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The number of construction dispute cases has surged in recent years. The effective exploration and management of risks associated with construction contracts helps to directly enhance the overall project performance. The existing approaches to identify the risks associated with construction project contracts have a heavy reliance on manual review techniques, which are inefficient and highly restricted by personnel experience. The existing intelligent approaches only work for the contract query and storage. Hence, it is necessary to improve the intelligence level for contract risk management. This study aims to propose a novel method for the intelligent identification of risks in construction contract clauses based on natural language processing.

This proposed method can formalize the linguistic logic and semantic information of contract clauses into multiple triples and transform the structural processing results of general clauses in a construction contract into rights and interests rules for risk review. In addition, the core semantic information of special clauses in a construction contract, rights and interests rules are used for semantic conflict detection. Finally, this study achieves the intelligent risk identification of construction contract clauses.

The method is verified by selecting several construction contracts that had been applied in engineering contracting as a corpus. The results showed a high level of accuracy and applicability of the proposed method.

This novel method can identify the risks in contract clauses with complex syntactic structures and realize rule extension according to the semantic relation network of the ontology. It can support efficient contract review and assist the decision-making process in contract risk management.

The pedestrian dead reckoning (PDR) based on smartphones has been widely applied in continuous indoor positioning. However, when the position of the mobile phone and the walking patterns of the pedestrian are mixed, traditional PDR tends to become confused and thus degrade performance. To address this issue, this paper aims to propose an improved PDR scheme by focusing on gait pattern recognition and the impact of short-period but negative transitions on tracking.

The overall solution uses the inertial sensor integrated within the phone for positioning. A binary classifier-based change point detection algorithm is used to identify the transition points in pedestrian gait. Additionally, to enhance the accuracy of gait recognition, this paper presents a combined CNN-attention-based bi-directional long short-term memory(ABiLSTM) model, integrating convolutional neural networks (CNN), bi-directional long short-term memory (Bi-LSTM) and an attention mechanism, to recognize the current gait pattern. The outcomes of this gait pattern recognition are then applied to PDR. Based on distinct gait patterns, corresponding PDR strategies are devised to enable continuous tracking and positioning of pedestrians.

Through experimental verification, the CNN-ABiLSTM model achieves a gait recognition accuracy of 99.52% on the self-constructed data set. The pedestrian navigation estimation method proposed in this paper, which is based on gait recognition assistance, demonstrates a 32.56% improvement in accuracy over traditional positioning algorithms in multi-gait scenarios.

The improved PDR scheme algorithm significantly enhances the robustness and smoothness of pedestrian tracking, particularly during multiple gait transitions. This, in turn, provides strong support for the utilization of low-cost inertial sensors integrated within mobile phones for indoor positioning applications.

This study aims to analyze the development direction of track geometry inspection equipment for high-speed comprehensive inspection train in China.

The development of track geometry inspection equipment for high-speed comprehensive inspection train in China in the past 20 years can be divided into 3 stages. Track geometry inspection equipment 1.0 is the stage of analog signal. At the stage 1.0, the first priority is to meet the China's railways basic needs of pre-operation joint debugging, safety assessment and daily dynamic inspection, maintenance and repair after operation. Track geometry inspection equipment 2.0 is the stage of digital signal. At the stage 2.0, it is important to improve stability and reliability of track geometry inspection equipment by upgrading the hardware sensors and improving software architecture. Track geometry inspection equipment 3.0 is the stage of lightweight. At the stage 3.0, miniaturization, low power consumption, self-running and green economy are co-developing on demand.

The ability of track geometry inspection equipment for high-speed comprehensive inspection train will be expanded. The dynamic inspection of track stiffness changes will be studied under loaded and unloaded conditions in response to the track local settlement, track plate detachment and cushion plate failure. The dynamic measurement method of rail surface slope and vertical curve radius will be proposed, to reveal the changes in railway profile parameters of high-speed railways and the relationship between railway profile, track irregularity and subsidence of subgrade and bridges. The 200 m cut-off wavelength of track regularity will be researched to adapt to the operating speed of 400 km/h.

The research can provide new connotations and requirements of track geometry inspection equipment for high-speed comprehensive inspection train in the new railway stage.

This study adopted the collaborative consumption triangle to explore the influence of online food delivery platforms (OFDP) on consumer purchase intentions. It investigates the effects of restaurants' corporate social responsibility (CSR) practices, individuals' food neophilic tendencies (FNT), and platforms' perceived benefits on purchase intention within OFDP. Furthermore, the study analyses differences in consumers' pro-environmental behaviour (PEB) on OFDP.

The 497 participants conducted a web-based self-completion survey, using structural equation modelling to analyse the path structure of consumer purchasing intention. Furthermore, differences in PEB among OFDP consumers were compared through multigroup analysis.

The findings indicate that CSR influences the perceived value of sustainability and that the perceived value of sustainability influences purchase intention. Additionally, the influence of the perceived value of sustainability on purchase intention is more pronounced among consumers with low PEB compared to those with high PEB.

The findings may not be generalisable to other countries due to cultural differences, CSR policies, and strategies for promoting sustainable development.

The study provides valuable contributions related to (1) restaurants increasing their revenue and meeting their long-term sustainable development goals; (2) providing reusable containers policy and reusable containers policy and category tags for restaurants within OFDP.

This study is a pioneering work examining factors influencing purchase intentions within OFDP from the tripartite collaborative consumption perspective post-COVID-19 and focuses on the differences in PEB concerning OFDP.

This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction.

A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted.

Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas).

The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector.

This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.

The accurate prediction of driving torque demand is essential for the development of motion controllers for mobile robots on complex terrains. This paper aims to propose a hybrid model of torque prediction, adaptive EC-GPR, for mobile robots to address the problem of estimating the required driving torque with unknown terrain disturbances.

An error compensation (EC) framework is used, and the preliminary prediction driving torque value is achieved using Gaussian process regression (GPR). The error is predicted using a continuous hidden Markov model to generate compensation for the prediction residual caused by terrain disturbances and uncertainties. As the final step, a gain coefficient is used to adaptively tune the significance of the compensation term through parameter resetting. The proposed model is verified on a sample set, including the driving torque of a mobile robot on three different sandy terrains with two driving modes.

The results show that the adaptive EC-GPR yields the highest prediction accuracy when compared with existing methods.

It is demonstrated that the proposed model can predict the driving torque accurately for mobile robots in an unconstructed environment without terrain identification.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

Financing the capital-constrained farmers to facilitate the production of agri-products is one of the greatest challenges facing the farming supply chain in the developing countries. In this study, we investigate the optimal financing scheme for the farming supply chain under random yield and investment information asymmetry environment to support rural economic development.

We analyze a stylized model of farming supply chain where the capital-constrained farmer produces and sells agri-products through the agribusiness firm, and investigate the optimal financing scheme incorporating the investment information asymmetry and the challenge of yield uncertainty.

The results show that there is no one financing scheme equilibrium dominates for all situations, the financing scheme equilibrium is affected by the bank’s supervision cost to monitor the farmer’s moral hazard behavior, the variance of random yield and the farmer’s initial capital. The preference of the financing scheme for the agribusiness firm may be different from that for the farmer. The agribusiness firm might suffer from overfinancing problem under trade credit financing when the bank’s supervision cost is larger and the farmer’s own initial capital is lower; the higher variance of random yield will flare up the effect.

This study sheds light on the choice of financing scheme under random yield and investment information asymmetry environment. This problem is particularly important for developing economies. Financing the capital-constrained farmers not only increases supplies of food and industrial raw materials, but also reduces poverty. The findings provide managerial implications for practitioners for how to leverage different financing scheme to support rural economic development.

This study develops new theoretical model for farming supply chain financing incorporating the challenge of yield uncertainty and investment information asymmetry, the two prominent factors that would impact the financial risk significantly. We analyze the equilibrium under both bank financing and trade credit financing schemes, and the results suggest that the financing scheme equilibrium is affected by the bank’s supervision cost to monitor the farmer’s moral hazard behavior, the variance of random yield and the farmer’s initial capital. The agribusiness firm might suffer from overfinancing problem under trade credit financing.

The geological conditions of Longyang Reservoir are complex and it is located in strong earthquake area. In order to determine its seismic characteristics, the seismic response and residual deformation of embankment dam should be studied to provide calculation basis for dam design and construction.

Based on the geological survey data of Longyang Reservoir, the dam filling materials are tested by dynamic deformation tests, and the equivalent linear constitutive model parameters of the filling materials are obtained. Based on Duncan-Chang E-B model, the stress state of embankment dam in Longyang Reservoir before earthquake is calculated, and the dynamic response and earthquake residual deformation of embankment dam in Longyang Reservoir under earthquake condition are calculated by using equivalent linear model and Shen Zhu-jiang’s residual deformation model.

The results show that with the increase of dynamic shear strain, the dynamic shear modulus decreases and the damping ratio increases. The scatter plot between dynamic shear modulus and dynamic shear strain, and the scatter plot between damping ratio and dynamic shear strain under different confining pressures show strips. The calculation results shows that the acceleration of embankment dam in Longyang Reservoir increases with the increase of dam height, and the acceleration distribution has obvious amplification effect. Combined with the maximum dynamic shear strain during the earthquake and the state before the earthquake, the maximum vertical residual deformation of embankment dam in Longyang Reservoir is 2.98 cm which occurs at the top of the dam, calculated by the Shen Zhu-jiang’s residual deformation model.

Finite element calculation model parameters of embankment dam are obtained by dynamic triaxial tests. Seismic dynamic responses and residual deformation of embankment dam are analyzed. With the increase of dam height, the acceleration distribution shows an obvious amplification effect. The vertical displacement of embankment dam is larger along the dam axis and decreases in the upstream and downstream direction. The maximum horizontal displacement of embankment dam occurs in the middle of upstream and downstream dam slopes.

• (1)

  Finite element calculation model parameters of embankment dam are obtained by dynamic triaxial tests.

• (2)

  Seismic dynamic responses and residual deformation of embankment dam are analyzed.

• (3)

  With the increase of dam height, the acceleration distribution shows an obvious amplification effect.

• (4)

  The vertical displacement of embankment dam is larger along the dam axis and decreases in the upstream and downstream direction.

• (5)

  The maximum horizontal displacement of embankment dam occurs in the middle of upstream and downstream dam slopes.

Finite element calculation model parameters of embankment dam are obtained by dynamic triaxial tests.

Seismic dynamic responses and residual deformation of embankment dam are analyzed.

With the increase of dam height, the acceleration distribution shows an obvious amplification effect.

The vertical displacement of embankment dam is larger along the dam axis and decreases in the upstream and downstream direction.

The maximum horizontal displacement of embankment dam occurs in the middle of upstream and downstream dam slopes.