Türkmen, Güzin

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Profile URL
https://hdl.handle.net/20.500.14411/7063
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
Main Affiliation
Computer Engineering
Status
Website
ORCID ID
0000-0003-0884-4876
Scopus Author ID
36020622300
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
G-9033-2019

Sustainable Development Goals

2

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11

SUSTAINABLE CITIES AND COMMUNITIES
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14

LIFE BELOW WATER
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6

CLEAN WATER AND SANITATION
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1

NO POVERTY
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5

GENDER EQUALITY
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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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17

PARTNERSHIPS FOR THE GOALS
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2

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15

LIFE ON LAND
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10

REDUCED INEQUALITIES
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7

AFFORDABLE AND CLEAN ENERGY
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8

DECENT WORK AND ECONOMIC GROWTH
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4

QUALITY EDUCATION
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4

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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3

GOOD HEALTH AND WELL-BEING
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Documents

10

Citations

121

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Documents

9

Citations

45

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Scholarly Output

23

Articles

9

Views / Downloads

90/279

Supervised MSc Theses

2

Supervised PhD Theses

0

WoS Citation Count

46

Scopus Citation Count

146

WoS h-index

3

Scopus h-index

5

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0

WoS Citations per Publication

2.00

Scopus Citations per Publication

6.35

Open Access Source

5

Supervised Theses

2

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JournalCount
UBMK 2018 - 3rd International Conference on Computer Science and Engineering -- 3rd International Conference on Computer Science and Engineering, UBMK 2018 -- 20 September 2018 through 23 September 2018 -- Sarajevo -- 1435604
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC -- 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'07 -- 3 September 2007 through 7 September 2007 -- Athens -- 721052
3rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEG2
International Journal of Computational and Experimental Science and Engineering2
Turkish Online Journal of Educational Technology1
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Now showing 1 - 10 of 23
  • Thumbnail Image
    Article
    Citation - WoS: 13
    Citation - Scopus: 29
    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
    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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    Conference Object
    Citation - WoS: 1
    An Undergraduate Curriculum for Deep Learning
    (Ieee, 2018) Tirkes, Guzin; Ekin, Cansu Cigdem; Sengul, Gokhan; Bostan, Atila; Karakaya, Murat
    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.
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    Conference Object
    Citation - Scopus: 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.
    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
    Developing a Data Warehouse for Distance Remote Laboratory
    (2007) Turkmen,G.; Cagiltay,N.E.
    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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    Master Thesis
    Üniversite Karar Destek Sistemi için Veri Ambarı Tasarımı
    (2007) Türkmen, Güzin; Çağıltay, Nergiz Ercil; Yazıcı, Ali
    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
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 49
    Open Source Learning Management Systems in E-Learning and Moodle
    (2010) Aydin,C.C.; Tirkes,G.
    In the last decade, the effect of Internet usage in education has increased gradually and new technologies have improved student's learning. By using distance learning tools, the student education can be more flexible with respect to place and time constraints. So, students can access information in every time and everywhere either in libraries or during the lectures. As is widely known that, distance learning is costly, and cost-effectiveness becomes more important as the institutions become large-scale providers of distance education. Cost which is the most important disadvantages of distance learning according to traditional learning environments can be removed with the extensive features of the Open Source Software. Generalizing the usage of Open Source Software will provide development of learning tools and increases the educational quality. As far as the literature is reviewed, not much research has already been conducted about the comparisons of open source learning management systems in distance education. In this study, some analyses and comparisons were made about open source learning management systems and Moodle was outstanding with many features among other LMS that aims to improve the educational quality and include the tools that an e-learning system should have. © 2010 IEEE.
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    Conference Object
    Deep Learning and Current Trends in Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Bostan,A.; Ekin,C.; Sengul,G.; Karakaya,M.; Tirkes,G.
    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. © 2018 IEEE.
  • Thumbnail Image
    Article
    Developing a Data Warehouse for Distance Remote Laboratory
    (IEEE, 2007) Türkmen, Güzin; Çağıltay, Nergiz
    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.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 2
    An Undergraduate Curriculum for Deep Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Tirkes,G.; Ekin,C.C.; Engul,G.; Bostan,A.; Karakaya,M.
    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. © 2018 IEEE.
  • Thumbnail Image
    Conference Object
    Deep Learning and Current Trends in Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2018) Bostan,A.; Ekin,C.; Sengul,G.; Karakaya,M.; Tirkes,G.
    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. © 2018 IEEE.