Person: ÜLKÜ, EYÜP EMRE
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ÜLKÜ
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EYÜP EMRE
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Publication Metadata only Forecasting greenhouse gas emissions based on different machine learning algorithms(2022-01-01) ÜLKÜ, EYÜP EMRE; Ulku I., ÜLKÜ E. E.© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.With the increase in greenhouse gas emissions, climate change is occurring in the atmosphere. Although the energy production for Turkey is increased at a high rate, the greenhouse gas emissions are still high currently. Problems that seem to be very complex can be predicted with different algorithms without difficulty. Due to fact that artificial intelligence is often included in the studies to evaluate the solution performance and make comparisons with the obtained solutions. In this study, machine learning algorithms are used to compare and predict greenhouse gas emissions. Carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), and fluorinated gases (F-gases) are considered direct greenhouse gases originating from the agriculture and waste sectors, energy, industrial processes, and product use, within the scope of greenhouse gas emission statistics. Compared to different machine learning methods, support vector machines can be considered an advantageous estimation method since they can generalize more details. On the other hand, the artificial neural network algorithm is one of the most commonly used machine learning algorithms in terms of classification, optimization, estimation, regression, and pattern tracking. From this point of view, this study aims to predict greenhouse gas emissions using artificial neural network algorithms and support vector machines by estimating CO2, CH4, N2O, and F-gases from greenhouse gases. The data set was obtained from the Turkish Statistical Institute and the years are included between 1990 and 2019. All analyzes were performed using MATLAB version 2019b software.Publication Metadata only A Performance Way Comparison of Docker Swarm and Kubernetes(2022-12-21) ÜLKÜ, EYÜP EMRE; Yurtsever O., ÜLKÜ E. E.People always try to find the best way to deploy their applications. Thus, the first solution was bare metal servers. In the bare metal server solution, each server was responsible for one application but that required as many servers as the number of applications, and in addition that this solution also required so much space in the server room. Subsequently, virtualization technology emerges. This technology is based on the abstraction of computer hardware. Virtualization technology enables us to host multiple operating systems in one host. Virtualization brings along with many advantages. One of the significant benefits is to reduce the quantity of physical equipment needed in the data center and helps to scale our applications. One of the remarkable developments in information technologies is container technology which emerged in the middle of 2010. Containers allow to package an application with all the parts it needs, such as libraries and other dependencies, and deliver it as a single package. Docker, developed by Google, is the essential tool to use in container technologies. Docker resembles a virtual machine, but as opposed to a virtual machine, instead of creating a whole virtual operating system, Docker allows applications to use the same Linux kernel as the system they use. This provides a performance boost and reduces the size of the application. Also, the development of microservice-based applications in recent years has made container technologies widely used. Now, we can run each of our applications, perhaps thousands of containers. However, this solution brings with it another problem, how do we manage these containers? In recent years, there have been a few breaks in the server side, which underlies the rapidly developing information technologies. The last of these is container technology. Before virtualization, companies were running all their applications on physical servers, and these systems were getting complex over time, making even simple problems inextricable. Accordingly, in this study we compare Docker Swarm and Kubernetes in terms of their performances under heavy load, two of the most used tools for container management. Thus, we aim to inform readers about container management.Publication Metadata only Forecasting greenhouse gas emissions based on different machine learning algorithms(Springer, Cham, 2022-01-01) ÜLKÜ, EYÜP EMRE; ÜLKÜ İ., ÜLKÜ E. E.With the increase in greenhouse gas emissions, climate change is occurring in the atmosphere. Although the energy production for Turkey is increased at a high rate, the greenhouse gas emissions are still high currently. Problems that seem to be very complex can be predicted with different algorithms without difficulty. Due to fact that artificial intelligence is often included in the studies to evaluate the solution performance and make comparisons with the obtained solutions. In this study, machine learning algorithms are used to compare and predict greenhouse gas emissions. Carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), and fluorinated gases (F-gases) are considered direct greenhouse gases originating from the agriculture and waste sectors, energy, industrial processes, and product use, within the scope of greenhouse gas emission statistics. Compared to different machine learning methods, support vector machines can be considered an advantageous estimation method since they can generalize more details. On the other hand, the artificial neural network algorithm is one of the most commonly used machine learning algorithms in terms of classification, optimization, estimation, regression, and pattern tracking. From this point of view, this study aims to predict greenhouse gas emissions using artificial neural network algorithms and support vector machines by estimating CO2, CH4, N2O, and F-gases from greenhouse gases. The data set was obtained from the Turkish Statistical Institute and the years are included between 1990 and 2019. All analyzes were performed using MATLAB version 2019b software.Publication Metadata only Applying social networks to engineering education(WILEY, 2018) DOĞAN, BUKET; Dogan, Buket; Demir, Onder; Ulku, Eyup E.Social networking sites (SNSs) are a popular Internet-based means for users to communicate and interact with each other. Although they have caught the attention of many researchers and are already being used as educational tools, very few studies have investigated the effects of using an SNS in engineering education. This study, therefore, aims to analyze the effects of using the Edmodo platform as a teaching and learning support tool on students' academic and practical performance in the Introduction to Information Technology and Algorithms course, as well as in the Computer Programming course they took in the following semester. It also considers the students' opinions about the Edmodo system. For this study, a total of 62 students studying in the Electrical and Electronics Engineering Department during the 2016-2017 fall semester were divided into two equally sized groups. The control group underwent a traditional face-to-face education, whereas the experimental group augmented this using the Edmodo system. A mixed-methods approach with a post-test-only control group design was used: quantitative data were obtained from student tests, together with qualitative data from follow-up interviews. The students' grades were analyzed using Student's t-test and correlation analysis, showing that the experimental group performed better in their academic and laboratory assessments and that there was a moderately positive relationship between the post-test results and performance in the subsequent Computer Programming course.Publication Metadata only Detection of suspicious activities on windows systems with log analysis(2022-12-21) ÜLKÜ, EYÜP EMRE; Öztürk A., ÜLKÜ E. E.In recent years, rapid technological developments in many different fields have brought along various problems along with many innovations. One of these problems is cyber-attacks. Storing many records and data in digital media has made it very important to protect these records and data. Continuous log records play an important role in taking necessary precautions against cyber-attacks by system administrators. With the logging mechanism found in Windows systems, every transaction made on the system is recorded. These log records are analyzed with various algorithms and tools. As a result of these analyzes, suspicious or attacker behaviors on the system are detected. In this study, various cyber-attacks were tested in an environment where these Windows systems are located. As a result of these tests, the logs formed in the systems were collected and analyzed with the ELK Stack toolkit. As a result of these analyzes, the attacks were determined and associated with the tactics and techniques on Mitre ATT & CK.Publication Metadata only Municipal solid waste management: A case study utilizing DES and GIS(2023-10-02) ÇALIŞ USLU, BANU; DOĞAN, BUKET; ÜLKÜ, EYÜP EMRE; Çaliş Uslu B., Kerçek V. A., Şahin E., Perera T., Doğan B., Ülkü E. E.This research aims to compare two well-known solution methodologies, namely Geographical Information Systems (GIS) and Discrete Event Simulation (DES), which are used to design, analyze, and optimize the solid waste management system based on the locations of the garbage bins. A significant finding of the study was that the application of the simulation methodology for a geographical area of a size of 278km2was challenging in that the addition of the geographical conditions to the developed model proved to be time-consuming. On the other hand, the simulation model that was developed without adding geographical conditions revealed that the number of bins could be reduced by 60.3% depending on the population size and garbage density. However, this model could not be implemented since the required walking distance was higher than 75 m, which is greater than the distance the residents could be reasonably expected to travel to reach a bin. Thus, using a cutoff value of 75 m, the total number of bins can be reduced by 30% on average with regard to the result obtained from the GIS-based solution. This can lead to an annual cost reduction of 93.706 € on average in the collection process and carbon dioxide release reduction of 18% on average.Publication Metadata only Yazılım geli̇şti̇rme projeleri̇nde farklı konumlarda çalışmanın etki̇leri̇(2022-06-17) ÜLKÜ, EYÜP EMRE; DOĞAN, BUKET; Şahin Aktaş H., ÜLKÜ E. E., DOĞAN B.Publication Metadata only Raspbraille: Conversion to braille alphabet with optical character recognition and voice recognition algorithm(2022-01-01) YILDIZ, KAZIM; ÜLKÜ, EYÜP EMRE; BÜYÜKTANIR, BÜŞRA; DALIP F., YILDIZ K., ÜLKÜ E. E. , BÜYÜKTANIR B.