Search results

This study aims to examine on-site particle concentration levels due to emissions from a wide spectrum of additive manufacturing techniques, including polymer-based material extrusion, metal and polymer-based powder bed fusion, directed energy deposition and ink-based material jetting.

Particle concentrations in the operating environments of users were measured using a combination of particle sizers including the TSI 3910 Nano SMPS (10–420 nm) and the TSI 3330 optical particle sizer (0.3–10 µm). Also, fumes from a MEX printer during printing were directly captured using laser imaging method.

The number and mass concentration of submicron particles emitted from a desktop open-type MEX printer for acrylonitrile-butadiene-styrene and polyvinyl alcohol approached and significantly exceeded the nanoparticle reference limits, respectively. Through laser imaging, fumes were observed to originate from the printer nozzle and from newly deposited layers of the desktop MEX printer. On the other hand, caution should be taken in the pre-processing of metal and polymer powder. Specifically, one to ten micrometers of particles were observed during the sieving, loading and cleaning of powder, with transient mass concentrations ranging between 150 and 9,000 µg/m³ that significantly exceeded the threshold level suggested for indoor air quality.

Preliminary investigation into possible exposures to particle emissions from different 3D printing processes was done, which is useful for the sustainable development of the 3D printing industry. In addition, automatic processes that enable “closed powder cycle” or “powder free handling” should be adopted to prevent users from unnecessary particle exposure.

The purpose of this paper is to analyze the readability and level of word complexity of search engine results pages (SERPs) snippets and associated web pages between Google and Bing.

The authors employed the Readability Test Tool to analyze the readability and word complexity of 3,000 SERPs snippets and 3,000 associated pages in Google and Bing retrieved on 150 search queries issued by middle school children.

A significant difference was found in the readability of SERPs snippets and associated web pages between Google and Bing. A significant difference was also observed in the number of complex words in snippets between the two engines but not in associated web pages. At the engine level, the readability of Google and Bing snippets was significantly higher than associated web pages. The readability of Google SERPs snippets was at a much higher level than those of Bing. The readability of snippets in both engines mismatched with the reading comprehension of children in grades 6–8.

The data corpus may be small. Analysis relied on quantitative measures.

Practitioners and other mediators should mitigate the readability issue in SERPs snippets. Researchers should consider text readability and word complexity simultaneously with other factors to obtain the nuanced understanding of young users’ web information behaviors. Additional theoretical and methodological implications are discussed.

This study measured the readability and the level of word complexity embedded in SERPs snippets and compared them to respective web pages in Google and Bing. Findings provide further evidence of the readability issue of SERPs snippets and the need to solve this issue through system design improvements.

This is the third of a series of studies on Chinese brand naming using content analysis from a linguistic perspective. The first study generalized the principles guiding Chinese brands in terms of syllable pattern, tone pattern, compounding structure and semantic preference. The second looked at specific branding rules, focusing on two entirely different products: cosmetic products and bicycles. The present study, following the same linguistic framework of analysis, analyzes three groups of closely related products: spirits, beers, soft drinks, to see how these brands are creatively and distinctively constructed. Finds that the brand naming patterns of the three drinks are basically in agreement with the general Chinese branding principles, and the differences among them directly reflect the development, the consumer markets and characteristics of each product.

The purpose of this paper is to conduct a survey on research in fabric and cloth simulation using mass spring model. Also in this paper some of the common methods in process of fabric simulation in mass spring model are discussed and compared.

This paper reviews and compares presented mesh types in mass spring model, forces applied on model, super elastic effect and ways to settle the super elasticity problem, numerical integration methods for solving equations, collision detection and its response. Some of common methods in fabric simulation are compared to each other. And by using examples of fabric simulation, advantages and limitations of each technique are mentioned.

Mass spring method is a fast and flexible technique with high ability to simulate fabric behavior in real time with different environmental conditions. Mass spring model has more accuracy than geometrical models and also it is faster than other physical modeling.

In the edge of digital, fabric simulation technology has been considered into many fields. 3D fabric simulation is complex and its implementation requires knowledge in different fields such as textile engineering, computer engineering and mechanical engineering. Several methods have been presented for fabric simulation such as physical and geometrical models. Mass spring model, the typical physically based method, is one of the methods for fabric simulation which widely considered by researchers.

This study aims to explore the collaborative potential of Microsoft Copilot and Anthropic Claude AI as an assistive technology in education and library services. The research delves into technical architectures and various use cases for both tools, proposing integration strategies within educational and library environments. The paper also addresses challenges such as algorithmic bias, hallucination and data rights.

The study used a literature review approach combined with the proposal of integration strategies across education and library settings.

The collaborative framework between Copilot and Claude AI offers a comprehensive solution for transforming education and library services. The study identifies the seamless combination of real-time internet access, information retrieval and advanced comprehension features as key findings. In addition, challenges such as algorithmic bias and data rights are addressed, emphasizing the need for responsible AI governance, transparency and continuous improvement.

Contribute to the field by exploring the unique collaborative framework of Copilot and Claude AI in a specific context, emphasizing responsible AI governance and addressing existing gaps.

This chapter investigates the behavior of Reddit’s news subreddit users and the relationship between their sentiment on exchange rates. Using graphical models and natural language processing, hidden online communities among Reddit users are discovered. The data set used in this project is a mixture of text and categorical data from Reddit’s news subreddit. These data include the titles of the news pages, as well as a few user characteristics, in addition to users’ comments. This data set is an excellent resource to study user reaction to news since their comments are directly linked to the webpage contents. The model considered in this chapter is a hierarchical mixture model which is a generative model that detects overlapping networks using the sentiment from the user generated content. The advantage of this model is that the communities (or groups) are assumed to follow a Chinese restaurant process, and therefore it can automatically detect and cluster the communities. The hidden variables and the hyperparameters for this model are obtained using Gibbs sampling.

Reports a study of 1,304 Chinese brand names of ten types of products in China. These brand names are content analyzed following a linguistic approach which the authors developed from their earlier studies. The ten types of brand names are presented in three broad categories representing the three different developing stages of the consumer product industry in China: brands of traditional products (illustrated by matches and spirits), brands of traditional products with current development (illustrated by bicycles, shoes, and toothpastes), and brands of new and modern products (illustrated by cosmetics, soft drinks, washing machines, refrigerators and TV sets). The conclusion drawn from the analysis is that one of the variables in determining how linguistic principles are being applied to Chinese brand naming is the respective stages of development of such products in the context of the Chinese market economy.

The performance of public–private partnerships (PPPs) can be determined by a variety of factors, i.e. influencing factors (IFs). This study is undertaken for a purpose of identifying how such factors determine the project's performance (i.e. factor transmission patterns), particularly from the key stakeholders' perspectives.

A hybrid approach, which comprises a Social Network Analysis, ISM (i.e. Interpretive Structural Modeling) and an improved DEMATEL (i.e. Decision-Making Trail and Evaluation Laboratory), was developed to analyze the causal relationships between the identified IFs as well as the transmission patterns of their impacts on PPPs. Data were collected from interviews and questionnaire surveys.

The transmission patterns of the identified IFs cascade from project environment and features and stakeholders' relationship to the project company capabilities and project process. It is identified that the public authority has a higher level than that of the private entity in PPPs.

It lacks longitudinal studies to investigate the dynamics of PPP stakeholder relationships and social networks. Future research needs to explore the transmission patterns of sub-factors affecting PPP performance and extend the applicability of the developed hybrid approach.

This research provides practitioners with a robust tool that is useful for and insights into enhancing the management of lifecycle performance. It ensures the public authorities and private entities embarking on PPPs will make an informed decision about the monitoring of the life cycle performance.

This study contributes to knowledge of managerial mechanisms that can be adopted to manage factors determining the performance of PPPs. It enables an understanding of stakeholders' roles in driving the life cycle performance of PPPs.

“Metaverse” has become a buzzword in the Chinese stock market. However, it remains unclear whether a firm's metaverse-related announcements will elicit positive stock market reactions. Whether and how stakeholder reactions are influenced by a firm's metaverse-related readiness also needs to be further explored. This study aims to discuss the aforementioned objective.

The authors derived a set of factors based on readiness theory and business ecosystem literature and extend them into the context of the metaverse. The authors used a sample of 642 Chinese listed firms in 2021 to investigate the hypotheses through the event study.

The study’s findings show that metaverse coverage induces a positive stock market reaction, but it is subject to three moderating effects. The authors introduce the novel concepts of IT readiness, ecosystem readiness and digital infrastructure readiness as the moderators. Stakeholders perceive metaverse announcements as overhyped, and stock prices do not fluctuate significantly after a metaverse announcement when the listed firms are not ready to embrace the metaverse.

This study is one of the first that introduces the event study method into the metaverse research, and it reveals that different levels of readiness influence stakeholders' evaluations and reactions to corporate metaverse coverage. This provides empirical evidence on metaverse development in China from the stock market's perspective.