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Path planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.

Firstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.

Simulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.

Aiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.

This paper uses the GB/T20984-2007 multiplicative method to assess the information security risk of a typical digital library in compliance with the principle and thought of ISO 27000. The purpose of this paper is to testify the feasibility of this method and provide suggestions for improving information security of the digital library.

This paper adopts convenience sampling to select respondents. The assessment of assets is through analyzing digital library-related business and function through a questionnaire which collects data to determine asset types and the importance of asset attributes. The five-point Likert scale questionnaire method is used to identify the threat possibility and its influence on the assets. The 12 respondents include directors and senior network technicians from the editorial department, comic library, children’s library, counseling department and the learning promotion centre. Three different Guttman scale questionnaires, tool testing and on-site inspection are combined to identify and assess vulnerabilities. There were different Guttman scale questionnaires for management personnel, technical personnel and general librarian. In all, 15 management librarians, 7 technical librarians and 72 ordinary librarians answered the vulnerability questionnaire. On-site inspection was conducted on the basis of 11 control domains of ISO 27002. Vulnerabilities were scanned using remote security evaluation system NSFOCUS. The scanning covered ten IP sections and a total of 81 hosts.

Overall, 2,792 risk scores were obtained. Among them, 282 items (accounting for 10.1 per cent of the total) reached the high risk level; 2 (0.1 per cent) reached the very high risk level. High-risk items involved 26 threat types (accounting for 44.1 per cent of all threat types) and 13 vulnerability types (accounting for 22.1 per cent of all vulnerability types). The evaluation revealed that this digital library faces seven major hidden dangers in information security. The assessment results were well accepted by staff members of this digital library, which testified to the applicability of this method to a Chinese digital library.

This paper is only a case study of a typical Chinese digital library using a digital library information security assessment method. More case-based explorations are necessary to prove the feasibility of the assessing strategy proposed in this study.

Based on the findings of recent literature, the authors found that very few researchers have made efforts to develop methods for calculating the indicators for digital library information security risk assessment. On the basis of ISO 27000 and other related information security standards, this case study proposed an operable method of digital library information security risk assessment and used it to assess a the information security of a typical Chinese digital library. This study can offer insights for formulating a digital library information security risk assessment scale.

As competition in the graduate labor market intensifies, extracurricular internships have become increasingly popular among university students. This paper explores whether and how students’ evaluation of the higher learning that they have received changes during extracurricular internships.

We interviewed 47 undergraduate students who had extracurricular internships across five Chinese universities. Data were analyzed innovatively through the lens of cross-cultural adaptation theory, which guides us to view internships as a transition from university culture to workplace culture through the stress-adaptation-growth dynamic.

The findings reveal that participants faced stress from multiple sources at the beginning of their internships, which collectively prompted them to adapt proactively to the workplace culture. While acquiring new habits and trying to acculturate into the surrounding work milieu, many participants deculturated from their old habits and student identity, putting aside higher learning. As the adaptation progressed, over half of the participants even began to critique university curricula and depreciate the value of higher learning.

The study offers theoretical insights into internships and the broader university-to-work transition as well as practical implications for universities in balancing learning and employability goals from a novel cross-cultural adaptation perspective.

This study established and examined a moderated mediation model connecting family motivation with proactive career behavior (PCB). Drawing on social cognitive career theory model of career self-management and person-environment fit theory, the authors posit that the influence of family motivation on PCB is mediated by career goal setting (CGS) and moderated by career support climate (CSC).

Using multilevel modeling techniques, data were collected from 98 leaders and 416 employees at two-time points.

Results show that family motivation has a positive direct and indirect effect on PCB through CGS. Additionally, CSC strengthens the positive effect of family motivation on PCB through CGS.

For employees, proactive career management and the establishment of clear career goals are vital for fulfilling family responsibilities. Simultaneously, for managers and organizations, creating a supportive work environment is crucial to encourage employees in career management.

While existing research highlights the detrimental effect of fulfilling family caregiving responsibilities on employees' career development, the comprehension of this relationship remains limited. Taking a family motivation perspective, this study explores the mechanisms through which family motivation stimulates employees to engage in PCB, with a specific focus on the moderating influence of CSC. The findings offer fresh insights into the role of family motivation in career development, contributing significantly to the broader literature on the intersection of family and careers.

Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of overestimating efficiency and ignoring undesirable outputs; therefore, according to the characteristics of safety production in construction industry, this paper innovatively develops a new cross-efficiency data envelopment analysis method to analyze safety efficiency, which can solve the limitations of traditional methods; and then the safety efficiency and its influencing factors of China's construction industry are analyzed, and some useful conclusions are obtained to improve its safety efficiency.

A new cross-efficiency data envelopment analysis method with undesirable outputs is proposed; and the two-stage efficiency analysis framework is designed.

First, the construction industries in different areas have different reasons for affecting their safety efficiency; second, the evaluation results of global safety priority tend to be more acceptable; third, frequent safety accidents and low resource utilization lead to a slow downward trend of the safety efficiency of China's construction industry in the long run; fourth, construction engineering supervision, construction industrial scale, and construction industrial structure have the significant impact on safety efficiency.

Theoretically, a new cross-efficiency data envelopment analysis method with undesirable outputs is proposed for evaluating safety efficiency; practically, the safety efficiency and its influencing factors of China's construction industry are analyzed.

To improve the accuracy of stock price trend prediction in the field of quantitative financial trading, this paper takes the prediction accuracy as the goal and avoid the enormous number of network structures and hyperparameter adjustments of long-short-term memory (LSTM).

In this paper, an adaptive genetic algorithm based on individual ordering is used to optimize the network structure and hyperparameters of the LSTM neural network automatically.

The simulation results show that the accuracy of the rise and fall of the stock outperform than the model with LSTM only as well as other machine learning models. Furthermore, the efficiency of parameter adjustment is greatly higher than other hyperparameter optimization methods.

(1) The AGA-LSTM algorithm is used to input various hyperparameter combinations into genetic algorithm to find the best hyperparameter combination. Compared with other models, it has higher accuracy in predicting the up and down trend of stock prices in the next day. (2) Adopting real coding, elitist preservation and self-adaptive adjustment of crossover and mutation probability based on individual ordering in the part of genetic algorithm, the algorithm is computationally efficient and the results are more likely to converge to the global optimum.

To improve the trajectory tracking accuracy of 6R decoupled manipulator in singularity region, this paper aims to propose a singularity avoidance algorithm named “singularity separation plus improved Gaussian distribution damped reciprocal”.

The manipulator is divided into forearm and wrist, and the corresponding singularity factors are separated based on kinematics calculation. Singularity avoidance is achieved by replacing the common reciprocal with the improved Gaussian distribution damped reciprocal.

Compared with common damped reciprocal algorithm and classical Gaussian distribution algorithm, the continuity of the proposed algorithm is improved and the tracking error is minimized. The simulation and experiment results prove effectiveness and practicability of the proposed algorithm.

This study has an important significance to improve the efficiency and operation accuracy of 6R decoupled manipulator.

Using a quantitative research method, health-care workers’ (HWs) well-being was taken as the dependent variable while the two independent variables were physical quality and service environment. This study aims to focus on the well-being of HWs in their physical environment.

This study used a hybrid method that is a combination of literature review and questionnaire survey. This study used quantitative research design which is a systematic study of phenomenon by collecting quantifiable data and performing statistical, mathematical or computational techniques. This study is conducted among HWs, with doctors and nurses at four Chinese government hospitals in the southern city of Changzhou (near Shanghai) as participants.

A total of 222 responses were obtained from a random sample of HWs from four hospitals in Changzhou City, Jiangsu Province. Three-fifth of the participants (n = 133, 60%) are satisfied with hospital equipment and half (n = 111.50%) of them are satisfied with the modern technology in place. About one-third (n = 67, 30%) are satisfied with ventilation and only one-fifth (n = 44, 20%) are satisfied with hygiene. Most HWs think it was necessary to provide tests for frontline workers.

In the wake of COVID-19 in 2020, HWs are working long hours every day facing high risk of infection and stress. This research investigates the satisfaction level and the difficulties experienced by HWs based on the current physical environment setting during COVID-19 pandemic.

The credit card business has been one of the key businesses for banks in Taiwan. The purpose of this paper is to use competitive dynamics and structured context analysis (SCA) to explore the competition relationships among market, resources, and strategies concerning the credit card issued banks in Taiwan.

The market commonality and resource similarity analysis of competitive dynamics in the first stage obtained the competitive mapping of four major credit card issue banks, as well as the differences of competition strategy. In the second stage, 1,968 pieces of data on credit card news from 2013 to 2014 were collected. SCA was used to analyze the competitive action, competitive response, number of responses, response lag, and response order.

The competitor mapping and four hypothesis obtained from competitive dynamics correspond to the credit card competition strategy, as obtained from SCA.

This research combined competitive dynamics and SCA to analyze the credit cards market in Taiwan. The research model could be used in the other financial market.

Coal and power generation are related upstream and downstream industries. Coal price marketization and electricity price regulation have caused the price of coal to be sensitive to the benefits of generators. The paper aims to discuss these issues.

As a financial tool, contracts for differences can both help balance interests and reduce risks caused by spot price fluctuation. This thesis regards coal demand as a triangular fuzzy stochastic variable while directing a levelling consideration towards risk returns for coal and power enterprises that are involved in coal generation contracts for differences. Risk and benefit measurement models were established between coal suppliers and power generators, and risk and benefit balance optimization models for contract negotiation were constructed.

A numerical example showed that the above models can be effectively used to avoid the risks of coal-electricity parties.

This thesis regards coal demand as a triangular fuzzy random variable while directing a levelling consideration towards the risk return to coal and power enterprises that are involved with coal generation contracts for differences. The features of this thesis are the following: demand information is regarded as a fuzzy random variable instead of a random variable. With historical data, sales experience and increasingly clear macro-economic conditions, coal and power enterprises are able to make a fuzzy decision – to a certain extent – when the transaction approaches. Accurate market information enables the supply chain system to satisfy the clients’ needs better, improve the profit level or avoid severe financial damages; by developing a feasible set of contracts for different parameters, it is possible to estimate whether the price difference enables supply chain coordination, requires changes or gives accounts to all involved parties of the supply chain; and without the assumption that the traditional M-V rule is unfavourable to decision makers, this thesis proposes the prospect M-V rule, which involves decision makers’ projections of future coal generation prices and enables wide applicability of the response method to contracts for differences.