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This paper investigates the temporal inflow profile that minimises the total cost of travel for a single route. The problem is formulated to consider the case in which the total demand to be serviced is fixed. The approach used here is a direct calculation of the first order variation of total system cost with respect to variations in the inflow profile. Two traffic models are considered; the bottleneck with deterministic queue and the kinematic wave model. For the bottleneck model a known solution is recovered. The wave model proves more difficult and after eliminating the possibility of a smooth inflow profile the restricted case of constant inflow is solved. As the space of possible profiles is finite dimensional in this case, the standard techniques of calculus apply. We establish a pair of equations that are satisfied simultaneously by the optimal inflow and time of first departure.

Absence of Health and Safety (H&S) induction training can expose workers to construction hazards and risks. To protect workers, construction organisations provide site H&S induction training. This training is used in the construction industry to train workers on organisation, project and client H&S practices and rules. While researchers have recognised its role in creating worker awareness, developing H&S culture and influencing accident rate, but there has been little research. Furthermore, there lacks a review that identifies the research trends, research focus and future research directions on H&S induction training in the construction industry. This study aims to review literature on H&S induction training in the construction industry.

Scopus, Web of Science, Science Direct and Google Scholar databases were used to identify articles. Initial search produced a total of 278 papers and final analysis resulted in ten articles. Content analysis was applied.

The identified three contributions to knowledge: (a) identifies specific trajectory or development trends of H&S induction training in the construction industry (three research areas were identified, namely, impact of H&S induction training on H&S culture, impact of H&S induction training on accident rate and barriers affecting supervisor’s skills and ability to conducting H&S induction training), (b) suggestions have been given on the contribution of H&S induction training to H&S culture and (c) future research directions have been proposed. The review provides knowledge that the contribution of H&S induction training to H&S culture is influenced by skills, knowledge and experience of presenter, language used, content covered, mode of delivery, technological tools used, type of assessment and duration.

The review is limited to studies related to H&S induction training in the construction industry. Other safety training studies and industries could have provided different findings. The review is limited to 2012 and 2022 and to ten articles.

Understanding the role of H&S induction training to worker behaviour, H&S culture and outcomes will improve H&S practices and standards within the construction industry. Construction organisations can consider the factors identified in this study to improve the effectiveness of H&S induction training.

Understanding the contribution of H&S induction training to H&S culture may help to improve H&S culture.

The study has identified three main research areas and future research directions. It further revealed the factors that researchers, practitioners and policy makers can consider to improve the effectiveness of H&S induction training in the construction industry.

Due to the important and extensive use of graphene in the engineering structures, the purpose of this paper is to investigate the low-velocity impact (LVI) response of a graphene-reinforced plate with a rectangular central hole.

In this paper, Halpin-Tsai theory is used to model the mechanical properties of the plate made of polymethyl methacrylate (PMMA) resin and graphene particles. First, the plate displacement field is presented, and then the strains and stresses are obtained. The motion equations are extracted using energy equations, Ritz method and generalized Lagrange equations. The verification of theoretical formulation shall be carried out using the ABAQUS finite element software suite.

The effects of graphene volume fraction, approaching the impact point to the corner of the rectangular plate, and different boundary conditions of the plate are studied for LVI of impactor with spherical tip on the rectangular central hole reinforced by graphene. Important responses of the impact, such as the contact force between the impactor and the plate as well as the displacement of the plate at the impact place, are investigated and analyzed in this research.

Considering the wide application of graphene in the engineering structures, the simulation of the LVI on the graphene-reinforced plate made of PMMA resin with a rectangular central hole is carried out in this paper using numerical and theoretical modeling.

The purpose of this study is to evaluate and minimize the losses of alternating current (AC) in the winding of electrical machines. AC winding losses are frequently disregarded at low frequencies, but they become a significant concern at high frequencies. This is the situation where applications require a high speed. The most significant applications in this category are electrical propulsion and drive systems.

An analytical model is used to predict the AC losses in the winding of electrical machines. The process involves dividing the slot into separate layers and then calculating the AC loss factor for each layer. The model aims to calculate AC losses for two different winding arrangements involving circular conductors. This application focuses on the stator winding of a permanent magnet synchronous motor that is specifically designed for electric vehicles. The model is integrated into an optimization process that makes use of the genetic algorithm method to minimize AC losses resulting from the arrangement of conductors within the slot.

This study and its findings demonstrate that the arrangement of the conductors within the slot has a comparable effect on the AC losses in the winding as the machine's geometric and physical properties. The effectiveness of electrical machines depends heavily on optimizing the arrangement of conductors in the slot to minimize AC winding losses.

The proposed strategy seeks to minimize AC winding losses in high-speed electric machines by providing a cost-effective and precise solution to improve energy efficiency.

This study aims to enhance the prediction accuracy of hydroelectricity consumption in China, with a focus on addressing the challenges posed by complex and nonlinear characteristics of the data. A novel grey multivariate prediction model with structural optimization is proposed to overcome the limitations of existing grey forecasting methods.

This paper innovatively introduces fractional order and nonlinear parameter terms to develop a novel fractional multivariate grey prediction model based on the NSGM(1, N) model. The Particle Swarm Optimization algorithm is then utilized to compute the model’s hyperparameters. Subsequently, the proposed model is applied to forecast China’s hydroelectricity consumption and is compared with other models for analysis.

Theoretical derivation results demonstrate that the new model has good compatibility. Empirical results indicate that the FMGM(1, N, a) model outperforms other models in predicting the hydroelectricity consumption of China. This demonstrates the model’s effectiveness in handling complex and nonlinear data, emphasizing its practical applicability.

This paper introduces a scientific and efficient method for forecasting hydroelectricity consumption in China, particularly when confronted with complexity and nonlinearity. The predicted results can provide a solid support for China’s hydroelectricity resource development scheduling and planning.

The primary contribution of this paper is to propose a novel fractional multivariate grey prediction model that can handle nonlinear and complex series more effectively.

Analyses the emergence of tortious liability on solicitors and the damages awarded against them for negligence in preparing wills, ie testamentary disposition, when this causes losses to beneficiaries recognisable in law; it is no longer the case that actions by clients against solicitors are always for breach of contract. Traces how negligence has been established as an independent tort, and shows how absence of privity does not debar a claim. Discusses the landmark case of Ross v Caunters, which showed that liability could be to a third party, ie the beneficiary of a will that was made void by solicitor negligence; discusses how the duty of care was ascertained in this and other cases. Outlines the control mechanisms that a third party has to prove before a court decides that a solicitor is liable: reliance on the solicitor, whether there is a causal link between negligence and loss, proximity and foreseeability; there is also the concept of fair, just and reasonable. Covers lastly the issues of unjust enrichment of unintended beneficiaries, professional indemnity insurance, social policy objectives for awarding damages, and the bounds of liability.

This study aims to investigate the most effective approach for governments and enterprises to combat desertification by considering the governance cycle. The focus is on understanding how the government can incentivize enterprises to actively engage in desertification combat efforts.

Both the government and the enterprise are treated as rational entities, making strategic choices for joint participation in combating desertification. Recognizing the dynamic nature of the desertification combat area, differential game models are employed to identify the optimal mode for combating desertification.

The findings underscore the significant influence of the governance cycle duration on the selection of desertification combat modes for government and enterprise. A cooperative mode is best suited to a short governance cycle, while an ecological subsidy mode is optimal for a longer cycle. Enhancing governance technology and shortening the governance cycle are conducive to combating desertification. Reducing taxes alone may not be an effective control strategy; rather, the government can better motivate enterprises by adopting tax rate policies aligned with the chosen governance mode.

This research contributes by elucidating the impact mechanism of the government cycle’s length on the desertification combat process. The results may offer valuable insights for governments in formulating strategies to encourage corporate participation in combating desertification and provide theoretical support for selecting optimal desertification combat modes.

In this essay, a new NDAGM(1,N,α) power model is recommended to resolve the hassle of the distinction between old and new information, and the complicated nonlinear traits between sequences in real behavior systems.

Firstly, the correlation aspect sequence is screened via a grey integrated correlation degree, and the damped cumulative generating operator and power index are introduced to define the new model. Then the non-structural parameters are optimized through the genetic algorithm. Finally, the pattern is utilized for the prediction of China’s natural gas consumption, and in contrast with other models.

By altering the unknown parameters of the model, theoretical deduction has been carried out on the newly constructed model. It has been discovered that the new model can be interchanged with the traditional grey model, indicating that the model proposed in this article possesses strong compatibility. In the case study, the NDAGM(1,N,α) power model demonstrates superior integrated performance compared to the benchmark models, which indirectly reflects the model’s heightened sensitivity to disparities between new and old information, as well as its ability to handle complex linear issues.

This paper provides a scientifically valid forecast model for predicting natural gas consumption. The forecast results can offer a theoretical foundation for the formulation of national strategies and related policies regarding natural gas import and export.

The primary contribution of this article is the proposition of a grey multivariate prediction model, which accommodates both new and historical information and is applicable to complex nonlinear scenarios. In addition, the predictive performance of the model has been enhanced by employing a genetic algorithm to search for the optimal power exponent.

The new customer churn prediction (CCP) utilizing deep learning is developed in this work. Initially, the data are collected from the WSDM-KKBox’s churn prediction challenge dataset. Here, the time-varying data and the static data are aggregated, and then the statistic features and deep features with the aid of statistical measures and “Visual Geometry Group 16 (VGG16)”, accordingly, and the features are considered as feature 1 and feature 2. Further, both features are forwarded to the weighted feature fusion phase, where the modified exploration of driving training-based optimization (ME-DTBO) is used for attaining the fused features. It is then given to the optimized and ensemble-based dilated deep learning (OEDDL) model, which is “Temporal Context Networks (DTCN), Recurrent Neural Networks (RNN), and Long-Short Term Memory (LSTM)”, where the optimization is performed with the aid of ME-DTBO model. Finally, the predicted outcomes are attained and assimilated over other classical models.

The features are forwarded to the weighted feature fusion phase, where the ME-DTBO is used for attaining the fused features. It is then given to the OEDDL model, which is “DTCN, RNN, and LSTM”, where the optimization is performed with the aid of the ME-DTBO model.

The accuracy of the implemented CCP system was raised by 54.5% of RNN, 56.3% of deep neural network (DNN), 58.1% of LSTM and 60% of RNN + DTCN + LSTM correspondingly when the learning percentage is 55.

The proposed CCP framework using the proposed ME-DTBO and OEDDL is accurate and enhances the prediction performance.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”