Bilgisayar Mühendisliği Bölümü

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An Experimental Study on Decomposition: Process First or Structure First?
(2019) Tokdemir, Gül; Suloğlu, Selma; Kaya, M. Çağrı; Karamanlıoğlu, Alper; Tokdemir, Gül; Doğru, Ali H.; 17411; Bilgisayar Mühendisliği
This article explores the answer to the question of considering the process or the structure dimensions earlier, in software development where decomposition is a preferred technique for top-down model construction. In this research, an experimental study was conducted to observe which software modeling practice is more convenient: process or structural modeling, for the beginning. The study was conducted in different courses that include software modeling where students work within groups to model a system with predefined requirements. The students used Business Process Modeling Notation and Component-Oriented Software Engineering Modeling Language modeling tools. Observations based on the results are analyzed and discussed. The results seem to prioritize the process dimension.
An Exploratory Study to Assess Digital Map Zoom/Pan/Rotate Methods with HoloLens
(2018) Yılmaz, Murat; Yılmaz, Murat; Yazılım Mühendisliği
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.
An ISO/IEC 12207 Perspective on Software Development Process Adaptation
(2018) Yılmaz, Murat; O’Connor, Rory V.; Yılmaz, Murat; Clarke, Paul; Yazılım Mühendisliği
In their earlier work, the authors had a sustained engagement with situational factors affecting software development, particularly how these factors affect the software development process. Part of this previous engagement involved the development of a situational factors reference framework. As part of an ongoing industrial engagement, the authors are currently examining situational factors and software development processes in a series of case studies. This latest case study is concerned with a small start-up organization. They start by identifying the software development process in this organization. Thereafter, the authors examine the situational context of the company, leading to an analysis of the relationship between the process and the situational context. Their general findings are consistent with their previous related work, supporting the case that a software development process is dependent on the organizational context, perhaps in a highly complex manner. In this particular case study, the authors also find that the role of organizational learning and process adaption is considered to be central to organizational survival.
Analysis of transfer learning for deep neural network based plant classification models
(2019) Kaya, Aydın; Keçeli, Ali Seydi; Çatal, Çağatay; Yalıç, Hamdi Yalın; Temuçin, Hüseyin; Tekinerdoğan, Bedir; 35304; 36190; 182651
Plant species classification is crucial for biodiversity protection and conservation. Manual classification is time-consuming, expensive, and requires experienced experts who are often limited available. To cope with these issues, various machine learning algorithms have been proposed to support the automated classification of plant species. Among these machine learning algorithms, Deep Neural Networks (DNNs) have been applied to different data sets. DNNs have been however often applied in isolation and no effort has been made to reuse and transfer the knowledge of different applications of DNNs. Transfer learning in the context of machine learning implies the usage of the results of multiple applications of DNNs. In this article, the results of the effect of four different transfer learning models for deep neural network-based plant classification is investigated on four public datasets. Our experimental study demonstrates that transfer learning can provide important benefits for automated plant identification and can improve low-performance plant classification models.
Approaches on the selection of web cameras and calibration targets for stereo vision
(IEEE, 2006) Eren, Hüseyin; Çelik, Ümit; Poyraz, Mustafa
In this paper, it is studied on the calibration by using specified web cameras. The performance of 3D computer vision depends on the accuracy of camera parameters. Therefore, camera calibration is very crucial in stereo vision. In this study, the options and selection of the target object that is used by the process of camera calibration are reviewed and evaluated some results obtained by web cameras. Webcams' costs are low relatively to the other digital consumer cameras but cannot be acquired a high resolution image.
Artırılmış Gerçeklik Tabanlı Sürekli İşe Alıştırma Sistemi
(2018) Yılmaz, Murat; Öge, İrem; Orkun, Bora; Yılmaz, Murat; Tüzün, Eray; Yazılım Mühendisliği
İşe yeni başlayan çalışanların verimli ve etkili bir işe adaptasyon süreci geçirmesi ilerleyen zamanlarda iş yerindeki çalışma performansı açısından oldukça önemli bir faktördür. Bu nedenle işe alıştırma süreci hem şirket hem de çalışanlar açısından iyi değerlendirilmesi gereken bir süreçtir. İşe alıştırma sürecinde ve sonrasında sanal ögelerin ve gerçek zamanlı ofis ortamının kullanılmasının bu süreci daha verimli hale getireceği düşüncesinden yola çıkarak, bildiride bahsedilen bu projede, işe alıştırma süreci, artırılmış gerçeklik (AG) teknolojisinden faydalanılarak yönetilmektedir. Artırılmış gerçeklik teknolojisi sayesinde etkileşimli bir biçimde yönlendirilen yazılım mühendislerinin iş arkadaşları ve çalışılan projelerle olan adaptasyon sürecini hızlandırmak, projenin başlıca amaçlarından biridir
Behavior Analysis Of Routing Protocols For A Health Decision Support System
(2014) Alyeksyeyenkov, Yuriy; Abdullah, Mohammed Najm; Tareq Nafea, Mustafa; Bilgisayar Mühendisliği
Mobile ad-hoc network (MANET) is an infrastructure less network, that is a collection of mobile devices connected together without centralized infrastructure that can be configured at any time and any where, it gives the network dynamic topology. The most important thing in MANETs is a routing protocol. MANETs have a three major routing protocols proactive, reactive and hybrid. In this work, the performance of reactive routing protocol Ad hoc on demand Distance Vector (AODV) and proactive routing protocol Destination Sequenced Distance Vector (DSDV) for a health decision support system (HDSS) were evaluated. The major goal of this work is to analyze the performance of well-known MANETs routing protocol in mobility case under low, medium and high density scenario. Hence it becomes important to study the performance of these routing protocols. The performance is analyzed with respect to Average End-to-End Delay, drop packets, Packet Delivery ratio (PDR) and Throughput. Simulation results verify that AODV gives better performance as compared to DSDV.
Büyük Veri Mahremiyeti ve Güvenliği
(Grafiker Yayınları, 2017) Saran, Ayşe Nurdan; 20868; Bilgisayar Mühendisliği
Bilim geliştikçe teknolojiler gelişmekte ve yeni teknolojilerde bilimin daha da gelişmesine ve bilinmezleri daha iyi anlamamıza, yeni çalışmalar yapmamıza en önemlisi çevremizi ve dünyamızı daha iyi anlamamızı kolaylaştırmaktadır. Son yıllarda “büyük veri”, “veri bilimi”, “açık veri” “büyük veri analitiği”, “bilgi ekonomisi” gibi başlıklar ülkemizde de pek çok etkinlikte tartışılmakta, çözümler geliştirilmeye çalışılmakta ve iyi örnekler oluşturulmaya çalışılmaktadır. Bu kitabın ülkemizde açık veri ve büyük veri analitiği, güvenliği ve mahremiyetinin gelişmesine katkılar sağlaması beklenmektedir. Verilerin günümüzün altın rezervleri olduğunun bilinciyle çalışmalar yapılmalıdır.
Cassandra ve MongoDB NoSQL Veri Tabanlarının Karşılaştırmalı Güvenlik Analizi
(2019) Saran, Murat; Saran, Nurdan; 17753; Bilgisayar Mühendisliği
In this study, we analyze the security of two NoSQL databases, MongoDB 3.6.3 and Cassandra 3.11.1 in a multi-node configuration in two steps. The first step is a comparative study of both databases’ security features according to ten selected criteria from the literature. The second step is analyzing data encryption overhead using the Yahoo Cloud Serving Benchmark tool. This study will help decision-makers and researchers to realize the most crucial security features concerning NoSQL databases as well as to be able to analyze the NoSQL databases regarding the security features. Our security comparison results show that both databases have noteworthy security features. However, Cassandra takes the lead as it supports more security criteria. Besides, the encryption/decryption performance of the MongoDB business version is 53% faster than the Cassandra business version, and the average amount of data that the MongoDB business version can process per minute is 45% higher than the Cassandra business version. This result shows that it is more appropriate to use MongoDB in environments where encryption is required.
Clustering Analysis for Vasculitic Diseases
(Springer-Verlag Berlin, 2010) Yıldırım, Pınar; Çeken, Çınar; Çeken, Kağan; Tolun, Mehmet R.; 1863
We introduce knowledge discovery for vasculitic diseases in this paper. Vasculitic diseases affect some organs and tissues and diagnosing can be quite difficult. Biomedical literature can contain hidden and useful knowledge for biomedical research and we develop a study based on co-occurrence analysis by using the articles in MEDLINE which is a widely used database. The mostly seen vasculitic diseases are selected to explore hidden patterns. We select PolySearch system as a web based biomedical text mining tool to find organs and tissues in the articles and create two separate datasets with their frequencies for each disease. After forming these datasets, we apply hierarchical clustering analysis to find similarities between the diseases. Clustering analysis reveals some similarities between diseases. We think that the results of clustered diseases positively affect on the medical research of vasculitic diseases especially during the diagnosis and certain similarities can provide different views to medical specialists.
Complexity metrics as predictors of maintainability and ıntegrability of software components
(Çankaya Üniversitesi, 2006) Salman, Nael; Bilgisayar Mühendisliği
The work presented in this paper introduces a set of metrics for component oriented software systems. The work focuses mainly on the complexity that results mainly from factors related to system structure and connectivity. Also, a new set of properties that a component-oriented complexity metric must possess are defined. The metrics have been evaluated using the properties defined in this paper. A case study has been conducted to detect the power of complexity metrics in predicting integration and maintenance efforts. The results of the study revealed that component oriented complexity metrics can be of great value in predicting both integration and maintenance efforts.
Contribution of Intelligent Repeat Engine in Mobile Learning for Enhancing Students’ Learning in Industrial Engineering Education
(1) Saran, Murat; Güleç, Ulaş; 17753; Bilgisayar Mühendisliği
Covariance Features for Trajectory Analysis
(Kaunas Univ Technology, 2018) Karadeniz, Talha; Maraş, Hadi Hakan; 304886; 34410; Yazılım Mühendisliği; Bilgisayar Mühendisliği
In this work, it is demonstrated that covariance estimator methods can be used for trajectory classification. It is shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. Compared to Dynamic Time Warping, application of explained technique is faster and yields more accurate results. An improvement of Dynamic Time Warping based on counting statistical comparison of base distance measures is also achieved. Results on Australian Sign Language and Character Trajectories datasets are reported. Experiment realizations imply feasibility through covariance attributes on time series.
D2 +Nin(T), n=7 and 9, Collision System
(1999) Güvenç, Ziya Burhanettin; Durmuş, Perihan; Özçelik, Süleyman; Güvenç, Ziya Burhanettin; Jellinek, Julius; Bilgisayar Mühendisliği
In this study the kinetics of reactions of Nin n=7 and 9, clusters with a deuterium D2 molecule are studied via quasiclassical molecular dynamics. Dissociative chemisorption probabilities as functions of impact parameters, collision energies, and a rovibrational state of a molecule are calculated. And the corresponding reactive cross sections are evaluated. Resonance formation in the low collision energy region is discussed.
Did satellite imagery supersede aerial imagery? A perspective from 3D geopositioning accuracy
(2016) Maraş, Hadi Hakan; Erdogan, Mustafa; Maraş, Hadi Hakan; Aktuğ, Bahadır; Maraş, Süleyman Sırrı; 34410; Bilgisayar Mühendisliği
In this study, the geometric accuracy comparison of aerial photos and WorldView-2 satellite stereo image data is evaluated with the different number and the distribution of the ground control points (GCPs) on the basis of large scale map production. Also, the current situation of rivalry between airborne and satelliteborne imagery was mentioned. The geometric accuracy of Microsoft UltraCam X 45 cm ground sampling distance (GSD) aerial imagery and WorldView-2 data both with and without GCPs are also separately analyzed. The aerial photos without any GCP by only using global navigation satellite system (GNSS) and inertial measurement unit (IMU) data with tie points give an accuracy of +/- 1.17 m in planimetry and +/- 0.71 m in vertical that means nearly two times better accuracy than the rational polynomial coefficient (RPC) of stereo WorldView-2. Using one GCP affects the accuracies of aerial photos and WorldView-2 in different ways. While this situation distorts the aerial photo block, it corrects the shift effect of RPC in WorldView-2 and increases the accuracy. By using four or more GCPs, 1/2 pixel (similar to 0.23 m) accuracy in aerial photos and 1 pixel (similar to 0.50 m) accuracy in WorldView-2 can be achieved in horizontal. In vertical, aerial photos have 1 pixel (similar to 0.55 m) and WorldView-2 has 1.5 pixels (similar to 0.85 m) accuracy. These results show that Worldview-2 imagery can be used in the production of class I 1: 5000 scale maps according to the ASPRS Accuracy Standards for Digital Geospatial Data in terms of geometric accuracy. It is concluded that the rivalry between aerial and satellite imagery will continue for some time in the future.
Digital Video Stabilization Using Radon Transform
(IEEE, 2012) Hassanpour, Reza; Bagheri-Khaligh, Ali; Hassanpour, Reza; 163907; Yazılım Mühendisliği
Digital video stabilization is a category of techniques used to reduce the impact of unintentional camera motion such as jitter, jiggle, and other unsteady motions. These unintentional shakings degrade visual quality of videos and reduce the performance of subsequent processes such as video compression. Digital video stabilization which is performed by post processing the acquired frames, suffers from inaccuracy of motion estimation which is mostly due to the local motions of internal moving objects included in videos, and long processing time which prohibits them from being used in real time applications. In this paper we propose a fast and accurate transform based motion estimation method which is robust to internal moving objects. Our experimental results with real and synthesized data indicate efficacy of our proposed method.
Energy dissipation characteristics of Wireless Sensor Networks with unidirectional links
(IEEE, 2012) Koyuncu, Murat; Tavlı, Bülent; Koyuncu, Murat; Uluslararası Ticaret ve Finansman
Link unidirectionality is a commonly encountered phenomena in Wireless Sensor Networks (WSNs), which is a natural result of various properties of wireless transceivers as well as the environment. Transmission power heterogeneity is the dominant factor that creates unidirectional links. In this study, we investigate the impact of transmission power heterogeneity on the lifetime of WSNs through a novel Linear Programming (LP) framework both for networks that utilize only bidirectional links and for those that can use bidirectional links as well as unidirectional links. Our results show that transmission power heterogeneity can lead to more than 25 % decrease in network lifetime for networks that utilize only bidirectional links when compared to a network without any heterogeneity. However, if the use of unidirectional links is also enabled then, the decrease in network lifetime is at most 12 %.
Evaluation of 3D high resolution images using inexpensive distributed parallel system: Application fields on medical images
(IEEE, 2007) Eren, Hüseyin; Çelik, Ümit; Poyraz, Mustafa
In the telesurgery operations, images should be high resolution and processed in real time. It seems difficult to accomplish this process in real time using only one computer. In our study, we propose to get 3d scene images inside and outside of surgery environment in real time and transfer them into different places. As known, 3d reconstruction needs intensive calculations. Nowadays, using distributed parallel systems are getting increase. Therefore, we investigate the performance rates using a group of inexpensive inert computers which work as a distributed parallel system supposed to be established in a medical environment.
Examining Reward Mechanisms for Effective Usage of Application Lifecycle Management Tools
(2017) Yılmaz, Murat; Yılmaz, Murat; Uzun, Eray; Clarke, Paul M.; O’Connor, Rory V.; Yazılım Mühendisliği
Application lifecycle management (ALM) highlights the rules of the road for the entire software ecosystems’ lifecycle. Successful ALM enables clarity around the entire delivery effort, from defining requirements to deploying the software product. One of the challenges in software engineering today is to orchestrate ALM tools to a set of software projects effectively. In particular, it is challenging for software practitioners to continuously fully engage with the tasks that are assigned to them. The goal of this study is to address such situations using a game theoretic approach by utilizing a reward mechanism, which we intent to test in a medium-sized software development organization. Based on a set of game elements, this study proposes an auction mechanism to address human resource allocation and task optimization issues, and consequently tackle the potential problem of software practitioners’ engagement.
Face Photograph Recognition via Generation from Sketches using Convolutional Neural Networks
(2019) Karasolak, Mustafa; Choupani, Roya; 21259
Face photo-sketch matching is an important problem for law enforcement agencies in terms of identifying suspects. In this study, a new sketch-photo generation and recognition technique is proposed by using residual convolutional neural network architecture. The suggested RCNN architecture consists of 6 convolutions, 6 ReLU, 4 poolings, 2 deconvolution layers. The proposed architecture is trained with face photos and sketches. Sketches are supplied as an input to the RCNN architecture and, generated face photos are obtained as the output. Then, the generated face photos are compared with the photos of the people in the database. Structural Similarity Index (SSIM) is used to measure the pairwise similarity and the photo with the highest index score is matched. CUHK Face Sketch Database containing 188 images is tested. In the experiments, 148, 20, and 20 images are used for training, validation, and testing, respectively. Data augmentation applied to 148 training images produced 444 images. Experimental results show that the success of the training curve is 90.55% and the validation success is 91.1%. True face recognition success from generated face images with SSIM is 93.89% for CUHK Face Sketch database (CUFS) and 84.55% AR database.

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