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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.

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.

To study the application of three‐dimensional differential geometric (DG) guidance commands to a realistic missile defense engagement, and the application of the Newton's iterative algorithm to DG guidance problems.

The classical differential geometry theory is introduced firstly to transform all the variables in DG guidance commands from an arc length system to the time domain. Then, an algorithm for the angle‐of‐attack and the sideslip angle is developed by assuming the guidance curvature command and guidance torsion command equal to its corresponding value of current trajectory. Furthermore, Newton's iteration is utilized to develop iterative solution of the stated algorithm and the two‐dimensional DG guidance system so as to facilitate easy computation of the angle‐of‐attack and the sideslip angle, which are formulated to satisfy the DG guidance law.

DG guidance law is viable and effective in the realistic missile defense engagement, and it is shown to be a generalization of gain‐varying proportional navigation (PN) guidance law and performs better than the classical PN guidance law in the case of intercepting a maneuvering target. Moreover, Newton's iterative algorithm has sufficient accuracy for DG guidance problem.

Provides further study on DG guidance problem associated with its iterative solution.

The paper aims to provide further study on the development and analysis of flight control system for two‐dimensional (2D) differential geometric (DG) guidance and control system based on the application of a set‐point weighting proportional‐integral‐derivative (PID) controller.

The commanded angle‐of‐attack is developed in the time domain using the classical differential geometry theory. Then, a set‐point weighting PID controller is introduced to develop a flight control system so as to form the 2D DG guidance and control system, and the gains of the PID controller are determined by the Ziegler‐Nichols method as well as the Routh‐Hurwitz stability criterion. Finally, the classical frequency method is utilized to study the relative stability and robustness of the designed flight control system.

The results demonstrate that the designed controller yields a fast responding and stable system which is robust to the high frequency parameters variation. Moreover, the DG guidance law is viable and effective in a realistic missile defense engagement.

This paper provides a novel approach on the development of DG guidance and control system associated with its stability analysis.

This paper aims to compare the aging behavior of water-based coatings and solvent-based coatings in sulfuric acid environments and to discuss the related mechanism.

A sulfuric acid solution with a concentration of 5 Wt.% was selected for immersion test at 23°C. The failure behavior of the coating was studied by combining the transformation rules of the macroscopic morphology and basic properties with the results of electrochemical impedance spectrum analysis.

The results showed that the surface smoothness of the water-based coating was lower than that of the solvent-based coating. The glossiness, thickness and hardness of the water-based coating exhibited more significant changes. The electrochemical test also indicated that the water-based coating was infiltrated by a large number of corrosive media, which may have induced corrosion under the coating. In contrast, the solvent-based coating showed good shielding properties, but the adhesion was seriously affected by the corrosive medium.

This work clarified the difference of failure behavior and mechanism between water-based coatings and solvent-based coatings in acidic environment and provided a theoretical basis for the selection and mechanism research of anticorrosive coatings.

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.

With the development of deep learning-based analytical techniques, increased research has focused on fatigue data analysis methods based on deep learning, which are gaining in popularity. However, the application of deep neural networks in the material science domain is mainly inhibited by data availability. In this paper, to overcome the difficulty of multifactor fatigue life prediction with small data sets,

A multiple neural network ensemble (MNNE) is used, and an MNNE with a general and flexible explicit function is developed to accurately quantify the complicated relationships hidden in multivariable data sets. Moreover, a variational autoencoder-based data generator is trained with small sample sets to expand the size of the training data set. A comparative study involving the proposed method and traditional models is performed. In addition, a filtering rule based on the R2 score is proposed and applied in the training process of the MNNE, and this approach has a beneficial effect on the prediction accuracy and generalization ability.

A comparative study involving the proposed method and traditional models is performed. The comparative experiment confirms that the use of hybrid data can improve the accuracy and generalization ability of the deep neural network and that the MNNE outperforms support vector machines, multilayer perceptron and deep neural network models based on the goodness of fit and robustness in the small sample case.

The experimental results imply that the proposed algorithm is a sophisticated and promising multivariate method for predicting the contact fatigue life of a coating when data availability is limited.

A data generated model based on variational autoencoder was used to make up lack of data. An MNNE method was proposed to apply in the small data case of fatigue life prediction.

The purpose of this paper is to investigate the evolution of the permeability of spherical packing during cold compaction by pore-scale modeling.

The discrete element method (DEM) is used to generate spherical packing structure under different compressive pressures and the Lattice Boltzmann method (LBM) is adopted to calculate the permeability of each spherical assembly.

It is found that the decrease of the porosity is the main reason of the reduction in permeability in the initial compression stage, but its influence becomes insufficient in the late compression stages. Besides, two empirical formulas are obtained, which describe the relation between the permeability and the equivalent mean diameter and the variation of normalized permeability with compressive pressure, respectively.

In this study, the authors study the spherical particles and ignore the non-spherical effects. Besides, the classical contact model, the linear-spring-damping model, is used in DEM, so the plastic deformation cannot be considered.

The DEM and the LBM are well combined to study the compaction effects on permeability of spherical packing. Two simple expressions of the spherical packing structure with uniform diameter distribution are given for the first time.

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 aim of this study was to investigate the effectiveness of restoration of gold foils on Dazu Grottoes using different parylene coatings.

The gold foil samples were applied with two types of parylene coating with six different thicknesses, C‐10, C‐15, C‐20, N‐10, N‐20, N‐25, respectively. Electrochemical impedance, surface morphology, and hydrophobicity properties were used to examine the behavior of the coatings.

The results showed that an increase in electrochemical corrosion resistance was observed as the degree of coating thickness was increased for both C‐parylene and N‐parylene coatings. In addition, the surface morphology study, using 3D topography measurement, indicated that the surface roughness was decreased for all parylene coatings. Furthermore, the parylene‐C coating was comparatively more effective than was the parylene‐N coating.

The results obtained from the three methods were in close agreement. This is an indication that the parylene‐C coating can be used to restore the gold foils on Dazu Grottoes and to support future restoration and consolidation to be applied on site on the Grottoes.