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Distribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.

Monte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.

Numerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.

The impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.

Remote handling (RH) manipulators have been widely studied for maintenance tasks in fusion reactors. Those tasks always require heavy load, high accuracy and large work space for manipulators. Traditionally, the maintenance of fusion devices always depends on manual RH. With the development of calculating ability, the intelligent automatic maintenance makes it possible for a fusion device instead of the previous manual operation. As the flexibility of arm and the deformation of manipulator will cause problems, which are mainly inaccuracy and lower efficiency. This paper aims to study an effective way to promote the arm behavior to solve these problems.

By making use of the experimental advanced superconducting tokamak articulated maintenance arm as a platform, a series of experiments is designed to measure errors of kinematics and to collect the database of the flexible arm. Through studying the data and the arm structure, recurrent neural network (RNN) method was adopted to estimate the deformation of flexible arm and eventually compensate deformation in robot control to achieve higher accuracy.

By means of delicate RNN modeling, errors of kinematics have been reduced to a smaller order than the RH mode. This intelligent maintenance method will also reduce complexity of operations in maintenance.

This paper presents the use of an artificial intelligent algorithm to solve a nonlinear deformation problem of the flexible arm. The results demonstrate that it is efficient in dealing with this problem in fusion application. The RNN’s successful application has also shown that intelligent algorithms can be widely applied in fusion maintenance.

Selective laser melting (SLM) is a promising additive manufacturing technology in the field of complex parts’ fabrication. High temperature gradient and residual stress are vital problems for the development of SLM technology. The purpose of this paper is to investigate the influence of substrate characteristics on the residual stress of SLMed Inconel 718 (IN718).

The SLMed IN718 samples were fabricated on the substrates with different characteristics, including pre-compression stress, materials and pre-heating. The residual stress at the center of the top surface was measured and compared through Vickers micro-indentation.

The results indicate that the residual stress reduces when the substrate contains pre-compression stress before the SLM process starts. Both substrate thermal expansion coefficient and thermal conductivity affect the residual stress. In addition to reducing the difference of thermal expansion coefficient between the substrate and the deposited material, the substrate with low thermal conductivity can also decrease the residual stress. Substrate pre-heating at 150°C reduces nearly 42.6 per cent residual stress because of the reduction of the temperature gradient.

The influence of substrate characteristics on the residual stress has been studied. The investigation results can help to control the residual stress generated in SLM processing.

In an integrated circuit (IC) substrate, more fillers, including talcum powder and aluminium hydroxide, are added, which leads to much higher rigidity and hardness compared with a traditional printed circuit board. However, the micro drilling of IC substrates is harder. This paper aims to test the drilling process of IC substrates to improve the drilling process and the micro hole quality.

Substrate drilling by a micro drill with 0.11-mm diameter was used under several drilling conditions. The influence of drilling conditions on the drilling process was observed. Drilling forces, drill wear and micro hole quality were also studied.

The deformation circle around holes, hole location accuracy, bugle hole and burrs were the major defects of micro holes that were observed during the drilling of the substrate. Reducing the drilling force and drill wear was the effective way to improve hole quality.

The technology and manufacturing of IC substrates has been little investigated. Research data on drilling IC substrates is lacking. The micro hole quality directly affects the reliability of IC substrates. Thus, improving the drilling technology of IC substrates is very important.

This article follows the overhaul in the teaching profession in Singapore which grants schools with more autonomy to decide their own manpower policies. It argues the need for more systemic, high‐commitment, mutually‐reinforcing human resource policies to reinforce the learning trajectory in schools. This encompasses heightening the strategic value of teachers by appointing a human resource manager; reforming the hiring and selection practices to include selection panels involving incumbent teachers, novel selection criteria and job previews; and replacing the compensation structure with one that is transparent, skill‐based, team‐oriented, and which pays premium wages and affords non‐monetary benefits like work/family programs. It is believed that such an environment would ultimately effect the transformation of all schools to become ardent learning organisations.

The successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC).

The KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed.

Results indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings.

There is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.

The purpose of this paper is to investigate an intelligent control for water hydraulic position servo system which is intent to be used in remote control robot for fusion reactor. The dynamic model of water hydraulic servo control system is built and proportional–integral–derivative (PID) controller is used.

PID control is the most common control algorithm used in industry and has been a conventional tool used to operate closed-loop control system; however, it is very difficult to achieve high accuracy and fast response by using the traditional way to tune its perimeters. To improve the control performance, optimization algorithm can be applied to search the best parameters of PID. This paper presents a search algorithm using particle swarm with H₂ control standards objective function to optimize PID parameters.

By comparing simulation and mock-up experiments’ results from different control methods, the particle swarm optimization algorithm presents better performance and is more effective for tuning PID parameters.

This paper presents an effective way to ensure safety and efficiency for remote handling maintenances of China Fusion Engineering Test Reactor.

While Singapore's outstanding educational achievements are well known worldwide, there is a disproportionate paucity of literature on school leadership practices that contribute to and support pedagogical initiatives that – along with socio‐cultural factors – are normally considered responsible for its educational success. The aim of this paper is to explicate system‐wide school leadership factors that contribute to Singapore's educational success.

The paper includes critical discussion, review of literature and conceptualization.

It is argued that three unique features of Singapore school leadership, namely – logistics of a small tightly‐coupled school system, human resource policies that reinforce alignment, and a distinctive “leader‐teacher compact” reflecting the predominant Chinese culture – account for the extraordinary level of tight coupling and alignment of leadership across the school system. In turn, these unique features bring synergies of sustainability, scalability, succession, and high performance across the entire Singapore school system.

Unique features of Singapore school leadership must be examined in conjunction with pedagogical initiatives and socio‐cultural factors for a more complete and nuanced understanding of educational success in Singapore.

Tightly coupled mechanisms of leadership underlie the success of Singapore education. Government needs to consider whether such tightly‐ coupled leadership will continue to serve it well in future, given the demand for twenty‐first century knowledge based skills.

The influence of socio‐cultural factors (e.g. leader‐teacher compact) on educational success merits inclusion in any explanation.

This paper addresses an important gap in the literature by promulgating crucial features of school leadership that contribute to Singapore's educational success.

Compared with the traditional printed circuit board (PCB) drilling process, the technology of drilling IC substrate is facing more problems, such as much smaller hole diameter, more intensive hole space, thinner sheet and more complicated materials are drilled in process. Moreover, the base material of IC substrate is different from traditional PCB, more kinds of fillers added in IC substrate which make the drill worn seriously during drilling process. Micro-drills wear and micro holes quality are the most important questions when drilling IC substrate so far. Wear morphology of micro-drill, holes wall roughness and hole location accuracy are researched in this paper. The influence factors of micro-drills wear and micro holes quality are also studied in this drilling process. The paper aims to discuss these issues.

Two drills with same structure and different diameter are used to drill different stacks of IC substrate and drill different holes in this paper. There are four experiments made and the drilling parameters including spindle speed (n), feed rate (v_f) and retraction speed (v_r) are recommended by drill manufacturing company. Wear morphologies of drill are observed, holes wall roughness (R_max) and holes location accuracy (C_pk) are measured in this paper. Analyzing the main factors influence on drill wear, holes wall roughness and holes location accuracy through these experiments.

The micro-drills of IC substrate wear more severely compared with other material of PCB through the experimental results in this paper. Drill diameter has influence on micro-drill wear when drilling IC substrate, the smaller of drill is, the more severely of micro-drill wears. Drill diameter affect the holes wall roughness too, the holes wall roughness of larger holes is better than smaller one in a certain range. The drilled holes number also has influence on micro-drills wear, holes wall roughness and holes location accuracy. The more drilled holes, the seriously of micro-drills wear, and the worn drill would destroy the hole quality. Therefore, the more drilled holes lead the bad holes wall roughness and holes location accuracy in this paper. In addition, stacks of IC substrate affect much on the holes location accuracy, the more stacks, the worse holes location accuracy.

Chinese Mainland is obviously lagging behind in technology and manufacturer of IC substrate which is incompatible with the nation circumstances. There is few research of drilling IC substrate in China and research data are lacking so far. It is most necessary to improve the technology level of drilling IC substrate in China. In order to reduce the wear of micro-drills and improve the quality of micro-holes, many experimental tests about drilling IC substrate are researched in this paper.

This purpose of this paper is to propose a recommendation approach for information retrieval.

Relevant results are presented on the basis of a novel data structure named FPT‐tree, which is used to get common interests. Then, data is trained by using a partial back‐propagation neural network. The learning is guided by users' click behaviors.

Experimental results have shown the effectiveness of the approach.

The approach attempts to integrate metric of interests (e.g., click behavior, ranking) into the strategy of the recommendation system. Relevant results are first presented on the basis of a novel data structure named FPT‐tree, and then, those results are trained through a partial back‐propagation neural network. The learning is guided by users' click behaviors.