Simulating Optimum Design of Handling Service Center System Based on WITNESS

This paper creates personnel dispatching model of handling service center using simulation software―WITNESS. It also makes recommendations for improvement and improvement measures via the research and analysis of handling pipeline to achieve the following objectives: improving the efficiency of operating personnel and tooling equipment; reducing the working hours consumption of handling, and reducing costs; reducing the handling efficiency problems due to fewer or lack of personnel; reducing logistics costs of enterprises, including handling with the most rapid speed and staff scheduling; finding bottleneck resources of this center and strategies to address artificial constraints

Research on Risk Prediction and Early Warning of Human Resource Management Based on Machine Learning and Ontology Reasoning

Talent is the first resource, the development of the enterprise to retain key talent is essential, the main research is based on machine learning and ontological reasoning, human resources analysis and management risk prediction and early warning methods, first of all, according to the specific situation and the target case, through the calculation of the similarity of the concept name and attribute of the similarity assessment of the source case in the case library, the matching of knowledge-based employees of the company\u27s case for the similarity prediction and human resources management risk prediction research. Then, according to the evaluation results, we can find out the most suitable job matches in specific risk problems and situations. This is a solution to the target cases and criteria for companies to evaluate candidates. Second, we have successfully developed and implemented a prediction model that applies machine learning to the early warning study of risk prediction for HR management. The model is optimized with a cross-validation function, and the convergence of the model training is accelerated by the regularization of Newton\u27s iterative method. Finally, our prediction model achieved 82% yield. Ontological reasoning and machine learning are promising in human resource management risk prediction and warning, which is proved by the high accuracy rate verified by examples. Finally, we analyze the proposed results of HRM risk prediction and early warning to contribute to the improvement of risk control and suggest measures for possible risks

An Efficient Numerical Inverse Scattering Algorithm for Generalized Zakharov-Shabat Equations with Two Potential Functions

rapport de rechercheThe inverse scattering problem for coupled wave equations has various applications such as waveguide filter design and electric transmission line fault diagnosis. In this paper, an efficient numerical algorithm is presented for solving the inverse scattering problem related to generalized Zakharov-Shabat equations with two potential functions. Inspired by the work of Xiao and Yashiro on Zakharov-Shabat equations with a single potential function, this new algorithm considerably improves the numerical efficiency of an algorithm proposed by Frangos and Jaggard, by transforming the original iterative algorithm to a one-shot algorithm

Development Of Structural-functional Integrated Energy Storage Concrete With Innovative Macro-encapsulated PCM By Hollow Steel Ball

Phase change materials (PCMs) have great potential for applications in energy efficient buildings. In this study, an innovative method of macro-encapsulation of PCM using hollow steel balls (HSB) was developed and the thermal and mechanical performance of PCM-HSB concrete was examined. The macro-encapsulation system (PCM-HSB) was attached with a metal clamp (c) for better mechanical interlocking with the mortar matrix. The latent heat of PCM-HSB-c that can be acquired is approximately 153.1 J/g, which can be considered to rank highly among PCM composites. According to the self-designed thermal performance evaluation, the PCM–HSB-c concrete panel is capable of reducing and deferring the peak indoor temperature. The indoor temperature of the room model using PCM-HSB-c panels was significantly lower than the ones with normal concrete panels by a range of 3–6%. Furthermore, the test room using a higher PCM-HSB-c content demonstrated a greater ability to maintain a lower indoor room temperature for a longer period of time during heating cycles. In consideration of the mechanical properties, thermal performance and other aspects of cost factors, 50% and 75% PCM-HSB-c replacement levels are recommended in producing concrete

Differences in diversity and community assembly processes between planktonic and benthic diatoms in the upper reach of the Jinsha River, China

Comparing spatio-temporal patterns between planktonic and benthic algae is helpful for understanding their associations and differences. However, such studies are still rare especially in large rivers. We used a dataset collected in the upper reach of the Jinsha River in different seasons to explore biodiversity and assembly processes of planktonic and benthic diatom assemblages. We found that planktonic and benthic diatoms presented different seasonal variation in species richness and community compositions. We also found evidence that planktonic and benthic diatoms were coupled in the summer. Planktonic diatom assemblages were mainly affected by spatial processes via directional spatial dispersal, especially in the summer. By comparison, benthic diatom assemblages were more affected by environmental processes. Our findings suggest that mass effect and species sorting paradigms explain the assembly processes of planktonic and benthic diatom assemblages, respectively, but the explanatory powers of these two paradigms vary seasonally. To effectively monitor and assess ecological conditions of large rivers, we recommend using benthic algae as a biotic indicator group as they had stronger correlations with environmental factors.Peer reviewe