields of medicine to get insights about diagnosis and treatment of certain diseases. This gives rise to more research on personalized medicine as patient data can be utilized to predict outcomes of certain treatment procedures. Accordingly, this study aims to create a model to provide decision support for surgeons in Neurooncology surgery. For this purpose, we have analyzed clinical pathology records of Neurooncology patients through various classification algorithms, namely Support Vector Machine, Multi Perceptron and Naive Bayes methods, and compared their performances with the aim of predicting surgery complication. A large number of factors have been considered to classify and predict percentage of patient's complication in surgery. Some of the factors found to be predictive were age, sex, clinical presentation, previous surgery type etc. For classification models built up using Support Vector Machine, Naive Bayes and Multi Perceptron, Classification trials for Support Vector Machine have shown %77.47 generalization accuracy, which was established by 5-fold cross-validation.
Citation - Scopus: 2
Application of Artificial Intelligence in Early–Stage Diagnosis of Sepsis
(Association for Computing Machinery, 2022) Par, O.E.; Sever, Hayri; Sezer, E.A.; Sever, H.; 11916; Bilgisayar Mühendisliği
Patient care is a critical task, which requires a lot of effort. Medical practitioners face many challenges, especially during diagnosing different diseases. Sepsis is one of the riskiest diseases, which proves to be lethal for Intensive Care Unit (ICU) patients. World Health Organization (WHO) has declared it a major cause of death worldwide. Early-stage diagnosis of sepsis can help in terminating it in the start. But unfortunately, medical practitioners encounter hitches in the early-stage diagnosis of sepsis. The study used SOFA (Sequential Organ Failure Assessment) for measuring the severity of sepsis in patients. The study employs artificial intelligence techniques such as Multilayer Perceptron (MLP) and Random Forest (RF) to diagnose early-stage of sepsis. The study compared the performance of MLP (connected and non-connected) and Random Forest (connected and non-connected) algorithms. The results indicate that for both of the algorithms, the connected method yielded better results than the non-connected method. Further, it was found that RF both connected and non-connected algorithms yielded better results than MLP algorithms and the Random Forest connected algorithm yielded highly accurate results for diagnosing early-stage sepsis in the 3rd hour. © 2022 ACM.

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