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Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

The flexible mode transitions, multiple power sources and system uncertainty lead to challenges for mode transition control of four-wheel-drive hybrid powertrain. Therefore, the purpose of this paper is to improve dynamic performance and fuel economy in mode transition process for four-wheel-drive hybrid electric vehicles (HEVs), overcoming the influence of system uncertainty.

First, operation modes and transitions are analyzed and then dynamic models during mode transition process are established. Second, a robust mode transition controller based on radial basis function neural network (RBFNN) is proposed. RBFNN is designed as an uncertainty estimator to approximate lumped model uncertainty due to modeling error. Based on this estimator, a sliding mode controller (SMC) is proposed in clutch slipping phase to achieve clutch speed synchronization, despite disturbance of engine torque error, engine resistant torque and clutch torque. Finally, simulations are carried out on MATLAB/Cruise co-platform.

Compared with routine control and SMC, the proposed robust controller can achieve better performance in clutch slipping time, engine torque error, vehicle jerk and slipping work either in nominal system or perturbed system.

The mode transition control of four-wheel-drive HEVs is investigated, and a robust controller based on RBFNN estimation is proposed. Compared results show that the proposed controller can improve dynamic performance and fuel economy effectively in spite of the existence of uncertainty.

A strong relationship exists in many cultures between ethnic identity and educational success. This study was conducted at a teacher training university in Southwest China in 1997. It examines how ethnic minority students, through a series of micro-level interactions, construct “scholar selves” within their families, villages, and schools. The study also looks at how macro-level structural supports, built into the Chinese education system, help minority students overcome obstacles to academic success. These supports include special schools and classes for ethnic students, training teachers for nationality areas, financial support for minority education and additional points awarded on national examinations. The chapter suggests what scholars and practitioners might learn from an educational system that demonstrates the characteristics of flexibility, inclusiveness and cohesiveness.

Developing general closed-form solutions for six-degrees-of-freedom (DOF) serial robots is a significant challenge. This paper thus aims to present a general solution for six-DOF robots based on the product of exponentials model, which adapts to a class of robots satisfying the Pieper criterion with two parallel or intersecting axes among its first three axes.

The proposed solution can be represented as uniform expressions by using geometrical properties and a modified Paden–Kahan sub-problem, which mainly adopts the screw theory.

A simulation and experiments validated the correctness and effectiveness of the proposed method (general resolution for six-DOF robots based on the product of exponentials model).

The Rodrigues rotation formula is additionally used to turn the complex problem into a solvable trigonometric function and uniformly express six solutions using two formulas.

The purpose of this paper is to improve the overall heat transfer performance and the temperature uniformity of the heat sink and to explore the effects of the jet Reynolds number and the nanoparticle volume fraction of the nanofluids on the flow and heat transfer performance.

A heat sink with discontinuous arc protrusions in the wall jet region is proposed for confined slot jet impingement. A sloping upper cover plate is added to improve the heat transfer effect in this area. An Al₂O₃–water nanofluid is selected as the working fluid of the jet for better heat transfer. The Standard k-e turbulence model is used for numerical calculation. The key structural parameters of the heat sink are optimized by the response surface method and a genetic algorithm. The effects of the jet Reynolds number (Re) and the nanofluid concentration (ϕ) on the flow and heat transfer performance of the optimized heat sink are investigated.

The average Nusselt number of the optimal heat sink is 8.2% higher and the friction resistance is 5.9% lower than that of the initial flat plate heat sink when ϕ = 0.02 and Re = 8,000. The discontinuous arc protrusions and the sloping upper cover plate substantially enhance the heat transfer in the later stage of jet development, improving the temperature uniformity of the heat sink. The maximum temperature difference of the optimal heat sink is 28.1% lower than that of the flat plate heat sink at the same nozzle height. As the jet Reynolds number and the nanofluid particle concentration increase, the Nusselt number of the optimized heat sink and the friction coefficients increase, resulting in a decrease in the evaluation coefficient. However, the overall temperature uniformity of the heat sink is improved under all conditions.

The novel heat sink structure provides a new way to enhance the heat transfer and temperature uniformity of confined slot jet impingement. The flow and heat transfer performance of the heat sink impinged by confined slot jet of nanofluids are obtained. The combination of response surface method and genetic algorithm can be applied to the multi-objective optimization of heat resistance and flow resistance of heat sink.

The purpose of this paper is to explore the flow and heat transfer characteristics of the jet impingement onto a conical heat sink and evaluate the ability of heat transfer enhancement.

A numerical study of the flow and heat transfer of liquid impingement on cone heat sinks was conducted, and transition SST turbulence model was validated and adopted. The flow and thermal performances were investigated with the Reynolds number that ranges from 5,000 to 23,000 and cone angle that ranges from 0° to 70° in four regions.

Local Nusselt numbers are large, and pressure coefficients drop rapidly near the stagnation point. In the conical bottom edge, a secondary inclined jet was observed, thereby introducing a horseshoe vortex that causes drastic fluctuations in the curves of the flow and heat transfer. The average Nusselt numbers are higher in a conical protuberance than in flat plates in most cases, thus indicating that the heat transfer performance of jet impingement can be improved by a cone heat sink. The maximum increase is 13.6 per cent when the cone angle is 60°, and the Reynolds number is 23,000.

The flow and heat transfer behavior at the bottom edge of the cone heat sink is supplemented. The average heat transfer capacity of different heat transfer radii was evaluated, which provided a basis for the study of cone arrays.

Inadequate balancing of resources often results in resource conflict in the multiproject management process. Past research has focused on how to allocate a small amount of resources optimally but has scarcely explored how to foresee multiproject resource conflict risk in advance. The purpose of this study is to address this knowledge gap by developing a model to predict multiproject resource conflict risk.

A fuzzy comprehensive evaluation method is used to transform subjective judgments into quantitative information, based on which an evaluation index system for multiproject resource conflict risk that focuses on the interdependence of multiple project resources is proposed. An artificial neural network (ANN) model combined with this system is proposed to predict the comprehensive risk score that can describe the severity of risk.

Accurately predicting multiproject resource conflict risks in advance can reduce the risk to the organization and increase the probability of achieving the project objectives. The ANN model developed in this paper by the authors can capture the essential components of the underlying nonlinear relevance and is capable of predicting risk appropriately.

The authors explored the prediction of the risks associated with multiproject resource conflicts, which is important for improving the success rate of projects but has received limited attention in the past. The authors established an evaluation index system for these risks considering the interdependence among project resources to describe the underlying factors that contribute to resource conflict risks. The authors proposed an effective model to forecast the risk of multiproject resource conflicts using an ANN. The model can effectively predict complex phenomena with complicated and highly nonlinear performance functions and solve problems with many random variables.

Color is the dominant element of visual communication design. For cities, color is one of their characteristics. Improving the overall style of a city through the control and planning of architectural color has been a hot issue in urban control and planning in recent years. Considering color pollution in urban planning, we analyze the important role of color in visual communication design from the perspective of the visual communication concept of media art. The current situation of residential building colors in Shanghai City is investigated. We determine the residents’ preferences and requirements related to architectural exterior color on the basis of a data analysis of color and material selection, color matching, composition, and others. This study changes the traditional architectural color design concept that centers on individuals and lacks overall control. Specifically, we construct a set of multi-scale color controlling and planning systems at the macro-, meso-, and micro-scales. We also guide and control the urban architectural color such that it is in accordance with the systematic color planning strategy. This method enables the systematic and holistic external color planning of urban residential buildings.

Strengthening the combination of technology and finance can significantly promote the development of economy and society. Urbanization is a crucial standard to measure the economic and social development of a country and region, and urban regional planning based on science and technology finance has always been the focus of both domestic and foreign research institutions. Thus, this paper takes Mianyang, the first city of science and technology, as the object of research, and from the angle of the development process of Mianyang, investigates the three stages of the construction and development of this science and technology city. This study analyzes the characteristics of regional planning of Mianyang City and sums up the idea of relying on the old city to build another new district, which boosts the development of science and technology as well as the economy. From two specific angles (i.e., urban spatial function region planning and urban and rural planning), this paper thoroughly studies a multiscale planning scheme of Mianyang’s urban area in recent years by researching the local policy, system, finance, and society. Empirical measurement proves that reasonable planning and construction of the science and technology city Mianyang can accelerate the development process of the western region, effectively promoting the economic development of the surrounding areas of Sichuan and remarkably improving the overall quality of the regional economy of both Chongqing and Sichuan Provinces.

This systematic review, following preferred reporting items for systematic reviews and meta-analysis guidelines, rigorously investigates the emergent role of virtual reality (VR) technology in human movement training. The purpose of this study is to explore the effectiveness and evolution of VR in enhancing movement training experiences.

Acknowledging its pivotal role in diverse applications, such as sports and rehabilitation, human movement training is currently experiencing accelerated evolution, facilitated by the proliferation of wearable devices and mobile applications. This review conducted an exhaustive search across five different electronic databases, such as Web of Science, PubMed and ProQuest, resulting in the selection of 69 eligible articles published within the past five years. It also integrates 40 studies into a narrative summary, categorized based on the level of immersion offered by respective VR systems.

Enhanced immersion in VR potentially augments the effectiveness of movement training by engendering more realistic and captivating experiences for users. The immersive and interactive environments provided by VR technology enable tailored training experiences accompanied by precise, objective feedback. This review highlights the benefits of VR in human movement training and its potential to revolutionize the way training is conducted.

This systematic review contributes significantly to the existing literature by providing a comprehensive examination of the efficacy and evolution of VR in human movement training. By organizing the findings based on the level of immersion offered by VR systems, it provides valuable insights into the importance of immersion in enhancing training outcomes. In addition, this study identifies the need for future research focusing on the impacts of VR on learning and performance, as well as strategies to optimize its effectiveness and improve accessibility.