Core Competitiveness Construction of Clothing Brands in Low-Carbon Economy

The climate issue has become an environmental concern for all sectors of the world and the low-carbon economy has thus become a new economic development model to combat climate change.With the development of low-carbon economy era,the textile and clothing industry plays an important role in stabilizing the development of low-carbon economy and society,and China has put forward the development requirements of low-carbon transformation for the textile and clothing industry,and also it has an important strategic value to promote the high-quality development of low-carbon economy and society,and the construction of brands’ core competitiveness is an inevitable choice for clothing brands in the face of the new form of international competition.As a result,the evaluation indicator of clothing brands’ core competitiveness in the low-carbon economy is used to measure the core competitiveness of clothing brands.Based on the corresponding verification results obtained by analytic hierarchy process(AHP) analysis,it can guide the low-carbon development of the clothing industry,thus proposing a more reasonable way to build the core competitiveness of clothing brands.It can promote the low-carbon transformation and upgrading of the clothing industry,effectively increase the market share of clothing brands,and promote the high-quality development of clothing brands.

Clothing Parsing Based on Multi-Scale Fusion and Improved Self-Attention Mechanism

Due to the lack of long-range association and spatial location information,fine details and accurate boundaries of complex clothing images cannot always be obtained by using the existing deep learning-based methods.This paper presents a convolutional structure with multi-scale fusion to optimize the step of clothing feature extraction and a self-attention module to capture long-range association information.The structure enables the self-attention mechanism to directly participate in the process of information exchange through the down-scaling projection operation of the multi-scale framework.In addition,the improved self-attention module introduces the extraction of 2-dimensional relative position information to make up for its lack of ability to extract spatial position features from clothing images.The experimental results based on the colorful fashion parsing dataset(CFPD)show that the proposed network structure achieves 53.68%mean intersection over union(mIoU)and has better performance on the clothing parsing task.

2023 National Textile and Clothing Standards Innovation Conference held

The 2023 National Textile and Clothing Standards Innovation Conference convened in Tai’an city,Shandong province on August 18-20,where national experts in this field gathered to discuss the innovative development of the standards system for China’s textile and clothing.

Analysis of the Influence of Clothing on Characterization from Symbolism: Taking The Scarlet Letter, Daisy Miller, and Dry September as Examples

In the novels, the clothing worn by the characters are symbols made and used by the authors to express the characters’ personality and deepen the theme, and grasping their symbolism helps to enter into the interior of the novels and understand their essence. This paper will analyze and interpret the clothing of typical female characters in The Scarlet Letter, Daisy Miller and Dry September from the perspective of symbolism, so as to illustrate how the symbolism of clothing, as a kind of symbols, shapes the image of the main characters.

Clothing Sales Forecast Considering Weather Information: An Empirical Study in Brick-and-Mortar Stores by Machine-Learning

Reliable sales forecasts are important to the garment industry. In recent years, the global climate is warming, the weather changes frequently, and clothing sales are affected by weather fluctuations. The purpose of this study is to investigate whether weather data can improve the accuracy of product sales and to establish a corresponding clothing sales forecasting model. This model uses the basic attributes of clothing product data, historical sales data, and weather data. It is based on a random forest, XGB, and GBDT adopting a stacking strategy. We found that weather information is not useful for basic clothing sales forecasts, but it did improve the accuracy of seasonal clothing sales forecasts. The MSE of the dresses, down jackets, and shirts are reduced by 86.03%, 80.14%, and 41.49% on average. In addition, we found that the stacking strategy model outperformed the voting strategy model, with an average MSE reduction of 49.28%. Clothing managers can use this model to forecast their sales when they make sales plans based on weather information.

Business Clothing For Females: Suitability For Effective Workplace Job Performance in Nigeria

The study investigated business clothing for females that are suitable for effective workplace job performance in Nigeria.It identified fabric characteristics of females’business clothing already used;fabric characteristics needed and deign style preference suitable for females’business clothing for workplace job performance.The study was guided by four research questions and two hypotheses.Population was 4,806 female civil servants in Delta state,Nigeria.Multi-stage sampling technique was utilized to select 136 females.Structured questionnaire was employed to collect data and descriptive statistics and t-test were used for data analysis.Finding showed that cotton,nylon,lacra fabrics,light and medium fabric weight,blue,black,gray,colors,cool texture,rough,smooth surface plain,stripe and flowered design among others were fabric characteristics of business clothing are being used in workplace.But prefer and need cotton,nylon,lacra,light weight,black,blue,gray,brown colours,cool,plain,surface fabrics.Net,organza,heavy weight,white,yellow,toweling fabrics were not preferred.Findings further showed that straight gown,waist flared and gathered gowns,skirt,blouse and suit/jacket,straight,shirt,long sleeves,garment with or without collar,below knee length,peter and convertible collars,among others were highly preferred design styles of clothes.In conclusion,office workers determine what they wear to perform workplace daily jobs promotes self-confidence,comfort,professional worth and productivity.It was recommended that female employees should not downplay appropriate work attires for comfort and organizational productivity to satisfy fashion trends.

The development of anti-fall functional clothing for elderly

Objective:The consequences of falls in the elderly are severe,ranging from skin abrasion to hip fracture,which is very easy to cause death.Using advanced technology to develop anti-fall clothing that meets the needs of the elderly can play a significant role in protecting the elderly.By reviewing and analyzing the existing literature on the importance of fall protection clothing in reducing falls and protecting the body of the elderly,it is hoped to explore further research that needs improvement.Methods:Guided by the preferred reporting items for systematic reviews and meta-analyses,eight related studies were identified through Web of Science,Scopus and Chinese National Knowledge Infrastructure.The research objects,approaches,material and equipment,protection principle,and survey results are extracted.Results:Two articles verified the fall detection algorithm adopted in the research through experiments,which significantly improved fall detection accuracy.Six papers found that selecting appropriate cushioning materials can effectively reduce the consequences of falls of the elderly through experimental comparative analysis.Finally,three attributes for significant design value are drawn:(1)size and fit;(2)cushioning materials;(3)wearable sensing elements.

A Comparison of Cultures between China and the West——Taking Chinese Clothing and British Clothing as an Example

This paper attempts to do study on the comparison of differences between Chinese and western cultures by taking the Chinese and British clothing as an example. This comparison is made form two aspects about clothing culture. One is the separate characteristics of the Chinese and British clothing. The other is the common features of the Chinese and British clothing.The paper aims at making the Chinese confidently promote the clothing culture of China to make efforts to realize the great rejuvenation of China and enrich the culture of all mankind.

Computer Vision Evaluation of Clothing Fit

Most of the research on clothing fit is dependent on the subjective experience,and there are few studies involved in quantitative analysis.In this regard,this topic is innovative,it is the combination of image processing technology and garment fit evaluation.Through the background of the image noise reduction,edge extraction,reference point selection,to obtain the actual size.And according to the membership function to obtain the scope of the fit,the computer way to determine the degree of clothing fit.

Analysis and Research on the phenomenon of multifunction clothing

The changes of the times to update the mode of life, so that people in the material consumption at the same time. the more the pursuit of spiritual enjoyment of consumption.＂Multi function clothing＂ in a single product can transform a variety of clothing style,with multi - variability and fashion.Not only reduces the scale of production and people＇s pursuit of fashion personality contradiction between them, also make life and travel more lightweight, functional, and intelligent, increased interest and personality clothing experience. Its low energy consumption, high utilization and other advantages, but also the expression of the concept of low carbon environmental protection.Its characteristics conform to the development trend of the times and the concept of the times, it can also meet the diverse psychological demands of the consumers, and have great market potential.

Heat strain in chemical protective clothing in hot-humid environment:Effects of clothing thermal properties

Heat strain experienced by individuals wearing chemical protective clothing(CPC)is severe and dangerous especially in hot-humid environment.The development of material science and interdisciplinary studies including ergonomics,physiology and heat transfer is urgently required for the reduction of heat strain.The aim of this paper was to study the relationship among clothing thermal properties,physiological responses and environmental conditions.Three kinds of CPC were selected.Eight participants wore CPC and walked(4 km/h,two slopes with 5%and 10%)on a treadmill in an environment with(35±0.5)℃ and RH of(60±5)%.Core temperature,mean skin temperature,heart rate,heat storage and tolerance time were recorded and analyzed.Physiological responses were significantly affected by the clothing thermal properties and activity intensity in hot-humid environment.The obtained results can help further development of heat strain model.New materials with lower evaporative resistance and less weight are necessary to release the heat strain in hot-humid environments.

An Application of Grey Clustering Method in the Sporting Clothing Style Evaluation

In this paper, a Grey clustering method is applied to the evaluation research of sporting clothing style, the result shows that the methods proposed in the paper is feasible and effective.

Study on the Relation between the Air Gap Size under Clothing and the Comfort Sensations

Combining two non-contact testing instruments of a three-dimensional body measure system and an infrared camera, the entrapped air gap under clothing and the clothing surface temperature distribution were measured without interfering the air gap state. It was discussed the effect of different air gap size on subjective clothing sensation. At the same time, taken the subjective sensations of moisture, adhesiveness and mugginess from the lower back as example, the relationship among the subjective evaluation, the air gap size and the clothing surface temperature were analyzed.

Evaluation of Relationship Between Clothing Pressure of Men's Suit and Comfort

An investigation on relationship between clothing pressure of men's suit and wearing comfort is conducted. With the pressure measurements at different parts of men's suit under normal standing posture and in motion, the objective assessment of the total comfort are related to the subjective ratings of clothing pressure. There is a common strong sensation of pressure on shoulder with normal standing posture, and a strong relationship between total comfort and clothing pressure in back armhole and the front of upper arm with posture in motion.

Skin Sensitive Difference of Human Body Sections under Clothing— Smirnov Test of Skin Surface Temperatures' Dynamic Changing

Skin sensitive difference of human body sections under clothing is the theoretic foundation of thermal insulation clothing design. By a new method of researching on clothing comfort perception, the skin temperature live changing procedure of human body sections affected by the same cold stimulation is inspected. Furthermore with the Smirnov test the skin temperatures dynamic changing patterns of main human body sections are obtained.

Intelligence in Clothing Pattern CAD System

It analyzes three recognition methods for five elements,i.e.dot,line,loop,clothing pattern as well as characters,and also applies intelligent points and tangential curve in the CAD system to solve the problem complained by CAD users.It indicates that recognition of five elements is a foundational technique of intelligence in clothing pattern CAD system.Common functions in operation state such as move,rotation,flip,measure,should precede ones in element state as dot,line,and pattern.Moreover,it is realized that the less skill the CAD user needs,the more the CAD software is high-tech.

Analysis on the Application of Image Processing Technology in Clothing Pattern Recognition

A clothing pattern is a significant embodiment of regional culture and national characteristics.The recognition of clothing patterns could be realized objectively and accurately by using digital image processing technology.The researches on the extraction techniques of various pattern elements were compared and analyzed.Then the researches on clothing pattern color,outline and fabric texture extraction were summarized.And the core technology chain model of clothing pattern extraction was constructed.The research status,the core technology and the development trend of pattern element extraction technology based on two-dimensional images were obtained.What’s more,a reference for the follow-up research of clothing patterns and the technology upgrading of textile and clothing industries were provided.

Effects of Dressing Poses on Clothing Thermal Insulation

With a thermal manikin, the effects of dressing poses on clothing thermal insulation are studied. It is found that the thermal insulation of still air layer over human body has not been influenced by the dressing poses, but the dressing poses have effects on the thermal insulation of clothing system.

Feature Fusion Multi_XMNet Convolution Neural Network for Clothing Image Classification

Faced with the massive amount of online shopping clothing images,how to classify them quickly and accurately is a challenging task in image classification.In this paper,we propose a novel method,named Multi_XMNet,to solve the clothing images classification problem.The proposed method mainly consists of two convolution neural network(CNN)branches.One branch extracts multiscale features from the whole expressional image by Multi_X which is designed by improving the Xception network,while the other extracts attention mechanism features from the whole expressional image by MobileNetV3-small network.Both multiscale and attention mechanism features are aggregated before making classification.Additionally,in the training stage,global average pooling(GAP),convolutional layers,and softmax classifiers are used instead of the fully connected layer to classify the final features,which speed up model training and alleviate the problem of overfitting caused by too many parameters.Experimental comparisons are made in the public DeepFashion dataset.The experimental results show that the classification accuracy of this method is 95.38%,which is better than InceptionV3,Xception and InceptionV3_Xception by 5.58%,3.32%,and 2.22%,respectively.The proposed Multi_XMNet image classification model can help enterprises and researchers in the field of clothing e-commerce to automaticly,efficiently and accurately classify massive clothing images.

Narrow Pooling Clothing Classification Based on Attention Mechanism

In recent years,with the rapid development of e-commerce,people need to classify the wide variety and a large number of clothing images appearing on e-commerce platforms.In order to solve the problems of long time consumption and unsatisfactory classification accuracy arising from the classification of a large number of clothing images,researchers have begun to exploit deep learning techniques instead of traditional learning methods.The paper explores the use of convolutional neural networks(CNNs)for feature learning to enhance global feature information interactions by adding an improved hybrid attention mechanism(HAM)that fully utilizes feature weights in three dimensions:channel,height,and width.Moreover,the improved pooling layer not only captures local feature information,but also fuses global and local information to improve the misclassification problem that occurs between similar categories.Experiments on the Fashion-MNIST and DeepFashion datasets show that the proposed method significantly improves the accuracy of clothing classification(93.62%and 67.9%)compared with residual network(ResNet)and convolutional block attention module(CBAM).