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The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.

A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research. The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage. The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics (age, driving experience or their combination) and the crash risk regarding cell phone engagements, as well as the correlation among the likelihood of the cell phone engagement during the driving, multiple driver demographic characteristics (gender, age and driving experience) and environment conditions.

Senior drivers face an extremely high crash risk when distracted by cell phone during driving, but they are not involved in crashes at a large scale. On the contrary, cell phone usages account for a far larger percentage of total crashes for young drivers. Similarly, experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving, and cell phone engagements are attributed to a lower percentage of total crashes for them. Furthermore, experienced, senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.

The results provide support to guide countermeasures and vehicle design.

The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com.

First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations.

To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines.

The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied.

This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies.

The technical architecture of ICVs as the “three rows and two columns” structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed.

This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.

The purpose of this paper is to deal with interval grey-stochastic multi-attribute decision-making problems. It proposes a VIKOR method based on prospect theory in which probabilities and the attribute value are both grey numbers.

In the prospect theory the results values and probability weight are used while the utility and probability values in the expected utility theory, which the more realistically reflect and describe the decision makers on the optimal process. VIKOR method makes the decision acceptable superiority and decision process stability. At the same time, a new interval grey number entropy is put forward, which is used to calculate the index weight of unknown.

The paper provides a VIKOR method based on prospect theory in which probabilities and the attribute value are both grey numbers. And the validity and feasibility of the method are illustrated by an example.

Although VIKOR is much closer to PIS than TOPSIS, at the same time VIKOR method can get the compromise solution with priority, researchers are encouraged to carry on comparative study further.

The paper includes interval grey-stochastic multi-attribute decision-making method and implications. The validity and feasibility of the method are illustrated by a case.

This paper proposes a VIKOR method based on prospect theory in which probabilities and the attribute value are both interval grey numbers. At the same time, a new interval grey number entropy is put forward, which is used to calculate the index weight of unknown.

This paper seeks to examine the further integration of machine translation technologies with cross language information access in providing web users the capabilities of accessing information beyond language barriers. Machine translation and cross language information access are related technologies, and yet they have their own unique contributions in handling information in multiple languages. This paper aims to demonstrate that there are many opportunities to further integrate machine translation with cross language information access, and the combination can greatly empower web users in their information access.

Using English and Chinese as the language pair for studying, this paper looks at machine translation in query translation‐based cross language information access at multiple important aspects, which include query translation, relevance feedback, interactive cross language information access, out‐of‐vocabulary term translation, and data fusion. The goal is to obtain more insights about the wide range usages of machine translation in cross language information access, and to help the community to identify promising future directions for both machine translation and cross language access.

Machine translation can be applied effectively in many places in the whole cross language information access process. Queries translated by a machine translation system are high quality and are more robust in handling potential untranslated terms. Translation enhancement, a relevance feedback method using machine translation generated returned documents, is not only a valid technique by itself, but also helps to generate more robust cross language information access performance when combined with other relevance feedback techniques. Machine translation is also found to play a significant role in resolving untranslated terms and in data fusion.

This set of comparative empirical studies on integrating machine translation and cross language information access was performed on a common evaluation framework, and examined integration at multiple points of the cross language access process. The experimental results demonstrate the value of further integrating machine translation in cross language information access, and identify interesting future directions for both machine translation and cross language information access research.

The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching topologies, where the states of the unmanned aerial vehicles need to form desired time-varying formations while tracking the trajectory of the virtual leader in finite time under jointly connected topologies.

A consensus-based formation control protocol is constructed to achieve the desired formation. In this paper, the time-varying formation is specified by a piecewise continuously differentiable vector, while the finite-time convergence is guaranteed by utilizing a non-linear function. Based on the graph theory, the finite-time stability of the close-loop system with the proposed control protocol under jointly connected topologies is proven by applying LaSalle’s invariance principle and the theory of homogeneity with dilation.

The effectiveness of the proposed protocol is verified by numerical simulations. Consequently, the proposed protocol can successfully achieve the predefined time-varying formation in finite time under jointly connected topologies while tracking the trajectory generated by the leader.

This paper proposes a solution to simultaneously solve the control problems of time-varying formation tracking, finite-time convergence, and switching topologies.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

In view of the particularity of innovative product diffusion under the background of market competition, this paper firstly uses consumer behavior theory to logically deduce the dynamic process of consumer behavior from the perspective of experience theory.

Bass and Lotka-Volterra model are used to describe and model the consumers' perceptual behavior in competitive environment. On this basis, interactive modeling technology is used to model and simulate the diffusion process of innovative products. Finally, the validity of the model is verified by comparing two scenarios with an example.

The research shows that the stronger the enterprise's competitiveness, the higher the market share of innovative products, and the positive impact on consumer perceived value, consumer perceived value can promote consumers' second purchase behavior. Positive word-of-mouth and advertising positively affect consumers' purchasing decisions; negative word-of-mouth negatively affects consumers' purchasing decisions.

The interaction modeling technology and AnyLogic software platform are used to simulate the complexity of consumers' experiential perception so as to build the interaction and competition mechanism among different Agent, which realizes the dynamic simulation of the diffusion process of innovative products. This study provides guidance for enterprises to formulate effective marketing strategies.

This study aims to examine how degree of servitization and breadth of servitization affect the firm performance, and the moderating roles of corporate social responsibility (CSR) and green innovation.

The hypotheses are tested using panel data regression models from 2010 to 2020 based on 10,539 firm-year observations from 2,362 Chinese listed manufacturers.

Considering the classification of servitization, the results show that both degree and breadth of servitization have positive impacts on firm performance. In addition, CSR strengthens these impacts, while green innovation only strengthens the impact of degree of servitization on firm performance.

This study suggests that manufacturers should obtain greater profits by actively implementing the servitization strategy, and effectively take their social responsibility by achieving value co-creation with stakeholders. Also, they should carry out green innovation, develop green products and provide eco-friendly services.

This study contributes to the servitization literature by deepening the understanding of the value creation effect of services based on the service-oriented logic. Also, this study contributes to the sustainability literature stream by revealing the moderating roles of CSR and green innovation based on the stakeholder theory.