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This article aims to understand users' information needs in the metaverse communities and to analyze the similarities and differences between their information needs and those of users in Internet communities.

This study conducted semi-structured interviews with users in the metaverse communities to gather raw data. Grounded theory research methods were employed to code and analyze the collected interview data, resulting in the extraction of 40 initial concepts, 15 subcategories and 5 main categories. Based on Maslow’s hierarchy of needs theory, this paper constructs the hierarchical model of users' information needs in the metaverse communities. It compares the differences between users' information needs in the metaverse and Internet fields.

The user’s information needs in the metaverse communities are divided into two types: deficiency needs and growth needs. Deficiency needs have two levels. The first level is the demand for basic information resources. The second level is the users demand for information assistance. Growth needs have three levels. The first level is the need for information interactions. The second level is the need for community rules. The ownership information in the community rules can provide proof of user status, assets and so on. The third level is the need for users to contribute and share their own created information content.

This article presents the latest research data from in-depth interviews with users in the metaverse communities. It aims to help builders and managers of metaverse communities understand users' information needs and improve the design of virtual communities.

The purpose of this paper is to investigate physiological indices related to comfort and health condition, based on which corresponding electronic equipment are selected and applied. A wearable monitoring system using sensor and liquid crystal display (LCD) techniques are then designed. Sensors are used to collect and transmit recording required signals from the wearer. A microcomputer with the type of AT89C52 is used to record and analyze the collected data. LCD is applied to display the health and comfort condition of the wearer.

A novel wearable monitoring system for the measurement of physiological indices and clothing microclimate is proposed in this study in order to monitoring both health and comfort condition of the wearer.

The proposed system provides reference for the application of sensor and display technologies in the field of smart clothing, which can be further applied to infant and child care, health care, home entertainment, military and industry.

This paper, first, investigated a framework of a wearable monitoring system considering both comfort and health condition and summarized the related physiological indices. The requirements of both comfort and health condition monitoring are analyzed to select appropriate electronic elements.

The purpose of this paper is to present a new collaborative design-based method for designing customized garments, aimed at the physically disabled people with scoliosis.

The proposed method is based on the virtual human model created using a 3D body scanner, permitting to simulate the consumer’s morphological shape with atypical physical deformations. Next, customized 2D and 3D virtual garment prototyping tools will be used to create products through interactions between the consumer, designer and pattern maker. The general principle of the proposed design method is based on the following sequence: design-display-evaluation-adjustment. After running the sequence for a number of times, the final design solution, which will be approved by both the designer and consumer, can be easily identified.

Design knowledge, which is already applied to normal body shapes successfully can be applied to 3D garment design using the concept which is based on collaborative design. Through this process, the classical 2D garment design knowledge, especially 2D patterns and design rules, can be modified and applied according to a normalized virtual garment sensory evaluation procedure quantitatively. This evaluation procedure, interactively performed by the designer and consumer, can permit to adapt the finished product to disabled people afflicted with severe scoliosis. The proposed method is also validated to be more advanced compared to 2D-to-3D virtual CAD design method, especially for atypical morphologies.

As a co-design method, 3D virtual draping and sensory evaluation can fully satisfy the interaction between the garment design technical space and perceptual space of the finished garments ensuring desired 3D garment fit effect by adjustment of technical parameters. 3D scanning technology is used to generate a complete digitalized 3D human model, permitting to extract the main features of body shapes without accurate measurements. As a knowledge-based design process, both the fashion design knowledge and the pattern making knowledge will be extracted to provide inspirations and references. Successful design solutions will be incorporated into the fashion design knowledge base in order to generate new design rules and enhance professional design knowledge.

This paper aims to evaluate and simulate the impact of the build platform temperature of the three-dimensional (3D) printer, the structure and heat transfer of textiles on the adhesion and durability after washing properties of 3D printed polymer onto textile materials using thin layers of conductive and non-conductive extruded poly lactic acid monofilaments (PLA) deposited on polyethylene terephthalate (PET) woven fabrics through fused deposition modeling (FDM) process.

Prior to FDM process, thermal conductivity, surface roughness and mean pore size of PET woven fabrics were assessed using the “hot disk,” the profilometer and the capillary flow porometry methods, respectively. After the FDM process, the adhesion and durability after the washing process properties of the materials were determined and optimized based on reliable statistical models connecting those properties to the textile substrate properties such as surface roughness, mean pore size and thermal conductivity.

The main findings point out that higher roughness coefficient and mean pore size and lower thermal conductivity of polyester woven textile materials improve the adhesion properties and the build platform presents a quadratic effect. Additionally, the adhesion strength decreases by half after the washing process and rougher and more porous textile structures demonstrate better durability. These results are explained by the surface topography of textile materials that define the anchorage areas between the printed layer and the textiles.

This study is for great importance in the development of smart textiles using FDM process as it presents unique and reliable models used to optimize adhesion resistance of 3D printed PLA primary layer onto PET textiles.

In the process of continuous casting and rolling of steel plate, due to the influence of rolling equipment and process, there are scratches, inclusions, patches, scabs and pitted surfaces on the surface of steel plate, which will not only affect the corrosion resistance, wear resistance and fatigue strength of steel plate but also may cause production accidents. Therefore, the detection of steel plate surface defect must be strengthened to ensure the production quality of steel plate and the smooth development of industrial construction.

(1) A steel plate surface defect detection technology based on small datasets is proposed, which can detect multiple surface defects and fill in the blank of scab defect detection. (2) A detection system based on intelligent recognition technology is built. The steel plate images are collected by the front-end monitoring device, then transmitted to the back-end monitoring center and processed by the embedded intelligent algorithms. (3) In order to reduce the impact of external light on the image, an improved Multi-Scale Retinex (MSR) enhancement algorithm based on adaptive weight calculation is proposed, which lays the foundation for subsequent object segmentation and feature extraction. (4) According to the different factors such as the cause and shape, the texture and shape features are combined to classify different defects on the steel plate surface. The defect classification model is constructed and the classification results are recorded and stored, which has certain application value in the field of steel plate surface defect detection. (5) The practicability and effectiveness of the proposed method are verified by comparison with other methods, and the field running tests are conducted based on the equipment commissioning field of China Heavy Machinery Institute.

When applied to small dataset, the precision of the proposed method is 94.5% and the time is 23.7 ms. In order to compare with deep learning technology, after expanding the image dataset, the precision and detection time of this paper are 0.948 and 24.2 ms, respectively. The proposed method is superior to other traditional image processing and deep learning methods. And the field recognition precision is 91.7%.

In brief, the steel plate surface defect detection technology based on computer vision is effective, but the previous attempts and methods are not comprehensive and the accuracy and detection speed need to be improved. Therefore, a more practical and comprehensive technology is developed in this paper. The main contributions are as follows: (1) A steel plate surface defect detection technology based on small datasets is proposed, which can detect multiple surface defects and fill in the blank of scab defect detection. (2) A detection system based on intelligent recognition technology is built. The steel plate images are collected by the front-end monitoring device, then transmitted to the back-end monitoring center and processed by the embedded intelligent algorithms. (3) In order to reduce the impact of external light on the image, an improved MSR enhancement algorithm based on adaptive weight calculation is proposed, which lays the foundation for subsequent object segmentation and feature extraction. (4) According to the different factors such as the cause and shape, the texture and shape features are combined to classify different defects on the steel plate surface. The defect classification model is constructed and the classification results are recorded and stored, which has certain application value in the field of steel plate surface defect detection. (5) The practicability and effectiveness of the proposed method are verified by comparison with other methods, and the field running tests are conducted based on the equipment commissioning field of China Heavy Machinery Institute.

The research documented in this paper aims to identify the components and characters of color perception and to establish the basis for color perception description and evaluation.

Ten pairs of antonyms obtained on the basis of investigation were suggested to evaluate the perception of color. About 15 color samples were prepared for subjective evaluation. The factorial analysis method and artificial neural network were applied to analyze the evaluation results given by professionals and to establish the objective basis for color perception evaluation.

The color perceptions could be distinguished by word pairs. These word pairs were grouped according to the perception characteristics. The relation between color parameters and color perception could be established by artificial neural network technique.

The results showed in this paper were obtained on the limited number of samples.

The principle of color perception was investigated on the subjective evaluation of color samples. The relation between color parameters and color perception was established and could be applied for reference of clothing color design.

The research in this paper aims to investigate the perception created by clothing style and semantic space to describe this perception. The results of study could be applied to establish relation between customers' feelings and design elements.

Women's overcoats were chosen as research objects. The technique of sensory engineering was applied to investigate the customers' feelings and demands related to product images. Card system, shape analytical method, and regression analysis were applied in this research.

Six word‐pair were selected to establish the semantic space. The product elements space with seven items and 25 categories was established. The relation between two spaces could be quantified according to the principle of sensory engineering.

The findings can be applied to women's overcoat and similar clothing for customer‐orientated design.

The theory of sensory engineering was applied for practical application purposes. Some useful parameters were obtained to explain the reliability of the research results and influences of design elements on perception judgment.

The purpose of this paper is to develop a simple and efficient conservative semi-Lagrangian scheme (SL) for solving advection equation in fast fluid dynamics (FFD), so FFD can provide fast indoor airflow simulations while preserving conservation for energy and species transport.

This study thus proposed a mass-fixing type conservative SL that redistributes global surplus/deficit on the advected field after performing the standard semi-Lagrangian advection. The redistribution weights were designed to preserve the properties of conservatives and monotonicity.

The effectiveness of the conservative SL was validated with several test cases, and the results show that the proposed scheme is indeed conservative with negligible impact on the accuracy of the standard solutions. The numerical tests show that the proposed scheme was indeed conservative with negligible impact on the accuracy of the flow prediction.

The FFD with conservative SL can effectively enforce the energy and species conservation for indoor airflow and predict airflow distributions with reasonable accuracy.

The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet‐based kind of knowledge market by considering both social and economic interactions.

A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of complex interactions in a fee‐based online question & answer (Q&A) knowledge market. The proposed model considers the dynamic, non‐linear, asymmetric, and reciprocal relationships between its components, and allows the study of the evolution of the market under assumed conditions.

Some illustrative results show that: this market is very sensitive to the prices that the customers choose; low‐priced questions are as important as high‐priced ones; gradually increasing experts' proportion of a question's price reduces customer satisfaction and experts' reputation; and training programs for experts result in higher customer satisfaction and researchers' reputation. Furthermore, three types of customers are identified and discussed.

This model can be used to change, manage, and control this market and also helps to design new similar markets. In addition, the proposed model helps to observe the behavior of a market under one or more policies before applying to the real world.

Since GA was shut down in 2006, the implications of this research serve as a strategic tool (strategic evaluation software) for understanding and examining the effects of policies for many existing similar Q&A business models. Furthermore, the SD approach can provide new insights into the field of online Q&A knowledge markets and overcome traditional econometric treatment of data for understanding the dynamic behavior of these markets.

Understanding the complex social and economic behavior of Q&A markets is one of the most important concerns for academics and practitioners in the areas of online markets' management. The paper shows how SD can provide attractive insights into the field of online fee‐based knowledge markets based on a qualitative and quantitative modeling. However, the background literature lacks a holistic view of these kinds of markets.