Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253
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Editorial Citation - WoS: 3Citation - Scopus: 4Improving Social Aspects of the Software Development Process: Games, Gamification and Related Approaches(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2016) Yilmaz, Murat; Yılmaz, Murat; O'Connor, Rory V.; Mora, Manuel; O’Connor, Rory V.; Yazılım MühendisliğiArticle Citation - Scopus: 6Design Effort Estimation Using Complexity Metrics(2004) Salman, N.; Salman, Nael; Doǧru, A.; Bilgisayar MühendisliğiComponent-oriented software development is a new trend and is becoming very popular these days. In addition to requiring a different development approach, the new orientation also requires a different metrics approach. A set of metrics for Component Oriented Software Engineering was first introduced in previous research. These metrics set were used to measure the quality of component-oriented software designs. The impact of these metrics on design effort is investigated in this paper. A statistical model is developed based on nine projects that carried out component-oriented software development. Design effort is expressed as a junction of a subset of the complexity metrics.Conference Object Citation - WoS: 49Citation - Scopus: 66Software Engineering Education and Games: a Systematic Literature Review(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2016) Kosa, Mehmet; Yılmaz, Murat; Yilmaz, Murat; O'Connor, Rory V.; Clarke, Paul M.; O’Connor, Rory V.; Yazılım MühendisliğiThe trend in using games in elementary level education also spreads through higher education levels and specific domains such as engineering. Recently, researchers have shown an increased interest in the usage of games in software engineering. In this paper, we are presenting a systematic review and analysis of 350 papers regarding games in software engineering education that was published in the last fifteen years. After applying our inclusion criteria and manual inspection of these studies, we have ended up with 53 primary papers. Based on a systematic process, we reported and discussed our findings with possible future research directions. The main results of this study indicate that the studies are accumulated around 5 categories: Games that learners/students play, games that learners/students develop as projects, curriculum proposals, developing/coming up with new approaches, tools, frameworks or suggestions and others.Article Citation - WoS: 7Citation - Scopus: 10A Literature Survey: Is It Necessary To Develop a New Software Development Methodology for Virtual Reality Projects(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2017) Güleç, Ulaş; Gulec, Ulas; Yilmaz, Murat; Yılmaz, Murat; Isler, Veysi; Bilgisayar Mühendisliği; Yazılım MühendisliğiSoftware development is a complex human endeavour with high failure rates. Although a variety of software development methodologies have been proposed to improve the software development process, there is no universal model for all software development organizations. Virtual reality (VR) is an emerging trend especially for the gaming industry, which should prepare itself for VR development. The goal of this study is to explore potential software development activities and determine whether designing a new software development methodology for VR projects is an important topic for software development organizations working on VR software development. For this purpose, a literature survey has been completed and 71 academic studies have been examined in detail. This study shows that no work is being conducted in the field of developing a new methodology for VR projects. However, the study does show that there are similar endeavours in the field of human computer interaction (HCI), such as game development methodology.Article Citation - WoS: 43Citation - Scopus: 53Gamification as a Disruptive Factor in Software Process Improvement Initiatives(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2014) Herranz, Eduardo; Yılmaz, Murat; Colomo-Palacios, Ricardo; de Amescua Seco, Antonio; Yilmaz, Murat; Yazılım MühendisliğiFor any Software Process Improvement (SPI) initiative to succeed human factors, in particular, motivation and commitment of the people involved should be kept in mind. In fact, Organizational Change Management (OCM) has been identified as an essential knowledge area for any SPI initiative. However, enough attention is still not given to the human factors and therefore, the high degree of failures in the SPI initiatives is directly linked to a lack of commitment and motivation. Gamification discipline allows us to define mechanisms that drive people's motivation and commitment towards the development of tasks in order to encourage and accelerate the acceptance of an SPI initiative. In this paper, a gamification framework oriented to both organization needs and software practitioners groups involved in an SPI initiative is defined. This framework tries to take advantage of the transverse nature of gamification in order to apply its Critical Success Factors (CSF) to the organizational change management of an SPI. Gamification framework guidelines have been validated by some qualitative methods. Results show some limitations that threaten the reliability of this validation. These require further empirical validation of a software organization.Article Citation - WoS: 6Citation - Scopus: 6Auction-Based Serious Game for Bug Tracking(Wiley, 2019) Usfekes, Cagdas; Tuzun, Eray; Yilmaz, Murat; Macit, Yagup; Clarke, PaulToday, one of the challenges in software engineering is utilising application lifecycle management (ALM) tools effectively in software development. In particular, it is hard for software developers to engage with the work items that are appointed to themselves in these ALM tools. In this study, the authors have focused on bug tracking in ALM where one of the most important metrics is mean time to resolution that is the average time to fix a reported bug. To improve this metric, they developed a serious game application based on an auction-based reward mechanism. The ultimate aim of this approach is to create an incentive structure for software practitioners to find and resolved bugs that are auctioned where participants are encouraged to solve and test more bugs in less time and improve quality of software development in a competitive environment. They conduct hypothesis tests by performing a Monte Carlo simulation. The preliminary results of this research support the idea that using a gamification approach for an issue tracking system enhances the productivity and decreases mean time to resolution.Article Citation - WoS: 2Citation - Scopus: 4On Time-Memory Trade-Offs for Password Hashing Schemes(Frontiers Media Sa, 2024) Saran, Ayse NurdanA password hashing algorithm is a cryptographic method that transforms passwords into a secure and irreversible format. It is used not only for authentication purposes but also for key derivation mechanisms. The primary purpose of password hashing is to enhance the security of user credentials by preventing the exposure of plaintext passwords in the event of a data breach. As a key derivation function, password hashing aims to derive secret keys from a master key, password, or passphrase using a pseudorandom function. This review focuses on the design and analysis of time-memory trade-off (TMTO) attacks on recent password hashing algorithms. This review presents a comprehensive survey of TMTO attacks and recent studies on password hashing for authentication by examining the literature. The study provides valuable insights and strategies for safely navigating transitions, emphasizing the importance of a systematic approach and thorough testing to mitigate risk. The purpose of this paper is to provide guidance to developers and administrators on how to update cryptographic practices in response to evolving security standards and threats.Article Citation - WoS: 2The Effect of Population and Tourism Factors on Covid-19 Cases in Italy: Visual Data Analysis and Forecasting Approach(Wiley, 2022) Ozyer, Baris; Ozyer, Gulsah Tumuklu; Tokdemir, Gul; Uguz, Sezer; Yaganoglu, MeteAt the beginning of 2020, the new coronavirus disease (Covid-19), a deadly viral illness, is declared as a public health emergency situation by WHO. Consequently, it is accepted as pandemic that affected millions of people worldwide. Italy is one of the most affected countries by Covid-19 disease among the world. In this article, our main goal is to investigate the effect of intensity of Covid-19 cases based on the population size and tourism factors in certain regions of Italy by visual data analysis. The regions of Lombardia, Veneto, Campania, Emilia-Romagna, Piemonte are the top five regions covering 58.50% of the total Covid-19 cases diagnosed in Italy. It has been shown by visual data analysis that population and tourism factors play an important role in the spread of Covid-19 cases in these five regions. In addition, a prediction model was created using Bi-LSTM and ARIMA algorithms to forecast the number of Covid-19 cases occurring in these five regions in order to take early action. We can conclude that these northern regions have been affected mostly by Covid-19 and the distribution of the resident population and tourist flow factors affected the number of Covid-19 cases in Italy.Article Citation - WoS: 13Citation - Scopus: 15The Diagnosis of Developmental Dysplasia of the Hip From Hip Ultrasonography Images With Deep Learning Methods(Lippincott Williams & Wilkins, 2023) Ureten, Kemal; Tokdemir, Gul; Tolunay, Tolga; Ciceklidag, Murat; Atik, Osman Sahap; Atalar, HakanBackground:Hip ultrasonography is very important in the early diagnosis of developmental dysplasia of the hip. The application of deep learning-based medical image analysis to computer-aided diagnosis has the potential to provide decision-making support to clinicians and improve the accuracy and efficiency of various diagnostic and treatment processes. This has encouraged new research and development efforts in computer-aided diagnosis. The aim of this study was to evaluate hip sonograms using computer-assisted deep-learning methods. Methods:The study included 376 sonograms evaluated as normal according to the Graf method, 541 images with dysplasia and 365 images with incorrect probe position. To classify the developmental hip dysplasia ultrasound images, transfer learning was applied with pretrained VGG-16, ResNet-101, MobileNetV2 and GoogLeNet networks. The performances of the networks were evaluated with the performance parameters of accuracy, sensitivity, specificity, precision, F1 score, and AUC (area under the ROC curve). Results:The accuracy, sensitivity, specificity, precision, F1 score, and AUC results obtained by testing the VGG-16, ResNet-101, MobileNetV2, and GoogLeNet models showed performance >80%. With the pretrained VGG-19 model, 93%, 93.5%, 96.7%, 92.3%, 92.6%, and 0.99 accuracy, sensitivity, specificity, precision, F1 score, and AUC results were obtained, respectively. Conclusion:In this study, in addition to the ultrasonography images of dysplastic and healthy hips, images were also included of probe malpositioning, and these images were able to be successfully evaluated with deep learning methods. On the sonograms, which provided criteria appropriate for evaluation, successful differentiation could be made of healthy hips and dysplastic hips.Article Citation - WoS: 22Citation - Scopus: 25Deep Learning Methods in the Diagnosis of Sacroiliitis From Plain Pelvic Radiographs(Oxford Univ Press, 2023) Ureten, Kemal; Maras, Yuksel; Duran, Semra; Gok, KevserObjectives The aim of this study is to develop a computer-aided diagnosis method to assist physicians in evaluating sacroiliac radiographs. Methods Convolutional neural networks, a deep learning method, were used in this retrospective study. Transfer learning was implemented with pre-trained VGG-16, ResNet-101 and Inception-v3 networks. Normal pelvic radiographs (n = 290) and pelvic radiographs with sacroiliitis (n = 295) were used for the training of networks. Results The training results were evaluated with the criteria of accuracy, sensitivity, specificity and precision calculated from the confusion matrix and AUC (area under the ROC curve) calculated from ROC (receiver operating characteristic) curve. Pre-trained VGG-16 model revealed accuracy, sensitivity, specificity, precision and AUC figures of 89.9%, 90.9%, 88.9%, 88.9% and 0.96 with test images, respectively. These results were 84.3%, 91.9%, 78.8%, 75.6 and 0.92 with pre-trained ResNet-101, and 82.0%, 79.6%, 85.0%, 86.7% and 0.90 with pre-trained inception-v3, respectively. Conclusions Successful results were obtained with all three models in this study where transfer learning was applied with pre-trained VGG-16, ResNet-101 and Inception-v3 networks. This method can assist clinicians in the diagnosis of sacroiliitis, provide them with a second objective interpretation and also reduce the need for advanced imaging methods such as magnetic resonance imaging.
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