WOS - Web of Science

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    Implementation of DBSCAN Method in Star Trackers to Improve Image Segmentation in Heavy Noise Conditions
    (2023) Nevsan ŞENGİL; Şengil, Nevsan; Türk Hava Kurumu Üniversitesi, Uzay Mühendisliği Bölümü, Ankara, Türkiye
    Star trackers are currently the most accurate sensors for determining the attitude of a spacecraft. These sensors comprise not only highly capable optical detectors and processor units but also complicated software solvers. One of the main solvers employed in star trackers is image segmentation. In this study, the aim is to develop a hybrid image segmentation method which is a combination of both global thresholding and density-based spatial clustering of applications with noise (DBSCAN) method to increase detection probability of the stars in heavy noise. Secondly, a sorting algorithm is added to list the detected stars in terms of their brightness to increase the efficiency of the star tracking algorithm. Then, this new approach and two different conventional segmentation methods are applied to the Orion star constellation image polluted with Gaussian, salt and pepper, and uneven background noises. The resulting images of these segmentation methods are compared in terms of denoising capabilities. Although computationally more expensive, the proposed DBSCAN-based hybrid method displays a background pixel recovery performance of 99.5%, compared to Otsu global thresholding and adaptive thresholding methods’ 73.5% and 79.9% recovery values, respectively. Additionally, it has been demonstrated that the sorting algorithm successfully listed the detected stars in accordance with their brightness.
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    Empirical Investigation of Small-Scale Aluminium Wool Packed Solar Air Heater Made with Waste Material
    (Politeknik Dergisi, 2021-12-01) Ataollah Khanları; Azim Doğuş Tuncer; Ceylin Şirin; Faraz Afshari; Afşin Güngör
    Waste production is an important problem for the developing world and globalization. The waste materials can be reused through recycling process and its environmental effects can be minimized. Utilizing renewable energy sources at the maximum level is also an important issue for a sustainable development in future as well as waste management. In this study, small-scale solar air heating systems were produced from waste materials to analyze the usability of waste material in renewable energy systems. Scrap metal elbows were used in the production of heaters. The first solar heater is hollow (SH) and the second one was modified by filling it with aluminum wool (SHAW). Both heaters were tested simultaneously at different flow rates (0.014, 0.010 and 0.006 kg/s). According to the experimental results, the thermal efficiency values for SH and SHAW were found in the range of 33.63-42.90% and 42.69-56.98%, respectively. In addition, it was observed that a low cost modification such as using aluminum wool can significantly increase thermal performance of the solar heating system. 
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    Effect of Cutting Parameters on Surface Roughness and Cutting Forces in Hard Turning of 1.2367 Hot Work Tool Steel
    (Politeknik Dergisi, 2023-10-01) Sümeyye ERDEM; Mustafa ÖZDEMİR; Mohammad RAFİGHİ; Mehtap YAVUZ
    Bu çalışmada 1.2367 sertleştirilmiş (55 HRC) sıcak takım çeliğinin tornalanmasında farklı kesme parametrelerinin yüzey pürüzlülüğü (Ra) ve kesme kuvvetleri üzerindeki etkisi incelenmiştir. Bu deneysel çalışmada, deney tasarımı Taguchi metodu kullanılarak yapılmış ve kesme parametreleri olarak sabit talaş derinliği, üç farklı kesme hızı ve üç farklı ilerleme miktarı seçilmiştir. Kesme parametrelerinin yüzey pürüzlülüğü ve kesme kuvvetleri üzerindeki etkisi varyans analizi (ANOVA) yapılarak değerlendirilmiştir. Sonuçlara göre ilerleme hızındaki artışa bağlı olarak yüzey pürüzlülüğü değerinin arttığı görülmüştür. Kesme hızının ise yüzey pürüzlülük değeri üzerinde belirli bir etkisi görülmemiştir. Radyal kuvvet (Fx), teğetsel kuvvet (Fy) ve ilerleme kuvveti (Fz) üzerinde ise, en etkili parametrenin ilerleme hızı olduğu görülmüştür.
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    Intrusion Detection Model Based on TF.IDF and C4.5 Algorithms
    (Politeknik Dergisi, 2021-12-01) Khaldoon AWADH; Ayhan AKBAŞ
    In recent years, the use of machine learning and data mining technologies has drawn researchers’ attention to new ways to improve the performance of Intrusion Detection Systems (IDS). These techniques have proven to be an effective method in distinguishing malicious network packets. One of the most challenging problems that researchers are faced with is the transformation of data into a form that can be handled effectively by Machine Learning Algorithms (MLA). In this paper, we present an IDS model based on the decision tree C4.5 algorithm with transforming simulated UNSW-NB15 dataset as a pre-processing operation. Our model uses Term Frequency.Inverse Document Frequency (TF.IDF) to convert data types to an acceptable and efficient form for machine learning to achieve high detection performance. The model has been tested with randomly selected 250000 records of the UNSW-NB15 dataset. Selected records have been grouped into various segment sizes, like 50, 500, 1000, and 5000 items. Each segment has been, further, grouped into two subsets of multi and binary class datasets. The performance of the Decision Tree C4.5 algorithm with Multilayer Perceptron (MLP) and Naive Bayes (NB) has been compared in Weka software. Our proposed method significantly has improved the accuracy of classifiers and decreased incorrectly detected instances. The increase in accuracy reflects the efficiency of transforming the dataset with TF.IDF of various segment sizes.
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    MANAGING EBOLA AND COVID-19 CRISES FOR AVIATION INDUSTRY: DID INDUSTRY LEARN HOW TO LEARN?
    (Universidad del Quindio, 2022-04-22) H.Bahar Aşcı; R.Dilek Koçak; Alper B. Dalmış; Göçmen, Firdevs Didem
    Learning is necessary for an organization to evolve, improve and innovate. We are all conditioned to benefit from the evident effects of our behaviors. After the first try, we do not touch the hot stove again. We are also conditioned to recognize complex scenarios and apply fast solutions. Companies are like humans and they also learn as people do. From this point of view, the aviation industry is discussed in this study beyond the learning loops approach of Agrysis which is an effective tool that encourages the kind of thought and action that is needed to transform an organization into a learning one. Turkish Airlines, EasyJet, Delta Airlines, Air China, United Airlines, China Eastern Airlines, China Southern Airlines, American Airlines, Southwest Airlines and Ryanair had chosen as the sample of this study and data collected from the annual reports of these companies was analyzed with document analysis methodology. By comparing the crisis management styles of the industry during Ebola and Covid-19 Diseases the question “did the industry learn how to learn?” tried to be answered and as a result, the study found that the way the industry responded to both crises had not gone too far from single loop learning, or in other words, the industry had only given a reaction to the actions on time and forgot every experience till the next crisis. In the end, the study discussed that single loop learning style of airline companies may be the reason for the rapid spread of those kinds of diseases all over the world.
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    Rhetorical Structure Appearances in Memoir-Type Text
    (Cukurova University Faculty of Education Journal, 2022-12-30) Çağrı KAYGISIZ; Nermin YAZICI
    Writing skill, which includes many factors and complex processes, is the linguistic skill that receives the lowest amount of support in the out-of-school social context among learning areas. Therefore, practices conducted at schools for the development of writing skills are significant. Such practices are aimed toward students gaining awareness of the functioning of the language system and producing texts that are compatible with discourse features developed in line with communicative purposes. Therefore, theories and approaches that describe how to make choices that match specific text types are an important component of writing education. This study aims to determine the appearance of the units in memoir-type texts that allow tracking the coherence relations on the text surface with the establishment of rhetorical relations between sections of text using the tools of the rhetorical structure theory and review and discuss at an academic level why these tools should be taken into account in the processes of writing education.
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    USE OF MACHINE LEARNING TECHNIQUES FOR THE FORECAST OF STUDENT ACHIEVEMENT IN HIGHER EDUCATION
    (Institute of Information Technologies and Learning Tools of NAES of Ukraine, 2021-04-25) Омер Фарук Акмеше; Хакан Кьор; Хасан Ербей
    The machine learning method, which is a sub-branch of artificial intelligence and which makes predictions with mathematical and statistical operations, is used frequently in education as in every field of life. Nowadays, it is seen that millions of data are recorded continuously, and a large amount of data accumulation has occurred. Although data accumulation increases exponentially, the number of analysts and their capabilities to process these data are insufficient. Although we live in the information age, it is more accurate to say that we live in the data age. By using stored and accumulated data, it is becoming increasingly essential to reveal meaningful relationships and trends and to make predictions for the future. It is important to analyze the data obtained from the education process and to evaluate the success of the students and the factors affecting success. These analyses may also contribute to future training activities. In this study, a data set, including socio-demographic variables of students enrolled in distance education at Hitit University, was used. The authors estimated the success of the students with demographic and social variables such as age, gender, city, family income, family education level. The primary purpose is to provide students with information about their estimated academic achievement at the beginning of the process. Thus, at the beginning of the education process, students' success can be increased by informing the students who are predicted to be unsuccessful. Diversification and enhancement of this data may also support other decision-making mechanisms in the training process. Additionally, the factors affecting students’ academic success were researched, and the students' educational outcomes were evaluated. Prediction success was compared using various machine learning algorithms. As a result of the analysis, it was determined that the Random Forest algorithm was more predictive of student achievement than others.
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    Isı Borulu-Isı Geri Kazanım Ünitesinde ZnO/Su ve ZnOAl2O3/Su Nanoakışkanları Kullanılarak Performansın İyileştirilmesi
    (Politeknik Dergisi, 2022-03-01) İpek AYTAÇ; Adnan SÖZEN
    Endüstride ve birçok atık ısı tesislerinde kullanılan atık ısı geri kazanım üniteleri gerekli temiz havanın ön ısıtılmasında kullanılan sistemlerdir. Bu çalışmada ısı değiştiricisi ısı borusu olan bir ısı geri kazanım ünitesinin performansının iyileştirilmesi ve böylece çalışma sıcaklık aralığının arttırılması amacıyla oluşturulan deney düzeneği üzerinde uygulamalı bir çalışma yapılmıştır. Çalışmanın özgün yanı ısı değiştiricisi olarak kullanılan ısı borularında son yıllarda pek çok uygulama olanağı bulan nanoakışkanların kullanılması hedeflenmiştir. ZnO/Su ve ZnOAl2O3/Su nanoakışkanları ısı borusunda çalışma akışkanı olarak kullanılmış ve temel akışkan suya göre ısı geri kazanım ünitesi ısıl performansındaki iyileşme oranları belirlenmeye çalışılmıştır. Soğuk hava bölgesinde (kondenser), soğuk hava hızı 0.437m/s ve Re=7100 olduğunda ZnOAl2O3 ve ZnO nanoakışkanları için sırasıyla %90 ve %80 oranında iyileşme elde edilmiştir.
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    On the stability analysis of a fractional order epidemic model including the most general forms of nonlinear incidence and treatment function
    (Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 2023-10-10) Esra KARAOĞLU; Karaoğlu, Esra
    In this paper, we propose to study a SEIR model of fractional order with an incidence and a treatment function. The incidence and treatment functions included in the model are general nonlinear functions that satisfy some meaningful biological hypotheses. Under these hypotheses, it is shown that the disease free equilibrium point of the proposed model is locally and globally asymptotically stable when the reproduction number $R_{0} $ is smaller than 1. When $ R_{0}>1 $, it is established that the endemic equilibrium of the studied system is uniformly asymptotically stable. Finally, some numerical simulations are provided to illustrate the theory.
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    Aircraft Selection Decision Support Model for Fleet Planning of the Low Cost Airlines
    (Eskisehir Osmangazi University Journal of Economics and Administrative Sciences, 2023-08-01) Cem GÜNTUT; Meriç GÖKDALAY; Gökdalay, Meriç Hatice
    In this study, a decision support model was created for the aircraft type selection in the fleet planning decision of a low-cost airline and 21 sub criteria were determined for the model in five main groups as technical, economic, environmental, political and other criteria. In this decision support model, the Fuzzy TOPSIS and Fuzzy MOORA Multi Criteria Decision methods were applied, and 17 different narrow body aircraft types produced by Airbus, Boeing, Embraer, and Airbus/Bombardier aircraft manufacturers were evaluated. In the evaluation, it was found that Airbus A321NEO was the most preferable aircraft for the low-cost airline business model among the aircraft types.