Browsing by Author "Türkmen, Güzin"

Now showing 1 - 14 of 14

Citation Count: 0
Comparative Analysis of Programming Languages Utilized in Artificial Intelligence Applications: Features, Performance, and Suitability
(Prof.Dr. İskender AKKURT, 2024) Türkmen,G.; Sezen,A.; Şengül,G.; Computer Engineering
This study presents a detailed comparative analysis of the foremost programming languages employed in Artificial Intelligence (AI) applications: Python, R, Java, and Julia. These languages are analysed for their performance, features, ease of use, scalability, library support, and their applicability to various AI tasks such as machine learning, data analysis, and scientific computing. Each language is evaluated based on syntax and readability, execution speed, library ecosystem, and integration with external tools. The analysis incorporates a use case of code writing for a linear regression task. The aim of this research is to guide AI practitioners, researchers, and developers in choosing the most appropriate programming language for their specific needs, optimizing both the development process and the performance of AI applications. The findings also highlight the ongoing evolution and community support for these languages, influencing long-term sustainability and adaptability in the rapidly advancing field of AI. This comparative assessment contributes to a deeper understanding of how programming languages can enhance or constrain the development and implementation of AI technologies. © IJCESEN.
Citation Count: 0
A Comparative Analysis of XGBoost and LightGBM Approaches for Human Activity Recognition: Speed and Accuracy Evaluation
(Prof.Dr. İskender AKKURT, 2024) Sezen,A.; Türkmen,G.; Computer Engineering
Human activity recognition is the process of automatically identifying and classifying human activities based on data collected from different modalities such as wearable sensors, smartphones, or similar devices having necessary sensors or cameras capturing the behavior of the individuals. In this study, XGBoost and LightGBM approaches for human activity recognition are proposed and the performance and execution times of the proposed approaches are compared. The proposed methods on a dataset including accelerometer and gyroscope data acquired using a smartphone for six activities. The activities are laying, sitting, standing, walking, walking downstairs, and walking upstairs. The available dataset is divided into training and test sets, and proposed methods are trained using the training set, and tested on the test sets. At the end of the study, 97.23% accuracy using the LightGBM approach, and 96.67% accuracy using XGBoost is achieved. It is also found that XGBoost is faster than the LightGBM, whenever the execution times are compared. © IJCESEN.
Citation Count: 0
Deep Learning and Current Trends in Machine Learning
(Ieee, 2018) Bostan, Atila; Sengul, Gokhan; Tirkes, Guzin; Ekin, Cansu; Karakaya, Murat; Computer Engineering
Academic interest and commercial attention can be used to identify how much potential a novel technology may have. Since the prospective advantages in it may help solving some problems that are not solved yet or improving the performance of readily available ones. In this study, we have investigated the Web of Science (WOS) indexing service database for the publications on Deep Learning (DL), Machine Learning (ML), Convolutional Neural Networks (CNN), and Image Processing to reveal out the current trend. The figures indicate the strong potential in DL approach especially in image processing domain.
Citation Count: 10
DEMAND FORECASTING: A COMPARISON BETWEEN THE HOLT-WINTERS, TREND ANALYSIS AND DECOMPOSITION MODELS
(Univ Osijek, Tech Fac, 2017) Tirkes, Guzin; Guray, Cenk; Celebi, Nes'e; Computer Engineering; Department of Metallurgical and Materials Engineering; Industrial Engineering
In food production industry, forecasting the timing of demands is crucial in planning production scheduling to satisfy customer needs on time. In the literature, several statistical models have been used in demand forecasting in Food and Beverage (F&B) industry and the choice of the most suitable forecasting model remains a central concern. In this context, this article aims to compare the performances between Trend Analysis, Decomposition and Holt-Winters (HW) models for the prediction of a time series formed by a group of jam and sherbet product demands. Data comprised the series of monthly sales from January 2013 to December 2014 obtained from a private company. As performance measures, metric analysis of the Mean Absolute Percentage Error (MAPE) is used. In this study, the HW and Decomposition models obtained better results regarding the performance metrics.
DEVELOPING A DATA WAREHOUSE FOR DISTANCE REMOTE LABORATORY
(IEEE, 2007) Türkmen, Güzin; Çağıltay, Nergiz; Computer Engineering; Software Engineering
Data warehouse is an important contemporary issue for many organizations and is relatively a new field in the realm of information technology. As data warehousing, e learning is also a new field. Little research has been done regarding the special considerations and characteristics of academic data and the complexity of analyzing such data. Educational institutions measure success very differently from business-oriented organizations and the analyses that are meaningful in such environments cause unique problems in data warehousing. Especially for the educational purposes, data warehouses offer several benefits. This paper discusses the use of Data Warehouse and Decision Support resources to aid in the assessment of Distance Remote Laboratory Environment.
Citation Count: 0
Developing a data warehouse for distance remote laboratory
(Ieee, 2007) Turkmen, Guzin; Cagiltay, Nergiz Ercil; Computer Engineering; Software Engineering
Data warehouse is an important contemporary issue for many organizations and is relatively a new field in the realm of information technology. As data warehousing, e-learning is also a new field. little research has been done regarding the special considerations and characteristics of academic data and the complexity of analyzing such data. Educational institutions measure success very differently from business-oriented organizations and the analyses that are meaningful in such environments cause unique problems in data warehousing. Especially for the educational purposes, data warehouses offer several benefits. This paper discusses the use of Data Warehouse and Decision Support resources to aid in die assessment of Distance Remote Laboratory Environment.
Citation Count: 0
Developing a data warehouse for distance remote laboratory
(2007) Turkmen,G.; Cagiltay,N.E.; Computer Engineering
Data warehouse is an important contemporary issue for many organizations and is relatively a new field in the realm of information technology. As data warehousing, e-learning is also a new field. Little research has been done regarding the special considerations and characteristics of academic data and the complexity of analyzing such data. Educational institutions measure success very differently from business-oriented organizations and the analyses that are meaningful in such environments cause unique problems in data warehousing. Especially for the educational purposes, data warehouses offer several benefits. This paper discusses the use of Data Warehouse and Decision Support resources to aid in the assessment of Distance Remote Laboratory Environment.
Citation Count: 0
Developing a data warehouse for distance remote laboratory
(2007) Turkmen,G.; Cagiltay,N.E.; Computer Engineering
Data warehouse is an important contemporary issue for many organizations and is relatively a new field in the realm of information technology. As data warehousing, e-learning is also a new field. Little research has been done regarding the special considerations and characteristics of academic data and the complexity of analyzing such data. Educational institutions measure success very differently from business-oriented organizations and the analyses that are meaningful in such environments cause unique problems in data warehousing. Especially for the educational purposes, data warehouses offer several benefits. This paper discusses the use of Data Warehouse and Decision Support resources to aid in the assessment of Distance Remote Laboratory Environment.
Citation Count: 4
Distance laboratory applications ERRL: A study on radio communication in electronic field
(2008) Aydin,C.Ç.; Türkmen,G.; Özyurt,E.; Aydm,E.U.; Çaǧiltay,N.E.; Özbek,M.E.; Kara,A.; Department of Electrical & Electronics Engineering; Computer Engineering
In the last decade, the effect of internet usage in education is gradually increased. When we look from academic perspective, the new technologies provided alternatives for students learning. As distance education becomes important everyday, the indispensable elements of teaching and education, laboratories must be reachable via remote connection. Consequently, the education that is going to be given to the students will be more flexible with respect to place and time constraints and students can reach laboratory facilities at any time and anywhere not only in lectures and practical hours. In this study, European Remote Radio Laboratory (ERRL) which is a distance remote Radio Frequency (RF) laboratory designed for electrical-electronics students, is described generally. The software architecture, infrastructure and experiment that can be done with a remote connection have been described.
Citation Count: 3
Online Learning Perceptions amid COVID-19 Pandemic: The Engineering Undergraduates' Perspective
(Tempus Publications, 2022) Eryilmaz, Meltem; Kalem, Guler; Kilic, Hurevren; Tirkes, Guzin; Topalli, Damla; Turhan, Cigdem; Yazici, Ali; Information Systems Engineering; Computer Engineering; Software Engineering
The COVID-19 pandemic caused face-to-face education in just about all universities worldwide to shift to online education. For most students, this educational model was a compulsory first experience. In this study, the survey results are analyzed and discussed related to a group of students in the Engineering Faculty of a university in Turkey regarding their online education perceptions. Briefly summarized, the findings of the study indicate that: (a) most of the students still prefer face-to-face learning, which is also favored if accompanied by distance learning; (b) the concentration level of the students has dropped due to the concerns about the COVID-19 pandemic which affects their learning negatively; and (c) around half of the students participating in the study feel that the online exams conducted without a secure exam software, is considered unsafe. Additionally, the study's results were further extended to evaluate the questionnaire results and reported along with the suggestions of necessary actions in emergency online learning (EOL).
Citation Count: 35
OPEN SOURCE LEARNING MANAGEMENT SYSTEMS IN DISTANCE LEARNING
(Turkish online Journal Educational Tech-tojet, 2010) Aydin, Cansu Cigdem; Tirkes, Guzin; Computer Engineering
This paper presents the major findings from evaluation the most widely used open source learning management systems and identify the most suitable open source e-learning platform. In this study, some analyses and comparisons were made about open source learning management systems the outcome of which was that Moodle was found to be outstanding with many features more than other LMS since it aims to improve the educational quality and include the tools that an e-learning system should have.
Citation Count: 0
Post-Pandemic Hybrid Curriculum Recommendations for an Undergraduate ICT Senior Project Course
(Tempus Publications, 2023) Tirkes, Guzin; Kalem, Guler; Kilic, Hurevren; Cagiltay, Nergiz Ercil; Computer Engineering; Software Engineering
Among the numerous aspects of everyday life affected by the COVID-19 pandemic, education stands out as one of those deeply impacted. In this context within university settings, the ICT senior project courses were no exception either. This study presents the recommendations for a hybrid curriculum based on the online implementation of a senior project course in the ICT departments of an engineering faculty. The data were collected to better understand the impact of this re-structured course on 99 undergraduate IT students and their projects during three semesters, and later analyzed qualitatively and quantitatively to obtain some insights. The results indicate that, during the pandemic, the students adapted their senior project studies to the related restrictions by changing certain aspects related to the project, improving their teamwork, and increasing the level of communication. However, they also reported certain problems related to their overall psychology as well as social interactions. In light of the pandemic effect on the software industry towards remote working environments, further suggestions are provided to eliminate the drawbacks of remote working reported by the students and to equip them with the necessary skills. The resulting recommendations could be used by other higher -education institutions and be further adjusted for application in other disciplines.
Citation Count: 1
An Undergraduate Curriculum for Deep Learning
(Ieee, 2018) Tirkes, Guzin; Ekin, Cansu Cigdem; Sengul, Gokhan; Bostan, Atila; Karakaya, Murat; Computer Engineering
Deep Learning (DL) is an interesting and rapidly developing field of research which has been currently utilized as a part of industry and in many disciplines to address a wide range of problems, from image classification, computer vision, video games, bioinformatics, and handwriting recognition to machine translation. The starting point of this study is the recognition of a big gap between the sector need of specialists in DL technology and the lack of sufficient education provided by the universities. Higher education institutions are the best environment to provide this expertise to the students. However, currently most universities do not provide specifically designed DL courses to their students. Thus, the main objective of this study is to design a novel curriculum including two courses to facilitate teaching and learning of DL topic. The proposed curriculum will enable students to solve real-world problems by applying DL approaches and gain necessary background to adapt their knowledge to more advanced, industry-specific fields.
Üniversite karar destek sistemi için veri ambarı tasarımı
(2007) Türkmen, Güzin; Çağıltay, Nergiz Ercil; Yazıcı, Ali; Computer Engineering; Software Engineering
Veri ambarı bir çok organizasyon için çagdas bir meseledir ve bilgi teknolojileri için yeni bir alandır. Özellikle egitimsel amaçlı kullanımda, veri ambarları birçok fayda saglar. Veri ambarları yeni bir alan oldugundan, akademik veri yapıları ve bu veriyi analiz etmedeki karmasa ile ilgili çok az sayıda arastırma yapılmıstır. Egitim kurumları basarıyı, ticari amaçlı organizasyonlardan çok farklı ölçer ve bu çevrede anlamlı olan analizler veri ambarlamada nadir problemler ortaya çıkarır. Bu tezin amacı, var olan Ögrenci Bilgi Sisteminden (MasterSIS) alınan veriyi sorgulayacak bir karar destek sistemi hazırlamak ve Atılım Üniversitesi Yüksek Lisans Programı'nda akademik karar vermeyi destekleyici rapor çıktıları almayı saglamaktır. Anahtar Kelimeler: Karar Destek Sistemleri, Veri Ambarı, Egitim