WOS - Web of Science
Permanent URI for this collectionhttps://acikarsiv.thk.edu.tr/handle/123456789/2552
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Publication 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, TürkiyeStar 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.Publication 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 GüngörWaste 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.Publication 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 YAVUZBu 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.Publication Intrapreneurship and expectations restrictions(Universidad Autonoma del Caribe, 2020-02-28) Olcay Okun; Korhan Arun; Suat BegecThis article develops arguments about the factors that promote intrapreneurship in relation to role theory. These are based on contributions from interactional and structural sociology. Fixed theoretical tools for intrapreneurship are not enough. So, the structural and interactionist perspective of sociology is necessary to understand the concept of intrapreneurship. The above approaches depend on individuals, organizations or environments to encourage potential employees to be intrapreneurs. Thus, Expectations can be a cornerstone for intrapreneurship because intrapreneurs learn from their roles.Publication The Use of Machine Learning Approaches for the Diagnosis of Acute Appendicitis(Hindawi Limited, 2020-04-25) Omer F. Akmese; Gul Dogan; Hakan Kor; Hasan Erbay; Emre DemirAcute appendicitis is one of the most common emergency diseases in general surgery clinics. It is more common, especially between the ages of 10 and 30 years. Additionally, approximately 7% of the entire population is diagnosed with acute appendicitis at some time in their lives and requires surgery. The study aims to develop an easy, fast, and accurate estimation method for early acute appendicitis diagnosis using machine learning algorithms. Retrospective clinical records were analyzed with predictive data mining models. The predictive success of the models obtained by various machine learning algorithms was compared. A total of 595 clinical records were used in the study, including 348 males (58.49%) and 247 females (41.51%). It was found that the gradient boosted trees algorithm achieves the best success with an accurate prediction success of 95.31%. In this study, an estimation method based on machine learning was developed to identify individuals with acute appendicitis. It is thought that this method will benefit patients with signs of appendicitis, especially in emergency departments in hospitals.Publication Intrusion Detection Model Based on TF.IDF and C4.5 Algorithms(Politeknik Dergisi, 2021-12-01) Khaldoon AWADH; Ayhan AKBAŞIn 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.Publication 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 DidemLearning 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.Publication Rhetorical Structure Appearances in Memoir-Type Text(Cukurova University Faculty of Education Journal, 2022-12-30) Çağrı KAYGISIZ; Nermin YAZICIWriting 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.Publication 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 ЕрбейThe 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.Publication A New Model of Team Teaching for Teacher Professional Development: A Case Study of In-Service English Teachers(Turkish Education Association, 2020-01-15) Özlem Canaran; İsmail Hakkı Mirici