Türkmen, Güzin

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Name Variants
Tirkes G.
T.,Guzin
G.,Türkmen
T., Güzin
Güzin, Türkmen
G., Turkmen
Türkmen,G.
Tirkeş G.
Turkmen, Guzin
G.,Turkmen
T.,Güzin
Turkmen G.
Turkmen,G.
Guzin, Turkmen
Türkmen, Güzin
Türkmen G.
T., Guzin
Tirkes, Guzin
G., Türkmen
Job Title
Doktor Öğretim Üyesi
Email Address
guzin.turkmen@atilim.edu.tr
ORCID ID
0000-0003-0884-4876
Scopus Author ID
36020622300
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output

7

Articles

3

Citation Count

14

Supervised Theses

1

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Now showing 1 - 7 of 7
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    Conference Object
    Citation Count: 0
    Developing a data warehouse for distance remote laboratory
    (2007) Türkmen, Güzin; 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.
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    Article
    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, Arda; Türkmen,G.; Türkmen, Güzin; 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.
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    Article
    DEVELOPING A DATA WAREHOUSE FOR DISTANCE REMOTE LABORATORY
    (IEEE, 2007) Türkmen, Güzin; Çağıltay, Nergiz; 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.
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    Conference Object
    Citation Count: 4
    Distance laboratory applications ERRL: A study on radio communication in electronic field
    (2008) Özyurt, Erdem; Özbek, Mehmet Efe; Kara, Ali; Aydm,E.U.; Türkmen, Güzin; 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.
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    Conference Object
    Citation Count: 0
    Developing a data warehouse for distance remote laboratory
    (2007) Türkmen, Güzin; 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.
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    Article
    Citation Count: 10
    DEMAND FORECASTING: A COMPARISON BETWEEN THE HOLT-WINTERS, TREND ANALYSIS AND DECOMPOSITION MODELS
    (Univ Osijek, Tech Fac, 2017) Türkmen, Güzin; Guray, Cenk; Güray, Cenk; Çelebi, Neşe; 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.
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    Master Thesis
    Üniversite karar destek sistemi için veri ambarı tasarımı
    (2007) Türkmen, Güzin; Çağıltay, Nergiz; 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