Tolun, Mehmet Reşit
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Tolun, Mehmet
Tolun, Mehmet Resit
Tolun, Mehmet R.
Tolun, M.R.
Tolun, Mehmet Resit
Tolun, Mehmet R.
Tolun, M.R.
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Prof. Dr.
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tolun@cankaya.edu.tr
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Yazılım Mühendisliği
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Current Staff
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Sustainable Development Goals
3
GOOD HEALTH AND WELL-BEING
3
Research Products
7
AFFORDABLE AND CLEAN ENERGY
1
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9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
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11
SUSTAINABLE CITIES AND COMMUNITIES
1
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13
CLIMATE ACTION
1
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17
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Documents
43
Citations
386
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7
Documents
35
Citations
280
Scholarly Output
35
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12
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3893/2235
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3
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0
WoS Citation Count
24
Scopus Citation Count
45
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2
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4
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0.69
Scopus Citations per Publication
1.29
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3
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Now showing 1 - 10 of 35
Conference Object Production and Retrieval of Rough Classes in Multi Relations(Ieee Computer Soc, 2007) Tolun, M.R.; Sever, H.; Gorur, A.K.Organizational memory in today's business world forms basis for organizational learning, which is the ability of an organization to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures. This basically requires consideration of different aspects of knowledge that may reside on top of a conventional information management system. Of them, representation, retrieval and production issues of meta patterns constitute to the main theme of this article. Particularly we are interested in a formal approach to handle rough concepts. We utilize rough classifiers to propose a preliminary framework based on minimal term sets with p-norms to extract meta patterns. We describe a relational rule induction approach, which is called rila. Experimental results are provided on the mutagenesis, and the KDD Cup 2001 genes data sets. © 2007 IEEE.Conference Object Citation - Scopus: 1Induction for Radiology Patients(Springer, 2009) Yildirim, Pinar; Tolun, Mehmet R.This paper represents the implementation of an inductive learning algorithm for patients of Radiology Department in Hacettepe University hospitals to discover the relationship between patient demo-graphics information and time that patients spend during a specific radiology exam. ILA has been used for the implementation which generates rules and the results are evaluated by evaluation metrics. According to generated rules, some patients in different age groups or birthplaces may spend more time for the same radiology exam than the others.Conference Object Citation - WoS: 1Citation - Scopus: 2Clustering Analysis for Vasculitic Diseases(Springer-verlag Berlin, 2010) Yildirim, Pinar; Ceken, Cinar; Ceken, Kagan; Tolun, Mehmet R.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.Article Citation - WoS: 2Citation - Scopus: 4An Intelligent System for Detecting Mediterranean Fruit Fly [Medfly; Ceratitis Capitata (Wiedemann)](Pagepress Publ, 2022) Eyyuboglu, Halil Tanyer; Sari, Filiz; Uzun, Yusuf; Tolun, Mehmet ResitNowadays, the most critical agriculture-related problem is the harm caused to fruit, vegetable, nut, and flower crops by harmful pests, particularly the Mediterranean fruit fly, Ceratitis capitata, named Medfly. Medfly's existence in agricultural fields must be monitored systematically for effective combat against it. Special traps are utilised in the field to catch Medflies which will reveal their presence and applying pesticides at the right time will help reduce their population. A technologically supported automated remote monitoring system should eliminate frequent site visits as a more economical solution. This paper develops a deep learning system that can detect Medfly images on a picture and count their numbers. A particular trap equipped with an integrated camera that can take photos of the sticky band where Medflies are caught daily is utilised. Obtained pictures are then transmitted by an electronic circuit containing a SIM card to the central server where the object detection algorithm runs. This study employs a faster region-based convolutional neural network (Faster R-CNN) model in identifying trapped Medflies. When Medflies or other insects stick on the trap's sticky band, they spend extraordinary effort trying to release themselves in a panic until they die. Therefore, their shape is badly distorted as their bodies, wings, and legs are buckled. The challenge is that the deep learning system should detect these Medflies of distorted shape with high accuracy. Therefore, it is crucial to utilise pictures containing trapped Medfly images with distorted shapes for training and validation. In this paper, the success rate in identifying Medflies when other insects are also present is approximately 94%, achieved by the deep learning system training process, owing to the considerable amount of purpose-specific photographic data. This rate may be seen as quite favourable when compared to the success rates provided in the literature.Article Citation - Scopus: 1Damage Detection in Aircraft Engine Borescope Inspection Using Deep Learning(Springer Science and Business Media Deutschland GmbH, 2025) Uzun, I.; Tolun, M.R.; Sari, F.; Alpaslan, F.N.Aircraft engine inspection is a key pillar of aviation safety as it helps to maintain adequate performance standards to ensure engine airworthiness. In addition, it is also vital for asset value retention. Borescope inspection is currently the most widely used visual inspection method for aircraft engines. However, borescope inspection is a time-consuming, subjective, and complex process that heavily depends on the experience and attention level of the inspector. Moreover, the cost savings of airlines and the maintenance, repair, and overhaul (MRO) centers expose pressure and workload on inspectors. These factors make an automated system to support damage detection during borescope inspection necessary in order to mitigate potential risks. In this paper, we propose a deep learning-based automated damage detection framework that employs aircraft engine borescope inspection images. Faster R-CNN-based deep learning model with Inception v2 feature extractor is utilized for the present architecture. Due to the limited number of images, data augmentation and other overfitting methods are also employed. The framework supports crack, burn, nick, and dent damage types across all modules of turbofan engines. It is trained and validated with moderate to complex borescope images obtained from the field. The framework achieves 92.64% accuracy for crack, 92.05% for nick or dent, and 81.14% for burn damage classes, with an overall 88.61% average accuracy. © The Author(s) 2025.Conference Object Yeşil BHT Bilgi ve Haberleşme Teknolojileri Akademisyen ve Uygulayıcılar Açısından Bir İnceleme(2011) Akba, Fırat; Medeni, İhsan Tolga; Medeni, Tunç Durmuş; Tolun, Mehmet Reşit; Öztürk, MehmetConference Object Citation - Scopus: 1Component-Based Project Estimation Issues for Recursive Development(Springer, 2008) Altunel, Yusuf; Tolun, Mehmet R.In this paper we investigated the component-based specific issues that might affect project cost estimation. Component-based software development changes the style of software production. With component-based approach the software is developed as the composition of reusable software components. Each component production process must be treated as a stand-alone software project, which needs individual task of management. A typical pure component-based development can be considered as decomposition/integration activities successively applied at different levels and therefore results in recursive style of development. We analyzed and presented our results of studies on the component-based software development estimation issues from recursive point of view.Master Thesis Makine Öğrenmesi Teknikleri Kullanılarak Sybil Botların Tespit Edilmesi(2025) Öcel, Cansu Betül; Tolun, Mehmet ReşitBu çalışma, NSL-KDD veri seti kullanılarak ağ tabanlı anomali tespiti amacıyla çeşitli makine öğrenmesi algoritmalarının performansını karşılaştırmalı olarak değerlendirmeyi amaçlamaktadır. NSL-KDD, saldırı türlerini dört ana başlıkta (DoS, Probe, R2L, U2R) toplayan, etiketli ve dengeli yapısıyla denetimli öğrenme yöntemleri için uygun bir veri seti olarak ele alınmıştır. Çalışma kapsamında veri seti üzerinde öncelikle istatistiksel analizler ve veri keşif çalışmaları gerçekleştirilmiş, ardından veri ön işleme adımları uygulanmıştır. Bu süreçte kategorik değişkenler sayısal forma dönüştürülmüş, eksik veriler temizlenmiş ve azınlıkta kalan sınıflar SMOTE yöntemiyle dengelenmiştir. Özellik seçimi için Mutual Information (MI) yöntemi kullanılarak en bilgilendirici 15 değişken belirlenmiş ve model eğitimi bu özellikler kullanılarak gerçekleştirilmiştir. Sonrasında tüm değişkenler kullanılarak modeller tekrar eğitilmiş ve sonuçlar kıyaslanmıştır. Modelleme aşamasında Lojistik Regresyon, Naive Bayes, Random Forest, K En Yakın Komşu (KNN), Destek Vektör Makineleri (SVM), AdaBoost ve Yapay Sinir Ağı (ANN) algoritmaları kullanılmıştır. Her model için hiper parametre optimizasyonu GridSearchCV veya RandomizedSearchCV yöntemleriyle yapılmıştır. Modellerin başarısı doğruluk (accuracy), kesinlik (precision), duyarlılık (recall) ve F1 skoru gibi değerlendirme metrikleri kullanılarak analiz edilmiştir.Elde edilen sonuçlar, NSL-KDD veri seti üzerinde bazı modellerin özellikle DoS gibi baskın sınıflarda yüksek doğruluk sağlarken, azınlıkta kalan R2L ve U2R saldırı türlerinde performans düşüşleri yaşandığını göstermektedir. Bu durum, dengesiz veri setlerinde kullanılacak yöntemlerin dikkatli seçilmesinin gerekliliğine işaret etmektedir.Conference Object Citation - Scopus: 4A 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.Article Yazılım süreç iyileştirmede CASE aracı kullanımının CMMI süreç yönetimi kategorisi açısından değerlendirilmesi(Çankaya Üniversitesi, 2010) Fidanboy, Cemalettin Öcal; Tolun, Mehmet R.Yazılım mühendisliğinin bilgi alanlarından biri olan yazılım kalitesinin belirlenmesi için temel oluşturan model ve standartlar her geçen gün değer kazanmaktadır. Yazılım kalitesini belirleyen temel unsurlar; yazılım süreçlerinin kuruluş ihtiyaçlarına uygun olarak belirlenmesi, yönetilmesi ve sistematik olarak iyileştirilmesidir. Uluslararası yazılım süreç iyileştirme model ve standartları temel alındığında, yazılım geliştirme projelerinin yüksek kalite düzeylerine ulaşması, projelerin istenen sürede ve en uygun maliyette tamamlanması mümkün olmaktadır. Bütünleşik Yetenek Olgunluk Modeli (CMMI), yazılım geliştirme, bakım ve süreç iyileştirme konularında, en iyi yönetim uygulamalarının birleştirilmesi sonucu oluşturulan önemli modellerden birisidir. Yazılım süreç iyileştirme, çalışmalarında CASE (bilgisayar destekli yazılım mühendisliği) araçlarının kullanılması; süreç iyileştirme sisteminin verimli bir şekilde kurgulanması, etkin bir konfigürasyon yönetiminin sağlanması ve sağlam bir metrik altyapısının kurulması açısından önemli faydalar sağlamaktadır. Bu makalede, öncelikli olarak CMMI Süreç Yönetimi kategorisinde yer alan ve kurumsal süreç iyileştirme uygulamalarını hedefleyen Kurumsal Süreç Tanımı ile Kurumsal Süreç Odaklanması Süreç alanları tanıtılmaktadır. Aynı zamanda, CMMI Süreç Yönetimi kategorisi kapsamında CASE aracı kullanımına yönelik örnekler verilmektedir. Ek olarak, CASE aracı kullanımının yazılım süreç iyileştirme uygulamalarına etkisini ortaya çıkarmak üzere yapılan bir kullanıcı anketine ilişkin sonuçlar sunulmakta ve bahsi geçen konularda CMMI modeli açısından değerlendirme yapılmaktadır.
