Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253
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Browsing Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu by Publication Index "TR-Dizin"
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Article Covid-19 Salgını Sırasında Evden Çalışma: Türk Yazılım Profesyonellerinin Deneyimleri(2021) Tokdemir, GulBu çalışma, Covid-19 salgını sırasında yazılım profesyonellerinin evden çalışma deneyimlerini araştırmaktadır. Bir anket aracılığıyla, bu tür çalışma ortamlarının özellikleriyle ilişkili olarak evden çalışmanın zorlukları incelenmiştir. Ayrıca, iki değişkenli analiz yoluyla, ev tabanlı çalışma özellikleri ile üretkenlik arasındaki ilişki araştırılmıştır. Bu çalışmanın sonuçları, yazılım profesyonellerinin pandemi döneminde daha uzun saatler çalıştıklarını ve evden çalışma ortamına adapte olmanın çoğunlukla kolay olduğunu göstermektedir. Evden çalışma ortamlarında ev işleri ve çocukların en önemli kesinti nedeni olduğu bildirilmiştir. Ayrıca yazılım profesyonelleri için öğleden sonraları ve sabahların en verimli çalışma aralıkları olduğu belirtilmiştir.Article Citation - WoS: 10Citation - Scopus: 11The Diagnosis of Femoroacetabular Impingement Can Be Made on Pelvis Radiographs Using Deep Learning Methods(Turkish Joint Diseases Foundation, 2023) Atalar, Ebru; Ureten, Kemal; Kanatli, Ulunay; Ciceklidag, Murat; Kaya, Ibrahim; Vural, Abdurrahman; Maras, YukselObjectives: The aim of this study was to evaluate diagnostic ability of deep learning models, particularly convolutional neural network models used for image classification, for femoroacetabular impingement (FAI) using hip radiographs. Materials and methods: Between January 2010 and December 2020, pelvic radiographs of a total of 516 patients (270 males, 246 females; mean age: 39.1 +/- 3.8 years; range, 20 to 78 years) with hip pain were retrospectively analyzed. Based on inclusion and exclusion criteria, a total of 888 hip radiographs (308 diagnosed with FAI and 508 considered normal) were evaluated using deep learning methods. Pre-trained VGG-16, ResNet-101, MobileNetV2, and Inceptionv3 models were used for transfer learning. Results: As assessed by performance measures such as accuracy, sensitivity, specificity, precision, F-1 score, and area under the curve (AUC), the VGG-16 model outperformed other pre-trained networks in diagnosing FAI. With the pre-trained VGG-16 model, the results showed 86.6% accuracy, 82.5% sensitivity, 89.6% specificity, 85.5% precision, 83.9% F1 score, and 0.92 AUC. Conclusion: In patients with suspected FAI, pelvic radiography is the first imaging method to be applied, and deep learning methods can help in the diagnosis of this syndrome.Article Citation - WoS: 11Citation - Scopus: 11Diagnosis of Osteoarthritic Changes, Loss of Cervical Lordosis, and Disc Space Narrowing on Cervical Radiographs With Deep Learning Methods(Turkish Joint Diseases Foundation, 2022) Tokdemir, Gul; Ureten, Kemal; Atalar, Ebru; Duran, Semra; Maras, Hakan; Maras, YukselObjectives: In this study, we aimed to differentiate normal cervical graphs and graphs of diseases that cause mechanical neck pain by using deep convolutional neural networks (DCNN) technology. Materials and methods: In this retrospective study, the convolutional neural networks were used and transfer learning method was applied with the pre-trained VGG-16, VGG-19, Resnet-101, and DenseNet-201 networks. Our data set consisted of 161 normal lateral cervical radiographs and 170 lateral cervical radiographs with osteoarthritis and cervical degenerative disc disease. Results: We compared the performances of the classification models in terms of performance metrics such as accuracy,Article Citation - WoS: 7Citation - Scopus: 10Extending a Sentiment Lexicon With Synonym-Antonym Datasets: Swnettr Plus(Tubitak Scientific & Technological Research Council Turkey, 2019) Genc, Burkay; Sever, Hayri; Saglam, FatihIn our previous studies on developing a general-purpose Turkish sentiment lexicon, we constructed SWNetTR-PLUS, a sentiment lexicon of 37K words. In this paper, we show how to use Turkish synonym and antonym word pairs to extend SWNetTR-PLUS by almost 33% to obtain SWNetTR++, a Turkish sentiment lexicon of 49K words. The extension was done by transferring the problem into the graph domain, where nodes are words, and edges are synonym- antonym relations between words, and propagating the existing tone and polarity scores to the newly added words using an algorithm we have developed. We tested the existing and new lexicons using a manually labeled Turkish news media corpus of 500 news texts. The results show that our method yielded a significantly more accurate lexicon than SWNetTR-PLUS, resulting in an accuracy increase from 72.2% to 80.4%. At this level, we have now maximized the accuracy rates of translation-based sentiment analysis approaches, which first translate a Turkish text to English and then do the analysis using English sentiment lexicons.Article Kapılı Tekrarlayan Hücreler Tabanlı Bulanık Zaman Serileri Tahminleme Modeli(2023) Arslan, SerdarZaman serisi tahminleme hava durumu, iş dünyası, satış verileri ve enerji tüketimi tahminleme gibi bir çok alanda uygulama alanına sahiptir. Bu alanlarda tahminleme yaparken kesin sonuçlar elde etmek çok önemlidir ama aynı zamanda zaman serilerinin karmaşık ve de belirsizlik içeren veriler olması nedeniyle çok zordur. Günümüzde, derin öğrenme metotları bu alanda klasik metotlara göre daha iyi sonuçlar vermektedir. Fakat literatürde bulanık zaman serileri tahminleme konusunda çok az çalışma vardır. Bu çalışmada, zaman serilerindeki karmaşıklığın ve belirsizliğin doğurduğu problemleri yok etmek için Yinelemeli sinir Ağları ile bulanık time serilerini bir arada kullanan bir model ortaya konmuştur. Bu çalışmada, Kapılı Tekrarlayan Hücreler kullanarak geçmiş veriler ile bulanık verilerin üyelik değerleri birleştirilerek tahminleme değeri hesaplanmıştır. Ayrıca, bu çalışmadaki model ilk seviye bulanık ilişkileri ele alabildiği gibi, çoklu seviye bulanık ilişkileri de kapsamaktadır. Testlerde literatürde var olan çalışmalar ilgili model ile iki açık veri seti ile karşılaştırılmış olup bahsi geçen modelin daha iyi veya benzer sonuçlar verdiği gözlemlenmiştir. Ayrıca model Covid-19 verileri kullanılarak da test edilmiş ve Uzun-Kısa Süreli Bellek modellerinden daha iyi sonuç vermiştir.Article 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 MühendisliğiData 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%).Article Citation - WoS: 3Observed Effects of Software Processes Change in Three Software Firms: Industrial Exploratory Case Study(Pamukkale Univ, 2019) Yilmaz, MuratSoftware development processes require continuous improvement in line with emerging new technologies and the possibilities it provides. A new generation of software development models based on product demands of software customers with marketable functions aims to increase the intermediate product production speed and thus the number of interim versions. In the light of these needs, software companies need to oversee their development processes to meet their customers' needs. But more importantly, companies are forced to change their processes in line with innovative practices in order not to cut back on the software production line. In this article, the software development methods of the three companies that develop software are examined in detail by the case study method, and the process change activities are systematically detailed. In the light of the information obtained, the experiences of the three firms in the software development methods are questioned and the effects of these acquisitions on the processes are discussed. As a result of the study, it has been observed that the software development success has a significant impact on the well-being of the process, and the software development teams are trying to design their own processes in the light of the gains they acquire.Article Citation - WoS: 1Using Text Mining for Research Trends in Empirical Software Engineering(Gazi Univ, 2021) Tokdemir, GulThis paper intends to examine the research trends in Empirical Software Engineering domain within the last two decades using text mining. It studies published articles in the relevant literature with an emphasis on abstracts of 10658 articles published in the literature on Experimental Software Engineering domain. Using a probabilistic topic modelling technique (Latent Dirichlet Allocation), it brings forward the main topics of research within this domain. By further analysis, the paper evaluates the changes of focus in published works in the last two decades and depicts the recent trends in research content wise. Through a timely comparison, it portrays the alteration of interest within empirical software engineering research and proposes a future research agenda to develop an advanced field, beneficial both for academics and practitioners.
