Bulgun, Ender

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Profile URL
https://hdl.handle.net/20.500.14365/7666
Name Variants
Bulgun, EY
Bulgun E.Y.
Bulgun, Ender Yazgan
Job Title
Email Address
ender.bulgun@ieu.edu.tr
Main Affiliation
06.02. Fashion and Textile Design
Status
Current Staff
Website
ORCID ID
0000-0002-8747-9434
Scopus Author ID
12793953400
Turkish CoHE Profile ID
14AEDB1778AE72F2
Google Scholar ID
jkNFBz4AAAAJ
WoS Researcher ID
EPI-2757-2022
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Ender_Yazgan_Bulgun.png (121.36 KB)

Sustainable Development Goals

NO POVERTY1
NO POVERTY
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ZERO HUNGER2
ZERO HUNGER
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GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
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QUALITY EDUCATION4
QUALITY EDUCATION
0
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GENDER EQUALITY5
GENDER EQUALITY
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
3
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REDUCED INEQUALITIES10
REDUCED INEQUALITIES
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SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
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CLIMATE ACTION13
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LIFE BELOW WATER14
LIFE BELOW WATER
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LIFE ON LAND15
LIFE ON LAND
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
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PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
1
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Documents

17

Citations

251

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Documents

16

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186

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Scholarly Output

12

Articles

10

Views / Downloads

37/86

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

35

Scopus Citation Count

104

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Projects

4

WoS Citations per Publication

2.92

Scopus Citations per Publication

8.67

Open Access Source

9

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JournalCount
Tekstil ve Mühendis3
Industria Textila2
International Journal of Clothing Science and Technology1
2013 21st Signal Processing and Communications Applications Conference, SIU 20131
Journal of Textiles and Engineer1
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Now showing 1 - 10 of 12
  • Thumbnail Image
    Article
    Citation - Scopus: 54
    Identification of Female Body Shapes Based on Numerical Evaluations
    (2011) Vuruskan A.; Bulgun E.
    Purpose: Identification of human body shapes has been a key issue to develop sizing standards for ready-to-wear and to develop made-to-measure applications. Current methods to identify the body shapes are mostly based on subjective/visual determination approaches. The purpose of this paper is to look for numerical evaluation parameters for an objective method in order to classify the body shapes and to build up an automated process link. Design/methodology/approach: Female subjects were chosen for the experimental design. 3D body scanning technology was integrated in the process for measurement taking and body silhouette detection of the sample group. Based on this sample data set, body shape identification was realized by referees as visual analyses, and additionally, an objective method was tried out by using body dimensions as numerical evaluation parameters. Obtained results with the sample group were inserted in a database and a body shape calculation tool was developed. Findings: Statistical analyses showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. The calculation tool was designed as web-based software in order to integrate with further developments and automation purposes. Originality/value: A new automatic tool was developed to make the body shape classification objective and repeatable. By integrating this tool to the product development chain, a continuous process link can be provided for the companies through the way for better fitting clothing. © Emerald Group Publishing Limited.
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    Article
    Citation - WoS: 21
    Citation - Scopus: 26
    Intelligent fashion styling using genetic search and neural classification
    (Emerald Group Publishing Ltd, 2015) Vuruşkan, Arzu; İnce, Türker; Bulgun, Ender; Guzelis, Cuneyt
    Purpose - The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes. Design/methodology/approach - With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style. Findings - The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling. Originality/value - The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.
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    Article
    Kişiye Özel Giysiler için Vücuda Uygunluk Analizi
    (2013) Bulgun, Ender; Gündoğan, Arzu Vuruşkan
    Giysilerde vücuda uygunluk ölçütü, tüketici memnuniyetini ve satın alma kararını etkileyen en önemli parametrelerden birisidir. Son yıllarda önemi gittikçe artan ve önemli bir rekabet avantajı sağlayacağı öngörülen kişiye özel giysilerin vücuda uygunluğu ve standart bedenler ile karşılaştırılması bu açıdan önem taşımaktadır. Bu çalışmada, en sık rastlanan kadın vücut şekillerini örnek alarak, m-t-m ve standart beden giysiler arasında vücuda uygunluk değerlendirmesi yapılmıştır. Sonuç olarak, m-t-m pantolonların daha iyi uyum gösterdiği belirlenmiştir. Standart beden pantolonlar özellikle küçük beden gruplarında iyi uyuma karşılık gelmektedir. Ancak çalışmaya katılan büyük bedenlerin tümünde standart pantolonlar için problem yaşandığı görülmüştür. Bu durum kişiye özel üretimin daha çok büyük bedenler veya standart dışı vücut şekilleri için gerekliliğini ortaya koymuştur.
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    Research Project
    Genetik Arama ve Artımlı Öğrenen Yapay Sinir Ağı Sınıflayıcı Topluluklarına Dayalı Giysi Tasarım Algoritması ve Web Tabanlı Bir Giysi Öneri Platformunun Geliştirilmesi
    (2017) Bulgun, Ender; İnce, Türker; Güzeliş, Cüneyt; Vuruşkan, Arzu
    Bu proje kapsamında, farklı vücut şekillerine uygun giysi tasarımı önerilerinin kullanıcılara sunulabilmesi için, genetik arama ve yapay sinir ağı sınıflandırması ile web tabanlı bir giysi tasarım platformu geliştirilmiştir. Çalışmada öncelikle, vücut şekli ve giysi formu arasında uyumu hedefleyerek, üst beden ve alt beden giysilerinin kombinasyonları veya elbise modelleri ile bunlara ait ayrıntıları içeren öznitelik kategorileri yaratılarak bir bilgi tabanı oluşturulmuştur. Tasarım önerilerinin geliştirilmesi ve kullanıcıya sunulması için 2 boyutlu 2080 giysi tasarımından oluşan bir arşiv yaratılmış ve 4 farklı vücut şekline uygun giysi kombinasyon örnekleri belirlenmiştir. Çalışmanın sonraki aşamasında, tasarım önerilerinin kullanıcıya sunulacağı etkileşimli web tabanlı bir platform tasarlanmıştır. Tasarlanan platformda, ilk olarak Yapay Sinir Ağı (YSA) sınıflayıcı olarak mevcut literatürden farklı olmak üzere, her bir giysi özelliğinin vücut şekli ile ilişkisini artımlı öğrenebilen YSA toplulukları kullanılmıştır. Böylece, kullanıcıların geri bildirimleriyle, sistemin sürekli bir biçimde artımlı olarak kendini geliştirmesi sağlanmıştır. Ancak, bu geliştirilen akıllı sistem yapısının artımlı öğrenme performansının istikrarlı olmadığı gözlenmiş ve iyileştirilememiştir. Artımlı öğrenme amacını YSA sınıflandırıcıları ile gerçekleştirmek yerine, Etkileşimli Genetik Algoritma (EGA) yöntemine başvurulmuştur ve özgün bir ?Artımlı Öğrenme ve Önerme Metodolojisi? geliştirilmiştir. Bu geliştirilen metodoloji ile gerçekleştirilen giysi öneri platformunun aynı anda artımlı öğrenme performansı ile vücut şekli/giysi şekli uyumluluğu performansı sanal kullanıcılar kullanılarak sınanmış ve iyi sonuçlar alınmıştır. Test aşamasının sonunda gerçek kullanıcılar ile yapılan anket neticesinde de, algısal olarak artımlı öğrenim sağlanmıştır. Gerçekleştirilen proje; 1)kadın vücut şekli ve giysi formu arasında uyumu hedefleyen giysi tasarımının akıllı sistemler ile gerçekleştirilmesi, 2)GA ve YSA?ya dayalı artımlı öğrenen bir akıllı sistem kullanılarak otomatik bir giysi tasarım süreci ve giysi öneri platformunun tasarlanması ve 3) geliştirilen akıllı sistemin kullanıcı etkileşimine dayalı olarak artımlı öğrenebilmesi, 4) böylece kişiye özel bir tasarım öneri sisteminin elde edilmesi açısından literatüre katkı sağlamaktadır.
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    Article
    Citation - Scopus: 3
    Fit Analysis for Made-To Garments
    (2013) Vuruşkan A.; Bulgun E.
    For apparel products, fit of the garments is one of the most important parameters affecting the customer satisfaction and the buying decision. Made-to-measure garments are expected to create a competitive advantage in the market and therefore, comparisons of the fit of standard sizes and the made-to-measure garments carry a great importance. In this study, by choosing the most typical female body shapes, fitting of standard and m-t-m garments were compared. Based on the trials of sample groups, it was seen that the fit of m-t-m garments were more satisfactory than standard sizes. Even though the standard size garments for smaller size groups corresponded to a better fit, garments in bigger size groups were problematic for a good fit. As a conclusion, it was stated that madeto- measure and apparel fit customization could be more essential for bigger size groups or irregular body shapes.
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    Article
    Citation - WoS: 6
    Citation - Scopus: 6
    Neural Network Based Thermal Protective Performance Prediction of Three-Layered Fabrics for Firefighter Clothing
    (Inst. Nat. Cercetare-Dezvoltare Text. Pielarie, 2019) Dursun M.; Şenol Y.; Bulgun E.Y.; Akkan T.
    The firefighter protective clothing is comprised of three main layers; an outer shell, a moisture barrier and a thermal liner. This three-layered fabric structure provides protection against the fire and extremely hot environments. Various parameters such as fabric construction, weight, warp/weft count, warp/weft density, thickness, water vapour resistance of the fabric layers have effect on the protective performance as heat transfer through the firefighter clothing. In this study, it is aimed to examine the predictability of the heat transfer index of three-layered fabrics, as function of the fabric parameters using artificial neural networks. Therefore, 64 different three layered-fabric assembly combinations of the firefighter clothing were obtained and the convective heat transfer (HTI) and radiant heat transfer (RHTI) through the fabric combinations were measured in a laboratory. Six multilayer perceptron neural networks (MLPNN) each with a single hidden layer and the same 12 input data were constructed to predict the convective heat transfer performance and the radiant heat transfer performance of three-layered fabrics separately. The networks 1 to 4 were trained to predict HTI12, HTI24, RHTI12, and RHTI24, respectively, while networks 5 and 6 had two outputs, HTI12 and HTI24, and RHTI12 and RHTI24, respectively. Each system indicates a good correlation between the predicted values and the experimental values. The results demonstrate that the proposed MLPNNs are able to predict the convective heat transfer and the radiant heat transfer effectively. However, the neural network with two outputs has slightly better prediction performance. © 2019 Inst. Nat. Cercetare-Dezvoltare Text. Pielarie. All rights reserved.
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    Article
    Citation - WoS: 1
    Citation - Scopus: 3
    Design of an Interactive Fashion Recommendation Platform With Intelligent Systems
    (Inst natl cercetare-dezvoltare textile pielarie-bucuresti, 2024) Vuruşkan, Arzu; Demırkıran, Gokhan; Bulgun, Ender; İnce, Türker; Güzeliş, Cuneyt
    Design platform intelligent systems With the increase in customer expectations in online fashion sales, greater integration of fashion recommender systems (RSs) allows more personalization. Design decisions rely on personal taste, as well as many other external influences, such as trends and social media, making it challenging to adapt intelligent systems for the fashion industry. Different methods for recommending personalized fashion items have been proposed, however, the literature still lacks an approach for recommending expert -suggested and personalized items. In this research, an interactive web -based platform is developed to support personalized fashion styling, focusing on users with diverse body shapes. To merge the user's taste and the expert's suggestion, the proposed methodology in this research combines genetic algorithms and machine learning techniques allowing the system to access expert knowledge (including external influences) and incremental learning capability, by adapting to the user preferences that unfold during interaction with the system.
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    Article
    Citation - WoS: 7
    Citation - Scopus: 8
    Design Methodology and Performance Studies of a Flexible Electrotextile Surface
    (Autex, 2015) Kayacan, Ozan; Kayacan, Ozlem; Bulgun, Ender; Eser, Burcin; Pamuk, Masuk
    The smart textiles' concept has to develop products based not only on design, fashion and comfort but also in terms of functions. The novel electro-textiles in the market open up new trends in smart and interactive gadgets. 'Easy to care and durability' properties are among the most important features of these products. On the other hand, wearable electronic knitwear has been gaining the attention of both researchers and industrial sectors. Combining knitting technology with electronics may become a dominant trend in the future because of the wide application possibilities. This research is concerned primarily with the design methodology of knitted fabrics containing electrically conductive textiles and especially in-use performance studies. The structural characteristics of the fabrics have been evaluated to enhance the performance properties.
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    Article
    Citation - Scopus: 1
    Integrating Light Elements in Fashion: Practice-Based Design Approach
    (Chamber of Textile Engineers, 2023) Vuruşkan, Arzu; Bulgun, Ender; Tekcan, Elif
    In history, the relationship between fashion and technology has influenced the ever-changing silhouettes of the body, the quality of materials used to construct these silhouettes, and the colors giving liveliness to the material. Today, influenced by the digital revolution and innovation in advanced materials, the fashion industry benefits from the increasing possibilities of technology to develop alternative functions even to the most conventional dress forms, such as wedding gowns. This integration, which necessitates the contribution of different know-how and expertise, also provides a creative platform for developing interdisciplinary, practice-based design research and applications. In this study, an innovative wedding dress using light as a design element was produced with the joint contribution of designers and engineers based in Izmir, considered the capital of bridalwear in Turkey. This project, which considers light as a new design element that increases the expressive power of the dress, aims to offer an alternative to both the wedding dress category and the existing examples incorporating light technologies. In accordance with the main framework, research questions, and project design concept, the study conducts a literature review examining current design examples using different light technologies (LED, optical fibers, etc.). Following this, the stages of design, sample development and production processes are presented with relevant visuals. It is believed that this study, whose research, design development, and production processes are shared in detail, will set an example for future interdisciplinary projects. © 2023, Tekstil ve Muhendis. All Rights Reserved.
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    Conference Object
    Citation - Scopus: 1
    Application of Evolutionary Algorithms To Garment Design
    (2013) İnce, Türker; Vuruşkan A.; Bulgun E.; Güzeliş C.
    In this study, we present the development of an intelligent system solution for fashion style selection for various female body shapes. The proposed intelligent system combines binary genetic algorithm (GA) or binary version of the particle swarm optimization (PSO) with PSO-trained artificial neural network. The former is used to search the solution space for the optimal design parameters corresponding to a best fit for the desired target, and the task of the latter is to evaluate fitness (goodness) of each evolved new fashion style. With the goal of creating natural aesthetic relationship between the shape of the body and the shape of the garment for fashion styling, combinations of upper body related and lower body related garment pieces together with detailed attribute categories were created as a knowledge base. The encouraging results of preliminary experiments demonstrate the feasibility of applying intelligent systems to fashion styling. © 2013 IEEE.