Ekin, Cansu Çiğdem

Ekin, Cansu Çiğdem

Name Variants

Aydin, Cansu Cigdem
Cansu Cigdem, Ekin
E.,Cansu Çiğdem
Aydin C.
Ekin, Cansu Cigdem
Ekin, Cansu
Aydin, C. C.
E., Cansu Çiğdem
C. C. Ekin
E., Cansu Cigdem
C.C.Ekin
C.Ç.Ekin
C., Ekin
Ekin, Cansu Çiğdem
C. Ç. Ekin
E.,Cansu Cigdem
Ekin, Cansu C.
Ekin,C.C.
Cansu Çiğdem, Ekin
C.,Ekin
Ekin,C.Ç.
Ekin C.
Aydın, Cansu Ciğdem
Rouyendegh, Babak Daneshvar
Rouyendegh (B Erdebilli), Babak Daneshvar

Job Title

Doçent Doktor

Email Address

cansu.aydin@atilim.edu.tr

ORCID ID

0000-0003-4838-9708

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Scholarly Output

24

Articles

12

Citation Count

307

Supervised Theses

3 Scholarly Output Search Results

Now showing 1 - 10 of 24

Citation Count: 0
AI-Driven Drought Management System: A Turkish Case Study
(Institute of Electrical and Electronics Engineers Inc., 2023) Ekin, Cansu Çiğdem; Ekin,C.C.; Computer Engineering
Nowadays, drought is one of the trending topics in the world that has turned into a challenge for the world. By developing countries and cities worldwide, especially in the economic aspect, governments started to damage the environment such as through the use of fossil fuels, pollution of the seas, unregulated use of fresh water also deforestation for personal purposes. The presented research aims to change the format of drought mitigation strategies from traditional ways into the up to date treats. Leveraging AI technologies, including machine learning algorithms and data analytics, a comprehensive AI-driven drought management system is designed and implemented. In this system, inconsistent data have been obtained from the Ministry of Agriculture and Forestry organization and transformed into insightful data and analyzed in real-Time style to provide the status of agricultural products in Turkey. This research contributes to the fields of environmental science and agriculture by innovatively augmenting traditional approaches with AI-driven solutions. Ultimately, our research offers a means to monitor weather conditions in different regions of Turkey, moving beyond manual drought prediction and guesswork that were prevalent in previous systems. Additionally, it facilitates the evaluation of vegetation health by considering precipitation and temperature averages in each area. © 2023 IEEE.
Citation Count: 16
Design and development of a smart storytelling toy
(Routledge Journals, Taylor & Francis Ltd, 2014) Ekin, Cansu Çiğdem; Aydin, Cansu Cigdem; Cagiltay, Kursat; Computer Engineering
Because computers generally make children passive listeners, new technological devices need to support children's storytelling activities. This article introduces the StoryTech, a smart toy that includes a virtual space comprised of computer-based graphics and characters as well as a real space that involves stuffed animals, background cards and a receiver panel. When children put real objects on the receiver panel, the computer displays related backgrounds and characters. Through this flexible context, children are expected to tell a story about what they see on the screen. The aim of this article is to present the development period of the StoryTech and to provide design principles for smart toy technologies based on the usability study. The article focuses on attributes of new technology and the significance of supporting storytelling activities to find the best combination of and moderation between real and virtual spaces.
Makine öğrenme tekniklerini kullanarak öğrencinin akademik performansinin tahmin edilmesi
(2023) Ekin, Cansu Çiğdem; Ekin, Cansu Çiğdem; Computer Engineering
Son dönemde eğitim sektörü, dünya genelinde insanların en fazla ilgisini çeken sektörlerden biri haline gelmiş ve bu, bu sektöre yatırım yapmak ve gelir elde etmek isteyenler için daha değerli hale gelmiştir. Bu nedenle, bu alanı daha istikrarlı hale getirmek için büyük çaba harcanmaktadır. Öğrenciler, bu alandaki en büyük paydaşlardır ve bu nedenle eğitimde daha fazla dikkat gerektirirler. Tüm üniversiteler, öğrencilerinin memnuniyetini sağlamak ve eğitim kalitesini artırmak için çaba sarf etmektedir. Çünkü eğitim kalitesi, öğrencilerin başarı oranı ve kurumun öğrencilerini elinde tutma yeteneğine bağlıdır. Öğrenci performansını tahmin etmek, başarısızlık riski taşıyan öğrencileri tanımlamanın bir yolu olduğu için yönetim, öğrenci performansını artırmak için kararlar alabilir. Bu analizler, Eğitim Veri Madenciliği (EDM) olarak adlandırılan, sonuçlar üretmek için çok büyük veri kümelerini keşfedebilen Makine Öğrenimi (ML) alt kümesi aracılığıyla gerçekleştirilebilir. Bu çalışmanın ana amacı, en uygun veri madenciliği algoritmalarını kullanarak öğrenci akademik performansını tahmin etmek ve lisans düzeyinde bilgisayar mühendisliği öğrencilerinin performansını etkileyen faktörleri belirlemektir. Öğrenci akademik performansı, Final Notu, Çalışma Süresi ve Bir Sonraki Dönem Ders Notu olmak üzere üç farklı açıdan analiz edilmiştir. Sonuçlarımız, Destek Vektör Makinesi (SVM) ve Karar Ağacı (DT) gibi iki en iyi ML algoritmasının olduğunu göstermektedir ve ayrıca sadece Final Notunun tahminde en değerli faktör olduğunu göstermiştir.
Citation Count: 0
Contemporary Research Trends in Mobile Learning
(Springer Science and Business Media Deutschland GmbH, 2024) Ekin, Cansu Çiğdem; Algabsi,S.E.; Computer Engineering
This study attempts to conduct a bibliometric analysis of the structure and development of mobile learning research. For this, 7829 publications included in the Elsevier SCOPUS database between 1984 and 2021 were examined using bibliometric analysis by identifying key research areas, most influential authors, co-authorship status of countries, and organizations. As a result of this study, most topics related to mobile learning were Computer Science. “Mobile Learning” was the most used keyword followed by “e-learning” and “higher education”. Top performing organizations were in Taiwan. Taiwan was the major contributor in m-learning publications’ co-citation with other co-authorship countries. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Citation Count: 35
Selecting the Best Project Using the Fuzzy ELECTRE Method
(Hindawi Ltd, 2012) Ekin, Cansu Çiğdem; Erol, Serpil
Selecting projects is often a difficult task. It is complicated because there is usually more than one dimension for measuring the impact of each project, especially when there is more than one decision maker. This paper is aimed to present the fuzzy ELECTRE approach for prioritizing the most effective projects to improve decision making. To begin with, the ELECTRE is one of most extensively used methods to solve multicriteria decision making (MCDM) problems. The ELECTRE evaluation method is widely recognized for high-performance policy analysis involving both qualitative and quantitative criteria. In this paper, we consider a real application of project selection using the opinion of experts to be applied into a model by one of the group decision makers, called the fuzzy ELECTRE method. A numerical example for project selection is given to clarify the main developed result in this paper.
Citation Count: 2
Selection of working area for industrial engineering students
(Elsevier Science Bv, 2012) Ekin, Cansu Çiğdem; Can, Gulin Feryal
Selection of working area is one of the most important turning points in the human life. The main purpose of the selection of working area is planning a happy and successful future. There are many factors that interact with one another in this decision making process. In this study, in the content of these factors; feeling interest of lessons took in university education period, career opportunities for various working areas and gender are examined for 14 industrial engineering working areas. In addition, the scope of this study, we used Fuzzy Analytic Network Process (FANP) method to analyze these criteria and to determine the work areas wanted to work by industrial engineering students in order of priority.
Citation Count: 2
An Undergraduate Curriculum for Deep Learning
(Institute of Electrical and Electronics Engineers Inc., 2018) Bostan, Atila; Ekin,C.C.; Ekin, Cansu Çiğdem; Karakaya, Kasım Murat; Karakaya,M.; 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. © 2018 IEEE.
Citation Count: 3
Improving the creativity in introductory engineering course applying fuzzy network process: a pilot study
(Elsevier Science Bv, 2011) Ergin, Merve Hande; Ergin, Merve Hande; Ekin, Cansu Çiğdem; Industrial Engineering
In Engineering Design course, students' background, knowledge and skills should be considered to stimulate the creativity. Thus, the Analytic Network Process (ANP) has been used in deciding the factor that ignites creativity. However, there is uncertainty and vagueness existing in the judgment of students' need and expectations. Fuzzy ANP approach is used to determine a way in improving the creativity of the students in introductory engineering course. ANP equipped with fuzzy logic helps in overcoming the impreciseness in the preferences. The findings will help the instructor to improve and modify the delivery of the course to meet the course objectives. (C) 2011 Published by Elsevier Ltd.
Citation Count: 63
An Application of the Fuzzy ELECTRE Method for Academic Staff Selection
(Wiley, 2013) Erkan, Turan Erman; Erkan, Turan Erman; Ekin, Cansu Çiğdem; Industrial Engineering
There are various methods regarding staff selection in different fields. Thanks to the increasing improvements in the field of education, universities around the world tend to demand high -quality and professional academic staff. Staff selection is a multi-criteria decision-making processes, and of strategic importance for most universities. This study deals with actual application of academic of staff selection using the opinion of experts to be applied into a model of group decision - making called the Fuzzy ELECTRE (Elimination Et Choix Traduisant la REaite) method. There are ten qualitative criteria for selecting the best candidate amongst five prospective applications. (c) 2012 Wiley Periodicals, Inc.
Citation Count: 17
Evaluating Projects Based on Intuitionistic Fuzzy Group Decision Making
(Hindawi Ltd, 2012) Ekin, Cansu Çiğdem
There are various methods regarding project selection in different fields. This paper deals with an actual application of construction project selection, using two aggregation operators. First, the opinion of experts is used in a model of group decision making called intuitionistic fuzzy TOPSIS (IFT). Secondly, project evaluation is formulated by dynamic intuitionistic fuzzy weighted averaging (DIFWA). Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers (DMs) for rating the importance of criteria and alternatives. A numerical example for project selection is given to clarify the main developed result in this paper.

Ekin, Cansu Çiğdem

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Scholarly Output

24

Articles

12

Citation Count

307

Supervised Theses

3

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