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The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River.

The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios.

The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 10⁸ to 62.20 × 10⁸ m³ in year 2020 and between 73.32 × 10⁸ and 89.27 × 10⁸ m³ in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users.

The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.

The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.

A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.

The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.

Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.

This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

This study constructs the influence mechanism model of sustainable marketing activities (SMAs), event image, commemorative product perceived value and tourists’ behavioral intentions (TBIs) in the sports tourism context of the Beijing Winter Olympic Games. Additionally, the article discusses the role of event image and product perceived value in enhancing the SMAs’ effect on TBIs.

The research analyzed 315 valid questionnaires from tourists in the Chinese market by structural equation modeling.

The results indicate that SMAs positively impact sports tourism event image, tourists’ perceived commemorative product value and TBIs. Meanwhile, event image and product perceived value mediate the SMAs and TBIs relationship.

Considering SMAs as essential for sustainable development, this paper contributes to the strategic management discipline. Additionally, the research expands the analysis of event image and product perceived value in the brand theory and customer behavior research.

The article outlines the principal value of SMAs implementation in enhancing behavioral intentions. It also reveals that a favorable event image and good perceived value can enhance SMAs’ effectiveness toward positively influencing TBIs, especially purchase intentions. It provides a new vision for nonprofit organizations to prioritize SMAs’ implementation in marketing strategies.

It is pioneering work with a complex research framework for SMAs implementation in the sports tourism context.

The purpose of this paper is to review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.

Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles with a controllable distance from obstacles.

First, combining satellite image and the Voronoi field algorithm (VFA) generates rasterized environmental information and establishes navigation area boundary. Second, establishing a hazard function associated with navigation area boundary improves the evaluation function of the A^* algorithm and uses the improved A^* algorithm for global path planning. Finally, to reduce the number of redundant nodes in the planned path and smooth the path, node optimization and gradient descent method (GDM) are used. Then, a continuous smooth path that meets the actual navigation requirements of unmanned vehicle is obtained.

The simulation experiment proved that the proposed global path planning method can realize the control of the distance between the planned path and the obstacle by setting different navigation area boundaries. The node reduction rate is between 33.52% and 73.15%, and the smoothness meets the navigation requirements. This method is reasonable and effective in the global path planning process of unmanned vehicle and can provide reference to unmanned vehicles’ autonomous obstacle avoidance decision-making.

This study establishes navigation area boundary for the environment based on the VFA and uses the improved A* algorithm to generate a navigation path that takes into account both safety and economy. This study also proposes a method to solve the redundancy of grid environment path nodes and large-angle steering and to smooth the path to improve the applicability of the proposed global path planning method. The proposed global path planning method solves the requirements of path safety and smoothness.

The key challenge that urban cities in most developing and transitional economies is confronting is municipal solid waste (MSW) management. Waste separation is a critical component to successful recycling management in terms of enhancing the quality of recyclables, reducing MSW and optimizing incineration. The urge to actualizing sustained waste separation behavior has been hindered by potential barriers. This study aims to examine the influences of external and internal stimuli of targeted households' waste separation intention in parts of China.

A multifactor framework predicting the process that leads to waste separation attitude and behavioral intention is proposed. SEM analysis is conducted in SmartPLS based on 371 survey questionnaires collected in Nanning city in China.

Policy regulation is the biggest determinant of attitude among external stimuli, while awareness of consequence has the strongest relationship with an attitude among internal stimuli. Facilitating conditions, subjective norms and moral norms are all significant predictors of attitude. As a result, increasing positive attitude leads to enhance waste separation lifestyle.

This study adopts a cross-sectional design to investigate the waste separation intention of local households. Data collection is restricted to one point in time for every individual. A mixed method is recommended. Quantitative research can examine variables provided in existing literature with numerical analysis. Qualitative research might be helpful to identify other unknown factors. Also, the survey questionnaires employ a self-reported manner, and respondents might be overrating to avoid embarrassment.

Future research is recommended to engage observation at houses or at the waste-collecting points for actual waste separation behavior. Moreover, this study measures intention toward household waste separation, but whether this intention will eventually lead to waste separation behavior is not a guarantee. Future study is recommended to examine whether intention translates into actual waste separation behavior.

Emphasizing the importance of policy element as a direct influence toward attitude, this paper focuses on the waste separation attitude accumulated from external and internal stimuli, and, concurrently, waste separation behavioral intention is influenced by accumulated attitudes. The study provides relevant policy development information of three Asian countries to enhance their present and future policy directions for a sustainable household waste separation management process

Auxiliary power system is an indispensable part of the train; the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways, which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters. Powered by DC-link voltage of traction converters, the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking. Meanwhile, powered by traction transformers, the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.

Uninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied. Failure reasons why previous solutions cannot be realized are analyzed. An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper. The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive. This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.

This scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid. Control objectives of uninterrupted power supply technology are proposed, which are no overvoltage, no overcurrent and uninterrupted power supply.

The control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section. Furthermore, this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

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).

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM) trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase). In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.

Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed.

To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem) and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem). Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.