Search results

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

Nowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing style and color design via computer language, which aims to edit and control the garment image based on the specified target attributes while preserving other details from the original image. The current image attribute editing model often generates images containing missing or redundant attributes. To address the problem, this paper aims for a novel design method utilizing the Fashion-attribute generative adversarial network (AttGAN) model was proposed for image attribute editing specifically tailored to women’s blouses.

The proposed design method primarily focuses on optimizing the feature extraction network and loss function. To enhance the feature extraction capability of the model, an increase in the number of layers in the feature extraction network was implemented, and the structure similarity index measure (SSIM) loss function was employed to ensure the independent attributes of the original image were consistent. The characteristic-preserving virtual try-on network (CP_VTON) dataset was used for train-ing to enable the editing of sleeve length and color specifically for women’s blouse.

The experimental results demonstrate that the optimization model’s generated outputs have significantly reduced problems related to missing attributes or visual redundancy. Through a comparative analysis of the numerical changes in the SSIM and peak signal-to-noise ratio (PSNR) before and after the model refinement, it was observed that the improved SSIM increased substantially by 27.4%, and the PSNR increased by 2.8%, serving as empirical evidence of the effectiveness of incorporating the SSIM loss function.

The proposed algorithm provides a promising tool for precise image editing of women’s blouses based on the GAN. This introduces a new approach to eliminate semantic expression errors in image editing, thereby contributing to the development of AI in clothing design.

The case is written on the basis of published sources only.

Doodlage, a start-up incorporated in 2012 by Kriti Tula, Paras Arora and Vaibhav Kapoor, used discarded waste to create sustainable fashion products. It had a first-mover advantage in recycled fashion goods in the first 10 years of its existence. The company contributed to sustainable fashion by providing an alternative to fast fashion production, creating enormous clothing waste and environmental degradation. In the first quarter of 2022, it saved and reused 15,000 m of fabric waste. From 2018 to 2021, the company grew 150% annually, targeting the right customers and regions to expand its business. It ensured that postproduction industrial waste and postconsumption garments were used to produce clothes. It also confirmed that the waste generated in its fabric screening process was used to create stationery items and other valuable accessories.

However, the sustainable fashion model that gave the company a competitive advantage became obsolete in 2022 due to increasing competition in the industry as various players using unique ideas entered the market. The company is encountering operational and logistical challenges that are affecting its performance. The demand for its products was also subdued due to high prices of upcycled and recycled clothes and less consumer spending post-COVID pandemic. The competitors of Doodlage offered multiple products produced using environmentally friendly farming and manufacturing techniques, attracting sustainable purchasers. What should be the new portfolio of products for the company to explore future growth opportunities? Considering their vast price, can consumers be encouraged to buy upcycled clothes? How should the company ride the winds of change in the industry?

The instructor should initiate the class discussion by asking questions such as how frequently do you shop for clothes? Do you care about the fabric of your apparel? After you discard your clothes, do you think about where these goods finally end up? Data on the amount of total waste generated in the fashion industry should be communicated to students to connect it with the importance of the concept of circular economy. Post this, the instructor should introduce the business model of Doodlage to bring the discussion into the context of the fashion industry before going ahead to discuss the company’s dilemma.

The apparel and textile sector poses a significant environmental challenge due to its substantial contribution to pollution in the form of air, water and soil pollution. To combat these issues, the adoption of sustainable practices is essential. This study aims to identify and analyse the barriers that hinder the progress of sustainability in the apparel and textile industry. By consulting experts in the field, critical barriers were identified and given special attention.

To achieve the research objective, an integrated approach involving Interpretive Structural Modelling (ISM) and fuzzy MICMAC decision-making techniques was employed. The results were further validated through the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The findings highlight that barrier related to clothing disposal, inadequate adaptation to modern technology, challenges affecting sector efficiency and issues related to fashion design are crucial in influencing the remaining six barriers. Based on the outcomes of the DEMATEL method, a comprehensive cause-and-effect diagram was constructed to gain a deeper understanding of these challenges.

This research provides valuable insights for policymakers and stakeholders in the apparel and textile industry. It offers a strategic framework to address and overcome sustainability barriers, promoting the development of a more environmentally responsible and resilient sector.

The purpose of this research is to conduct an in-depth investigation of the barriers apparel and textile sectors. It is feasible that both the management team and the medical experts who provide direct patient care could benefit from this research.

Based on the knowledge-attitude-behavior model, this study is aimed at investigating the influential mechanism underlying the purchase of green clothing by dividing this clothing category into green home-in wear and home-out wear within the context of green consumption. The mediating effects of perceived greenwashing (PG), perceived value (PV) and expected moral benefit (EMB) and the moderating effect of green clothing type (GCT) were examined.

The data for this study were collected from 366 valid samples through a between-subject design survey administered in China. Moderation analysis and mediation analysis using SPSS/PROCESS macro were applied to test the proposed hypotheses.

The results indicate that consumers' level of environmental knowledge (EKL) not only has a direct effect on purchase intention (PI) but also has an indirect effect through perceived value and expected moral benefit. However, perceived greenwashing did not play a mediating role in this relationship.

The study's findings show a moderating effect of green clothing type (green home-in wear vs green home-out wear). That is, compared to green home-out wear, the relationship between expected moral benefit and perceived greenwashing for green home-in wear had a weaker negative effect on purchase intentions.

The objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.

This study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.

The 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.

It is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.

This study aims to investigate the ecological awareness of Chinese consumers towards fast fashion and examine the effect of social sustainability claims on green brand image and purchase intentions in China, considering China’s unique environmental policy landscape and its significant role in the global fast fashion industry. The study explores the role of altruistic values in promoting sustainability within the well-known fast fashion brand “H” and how they shape brand image, consumer satisfaction and brand equity.

The study collected data from 257 Chinese participants and used a serial mediation model through the PROCESS macro in SPSS to analyse the correlation between green brand image, created through sustainability claims and consumer purchase intentions. The model also assessed the intermediary effects of brand image, satisfaction and equity.

The findings of the research indicate a direct and positive relationship between green brand image and consumer purchase intentions, emphasising the need for clothing and textile industry marketers to strategically promote altruistic values in their sustainability efforts and highlighting the importance of ecological awareness in shaping consumer behaviour in the Chinese context. This approach enhances green satisfaction and green brand equity and ultimately leads to higher green purchase intentions.

This study provides significant insights into the effectiveness of incorporating social sustainability claims in advertising to improve a brand’s green image and influence consumer behaviour. It emphasises the importance of altruistic values in sustainability strategies, offering valuable guidelines for marketers in enhancing green satisfaction and brand equity, thereby boosting consumer purchase intentions in the context of green branding and sustainability advertising. Focussing specifically on the Chinese market, this research sheds light on the impact of ecological awareness among Chinese consumers within the fast-fashion industry. Given China’s substantial role in shaping global fast-fashion production and its evolving environmental policies, this focus adds significant depth to our understanding of sustainability claims’ influence within this crucial consumer base.

This study aims to analyze how conventional Bedouin weaving techniques have changed through the history of Israel, offering knowledge on the craft’s cultural relevance and historical development among the Bedouin people and how their weaving and embroidery differ based on the three main geographic characteristics. It tries to comprehend the causes of the transition from organic to synthetic materials and the part played by the Lakiya Negev Bedouin Weaving women’s cooperative in maintaining this legacy.

The main goal of this study is to trace the emergence of Bedouin weaving traditions in the Negev Desert using a qualitative research methodology that combines historical analysis and ethnographic investigation. A thorough grasp of the subject’s significance is provided through the data gathering, which consists of interviews, archival research and field observations.

Through the years, Bedouin weaving techniques have significantly shifted away from using traditional organic materials in favor of synthetic replacements, according to the research. It emphasizes the crucial part played by the Lakiya Negev Bedouin Weaving women’s organization in safeguarding this traditional legacy and giving Bedouin women access to economic prospects.

The limitation of the study includes its emphasis on the Negev region and the Israeli Bedouin community, which may not accurately reflect all Bedouin weaving techniques. Greater regional settings may be explored in future studies.

The investigation emphasizes the value of investing in initiatives for cultural preservation and the empowerment of underprivileged groups through economic possibilities.

By preserving ancient weaving techniques, this research enables Bedouin women in the Negev Desert to maintain their cultural identity and socioeconomic well-being.

By emphasizing the socio-cultural dimensions and the organization’s role in preserving traditional craftsmanship in a changing socio-economic environment, this research presents a unique investigation of the evolution of Bedouin weaving techniques in Israel.

Non-profit organizations (NPOs) are exposed to a highly competitive environment in which they are forced to grow their commercial activity to acquire additional financial resources. This study aims to create an understanding of how NPOs involved in textile reuse as a revenue-generating programme manage their reverse supply chains (RSC).

The research involves an embedded single-case study of NPOs in Finland involved in post-use textile collection. The main data sources are semi-structured interviews and participant observations.

This study is inspired by the microfoundations movement and identifies the underlying microfoundations of the NPOs’ capabilities for managing RSC for textile reuse. The study contributes to the literature by demonstrating NPOs’ lower-level, granular practices and their adaptations for achieving quality outcomes in textile reuse.

The findings have context sensitivity and apply to the NPOs which operate in a context similar to Finland, such as in other Nordic countries.

This study continues the discussion on the adoption of “business-like” practices in the NPOs’ pursuit of additional revenue streams to finance humanitarian work. The findings of this study can also be transferred to the growing area of domestic textile circularity.

Using the case of NPOs in textile reuse, the study illustrates how RSC management can serve a social, non-profit cause and transform unwanted textile products into a source of fundraising for humanitarian work.

This enriches the understanding of NPOs’ practices within the scope of revenue-generating programmes by examining one of them – textile reuse through charity shops from an RSC perspective.

This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.

In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.

According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.

In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.