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Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.

In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.

The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.

The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.

This paper aims to investigate the hydrodynamic instability properties of a mixed convection flow of nanofluid in a porous channel.

The treated single-phase nanofluid is a suspension consisting of water as the working fluid and alumina as a nanoparticle. The anisotropy of the porous medium and the effects of the inclination of the magnetic field are highlighted. The effects of viscous dissipation and thermal radiation are incorporated into the energy equation. The eigenvalue equation system resulting from the stability analysis is processed numerically by the spectral collocation method.

Analysis of the results in terms of growth rate reveals that increasing the volume fraction of nanoparticles increases the critical Reynolds number. Parameters such as the mechanical anisotropy parameter and Richardson number have a destabilizing effect. The Hartmann number, permeability parameter, magnetic field inclination, Prandtl number, wave number and thermal radiation parameter showed a stabilizing effect. The Eckert number has a negligible effect on the growth rate of the disturbances.

Linear stability analysis of Magnetohydrodynamics (MHD) mixed convection flow of a radiating nanofluid in porous channel in presence of viscous dissipation.

Innovation is the most important quality of enterprise management. It is an important and controversial issue whether the heterosexual leadership structure of the chairman and chief executive officer (CEO) makes the work “easy” or “very tired” in enterprise innovation. This study investigates the specific impact of the heterosexual leadership structure on enterprise innovation investment, and further explores influence mechanism between them from two perspectives. Specifically, from the perspective of enterprise leaders including the chairman and CEO, this paper analyzes the impact of surname sharing, intergenerational differences and top management team (TMT) external social network between the heterosexual leadership structure and enterprise innovation investment. And from the perspective of enterprise itself, this study explores the impact of ownership and organizational slack between the heterosexual leadership structure and enterprise innovation investment.

By using ordinary least squares regression (OLS), this study mainly takes the unbalanced panel data of A-share listed companies from 2008 to 2019 in Shanghai and Shenzhen as the research sample to empirically analyze the relationship and influence mechanism between the heterosexual leadership structure and enterprise innovation investment.

The results show that the heterosexual leadership structure of the chairman and CEO has a negative impact on enterprise innovation investment. Surname sharing and ownership positively moderate the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment. Intergenerational differences and TMT external social network negatively moderate the relationship between the heterosexual leadership structure of the chairman and CEO and enterprise innovation investment. In addition, the moderating effects of intergenerational differences and TMT external social network on the relationship between the heterosexual leadership structure and enterprise innovation investment both depend on organizational slack. When organizational slack is lower and intergenerational differences are higher, the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment will be the strongest. And when organizational slack is lower and TMT external social network is higher, the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment will be the strongest.

By exploring the influence and the boundary mechanism of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment, the “heterosexual difference effect” is verified in this paper, that is, when men and women work together, work is very tired. This not only enriches the existing research of enterprise innovation investment, but also provides practical guidance for effectively improving enterprise innovation investment from a new perspective. In addition, it broadens the moderating mechanism of the impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment, which is conducive to reasonable response to improve enterprise innovation investment.

A novel type of heat transfer fluid known as hybrid nanofluids is used to improve the efficiency of heat exchangers. It is observed from literature evidence that hybrid nanofluids outperform single nanofluids in terms of thermal performance. This study aims to address the stagnation point flow induced by Williamson hybrid nanofluids across a vertical plate. This fluid is drenched under the influence of mixed convection in a Darcy–Forchheimer porous medium with heat source/sink and entropy generation.

By applying the proper similarity transformation, the partial differential equations that represent the leading model of the flow problem are reduced to ordinary differential equations. For the boundary value problem of the fourth-order code (bvp4c), a built-in MATLAB finite difference code is used to tackle the flow problem and carry out the dual numerical solutions.

The shear stress decreases, but the rate of heat transfer increases because of their greater influence on the permeability parameter and Weissenberg number for both solutions. The ability of hybrid nanofluids to strengthen heat transfer with the incorporation of a porous medium is demonstrated in this study.

The findings may be highly beneficial in raising the energy efficiency of thermal systems.

The originality of the research lies in the investigation of the Darcy–Forchheimer stagnation point flow of a Williamson hybrid nanofluid across a vertical plate, considering buoyancy forces, which introduces another layer of complexity to the flow problem. This aspect has not been extensively studied before. The results are verified and offer a very favorable balance with the acknowledged papers.

The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event industry and what research topics are the most promising for further exploration.

A bibliometric analysis of the existing body of knowledge on the topic was conducted and the results were visualized using CiteSpace 5.8.R3. A total of 1999 articles and proceeding papers from the Web of Science Core Collection published between 2007 and 2022 were selected for our analysis. Based on the articles and proceeding papers in the Web of Science Core Collection database, we selected a set of publications for our analysis. The data were obtained through specific keywords related to our research topic. The method involves a process of three main stages: data collection, data processing and the bibliometric analysis.

Co-citation analysis indicated that issues of crowd management and tracking human mobility during mass events are important for the event industry and that technologies such as the Internet of Things, special-purpose mobile applications and systems make it easier for an event organizer to handle the issues. The findings demonstrated a weak scientific collaboration between countries in the topic studied and shift of research hotspots to study of satisfaction, motivation and behavioral patterns of events attendees. Based on this analysis, three directions for future research were revealed.

The results should be interpreted in light of our sample, because the analysis was conducted within our sample which has boundaries. We collected data from all categories in the Web of Science Core Collection database, but we considered only articles and proceeding papers as opposed to all possible types of scientific publications and other databases. In the study, we focused on detecting the state-of-the-art of the event industry in the context of digitalization overall. More specific topics that could be analyzed remain, for example, the dependency of digital technologies from the event type, etc.

This study reflects the state-of-the-art of the event industry in the context of digitalization. It provides researchers with key developmental trends in the event industry, which assists them in more deeply understanding the evolution of research hotspots in the field during last 15 years and defining future research agenda. The paper presents an overview of digital technologies used in various types of events and describes the issues and results related to the implementing digital technologies. The results obtained were extremely important, as they can be used by event managers and organizers to enhance customers’ experience during the events.

This study reflects the state-of-the-art of the event industry in the context of digitalization. This is the first attempt to make an overall analysis of scientific papers published in the Web of Science Core Collection on the topic studied without excluding any categories. The search procedure is transparent, and the results can be reproduced in other search fields using the same approach. Based on this analysis, three directions for future research were revealed including technological aspects of online event-based social networks, issues of crowd management and security at mass events and issues of attendees’ acceptance of novel digital technologies.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

This study aims to study the thermal identification issue by harvesting both solar energy and atmospheric thermal updraft for a solar-powered unmanned aerial vehicle (SUAV) and its electric energy performance under continuous soaring conditions.

The authors develop a specific dynamic model for SUAVs in both soaring and cruise modes. The support vector machine regression (SVMR) is adopted to estimate the thermal position, and it is combined with feedback control to implement the SUAV soaring in the updraft. Then, the optimal path model is built based on the graph theory considering the existence of several thermals distributed in the environment. The procedure is proposed to estimate the electricity cost of SUAV during flight as well as soaring, and making use of dynamic programming to maximize electric energy.

The simulation results present the integrated control method could allow SUAV to soar with the updraft. In addition, the proposed approach allows the SUAV to fly to the destination using distributed thermals while reducing the electric energy use.

Two simplified dynamic models are constructed for simulation considering there are different flight mode. Besides, the data-driven-based SVMR method is proposed to support SUAV soaring. Furthermore, instead of using length, the energy cost coefficient in optimization problem is set as electric power, which is more suitable for SUAV because its advantage is to transfer the three-dimensional path planning problem into the two-dimensional.

This study aims to determine the most similar set of recommendation books to the user selections in LibraryThing.

For this purpose, 30,000 tags related to History on the LibraryThing have been selected. Their tags and the tags of the related recommended books were extracted from three different recommendations sections on LibraryThing. Then, four similarity criteria of Jaccard coefficient, Cosine similarity, Dice coefficient and Pearson correlation coefficient were used to calculate the similarity between the tags. To determine the most similar recommended section, the best similarity criterion had to be determined first. So, a researcher-made questionnaire was provided to History experts.

The results showed that the Jaccard coefficient, with a frequency of 32.81, is the best similarity criterion from the point of view of History experts. Besides, the degree of similarity in LibraryThing recommendations section according to this criterion is equal to 0.256, in the section of books with similar library subjects and classifications is 0.163 and in the Member recommendations section is 0.152. Based on the findings of this study, the LibraryThing recommendations section has succeeded in introducing the most similar books to the selected book compared to the other two sections.

To the best of the authors’ knowledge, itis for the first time, three sections of LibraryThing recommendations are compared by four different similarity criteria to show which sections would be more beneficial for the user browsing. The results showed that machine recommendations work better than humans.