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The purpose of this paper is to achieve the optimal system design of a four-wheel mobile robot on transmission line maintenance, as the authors know transmission line mobile robot is a kind of special robot which runs on high-voltage cable to replace or assist manual power maintenance operation. In the process of live working, the manipulator, working end effector and the working environment are located in the narrow space and with heterogeneous shapes, the robot collision-free obstacle avoidance movement is the premise to complete the operation task. In the simultaneous operation, the mechanical properties between the manipulator effector and the operation object are the key to improve the operation reliability. These put forward higher requirements for the mechanical configuration and dynamic characteristics of the robot, and this is the purpose of the manuscript.

Based on the above, aiming at the task of tightening the tension clamp for the four-split transmission lines, the paper proposed a four-wheel mobile robot mechanism configuration and its terminal tool which can adapt to the walking and operation on multi-split transmission lines. In the study, the dynamic models of the rigid robot and flexible transmission line are established, respectively, and the dynamic model of rigid-flexible coupling system is established on this basis, the working space and dynamic characteristics of the robot have been simulated in ADAMS and MATLAB.

The research results show that the mechanical configuration of this robot can complete the tightening operation of the four-split tension clamp bolts and the motion of robot each joint meets the requirements of driving torque in the operation process, which avoids the operation failure of the robot system caused by the insufficient or excessive driving force of the robot joint torque.

Finally, the engineering practicability of the mechanical configuration and dynamic model proposed in the paper has been verified by the physical prototype. The originality value of the research is that it has double important theoretical significance and practical application value for the optimization of mechanical structure parameters and electrical control parameters of transmission line mobile robots.

The purpose of this study is to investigate the flexible dynamic characteristics about hydro-viscous drive providing meaningful insights into the credible speed-regulating behavior during the soft-start.

A comprehensive dynamic transmission model is proposed to investigate the effects of key parameters on the dynamic characteristics. To achieve a trade-off between the transmission efficiency and time proportion of hydrodynamic and mixed lubrication, a multi-objective optimization of friction pair system by genetic algorithm is presented to obtain the optimal combination of design parameters.

Decreasing the engagement pressure or the ratio of inner and outer radius, increasing the lubricating oil viscosity or the outer radius will result in the increase of time proportion of hydrodynamic and mixed lubrication, as well as the transmission efficiency and its maximum value. After optimization, main dynamic parameters including the oil film thickness, angular velocity of the driven disk, viscous torque and total torque show remarkable flexible transmission characteristics.

Both the dynamic transmission model and multi-objective optimization model are established to analyze the effects of main design parameters on the dynamic characteristics of hydro-viscous flexible drive.

Hepatitis A is a prevalent disease that is largely preventable by vaccine usage. The vaccine for this illness is highly underused in most regions. In an attempt to find the strategies that are most beneficial in regard to quality-adjusted life years (QALYs) and cost in current environments, the purpose of this paper is to conduct cost-effectiveness analyses to investigate vaccination strategies in a more economically developed country (MEDC), generally known as a “developed” area: the USA, and a less economically developed country (LEDC), generally known as a “developing” area: the state of Rio de Janeiro, Brazil.

This study used a dynamic transmission model for comparative effectiveness analyses. The model ran two different scenarios. The two regions studied have different policies and strategies for Hepatitis A vaccination currently, and also used different strategies in 2009. In the USA, a universal vaccination policy was modeled, along with a scenario in which it was removed. In Rio de Janeiro, a no vaccination policy was modeled, along with a scenario in which a universal vaccination policy was effected.

The comparison of resulting incremental cost-effectiveness ratio values to accepted threshold values showed universal vaccination to be cost-effective in both the USA and Rio de Janeiro as compared to no vaccination. When episode and vaccination costs and vaccination efficacy were varied, this still remained true. Universal vaccination was found to result in lower incidence of Hepatitis A in both the USA and Rio de Janeiro. Over the twenty-year time horizon, universal vaccination is projected to prevent 506,945 cases of symptomatic Hepatitis A in the USA and 42,318 cases of Hepatitis A in Rio de Janeiro. Other benefits include a projected increase in cumulative QALYs through the use of universal vaccination.

This analysis showed universal vaccination to be cost-effective as compared to no vaccination, and portions of the study’s approach had not previously been applied in tandem to investigate Hepatitis A interventions. The results may help foster higher compliance rates for Hepatitis A vaccination and even greater per-person economic benefits of universal vaccination, particularly in the USA. The purpose of this study is also to encourage elevated levels of surveillance on age of infection in developing regions and consistent reevaluation utilizing dynamic transmission models in both the USA and Brazil, as well as other rapidly developing regions, in order to prevent future epidemics and costs associated with the disease.

This paper aims to present a linear mathematical framework for modeling and optimizing road transport infrastructure. The framework assesses and optimizes performance of existing transport facility rather than relying on building new roads for the ever-increasing travel demand.

The mathematical framework is built upon a traffic model called Cell Transmission Model (CTM). CTM describes the relationship and evolution of traffic flow and concentration over space and time. The model is parsimonious and accurate in predicting traffic dynamics. More importantly, the traffic flow model is piecewise linear with which the corresponding transport facility optimization problem can be formulated as a Linear Programming (LP) problem and solved by established solution algorithm for global optimality.

We select a section on England Motorway M25 as a case study. With traffic data, we first calibrate the CTM, and we are able to produce traffic estimation with a reasonable error rate of 12 per cent. The corresponding LP then seeks an optimal ramp metering strategy that minimizes the delay on the motorway. It is shown that an optimal and practical strategy can be derived which reduces the motorway delay by 10 per cent without significantly hurting the surrounding connectors.

Instead of the tedious microscopic models used by many traditional tools, the underlying CTM is parsimonious and reliable. The tools developed herein are based upon plausible traffic theory and will be accessible for a wide range of users. The LP formulation can be easily implemented and solved for optimal and practical control strategies for real-world transport networks by using existing computer software (CPLEX) within reasonable computational time. The present work will certainly contribute to the sustainable development of transport facility.

This study aims to highlight the role of individual and instructional design factors on training transfer and explore and review focal training factors that influence the transfer of training.

A conceptual framework has been developed for this study to better present the prevalent factors that have been empirically validated.

The facets of transfer encompassed in this study have gathered enough evidence to demonstrate a positive association with the transfer. This review points out that all predictor variables (learner characteristics, instructional design and environmental factors) positively and significantly influence the transfer of training. A mix of variables is proposed, with further investigation recommended to develop a robust training transfer hypotheses.

This study contributes to the training transfer literature in three ways. First, the authors have shown the positive influence of pre-training factors on training transfer. This study is grounded in a robust theoretical framework, thus fulfilling the previous gaps. This conceptual study elaborates on the importance of factors to establish the training transfer hypothesis. Future studies should test the suggested framework and look for other things that could help learners be more effective and motivated so that training can be more effective and transferable.

This study has significant findings for organizations operating in the current business scenario to enhance learning transfer, where the transfer is very low and a significant cause of concern for every organization. By making management aware of the success factors of training transfer, they can ensure a better training transfer. In this study, the transfer design considerations are discussed in detail, and their practical consequences are provided for training transfer in general and training professionals in particular.

The training transfer literature showcases two significant gaps; first, it lacks appropriate characteristics, and second, there is variability in the results. This study bridges the gaps and attempts to advance our understanding of training transfer grounded in the theoretical framework by focusing on learner characteristics, instructional design and work environment in training transfer, which predictor variables can improve training transfer. This study also contributes to the current training transfer literature by proposing a combination of factors that provide a theoretical foundation for developing a solid training transfer theory.

The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

The purpose of this paper is to improve the efficiency of accident management from the angle of reducing highway accident response times while taking into account total daily work hours.

The authors developed a patrol beat scheduling model, which is formulated as a chance-constrained optimization model, with the objective of minimizing the sum of officer work hours. Along with the model, a simulation program was also developed to help evaluate the effectiveness of the model-generated beat schedule in terms of response times.

This study concluded that, first, the current manually designed beat schedule could be improved should the National Highway Police Bureau adopt the proposed model. Second, the total daily work hours of the model-generated schedule at the confidence level of 100 percent were 64 hours, 21 hours less than the average work hours recorded in the 2006 data, or about an improvement of 24 percent. Should the model be adopted, not only response times will be improved, the 24 percent reduction in work hours could be translated into a cut in personnel cost.

The scheduling model and simulation program are both built upon one-year historical data whose accuracy and completeness is prerequisite.

The proposed model can be adopted by other public service agencies such as fire departments, or emergency service centers. By replacing the historical data used in the study with their own data, agencies can evaluate the efficiency of their existing schedule or generate various schedules based on institutional needs.

This model utilizes historical accident data to generate optimal beat schedule and evaluate the efficiency of such schedule. Similar models have not been found in other studies.

The purpose of this paper is to better depict the features of individual and group behaviors in sequential decisions under the effect of public belief drift.

In this paper, the authors design a two‐shots game which is closer to decisions condition in the real market by using the method of experimental economics two shots game.

The experimental results show that information cascade occurs more frequently in the second stage and the decision accuracy is decreased. The conclusion may provide experimental evidence for the “Animal Spirits Theory” of Keynes. Additionally, decision‐maker ranking in the middle of the decision sequence systematically deviates from his/her private information in balance state.

As existing information cascade theory of one shot decision fails to describe the belief‐dependent mechanism, the authors design the multi‐shots information cascade experiment; in which every individual decision maker has more than one sequential decision chance on the same event.

The purpose of this paper is to investigate the dynamic responses of a spur gear pair with unloaded static transmission error (STE) excitation numerically and experimentally and the influences of the system factors including mesh stiffness, error excitation and torque on the dynamic transmission error (DTE).

A simple lumped parameters dynamic model of a gear pair considering time-varying mesh stiffness, backlash and unloaded STE excitation is developed. The STE is calculated from the measured tooth profile deviation under the unloaded condition. A four-square gear test rig is designed to measure and analyze the DTE and vibration responses of the gear pair. The dynamic responses of the gear transmission are studied numerically and experimentally.

The predicted numerical DTE matches well with the experimental results. When the real unloaded STE excitation without any approximation is used, the dynamic response is dominated by the mesh frequency and its high order harmonic components, which may not be result caused by the assembling error. The sub-harmonic and super-harmonic resonant behaviors are excited because of the high order harmonic components of STE. It will not certainly prevent the separations of mesh teeth when the gear pair is under the condition of high speed and heavy load.

This study helps to improve the modeling method of the dynamic analysis of spur gear transmission and provide some reference for the understanding of the influence of mesh stiffness, STE excitation and system torque on the vibration behaviors.

The electromechanical planetary transmission system has the advantages of high transmission power and fast running speed, which is one of the important development directions in the future. However, during the operation of the electromechanical planetary transmission system, friction and other factors will lead to an increase in gear temperature and thermal deformation, which will affect the transmission performance of the system, and it is of great significance to study the influence of the temperature effect on the nonlinear dynamics of the electromechanical planetary system.

The effects of temperature change, motor speed, time-varying meshing stiffness, meshing damping ratio and error amplitude on the nonlinear dynamic characteristics of electromechanical planetary systems are studied by using bifurcation diagrams, time-domain diagrams, phase diagrams, Poincaré cross-sectional diagrams, spectra, etc.

The results show that when the temperature rise is less than 70 °C, the system will exhibit chaotic motion. When the motor speed is greater than 900r/min, the system enters a chaotic state. The changes in time-varying meshing stiffness, meshing damping ratio, and error amplitude will also make the system exhibit abundant bifurcation characteristics.

Based on the principle of thermal deformation, taking into account the temperature effect and nonlinear parameters, including time-varying meshing stiffness and tooth side clearance as well as comprehensive errors, a dynamic model of the electromechanical planetary gear system was established.