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To address the shortcomings of the traditional back propagation (BP) neural network agent model, such as insufficient fitting accuracy and low computational efficiency, an improved method is proposed.

In this study, an improved sparrow search algorithm (ISSA) is developed to optimize the reliability calculation of the BP neural network (ISSA-BP) using an enhanced BP neural network model. The traditional sparrow search algorithm is enhanced by incorporating a golden sine strategy to improve its position-updating mechanism, thereby overcoming its tendency to converge prematurely to local optima. Additionally, an opposition-based learning strategy is integrated to explore the reverse solution around the optimal solution of the sparrow search algorithm, mitigating the risk of local optima.

The results of the test function demonstrate that the proposed method significantly enhances fitting accuracy while maintaining computational efficiency. Finally, by applying this approach to the metro bogie frame as a case study, the structural reliability of the bogie frame is evaluated using the Monte Carlo method, providing valuable insights for subsequent analysis and structural optimization.

The use of the surrogate model approach for structural reliability analysis significantly improves solution efficiency. Furthermore, the integration of ISSA with the BP neural network enhances both fitting accuracy and computational efficiency, demonstrating the superiority and practicality of the proposed method.

Culture is a central concept broadly studied in social anthropology and sociology. It has been gaining increasing attention in economics, appearing in research on labor market discrimination, identity, gender, and social preferences. Most experimental economics research on culture studies cross-national or cross-ethnic differences in economic behavior. In contrast, we explain laboratory behavior using two cultural dimensions adopted from a prominent general cultural framework in contemporary social anthropology: group commitment and grid control. Groupness measures the extent to which individual identity is incorporated into group or collective identity; gridness measures the extent to which social and political prescriptions intrinsically influence individual behavior. Grid-group characteristics are measured for each individual using selected items from the World Values Survey. We hypothesize that these attributes allow us to systematically predict behavior in a way that discriminates among multiple forms of social preferences using a simple, parsimonious deductive model. The theoretical predictions are further tested in the economics laboratory by applying them to the dictator, ultimatum, and trust games. We find that these predictions are confirmed overall for most experimental games, although the strength of empirical support varies across games. We conclude that grid-group cultural theory is a viable predictor of people’s economic behavior, then discuss potential limitations of the current approach and ways to improve it.

The purpose of this paper is to evaluate the effectiveness of a career management program embedded within a business module, with a specific focus on enhancing the employability of students.

The study involved five one-hour workshops based on the DOTS model, covering aspects like resume writing and professional communication. Surveys, using a structured questionnaire and a Likert scale, measured participants' perceived employability. The pre-survey included demographic details, while the post-survey evaluated the effectiveness of the Career development learning workshop. Incentives and QR codes were employed to boost participation, and data were collected at the semester's start and end, with responses linked through students' phone numbers.

The results confirmed a positive connection between the perceived effectiveness of skill programs and students' employability. Integration of career management into the curriculum cultivates a heightened professional mindset and boosts employability. Validation through a paired-samples t-test demonstrates a substantial increase in perceived employability after program participation, affirming the program's role in fostering psychosocial empowerment and elevating students' confidence in job seeking.

This pioneering research integrates a career management program into a business module, addressing employability challenges in Industry 4.0. It provides empirical evidence of the program's positive impact on students' perceived employability.

The purpose of this paper is to investigate the wettability of an active Sn2Ti solder on an Al₂O₃ ceramic material at temperatures of 700°C and higher. Based on the results of the wettability study, soldered joints of Al₂O₃ ceramics/Sn2Ti solder/steel type AISI 321 were fabricated and the variation of shear strength with time was determined.

For determining melting points, differential scanning calorimetry analysis was performed. The wetting angle of Sn2Ti solder on Al₂O₃ ceramics was measured using specially developed equipment with a 10‐3 Pa vacuum at temperatures of 700, 800, 850 and 900°C. The wetting angle on AISI 321 steel at a temperature of 850°C was also determined. The joints of Al₂O₃ ceramics/Sn2Ti solder/steel type AISI 321 were prepared at 900°C, in a vacuum for times 5, 10, 15 and 20 min.

The best wettability of Sn2Ti solder was achieved at a temperature of 900°C. The wetting angle at the parameter of 900°C/ for 15 min was 47.5°. The joints of Al₂O₃ ceramics/Sn2Ti solder/steel type AISI 321 attained a strength of 18.3 MPa. It was found that the microstructure of Sn2Ti solder consists of a tin matrix with the presence of a αTi6Sn5 phase.

The results of the work are of significance for the further development of soldering with active solders in a vacuum, as well as with the application of power ultrasound. The possibility of soldering Al₂O₃ ceramics with SnTi‐based solders was thus demonstrated.

Although the field of neuroscience has evolved dramatically, little research has attempted to conceptualize the impact of neuroscience on the field of human resource development (HRD). The purpose of this study is an integrative review of the influential relationship between neuroscience and workplace learning including applicable implications for HRD research and practice.

By reviewing 93 studies on neuroscience and brain-based learning published between 1995 and 2017, the authors synthesized their findings.

This study discusses the basic concepts of neuroscience such as the structure and functions of the brain, neuroscientific findings about memory and cognition, the effect of neural transmitters on memory and cognition and the neuroscience of learning. This study also illustrates brain-based learning styles affecting learning and describes various neuroscientific learning principles and models that can be applied to practical planning and the delivery of workplace learning and HRD activities.

This study concludes with brain-based learning principles called neuroscientism compared with traditional learning theories. It also includes several brain-based learning cases from workplace settings and implications for future research and further HRD practices.

This paper is a study of the current trends and conditions of electronic resources for Chinese studies, based on a recent survey on the Internet of 29 Chinese libraries in North America and eight Chinese libraries in China, Taiwan and Hong Kong. The survey discussed current electronic resources for Chinese studies, with a union list of major Chinese language databases currently used in libraries in Asia and the US. Current views on the use and development of electronic resources for Chinese studies were summarised.

This paper presents a Monotonic Unbounded Schemes Transformer (MUST) approach to bound/monotonize (remove undershoots and overshoots) unbounded spatial differencing schemes automatically, and naturally. Automatically means the approach (1) captures the critical cell Peclet number when an unbounded scheme starts to produce physically unrealistic solution automatically, and (2) removes the undershoots and overshoots as part of the formulation without requiring human interventions. Naturally implies, all the terms in the discretization equation of the unbounded spatial differencing scheme are retained.

The authors do not formulate new higher-order scheme. MUST transforms an unbounded higher-order scheme into a bounded higher-order scheme.

The solutions obtained with MUST are identical to those without MUST when the cell Peclet number is smaller than the critical cell Peclet number. For cell Peclet numbers larger than the critical cell Peclet numbers, MUST sets the nodal values to the limiter value which can be derived for the problem at-hand. The authors propose a way to derive the limiter value. The authors tested MUST on the central differencing scheme, the second-order upwind differencing scheme and the QUICK differencing scheme. In all cases tested, MUST is able to (1) capture the critical cell Peclet numbers; the exact locations when overshoots and undershoots occur, and (2) limit the nodal value to the value of the limiter values. These are achieved by retaining all the discretization terms of the respective differencing schemes naturally and accomplished automatically as part of the discretization process. The authors demonstrated MUST using one-dimensional problems. Results for a two-dimensional convection–diffusion problem are shown in Appendix to show generality of MUST.

The authors present an original approach to convert any unbounded scheme to bounded scheme while retaining all the terms in the original discretization equation.

The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.

To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.

Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.

It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.

The purpose of this paper is to present an on-line modeling and controlling scheme based on the dynamic recurrent neural network for wastewater treatment system.

A control strategy based on rule adaptive recurrent neural network (RARFNN) is proposed in this paper to control the dissolved oxygen (D_O) concentration and nitrate nitrogen (S_No) concentration. The structure of the RARFNN is self-organized by a rule adaptive algorithm, and the rule adaptive algorithm considers the overall information processing ability of neural network. Furthermore, a stability analysis method is given to prove the convergence of the proposed RARFNN.

By application in the control problem of wastewater treatment process (WWTP), results show that the proposed control method achieves better performance compared to other methods.

The proposed on-line modeling and controlling method uses the RARFNN to model and control the dynamic WWTP. The RARFNN can adjust its structure and parameters according to the changes of biochemical reactions and pollutant concentrations. And, the rule adaptive mechanism considers the overall information processing ability judgment of the neural network, which can ensure that the neural network contains the information of the biochemical reactions.

This work evaluates the risk of wastewater in transmitting intestinal helminths to a population living near an urban effluent.

This study is a copro‐epidemiological evaluation of the school‐age children of Sidi Daoui, a neighbourhood in the discharge area of the main sewer of the city of El Jadida and a control group from Sidi Moussa, a district far from the discharge area.

Intestinal helminths are more prevalent among the children of the study group of Sidi Daoui by 43 percent, compared with 20 percent in the control group, mainly caused by ascariasis and hymenolepiasis. Enterobiasis is an intestinal vermin present with similar expansion in both zones. Polyparasitism, which cannot be found in the control group, is 6 percent in the discharge area. A total of 22 percent of helminthiasis cases among these children are attributed to wastewater, in particular ascariasis (17 percent) and hymenolepiasis (11 percent). It was found that boys are the most vulnerable, mostly between the ages of seven to nine.

Provides some useful information concerning the risk of wastewater transmitting intestinal helminths.