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Peer‐to‐peer (P2P) communities have the capability to construct a powerful virtual supercomputer by assembling idle internet cycles. The purpose of this paper is to present the scheduling issues in an unstructured P2P‐based high performance computing (HPC) system to achieve high performance for applications.

A new application model is proposed for the system, where applications are parallelized in the program level. To address high performance for these applications, the system resources are controlled in a semi‐centralized 3‐layer network, where volunteers form many autonomous unstructured P2P domains. Furthermore, based on such a resource management policy, a job scheduling strategy is adopted, which is collaborated by global and domain scheduling. The global scheduling is responsible for the balance among domains, while the domain scheduling resolve workpiles' execution in a domain.

Theoretical analysis and a benchmark experiment show that the scheduling provides scalable and enormous computing capability in the P2P‐based HPC system.

The paper shows that scheduling helps P2HP (an unstructured P2P‐based HPC system) provide scalable and enormous computing capability for HPC applications.

Telepresence robots (TPRs) are an emerging field of application and research that have received attention from various disciplines, including computer science, telehealth and education. The purpose of this study is to conduct a bibliometric analysis of publications on TPR in the Web of Science database from 1980 to 2022 to gain a better understanding of the state of research on TPRs and explore the role of pedagogical and psychological aspects in this research.

The analysis of research publications on TPRs was made on the basis of papers published in the Web of Science database from 1980 to 2022. The following research questions were proposed: What are the main tendencies in publication years, document types, countries of origin, source titles, publication authors, affiliations of authors and the most cited articles related to TPRs? What are the main topics discussed in the publications from the perspective of psychology? What are the main topics discussed in the publications from the perspective of educational sciences?

The results indicate that it is in the computer science where most of the existing research has been conducted, whereas the interest in the psychology and educational science has been relatively low. The greatest regional contributor has been the USA, whereas the effort in the European Union lags behind. Research publications in psychology in the Web of Science database related to TPRs can be grouped into three broad thematic categories: features of TPRs, degree of social presence compared to physical presence or other mediated technologies and opportunities for using TPRs. The results suggest that from the perspective of psychology, TPRs are one of the approaches that could enable greater social presence in remote communication. Most of the analysed papers in educational sciences investigated the opportunities of using TPRs in various educational fields. However, while the findings of the studies indicated significant potential of TPRs for education, their acceptance for wider use is still challenged.

The limitations of this research are that this study only analysed research papers in the Web of Science database and therefore only covers a limited number of scientific papers published in the field of psychology and educational sciences on TPRs. In addition, only publications with the term “telepresence robots” in the topic area of the Web of Science database were analysed. Therefore, several relevant studies are not discussed in this paper that are not reflected in the Web of Science database or were related to other keywords.

The field of TPRs has not been explored using a bibliographic analysis of publications in the Web of Science database from the perspective of psychology and educational sciences. The findings of this paper will help researchers and academic staff better understand the state of research on TPRs and the pedagogical and psychological aspects addressed in this research.

Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic.

The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed.

Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account.

Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future.

Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world.

A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.

The purpose of this study is to examine the role of retail investors’ green attention in promoting corporate environmental investments (EIs) using a communication sample on “Hudongyi” from 2011 to 2022.

In this paper, Python is used to capture data and text analysis techniques to obtain green attention information. In the word-matching process, words are matched in the target document one by one based on the preset dictionary and vocabulary rules. In addition to employing fixed effects, this study also incorporates instrumental variables using two-stage least squares (2SLS) estimation and applies the Heckman two-step method to verify the regression results.

First, this paper empirically examines the positive influence of retail investors’ green attention on EIs. Second, the findings show that retail investors’ green attention promotes EIs through decreasing principal-agent costs and principal-principal costs. Third, the results show that retail investor’s supervision effect is strengthened under the following three circumstances: executives with stronger green conception, corporations with less information asymmetry and areas with higher level of investor protection.

Our findings broaden the scope of prior research by exploring the impact of retail investor activism on nonfinancial outcomes, contributing to understanding the “black box” of how investor attention fosters EIs. Moreover, by leveraging the power of technology, retail investors have evolved from being the “silent majority” to being actively engaged. The internet has empowered retail investors by providing them with access to information and enabling them to exercise “voice” rights by appealing companies to engage in pro-environmental activities. Our study can provide useful suggestions for the green development of listed companies in China, as well as in other emerging countries.

Unlike other studies that focus on the deterrent effect and corporate financial outcomes of retail investors, we focus on the supervisory effect of retail investors and verify its role in driving EIs. This fills the knowledge gap in prior studies and contributes new insights to explain EIs and extends the understanding of retail investor activism.

We examine the effectiveness of signaling by disclosing innovation in annual reports in terms of securing R&D subsidies, using a novel text-based measure of firm-level innovation intensity.

The empirical analysis includes regressions with firm and year-fixed effects and an instrumental variable approach. Both mediation and moderation analysis are conducted to identify the plausible channels.

We find that firms are likely to receive research and development (R&D) subsidies if their annual reports contain intensive disclosure of information about innovation. We also identify the site visits by government officials as a plausible channel through which innovation disclosure in annual reports can help firms receive R&D subsidies. Additional analysis shows the main effect of innovation disclosure is especially pronounced in firms with severe information asymmetry and those facing a low-trust environment.

Current studies have shown the effectiveness of signaling in capital markets in terms of securing bank loans and venture capital (Cassar et al., 2015; Hoenig and Henkel, 2015; Connelly et al., 2016; Plummer et al., 2016). It is unclear if such a signaling can attract the attention of government officials. Our results suggest that government officials view annual reports as an important means of mitigating information asymmetry, which in turn helps firms to receive external R&D funding.

Facing turbulent environments, firms have strived to achieve greater supply chain resilience (SCR) to leverage the resources and knowledge of supply chain members. Both SCR and supply chain integration (SCI) require digitization in the supply chain, but their interrelationships have rarely been researched empirically. This paper aims to uncover the impact of digital technology (DT) on SCR and SCI and the role of SCI in mediating between DT and SCR.

China manufacturing enterprises were surveyed through a Web-based questionnaire, and 96 responses were received. Structural equation modeling was used to test the conceptual model.

The level of enterprise digitization is not directly related to supply chain resilience, but the level of enterprise digitization has a positive impact on the improvement of SCI and SCI also has a positive effect on SCR. Therefore, SCI has a complete intermediary effect between the level of DT and SCR.

This is a pioneer study to examine the relationships among DT, SCI and SCR. The findings of this study present that firms need to improve DT, SCI and SCR consequently.

This paper aims to calibrate the mounted parameters between the LIDAR and the motor in a low-cost 3D LIDAR device. It proposes the model of the aimed 3D LIDAR device and analyzes the influence of all mounted parameters. The study aims to find a way more accurate and simple to calibrate those mounted parameters.

This method minimizes the coplanarity and area of the plane scanned to estimate the mounted parameters. Within the method, the authors build different cost function for rotation parameters and translation parameters; thus, the parameter estimation problem of 4-degree-of-freedom (DOF) is decoupled into 2-DOF estimation problem, achieving the calibration of these two types of parameters.

This paper proposes a calibration method for accurately estimating the mounted parameters between a 2D LIDAR and rotating platform, which realizes the estimation of 2-DOF rotation parameters and 2-DOF translation parameters without additional hardware.

Unlike previous plane-based calibration techniques, the main advantage of the proposed method is that the algorithm can estimate the most and more accurate parameters with no more hardware.

In the mobile internet era, the path and mechanism of hospital patient-perceived quality have been changed radically. The purpose of this study is to develop a scale that adequately captures the characteristics of hospital service quality from the patient’s perspective under the background of the mobile internet.

Based on previous related research and interviews with focus groups, this paper conceptualized, constructed, refined and tested a multiple-item scale that examined key dimensions of hospital process service quality in the mobile context. To validate this scale, data were collected through two formal surveys in Chinese hospitals and were used to test the reliability and validity of the instrument.

The final measurement scale contains three dimensions, that is, environment conditions, attitude and behavior and technical convenience. With the help of this quality scale, hospital managers could have a better understanding of patients’ expectations under the new condition and pinpoint appropriate initiatives to fill the service gap.

This study focuses on service quality measurement issues related to the application of mobile internet technology in traditional clinical settings, such as hospitals. This paper develops an original and specific service quality scale that catches the online and offline characteristics of the hospital process in the mobile setting and considers both human-technology interaction and human-human interaction.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.