Aerospace medicine and Biology: A continuing bibliography with indexes, supplement 177

This bibliography lists 112 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1978

Textile Taxonomy and Classification Using Pulling and Twisting

Identification of textile properties is an important milestone toward advanced robotic manipulation tasks that consider interaction with clothing items such as assisted dressing, laundry folding, automated sewing, textile recycling and reusing. Despite the abundance of work considering this class of deformable objects, many open problems remain. These relate to the choice and modelling of the sensory feedback as well as the control and planning of the interaction and manipulation strategies. Most importantly, there is no structured approach for studying and assessing different approaches that may bridge the gap between the robotics community and textile production industry. To this end, we outline a textile taxonomy considering fiber types and production methods, commonly used in textile industry. We devise datasets according to the taxonomy, and study how robotic actions, such as pulling and twisting of the textile samples, can be used for the classification. We also provide important insights from the perspective of visualization and interpretability of the gathered data

DTI Economics Paper No. 2: A comparative study of the British and Italian Textile and Clothing Industries.

Commissioned by: Association of Suppliers to the British Clothing Industry Conference, Hucknell, Nottingham, February 2004 During the 1990s the Italian clothing and textiles industry grew while the British, French and German textile and clothing industries declined by 40%. In 2001 the Italian textiles & clothing sector was three times larger than the British, accounting for 11.7% of Italian manufacturing output but only 3.3% in Britain. In 2000 Italian fabric exports were 15 times that of the UK. The study was conducted in response to a recommendation by the Textiles and Clothing Strategy Group (TCSG), comprising UK industry, trade unions, Higher Education and the DTI. The purpose of the study was to account for these differences, assess relative merits against value for money and identify best practice in the Italian industry. The methodology comprised comparative analysis and case studies of British and Italian textile mills and tailoring manufacturers, based on my initial recommendations. We visited 5 textile mills in Yorkshire and 15 in Italy plus 3 factories in each country. I conducted a detailed comparative technical analysis of the construction of suit jackets against 13 devised criteria, a number of interviews,compared technologies, equipment and manufacturing methods across all factories, against 8 criteria, drawing on my specialist knowledge and experience as a menswear clothing technologist. The technical reports I compiled formed a section of the final report. Findings were presented to the Clothing Strategy Group and published by the DTI as their Economic Paper No 2 . I made further presentations to industry and academic groups including ASBCI, FCDE, The Textile Society, Savile Row Tailors Association, and LSE. Other outcomes were a publication in the Journal of the Textile Society Text, an article in Selvedge magazine and contributions to the Encyclopaedia of Clothing by Thomson Gale. As a result of this research further consultancy projects have been conducted with the Industry Forum and ASBCI

A creative journey developing an integrated high-fashion knitwear development process using computerized seamless v-bed knitting systems

This PhD applied a participatory action research approach to address the organizational problems that compromise the use of computerized seamless V-bed knitwear systems in the high-fashion knitwear sector. The research is a response to a widely acknowledged conflict between high-fashion design processes and processes by which designs are developed on computerized seamless V-bed knitting systems. The social, organizational, and technical aspects of design and manufacturing using computerized seamless V-bed knitting technology in high-fashion knitwear design were analyzed as a socio-technical system (STS). This approach led to a review of the workflows, tasks and roles; identifying and testing new design and manufacturing processes, design methods, and garment solutions; creating a theory model of a new integrated design process; and developing and testing new design processes, design methods, and fashion design education courses that teach these new fashion knitwear approaches.The research was undertaken using a Shima Seiki WholeGarment® system, a current computerized seamless V-bed knitting design and manufacturing technology. The studio workspace, yarn, use of the Shima Seiki system; involvement in fashion projects, and associate supervision were provided by the Department of Agriculture and Food Western Australia (DAFWA).The research demonstrated a high-fashion knitwear designer can undertake all aspects of managing computerized seamless V-bed knitwear design and production to the completion of 1st sample, the first successful sample of a new fabric or garment, was produced using the computer knit data. This finding was developed into a new integrated design process and design methods that remove most of the problems of computerized seamless V-bed knitting systems in high-fashion and offers additional benefits including reduction in time to market and design costs, and increases in the creative solution space for high-fashion knitwear design.The researcher has called this new role, a ‘designer-interpreter’ to denote a professional knitwear designer with additional training in managing computerized seamless knitting machines. Within the context of ‘designer-interpreter’, this research also established the feasibility of a new form of a ‘post-industrial craft-based one-person knitwear production system’

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 164

This bibliography lists 275 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1977

Using object detection technology to identify defects in clothing for blind people

Blind people often encounter challenges in managing their clothing, specifically in identifying defects such as stains or holes. With the progress of the computer vision field, it is crucial to minimize these limitations as much as possible to assist blind people with selecting appropriate clothing. Therefore, the objective of this paper is to use object detection technology to categorize and detect stains on garments. The defect detection system proposed in this study relies on the You Only Look Once (YOLO) architecture, which is a single-stage object detector that is well-suited for automated inspection tasks. The authors collected a dataset of clothing with defects and used it to train and evaluate the proposed system. The methodology used for the optimization of the defect detection system was based on three main components: (i) increasing the dataset with new defects, illumination conditions, and backgrounds, (ii) introducing data augmentation, and (iii) introducing defect classification. The authors compared and evaluated three different YOLOv5 models. The results of this study demonstrate that the proposed approach is effective and suitable for different challenging defect detection conditions, showing high average precision (AP) values, and paving the way for a mobile application to be accessible for the blind community.This work has been supported by national funds through FCT—Fundacão para a Ciência e Tecnologia, within the Projects Scope: UIDB/00319/2020, UIDB/05549/2020, UIDP/05549/2020, UIDP/04077/2020, and UIDB/04077/2020

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 324)

This bibliography lists 200 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during May, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Identification of Soils on Firefighter Turnout Gear from the Philadelphia Fire Department

The purpose of this research was to identify the composition of soils on firefighter turnout gear from the Philadelphia Fire Department and to determine which soils contain hazardous materials. The objective of the research was to identify the composition of soils remaining on the firefighter turnout gear to enable the industry to design an effective cleaning procedure for removal of soils. A pilot study was conducted on hoods from the Philadelphia fire department to evaluate the test methods that would be used to identify the composition of soils. Soils that had been identified from previous studies were targeted in the analysis of the extraction of the samples removed from the hoods. Samples were removed from areas of the coats and pants where dermal absorption is reported as high areas of skin absorption, including areas in the neck, armpit, crotch and wrist locations

A CNN Based Approach for Garments Texture Design Classification

Identifying garments texture design automatically for recommending the fashion trends is important nowadays because of the rapid growth of online shopping. By learning the properties of images efficiently, a machine can give better accuracy of classification. Several Hand-Engineered feature coding exists for identifying garments design classes. Recently, Deep Convolutional Neural Networks (CNNs) have shown better performances for different object recognition. Deep CNN uses multiple levels of representation and abstraction that helps a machine to understand the types of data more accurately. In this paper, a CNN model for identifying garments design classes has been proposed. Experimental results on two different datasets show better results than existing two well-known CNN models (AlexNet and VGGNet) and some state-of-the-art Hand-Engineered feature extraction methods