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This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.

This study aims to address the challenge of automatic guided vehicle (AGV) scheduling for parcel storage and retrieval in an intelligent warehouse.

This study presents a scheduling solution that aims to minimize the maximum completion time for the AGV scheduling problem in an intelligent warehouse. First, a mixed-integer linear programming model is established, followed by the proposal of a novel genetic algorithm to solve the scheduling problem of multiple AGVs. The improved algorithm includes operations such as the initial population optimization of picking up goods based on the principle of the nearest distance, adaptive crossover operation evolving with iteration, mutation operation of equivalent exchange and an algorithm restart strategy to expand search ability and avoid falling into a local optimal solution. Moreover, the routing rules of AGV are described.

By conducting a series of comparative experiments based on the actual package flow situation of an intelligent warehouse, the results demonstrate that the proposed genetic algorithm in this study outperforms existing algorithms, and can produce better solutions for the AGV scheduling problem.

This paper optimizes the different iterative steps of the genetic algorithm and designs an improved genetic algorithm, which is more suitable for solving the AGV scheduling problem in the warehouse. In addition, a path collision avoidance strategy that matches the algorithm is proposed, making this research more applicable to real-world scheduling environments.

This study aims to discuss the effect of carbon fiber on the electric-respone of shape memory epoxy property. Epoxy (EP) is a typical excellent thermosetting shape memory polymer (SMP). To enrich the shape memory epoxy (SMEP) responsive mode, the carbon fiber fabric-reinforced SMEP composites were prepared, and the mechanical properties and the electric- and light-responsive shape memory effect of the composites were investigated and confirmed.

The carbon fiber fabric/SMEP composites were prepared via a dipping method. The carbon fiber fabric was dipped into the waterborne epoxy emulsion and dried at room temperature and then post-cured in the oven at 120 °C for 2 h. The mechanical properties and the multi-responsive shape memory properties of the composites were tested and confirmed via tensile test instrument, DC electrical source and near-infrared (NIR) laser source control system.

The carbon fiber fabric/SMEP composites showed excellent electric- and light-responsive shape memory effect.

High performance and multi-responsive shape memory materials have always been the goal of the scientists. Carbon fiber fabric and SMEP both consist of a good reputation in the field of composites, and the combination of both would set a solid foundation for getting a high performance and multi-responsive shape memory effect materials, which will enrich the responsive mode and broaden the application of SMEP.

Multi-responsive SMEP composites were prepared from waterborne epoxy and carbon fiber fabric.

The study aims to find out the university students' health information service needs in post-COVID-19 age and then consider how to do the health information services well and promote it in further work.

This study uses Kano model to design a questionnaire about university students' health information service needs from academic library and investigates 243 students from seven universities in China. The data generated were analyzed using a statistical tool and presented in tables.

The results show the students' different requirements level of health information services from academic library as must-be requirements, one-dimensional requirements, attractive quality attributes and indifferent quality in post-COVID-19 age.

The questionnaire design and the scale of respondents have limitation, such as only focus on Chinese university, have not characteristically research on different group of students. It could optimize to cover more worldwide university students and refer to different groups of students' needs in further research.

The paper expands and deepens the theory about university library health information service and provides a practical reference and proposes some suggestions for academic libraries on how to carry out health information services and give the social health institutions inspiration on how to promote the health services, especially in post-COVID-19 age.

This paper aims to propose a novel real-time three-dimensional (3D) model-based work-piece tracking method with monocular camera for high-precision assembly. Tracking of 3D work-pieces with real-time speed is becoming more and more important for some industrial tasks, such as work-pieces grasping and assembly, especially in complex environment.

A three-step process method was provided, i.e. the offline static global library generation process, the online dynamic local library updating and selection process and the 3D work-piece localization process. In the offline static global library generation process, the computer-aided design models of the work-piece are used to generate a set of discrete two-dimensional (2D) hierarchical views matching libraries. In the online dynamic library updating and selection process, the previous 3D location information of the work-piece is used to predict the following location range, and a discrete matching library with a small number of 2D hierarchical views is selected from dynamic local library for localization. Then, the work-piece is localized with high-precision and real-time speed in the 3D work-piece localization process.

The method is suitable for the texture-less work-pieces in industrial applications.

The small range of the library enables a real-time matching. Experimental results demonstrate the high accuracy and high efficiency of the proposed method.

This chapter presents a theoretical framework of the industrial relations (IR) system in China’s coal mining industry, combining the roles of management organizations, workers, and trade unions, as well as government agencies. It is one of the first empirical attempts to investigate the relationship between human resource (HR) practices, labor relations, and occupational safety in China’s coal mining industry over the past 60 years, based on the secondary data on coal mining accidents and case studies of two state-owned coal mines in a northern city in Anhui Province, China. The fluctuating occupational safety has been affected by government regulations over different time spans, marked by key political agendas, and by coal mining firms taking concrete measures to respond to these regulations, while exhibiting differing safety performance in state-owned versus township-and-village-owned mines. The field studies compared a safety-oriented to a cost-control-oriented HR and labor relations system, and their influences on safety performance. Coal mining firms and practitioners are advised to shift the traditional personnel management paradigm to a modern HR management system. In addition, although workers are often blamed directly for accidents, it is suggested that workers’ participation and voice in various processes of decision-making and policy implementation, and trade unions’ active involvement in protecting workers from occupational hazards, be encouraged.

Inspired by the basic idea of gradient boosting, this study aims to design a novel multivariate regression ensemble algorithm RegBoost by using multivariate linear regression as a weak predictor.

To achieve nonlinearity after combining all linear regression predictors, the training data is divided into two branches according to the prediction results using the current weak predictor. The linear regression modeling is recursively executed in two branches. In the test phase, test data is distributed to a specific branch to continue with the next weak predictor. The final result is the sum of all weak predictors across the entire path.

Through comparison experiments, it is found that the algorithm RegBoost can achieve similar performance to the gradient boosted decision tree (GBDT). The algorithm is very effective compared to linear regression.

This paper attempts to design a novel regression algorithm RegBoost with reference to GBDT. To the best of the knowledge, for the first time, RegBoost uses linear regression as a weak predictor, and combine with gradient boosting to build an ensemble algorithm.

In light of growing concerns related to the psychological vulnerability during the pandemic, this study aims to examine the impact of fear or trauma of COVID-19 on stress, anxiety and depression among management students. Additionally, the study also explores the possible strategies adopted by professional students to cope with the pandemic situation.

With an approach to establish a probable concrete relationship between fear with the level of stress, anxiety and depression, the data for the study was collected from 1,408 management students through a structured questionnaire designed in Google Form and administered through WhatsApp. The survey was carried out in the month of July and August 2020 during the lockdown period. Correlation and structural equation modeling have been used to examine the relationship among the test attributes.

The results from the study discovered that “fear of COVID-19” has a significant and considerable impact on the increased level of anxiety and stress among the professional students, but the observations did not demonstrate a significant influence of the “fear” on “depression.” The responses reveal that students have developed anxiety and felt stressed mostly due to uncertainty in the upcoming academic plans, disturbances in their regular academic routines and concerns about their future careers. Further, the findings have portrayed that students have adopted both protective and avoidance coping strategies to overcome the adverse consequences of the pandemic.

The study gives an insight on the psychological vulnerability of the management students and their capability to overcome such sudden disruptions due to pandemics. This research could thus, serve as a reference to the policymakers, universities and institutions while planning out programs and schemes, which would encourage the aspiring managers to overcome the crisis and prepare themselves to befit the vibrant corporate world.

Several studies exist on the impact of the pandemic on undergraduate students in different universities. However, there are a dearth of literature, which reflects the psychological vulnerability of professional graduates especially management students who are on the verge of starting their professional career.

The purpose of this paper is to evaluate the applicative potentiality of functional/self-responsive materials in aeronautics. In particular, the study aims to experimentally validate the enhancement of structural performances of carbon fibers samples in the presence of nanofillers, as multi-walled carbon nanontubes or microcapsules for the self-healing functionality.

The paper opted for a mechanical study. Experimental static and dynamic tests on “blank” and modified formulations were performed in order to estimate both strength and damping parameters. A cantilever beam test set-up has been proposed. As a parallel activity, a numerical FE approach has been introduced to assess the correct modeling of the system.

The paper provides practical and empirical insights about how self-responsive materials react to mechanical solicitations. It suggests that reinforcing a sample positively affects the samples properties since they, de facto, improve the global structural performance. This work highlights that the addition of carbon nanotubes strongly improves the mechanical properties with a simultaneous slight enhancement in the damping performance. Damping properties are, instead, strongly enhanced by the addition of self-healing components. A balanced combination of both fillers could be adopted to increase electrical conductivity and to improve global performance in damping and auto-repairing properties.

The paper includes implications for the use of lightweight composite materials in aeronautics.

This paper fulfills an identified need to study new lightweight self-responsive smart materials for aeronautical structural application.

The purpose of this study is determination of cadmium using silver-gold bimetallic nanoparticles (Ag-Au BMNPs) and an aptamer modified glassy carbon electrode.

The maximum response of modified electrode was obtained with, 50 mV pulse amplitude, 20 mV/s scan rate in phosphate buffer of pH 4.0. Ag-Au BMNPs, as the mediators improved electron transmit during the entire electron transfer process and the aptasensor response. Herein, the authors used aptamer as the capture probe to prepare an aptasensor with enhanced stability.

The proposed aptasensor exhibited a wide linearity to cadmium in the range of 0.001–0.100 µg/L with a low detection limit of 0.005×10⁻³ µg/L. The glassy carbon electrodes with Ag-Au BMNPs showed a lower detection limit.

This aptasensor has good reproducibility, stability and repeatability and is cost-effective to regenerate. The specificity and selectivity of the novel modified electrode is tested in the presence of other interfering metal ions such as Fe²⁺, Mn²⁺, Mg²⁺, Sb³⁺ and Bi³⁺. The aptasensor shows 10 times more sensitivity and selectivity for Cd²⁺ ions.