Abstract This article aimed at providing a new biomechanical three-dimensional dynamic finite element model of the hand–glove combination for exploring the distribution of the overall continuous dynamic contact pressure of the hand with the flexible glove in the state of grabbing an object, and further predicting the accuracy of sensors of wearable smart gloves. The model was validated by garment pressure experiments at eight muscle points. The results showed that the pressure value measured with three flexible gloves was highly consistent with the finite element simulation value. Based on the model, the distribution of dynamic pressure between the soft tissue of the hand and the fabric in the process of flexing the fingers and grabbing external objects were predicted accurately and effectively, which indicated that the model with high accuracy could be applied to evaluate the accuracy of the pressure value collected by sensors of smart gloves. In addition, the model had been confirmed that it has a certain application value. The findings could help to provide a reference for dynamic continuous monitoring equipment or other intelligent wearable devices, and promote the development of the intelligent clothing industry in the future.
{"title":"Accuracy prediction of wearable flexible smart gloves","authors":"Yan Zhang, Hong Xie, Mark J. Lake","doi":"10.1515/aut-2023-0008","DOIUrl":"https://doi.org/10.1515/aut-2023-0008","url":null,"abstract":"Abstract This article aimed at providing a new biomechanical three-dimensional dynamic finite element model of the hand–glove combination for exploring the distribution of the overall continuous dynamic contact pressure of the hand with the flexible glove in the state of grabbing an object, and further predicting the accuracy of sensors of wearable smart gloves. The model was validated by garment pressure experiments at eight muscle points. The results showed that the pressure value measured with three flexible gloves was highly consistent with the finite element simulation value. Based on the model, the distribution of dynamic pressure between the soft tissue of the hand and the fabric in the process of flexing the fingers and grabbing external objects were predicted accurately and effectively, which indicated that the model with high accuracy could be applied to evaluate the accuracy of the pressure value collected by sensors of smart gloves. In addition, the model had been confirmed that it has a certain application value. The findings could help to provide a reference for dynamic continuous monitoring equipment or other intelligent wearable devices, and promote the development of the intelligent clothing industry in the future.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139004233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Although the color characteristics of She nationality clothing are slightly different, there are multiple similarities in shapes and textures. Therefore, it is difficult to effectively distinguish different branches of She nationality clothing. To address this problem, this article, taking into account color feature fusion, proposes a recognition method based on a hybrid algorithm of particle swarm optimization and support vector machine (PSO-SVM). First, the color histogram and color moment (CM) feature descriptors were extracted from the five branches of She nationality clothing, and the color feature distribution of each branch was obtained. Then, color feature fusion is performed through optimization and dimensionality reduction of principal components. Furthermore, PSO was introduced to independently optimize parameter combinations. Finally, the different branches of She nationality clothing were automatically recognized. The results demonstrated that the proposed method could effectively distinguish different branches of She nationality clothing. Compared with the recognition accuracy of approaches using single-color histogram and CM feature, the performance of our proposed method was increased by 5.25 and 6.44%, respectively. When the penalty parameter γ gamma and kernel parameter δ 2 {delta }^{2} of SVM were 123.29 and 1.16, respectively, the recognition accuracy of the model was the highest, reaching 98.67%. The proposed method could be a reference for the subdivision recognition of She nationality clothing.
{"title":"Research on She nationality clothing recognition based on color feature fusion with PSO-SVM","authors":"Xiaojun Ding, Tao Li, Jingyu Chen, Fengyuan Zou","doi":"10.1515/aut-2023-0005","DOIUrl":"https://doi.org/10.1515/aut-2023-0005","url":null,"abstract":"Abstract Although the color characteristics of She nationality clothing are slightly different, there are multiple similarities in shapes and textures. Therefore, it is difficult to effectively distinguish different branches of She nationality clothing. To address this problem, this article, taking into account color feature fusion, proposes a recognition method based on a hybrid algorithm of particle swarm optimization and support vector machine (PSO-SVM). First, the color histogram and color moment (CM) feature descriptors were extracted from the five branches of She nationality clothing, and the color feature distribution of each branch was obtained. Then, color feature fusion is performed through optimization and dimensionality reduction of principal components. Furthermore, PSO was introduced to independently optimize parameter combinations. Finally, the different branches of She nationality clothing were automatically recognized. The results demonstrated that the proposed method could effectively distinguish different branches of She nationality clothing. Compared with the recognition accuracy of approaches using single-color histogram and CM feature, the performance of our proposed method was increased by 5.25 and 6.44%, respectively. When the penalty parameter γ gamma and kernel parameter δ 2 {delta }^{2} of SVM were 123.29 and 1.16, respectively, the recognition accuracy of the model was the highest, reaching 98.67%. The proposed method could be a reference for the subdivision recognition of She nationality clothing.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139003358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This study was prompted by the unsustainable issues facing the garment industry and the trend toward digitalisation in the post-coronavirus disease 2019 (COVID-19) pandemic era. COVID-19 substantially affected global trade, which caused significant garment industry stagnation due to embargoes and international restrictions. Consequently, the stagnation led to a significant inventory backlog and hindered product distribution, which compelled garment companies to turn to online commerce. A circular economy (CE) attempts to halt commodity flow and convert waste into resources; therefore, it can alleviate the substantial garment industry pollution and waste produced under a linear economy and maximise product life cycles. Industrial Revolution 4.0 incorporates technological innovation and information technology to transform the garment industry, which technologically enhances manufacturing intelligence and inspires garment industry transformation into a CE. This systematic literature review discusses the necessity of transforming the garment industry into a CE and the technological advantages and challenges to promoting sustainable garment industry development. The findings demonstrated that transforming the garment industry into a CE can not only resolve its environmental pollution and excess supply issues but can also accommodate new supply and demand requirements, such as market digitisation, consumer personalisation, and industry chain transparency. Finally, a technology integration initiative was proposed to promote garment industry transformation into a CE by digitising product development to achieve sustainable development.
{"title":"Technology integration to promote circular economy transformation of the garment industry: a systematic literature review","authors":"Wang Yiyan, Norsaadah Zakaria","doi":"10.1515/aut-2023-0006","DOIUrl":"https://doi.org/10.1515/aut-2023-0006","url":null,"abstract":"Abstract This study was prompted by the unsustainable issues facing the garment industry and the trend toward digitalisation in the post-coronavirus disease 2019 (COVID-19) pandemic era. COVID-19 substantially affected global trade, which caused significant garment industry stagnation due to embargoes and international restrictions. Consequently, the stagnation led to a significant inventory backlog and hindered product distribution, which compelled garment companies to turn to online commerce. A circular economy (CE) attempts to halt commodity flow and convert waste into resources; therefore, it can alleviate the substantial garment industry pollution and waste produced under a linear economy and maximise product life cycles. Industrial Revolution 4.0 incorporates technological innovation and information technology to transform the garment industry, which technologically enhances manufacturing intelligence and inspires garment industry transformation into a CE. This systematic literature review discusses the necessity of transforming the garment industry into a CE and the technological advantages and challenges to promoting sustainable garment industry development. The findings demonstrated that transforming the garment industry into a CE can not only resolve its environmental pollution and excess supply issues but can also accommodate new supply and demand requirements, such as market digitisation, consumer personalisation, and industry chain transparency. Finally, a technology integration initiative was proposed to promote garment industry transformation into a CE by digitising product development to achieve sustainable development.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138585474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Contingency and uniqueness are regarded as typical artistic characteristics. To accomplish the realistic effect of each tie-dyeing pattern artwork, we propose a digital tie-dyeing pattern fast-generation algorithm based on auxiliary-classifier deep-convolution generative adversarial network (AC-DCGAN) and image-processing technology. To apply this algorithm, the designer first draws the planar layout diagram of the tie-dyeing patterns. The diagram consists of a white background and polychrome circles, and the regional-connectivity algorithm is used to extract information on all the circle positions as well as the pattern categories in the diagram. Then the AC-DCGAN-generated background image is color-corrected to stitch and complete its construction. The AC-DCGAN-generated tie-dyeing pattern image is also color-corrected and is then segmented and copied to the circle area. Mean filtering creates the final digital tie-dyeing patterns. Results show no obvious color difference in generated patterns, splicing edges show uniform transition, and unique patterns exhibit tie-dye characteristics, achieving realistic artistic effects.
{"title":"Tie-dyeing pattern fast-generation method based on deep-learning and digital-image-processing technology","authors":"Suqiong Liu, Xiao-Shuang Xing, Shan-shan Wang, Jinxiong Zhou","doi":"10.2478/aut-2022-0034","DOIUrl":"https://doi.org/10.2478/aut-2022-0034","url":null,"abstract":"Abstract Contingency and uniqueness are regarded as typical artistic characteristics. To accomplish the realistic effect of each tie-dyeing pattern artwork, we propose a digital tie-dyeing pattern fast-generation algorithm based on auxiliary-classifier deep-convolution generative adversarial network (AC-DCGAN) and image-processing technology. To apply this algorithm, the designer first draws the planar layout diagram of the tie-dyeing patterns. The diagram consists of a white background and polychrome circles, and the regional-connectivity algorithm is used to extract information on all the circle positions as well as the pattern categories in the diagram. Then the AC-DCGAN-generated background image is color-corrected to stitch and complete its construction. The AC-DCGAN-generated tie-dyeing pattern image is also color-corrected and is then segmented and copied to the circle area. Mean filtering creates the final digital tie-dyeing patterns. Results show no obvious color difference in generated patterns, splicing edges show uniform transition, and unique patterns exhibit tie-dye characteristics, achieving realistic artistic effects.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42184236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jianping Wang, Bin Zhang, Xiaofeng Yao, Jinzhu Shen, Luning Yuan, Ting Pan, Deyao Shen, Yupeng Li
Abstract In order to meet the functional requirements of professional skiers for ski underwear, such as warmth, breathability, moisture absorption, sweat drainage, and stretch elasticity, six single-sided jacquard knit fabric structures were designed and then knitted with polyester and DRYARN. Then, 12 fabrics were acquired and ranked comprehensively by the one-way analysis of variance and grey correlative analysis based on entropy. According to the fabric properties and sweat distribution on the human skin surface, the professional ski underwear was zoning designed and the wearing experiment and evaluation were carried out on the “Newton” sweated manikin system. The analysis results show that the fabric with DRYARN® material has better air permeability and moisture permeability. Thermal resistance, Clo value, and permeability play important roles in comprehensive evaluation. The results of wearing experiment show that the seamless professional ski underwear woven based on body mapping sportswear has superior function and reasonable design, which can provide technical support for the design of professional seamless ski underwear.
{"title":"Single-sided Jacquard knit fabric development and seamless ski underwear zoning design based on body mapping sportswear","authors":"Jianping Wang, Bin Zhang, Xiaofeng Yao, Jinzhu Shen, Luning Yuan, Ting Pan, Deyao Shen, Yupeng Li","doi":"10.2478/aut-2022-0033","DOIUrl":"https://doi.org/10.2478/aut-2022-0033","url":null,"abstract":"Abstract In order to meet the functional requirements of professional skiers for ski underwear, such as warmth, breathability, moisture absorption, sweat drainage, and stretch elasticity, six single-sided jacquard knit fabric structures were designed and then knitted with polyester and DRYARN. Then, 12 fabrics were acquired and ranked comprehensively by the one-way analysis of variance and grey correlative analysis based on entropy. According to the fabric properties and sweat distribution on the human skin surface, the professional ski underwear was zoning designed and the wearing experiment and evaluation were carried out on the “Newton” sweated manikin system. The analysis results show that the fabric with DRYARN® material has better air permeability and moisture permeability. Thermal resistance, Clo value, and permeability play important roles in comprehensive evaluation. The results of wearing experiment show that the seamless professional ski underwear woven based on body mapping sportswear has superior function and reasonable design, which can provide technical support for the design of professional seamless ski underwear.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43838287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Han Chen, Han Xu, Yudian Zhang, Shi-you Gu, Dandan Wang
Abstract The indiscriminate discharge of industrial and domestic wastewater leads to the pollution of production, living, and landscape waters with heavy metals, including Pb2+. To protect people working in environments with risk of water pollution by Pb2+, the Pb2+ chemosensor based on fluorescent carbon dots (CDs) was designed in this study. Based on quenching of the fluorescence of CDs via electron or energy transfer between Pb2+ and CDs, the sensor induces a significant “dark blue to light blue” fluorescence burst color change under the naked eye. Results suggest that the fluorescence intensity of CDs positively correlated with the concentrations of Pb2+ (R2 = 0.823–0.986), which is conducive to the detection of Pb2+-containing wastewater by CDs. On this basis, we integrated CD fluorescent sensors into wearable gloves via a mediated coating method. With no additional burden (off-site, long lead times, high cost, etc.), the designed wearable gloves enable front loading of the detection window for Pb2+-contaminated water to protect the wearer from poisoning. Eight watershed environmental occupants reported a 57.42% reduction in occupational anxiety after using our safety gloves. We believe that the proposed flexible and stable wearable sensing system will not only have great potential applications in Pb2+ field detection but also stimulate the development of other environmental pollution sensing devices.
{"title":"Wearable design for occupational safety of Pb2+ water pollution monitoring based on fluorescent CDs","authors":"Han Chen, Han Xu, Yudian Zhang, Shi-you Gu, Dandan Wang","doi":"10.2478/aut-2022-0029","DOIUrl":"https://doi.org/10.2478/aut-2022-0029","url":null,"abstract":"Abstract The indiscriminate discharge of industrial and domestic wastewater leads to the pollution of production, living, and landscape waters with heavy metals, including Pb2+. To protect people working in environments with risk of water pollution by Pb2+, the Pb2+ chemosensor based on fluorescent carbon dots (CDs) was designed in this study. Based on quenching of the fluorescence of CDs via electron or energy transfer between Pb2+ and CDs, the sensor induces a significant “dark blue to light blue” fluorescence burst color change under the naked eye. Results suggest that the fluorescence intensity of CDs positively correlated with the concentrations of Pb2+ (R2 = 0.823–0.986), which is conducive to the detection of Pb2+-containing wastewater by CDs. On this basis, we integrated CD fluorescent sensors into wearable gloves via a mediated coating method. With no additional burden (off-site, long lead times, high cost, etc.), the designed wearable gloves enable front loading of the detection window for Pb2+-contaminated water to protect the wearer from poisoning. Eight watershed environmental occupants reported a 57.42% reduction in occupational anxiety after using our safety gloves. We believe that the proposed flexible and stable wearable sensing system will not only have great potential applications in Pb2+ field detection but also stimulate the development of other environmental pollution sensing devices.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42728549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Adhesion between additively printed elements on textiles is one of the most important quality characteristics. Applied elements must form very good adhesion with the textile substrate in order to produce functional textiles. The request for non-planar printing directly on textiles is growing, especially in the fields of orthopaedic engineering and protective clothing. This new printing technique can open up new areas of application. For such a production of non-planar elements on textiles, new test methods have to be developed, as the current adhesion tests (180° peel test) are not applicable to non-planar prints on textiles. For non-planar additive printing on textiles, a cylindrical print bed for a fused filament fabrication printer was developed and modified accordingly in the first step. In the next step, a new measurement method was developed to investigate the adhesion between the textile and the non-planar three-dimensional-printed element. The study shows the challenges and the adhesion differences of non-planar printed objects on pre-stretched textiles on a cylindrical print bed. Several factors influencing adhesion were identified. The alignment of the printing nozzle to the textile substrate is the key factor influencing adhesion. The alignment also has a significant influence on the visual print quality.
{"title":"Non-planar 3D printed elements on textile substrate using a fused filament fabrication 3D printer","authors":"Dominik Muenks, Luca Eckelmann, Y. Kyosev","doi":"10.2478/aut-2022-0026","DOIUrl":"https://doi.org/10.2478/aut-2022-0026","url":null,"abstract":"Abstract Adhesion between additively printed elements on textiles is one of the most important quality characteristics. Applied elements must form very good adhesion with the textile substrate in order to produce functional textiles. The request for non-planar printing directly on textiles is growing, especially in the fields of orthopaedic engineering and protective clothing. This new printing technique can open up new areas of application. For such a production of non-planar elements on textiles, new test methods have to be developed, as the current adhesion tests (180° peel test) are not applicable to non-planar prints on textiles. For non-planar additive printing on textiles, a cylindrical print bed for a fused filament fabrication printer was developed and modified accordingly in the first step. In the next step, a new measurement method was developed to investigate the adhesion between the textile and the non-planar three-dimensional-printed element. The study shows the challenges and the adhesion differences of non-planar printed objects on pre-stretched textiles on a cylindrical print bed. Several factors influencing adhesion were identified. The alignment of the printing nozzle to the textile substrate is the key factor influencing adhesion. The alignment also has a significant influence on the visual print quality.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46247241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Under the production mode of small-batch and multi-item, the recognition of yarn-dyed fabric patterns is a crucial task in the textile industry. In this article, an automatic recognition system based on pixel-level features is proposed to recognize the density, the weave pattern, and the color pattern. In this system, the fabric images are captured by a scanner. First, a method based on the Hough transform is used to correct the skew of the yarns, including warp and weft. Second, the yarns and nodes are located in the enhanced images with a brightness-projection method. The density can be calculated by using the results. Then, the type of each node is identified based on the boundary information. We can obtain the weave pattern after knowing the type of each node. Finally, the fuzzy C-means algorithm is used to determine the color of each node, and thus we obtain the color pattern of the yarn-dyed fabric. Experimental results demonstrate that the proposed recognition system is effective for detecting the structural parameters of yarn-dyed fabric.
{"title":"Automatic recognition of density and weave pattern of yarn-dyed fabric","authors":"Jun Xiang, R. Pan","doi":"10.2478/aut-2022-0025","DOIUrl":"https://doi.org/10.2478/aut-2022-0025","url":null,"abstract":"Abstract Under the production mode of small-batch and multi-item, the recognition of yarn-dyed fabric patterns is a crucial task in the textile industry. In this article, an automatic recognition system based on pixel-level features is proposed to recognize the density, the weave pattern, and the color pattern. In this system, the fabric images are captured by a scanner. First, a method based on the Hough transform is used to correct the skew of the yarns, including warp and weft. Second, the yarns and nodes are located in the enhanced images with a brightness-projection method. The density can be calculated by using the results. Then, the type of each node is identified based on the boundary information. We can obtain the weave pattern after knowing the type of each node. Finally, the fuzzy C-means algorithm is used to determine the color of each node, and thus we obtain the color pattern of the yarn-dyed fabric. Experimental results demonstrate that the proposed recognition system is effective for detecting the structural parameters of yarn-dyed fabric.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45379782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Militký, D. Křemenáková, M. Venkataraman, J. Večerník, L. Martinková, Jan Marek, J. Procházka
Abstract The human body constantly produces thermal electromagnetic radiation with a maximum of about 10 µm. This thermal radiation has a number of positive effects on the human body and, in addition, allows the insulation under clothing to be improved under extreme climatic conditions, causing a significant reduction in ambient temperature. With so-called far-infrared (FIR) textiles, it is possible to ensure the reflection of thermal radiation back to the human body. In the first part of this review, the generation of heat by the human body and its propagation by radiation through the skin are comprehensively explained. The thermal characteristics of the individual skin layers as an emitter of infrared radiation are given. The second part discusses the basic preparation methods of FIR textiles. Suitable particle systems are described based on metals and their oxides, porous carbon, and special ceramics. Modification of the fiber phase (especially the fineness of the fibers and the porosity of the fabric) in combination with the surface coating of metals is also used for their health-promoting effects. The main manufacturers of FIR textiles and their typical products are mentioned.
{"title":"A review of textiles reflecting FIR produced by the human body","authors":"J. Militký, D. Křemenáková, M. Venkataraman, J. Večerník, L. Martinková, Jan Marek, J. Procházka","doi":"10.2478/aut-2022-0035","DOIUrl":"https://doi.org/10.2478/aut-2022-0035","url":null,"abstract":"Abstract The human body constantly produces thermal electromagnetic radiation with a maximum of about 10 µm. This thermal radiation has a number of positive effects on the human body and, in addition, allows the insulation under clothing to be improved under extreme climatic conditions, causing a significant reduction in ambient temperature. With so-called far-infrared (FIR) textiles, it is possible to ensure the reflection of thermal radiation back to the human body. In the first part of this review, the generation of heat by the human body and its propagation by radiation through the skin are comprehensively explained. The thermal characteristics of the individual skin layers as an emitter of infrared radiation are given. The second part discusses the basic preparation methods of FIR textiles. Suitable particle systems are described based on metals and their oxides, porous carbon, and special ceramics. Modification of the fiber phase (especially the fineness of the fibers and the porosity of the fabric) in combination with the surface coating of metals is also used for their health-promoting effects. The main manufacturers of FIR textiles and their typical products are mentioned.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43579368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract “According to Lingaro’s analysis, the return of a product generates 5 times more CO2 than the purchase itself. Thus, the optimization of online e-commerce purchasing processes is a serious challenge not only for business, but mainly for the protection of the environment and our global health.” Presentation of textiles and clothing in e-commerce in Poland has remained unchanged since the beginning of e-commerce (the setup of Allegro auction site in the early 2000s) until now with little exceptions of new technology trends powered by EU funds. In Poland, WearFits introduces an R&D solution in the form of a virtual fitting room presented in augmented reality (AR) view to decrease returns of textile clothing bought online. It uses an avatar of human size and shape of the customer’s body for fitting the three-dimensional models in AR view. The purpose of the article is to review the state of the art of presentation of clothing textiles in e-commerce in the world and in Poland for selling textiles online and to emphasize the problem of size matching in the context of returns.
{"title":"State of the art of presentation of clothing textiles in E-commerce with size matching issues","authors":"J. Wojciechowski, Renata Lisowska, E. Skrzetuska","doi":"10.2478/aut-2022-0030","DOIUrl":"https://doi.org/10.2478/aut-2022-0030","url":null,"abstract":"Abstract “According to Lingaro’s analysis, the return of a product generates 5 times more CO2 than the purchase itself. Thus, the optimization of online e-commerce purchasing processes is a serious challenge not only for business, but mainly for the protection of the environment and our global health.” Presentation of textiles and clothing in e-commerce in Poland has remained unchanged since the beginning of e-commerce (the setup of Allegro auction site in the early 2000s) until now with little exceptions of new technology trends powered by EU funds. In Poland, WearFits introduces an R&D solution in the form of a virtual fitting room presented in augmented reality (AR) view to decrease returns of textile clothing bought online. It uses an avatar of human size and shape of the customer’s body for fitting the three-dimensional models in AR view. The purpose of the article is to review the state of the art of presentation of clothing textiles in e-commerce in the world and in Poland for selling textiles online and to emphasize the problem of size matching in the context of returns.","PeriodicalId":49104,"journal":{"name":"Autex Research Journal","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49530965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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