Ünlütürk, Mehmet Süleyman
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01.01.09.07. Yazılım Mühendisliği Bölümü
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Sustainable Development Goals
1NO POVERTY
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2ZERO HUNGER
2
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3GOOD HEALTH AND WELL-BEING
1
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4QUALITY EDUCATION
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5GENDER EQUALITY
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6CLEAN WATER AND SANITATION
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7AFFORDABLE AND CLEAN ENERGY
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8DECENT WORK AND ECONOMIC GROWTH
1
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
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10REDUCED INEQUALITIES
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11SUSTAINABLE CITIES AND COMMUNITIES
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
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13CLIMATE ACTION
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14LIFE BELOW WATER
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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Documents
41
Citations
281
h-index
7
Documents
28
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176
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15
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9
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Supervised MSc Theses
2
Supervised PhD Theses
4
WoS Citation Count
25
Scopus Citation Count
32
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2
WoS Citations per Publication
1.67
Scopus Citations per Publication
2.13
Open Access Source
1
Supervised Theses
6
| Journal | Count |
|---|---|
| Journal of Testing and Evaluation | 2 |
| Engineering Applications of Artificial Intelligence | 2 |
| Studies in Informatics and Control | 1 |
| Computer Methods and Programs in Biomedicine | 1 |
| Neural Computing and Applications | 1 |
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15 results
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Now showing 1 - 10 of 15
Article Citation - WoS: 8Citation - Scopus: 10Automated personnel-assets-consumables-drug tracking in ambulance services for more effective and efficient medical emergency interventions(ELSEVIER IRELAND LTD, 2016-04) Semih Utku; Mehmet Hilal Ozcanhan; Mehmet Suleyman Unluturk; Unluturk, Mehmet Suleyman; Utku, Semih; Özcanhan, Mehmet HilalPatient delivery time is no longer considered as the only critical factor in ambulatory services. Presently five clinical performance indicators are used to decide patient satisfaction. Unfortunately the emergency ambulance services in rapidly growing metropolitan areas do not meet current satisfaction expectations, because of human errors in the management of the objects onboard the ambulances. But human involvement in the information management of emergency interventions can be reduced by electronic tracking of personnel assets consumables and drugs (PACD) carried in the ambulances. Electronic tracking needs the support of automation software which should be integrated to the overall hospital information system. Our work presents a complete solution based on a centralized database supported by radio frequency identification (RFID) and bluetooth low energy (BLE) identification and tracking technologies. Each object in an ambulance is identified and tracked by the best suited technology. The automated identification and tracking reduces manual paper documentation and frees the personnel to better focus on medical activities. The presence and amounts of the PACD are automatically monitored warning about their depletion non-presence or maintenance dates. The computerized two way hospital-ambulance communication link provides information sharing and instantaneous feedback for better and faster diagnosis decisions. A fully implemented system is presented with detailed hardware and software descriptions. The benefits and the clinical outcomes of the proposed system are discussed which lead to improved personnel efficiency and more effective interventions. (C) 2015 Elsevier Ireland Ltd. All rights reserved.Master Thesis Hazır giyim sektörü için tasarlanan modellerin beğenisinin yapay sinir ağları kullanılarak öngörülmesi(2017) Hekimoğlu, Caner Kıvanç; Ünlütürk, Mehmet SüleymanBu araştırma, moda tasarım şirketleri için bir moda danışmanı olarak kullanılabilecek bir yapay sinir ağı sunmaktadır. Bu çalışmada, makine öğrenme teknikleri moda alanında kullanılmıştır. Sinir ağları tekniğiyle geliştirilen bir yazılım, hazır giyim tasarım örneklerini kabul veya reddetmek için moda danışmanı olarak uygulanmıştır. Ayrıca, bu model, geri yayılımlı sinir ağı devresi ve SVM modeli kullanarak müşteri tercihlerini öğrenmektedir. Bu sinir ağı uygulaması, müşterinin geçmişinde tercih ettiği moda tarzına dayanarak, müşteriye özel olarak hazırlanan özel moda tasarımlarını puanlandırmaktadır. Skora göre, şirket; giyim tasarım örneğini inceleme süreci için müşterisine göndermeye veya göndermemeye karar verebilir ve bu karar şirkete zaman kazandırır ve kaynak harcamasını azaltır. Çalışmanın sonuçlarına göre, geri yayılım sinir ağı ve SVM modeli bir moda danışmanı olarak etkin bir şekilde kullanılabilir.Master Thesis Yazılım algoritmalarının verimlilik tekniklerinin titiz analizi(2020) Ayaydın, Atabarış; Ünlütürk, Mehmet SüleymanEfficiency, in programming, generally treated as a concept of 'on-demand' rather than an integral part of the programming. However, as it is a part of the software quality measurements, the programmer also responsible to write a program that will meet the requirements. Since there is no known technique to find the least time or space complexity for the problem on the hand, augmenting the programmer's knowledge with the known techniques is essential. As the meaning of efficiency changes throughout the time, these mentioned techniques must be reevaluated to adapt to current necessities. This thesis address, the categorization of the mentioned techniques as well as the expansion of them. The runtime comparison between the different versions of the solutions states that efficiency is not a lesser subject to deal with, instead, it requires more attention than it gets.Article Automated Detection and Quantification of Honey Adulteration Using Thermal Imaging and Convolutional Neural Networks(Pergamon-Elsevier Science Ltd, 2026-02) Unluturk, Mehmet S.; Unluturk, Sevcan; Berk, BerkayHoney is a valuable natural food rich in bioactive substances beneficial to health. Despite strict regulations prohibiting adulteration, honey remains one of the most frequently adulterated foods, often with low-cost commercial syrups. Conventional detection methods require expensive instruments, expert operators, and lengthy analysis times, limiting their practical use. This study introduces a rapid and automated method for detecting and quantifying honey adulteration using thermal image analysis combined with a tailored Convolutional Neural Network (CNN) architecture. Thirty-six pure honey samples (blossom and honeydew) from different regions of Türkiye were adulterated with inverted sugar, maltose, and glucose syrups at varying levels (3 %-60 % weight/weight (w/w)). Samples were heated to 60 degrees C and thermal images were captured during cooling using a custom image-capturing unit. The CNN model employed a multi-layer structure, starting with a shallow network for binary classification (pure vs adulterated honey) achieving 100 % accuracy, followed by specialized deeper CNN regressors to quantify adulterant levels with mean squared errors of 0.0003, 0.001, and 0.0002 for glucose, maltose, and inverted sugar, respectively. This layered CNN approach leverages thermal patterns linked to adulteration, enabling sensitive, rapid, and non-destructive quality control. Furthermore, the method is integrated into a user-friendly hardware-software system called Compact Adulteration Testing Cabinet on Honey (CATCH), requiring no specialized expertise, demonstrating strong potential for automated honey authenticity verification in practical settings.Article Citation - WoS: 4Citation - Scopus: 8QUANTIFYING PRODUCTIVITY OF INDIVIDUAL SOFTWARE PROGRAMMERS: PRACTICAL APPROACH(SLOVAK ACAD SCIENCES INST INFORMATICS, 2015) Mehmet Suleyman Unluturk; Kaan Kurtel; Unluturk, Mehmet Suleyman; Kurtel, KaanSoftware measurement is a crucial part of a good software engineering. Software developers quantify the software to see if the use cases are complete if the analysis model is consistent with requirements and if the code is ready to be tested. Software project managers assess the software process and the software product to determine if it is going to be finished on time and within budget. Customers evaluate the final product if it meets their needs. Overall the main purpose of software engineering is to make software systems controllable and foreseeable activities with a solid method rather than intuitional complicated or unprincipled. Software measurement studies are about quantifying the software engineering entities and attributes both of which aim to support software development efforts and quality improvement. In this paper we quantify a set of relationships using the current size defect and object-oriented software metrics practically and pragmatically. Our paper proposes a method to measure the productivity of individual software programmers. Furthermore this method provides a common opinion for understanding controlling and improving the software engineering practices.Article Citation - WoS: 6Citation - Scopus: 6Wavelet Analysis With Different Frequency GPR Antennas for Bridge Health Assessment(AMER SOC TESTING MATERIALS, 2016-01-01) Gokhan Kilic; Mehmet S. Unluturk; Unluturk, Mehmet S.; Kilic, GokhanThis study presents an examination and a presentation of ground-penetrating radar (GPR) on a heavily used high-speed railway bridge in Turkey. This study also considers GPR mapping using two different antennas (2 GHz and 500 MHz) and their reliability in terms of locating subsurface features such as rebar (lower and upper reinforcement) and the presence of moisture. Moreover GPR interesting results in terms of the structural crack locations by detecting discontinuities and breakdowns in the wavelets' travel with the incorporation of wavelet analysis into the process of the collected raw data of the highspeed railway bridge under survey. This study promotes the GPR and the wavelet analyses in the health monitoring and assessment of bridge structures. By increasing insight into the kinds of structural deterioration that can occur in structures such as high-speed railway bridges this study also has implications for the process of tool selection in structural inspection. The wavelet analysis can be used as an effective tool in analyzing and presenting the results of the GPR survey.Article Citation - WoS: 1Citation - Scopus: 1GPR Raw-Data Analysis to Detect Crack Using Order Statistic Filtering(AMER SOC TESTING MATERIALS, 2016-09-01) Gokhan Kilic; Mehmet S. Unluturk; Unluturk, Mehmet S.; Kilic, GokhanGround penetrating radar (GPR) uses data collected with the aid of electromagnetic waves transmitted into a structure by antenna to assess and monitor the structural health of many different kinds of civil infrastructure. With GPR technology promoting their system with promises of the achievement of in excess of 1000 sample points per scan this research demonstrated on the basis of the Nyquist theorem that 256 sample points per scan provided equally reliable inspection results. Furthermore 256 sample points per scan GPR data were further analyzed by order statistic filtering with neural networks to locate cracks within concrete materials. The results showed that the neural network order statistic filters are effective in their use of detecting cracks in noisy environments using 256 sample points per scan GPR data.Article Citation - WoS: 4Citation - Scopus: 4Classification of organic and conventional olives using convolutional neural networks(Springer Science and Business Media Deutschland GmbH, 2021-07-03) Mehmet Suleyman Ünlütürk; Seçil Küçükyaşar; Fikret Pazir; Unluturk, Mehmet S.; Pazir, Fikret; Kucukyasar, SecilThis paper presents a convolutional neural network (CNN) to classify between the conventionally and organically cultivated Memecik varieties of green olives. The image forming method called the rising paper chromatography is utilized in preparing the images of Memecik varieties of green olives for CNN. In the rising chromatography method 20 30 and 40% sample concentrations were determined as the suitable concentrations for both organic and conventional olives. The concentrations of AgNO3 and FeSO4 were determined as 0.25 0.5 0.75 and 1% for both conventional and organic samples. The visual differences used for differentiation of different types of Memecik green olives are usually determined according to the regional color differences the vivid color occurrence the width and the frequency of bowl occurrence the thin line and the picks at drop zone by the expert assessors. The testing results in this study verified the effectiveness of the CNN methodology in differentiating between the organically and conventionally cultivated Memecik green olives. The newly designed neural network achieved 100% accuracy. Furthermore this high accuracy achieved by CNN might suggest that it can be effectively used in place of the expert assessors. © 2021 Elsevier B.V. All rights reserved.Article Citation - WoS: 2Citation - Scopus: 3Convolutional Neural Network for Cotton Yield Estimation(National Institute for R and D in Informatics, 2024-06-27) Mehmet Suleyman Ünlütürk; Murat Komesli; Asli Keceli; Unluturk, Mehmet Suleyman; Komesli, Murat; Keceli, AsliThe objective of this paper was to estimate the cotton yield potential of different cotton varieties using high-resolution field images based on a convolutional neural network (CNN). The yield estimation for different cotton varieties in grams in breeding studies has a great importance for the determination of superior cultivars to be commercialized. Due to the cost and excessive time consumption typical of traditional methods alternative ways for cotton yield estimation have been investigated over the years. This paper proposes an automated system for cotton yield prediction based on color images obtained by an unmanned aerial vehicle (UAV). Two replicational field experiments including three different cotton genotypes were conducted at May Seed R&D station in Torbali Izmir Turkey. Three different planting patterns including three four and six rows respectively in ten-meter wide areas were used as experimental plots. The ground-truth yield values for a total of six hundred planted areas were obtained by weighing the harvested cotton bolls after field images were taken. Achieving an absolute difference of no more than 350 grams for 114 out of 120 planted areas which were randomly selected only for testing purposes indicates that the CNN can effectively capture important features related to cotton yield from the field images obtained by the UAV. The combination of drone technology with reliable CNN models holds great potential for optimizing agricultural practices improving agricultural productivity and reducing operational costs. © 2024 Elsevier B.V. All rights reserved.Doctoral Thesis Derin öğrenme kullanılarak müziksel benzerliklerin tespiti(2025) Sofuoğlu, İlhan; Ünlütürk, Mehmet SüleymanMüzik, yüzyıllardır insanları büyüleyen karmaşık ve çok yönlü bir sanat biçimidir. Derin öğrenmedeki son gelişmeler nedeniyle, bu teknolojinin müzik içeriğini araştırmak ve anlamak için kullanılmasına yönelik artan bir odaklanma olmuştur. Bu tezde, derin öğrenme tekniklerini kullanarak müzik benzerliğini tespit etme zorluğunu ele almayı amaçlıyoruz. Derin öğrenme modellerinin karmaşık müzik özelliklerini etkili bir şekilde yakalama ve analiz etme potansiyeline sahip olduğunu ve müzik benzerliklerinin doğru bir şekilde tespit edilmesini sağladığını savunuyoruz. Bunun müzik öneri sistemlerinde, müzik prodüksiyonunda ve hatta intihal tespitinde çok sayıda uygulaması olabilir. Büyük müzik besteleri kümeleri üzerinde eğitilen derin öğrenme modellerinin kullanımıyla, farklı müzik parçaları arasındaki benzerlikleri temsil eden önemli özellikleri ve kalıpları tespit edip çıkarabiliriz. Sağlam ve doğru müzik benzerliği tespiti elde etmek için derin sinir ağlarını gelişmiş özellik çıkarma teknikleriyle birleştiren bir çerçeve öneriyoruz. Önerilen çerçeve, müzik benzerliğini yüksek doğrulukla tespit etmek için derin sinir ağlarını ve gelişmiş özellik çıkarma tekniklerini kullanır. Performanslarını değerlendirmek için çeşitli müzik veri kümeleri üzerinde testler yapmak üzere önerilen çerçeveyi kullanıyoruz. Bulgular, metodolojimizin geleneksel teknikleri geride bıraktığını ve müzikal benzerlikleri belirlemede olağanüstü hassasiyet seviyelerine ulaştığını göstermektedir. Ayrıca, müzikal benzerlik tespiti alanında derin öğrenme yöntemlerini uygulamayla ilişkili kısıtlamaları ve zorlukları analiz ediyoruz. Genel olarak, tez, müzikal benzerlikleri doğru bir şekilde tespit etmek için derin öğrenmenin potansiyelini vurgulamaktadır.
