Relationship Model between Human Resource Management Activities and Performance Based on LMBP Algorithm

The research on the relationship between human resource management activities and performance is an important topic of enterprise human resource management research. There are some errors between the relationship between human resource management activities and performance and the real situation, so it is impossible to accurately predict the performance fluctuation. Therefore, the relationship model between human resource management activities and performance based on the LMBP algorithm is constructed. Using the Levenberg–Marquardt (LM) algorithm and BP (back-propagation) neural network algorithm to establish a new LMBP algorithm, control the convergence of the new algorithm, optimize the accuracy of the algorithm, and then apply the LMBP algorithm to predict the risk of performance fluctuation under human resource management activities of enterprises, the indicators of human resource management activities of enterprises are determined, to complete the mining of enterprise performance data, the grey correlation analysis is combined, and the relationship model between human resource management activities and performance is built. The experimental samples are selected from CSMAR database, and the simulation experiment is designed. Using different algorithms to forecast the fluctuation of enterprise performance, the experimental results show that the LMBP algorithm can more accurately reflect the relationship between enterprise HRM and performance.

Teaching Design of Online Ideological and Political Course Based on Deep Learning Model Evaluation

In practical terms, teachers are supported to use more straightforward teaching methods, such as creating real-life contextual problems, to help students develop deep learning skills. In this paper, using Bayesian theory and Bayesian classifier research methods, a machine learning model was constructed using Python to establish the correspondence between online teaching of civics and high-level semantic features and to achieve computer learning through text and teaching design evaluation research that can identify high-frequency knowledge points. The inter-relationship model knowledge mapping, the accuracy is 90%, and the continuous knowledge update help to improve the model accuracy.

Metrological Analysis of the Relationship Model between the Properties of Piezoelectric Materials

The properties of piezoelectric materials due to the effect of electrical, mechanical, thermal, radiation, and chemical parameters are systematized. On the basis of Maxwell's relations (obtained from expressions for thermodynamic functions) and the application of the system analysis methodology, it made it possible to develop an analytical model of the relationship between the parameters and properties of piezoelectrics in the form of a system of equations. The results of the metrological analysis of an analytical model, which made it possible to identify the sources of additional errors in the measurement of parameters, to derive formulas for their calculation, which in turn contributes to an increase in the accuracy of measurements of the piezoelectrics parameters and products based on them, are presented.

Corrosion Detection of Structural Reinforcement Based on Artificial Intelligence Technology

Due to the environmental degradation caused by soil erosion, it is of great significance to establish the relationship model between geological environmental factors and piping erosion. The method to determine the prone area of pipeline corrosion is limited. This paper introduces the mechanism of reinforcement corrosion, points out the non-destructive detection methods of common steel corrosion, and puts forward the measures to prevent and maintain the corrosion of reinforcement from the aspects of design, construction and material selection, so as to prolong the service life of concrete structure. Abrasion, capitation and chemical attack in concrete hydraulic structures can lead to deterioration of spillways, stilling basins, chutes, slabs and transverse joints, concrete blocks under sluices and any irregular surfaces affected by high flow rates. There are numerous coatings on the market that can be used to repair damaged surfaces. However, the basic data provided by the manufacturer is very limited, and if so, it is usually limited to room temperature values. The results show that the data of concrete, corrosion solution and chloride ion are 0.534, 0.673 and 0.384 respectively.

DETERMINANTS OF PERSONAL BANKRUPTCY DISCHARGE IN MALAYSIA: A SOCIAL CAPITAL APPROACH OF AL-NAHD AND TA’AWUN

This study investigates the relationship between Gross Domestic Product (GDP), Consumer Price Index (CPI), Unemployment Rate (UE), Interest rate (IR), Household Debt (HD) on bankruptcy discharge and test the application of an Islamic concept of mutual cooperation, Social Relief Fund (SRF) to enhance the bankruptcy discharge. The study period is from 2000 to 2019. The autoregressive distributed lag (ARDL) was used in the study. Two models were tested; Model 1 consists of the macroeconomic variables without SRF and Model 2, with SRF. Model 1 shows none of the variables has significant effect on bankruptcy discharge for long run relationship. However, Model 2 shows GDP, CPI and SRF have significant positive long run relationship with bankruptcy discharge. This provides statistical evidence that SRF has a beneficial long-run relationship to enhance bankruptcy discharge in Malaysia. For short run relationship, Model 1 reveals GDP, CPI, and UE as significant variables to discharge. Model 2 shows stronger short run relationships in which GDP, IR, HD, SRF are positive and CPI is negative to bankruptcy discharge. These variables are significant at 1 percent level. The findings contribute new knowledge on determinants of bankruptcy discharge in Malaysia. The study provides empirical evidence that SRF is a potential component as a social safety net in providing financial assistance among distressed debtors from bankruptcy. We recommend the use of SRF as the current bankruptcy reform is being viewed from the legislative lens and lacks the social capital component to assist debtors achieve financial restitution.

Minimizing uncertainty in complete automation of Douglas-Peucker Algorithm for geospatial mapping

It is qualitatively evident that the greater the map scale change, the greater the optimal distance threshold of the Douglas-Peucker Algorithm, which is used in polyline simplification. However, no specific quantitative relationships between them are known by far, causing uncertainties in complete automation of the algorithm. To fill this gap, the current paper constructs quantitative relationships based on the spatial similarity theories of polylines. A quantitative spatial similarity relationship model was proposed and evaluated by setting two groups of control experiments and taking <C, T> as coordinates. In order to realize the automatic generalization of the polyline, we verified whether these quantitative relationships could be fitted using the same function with the same coefficients. The experiments revealed that the unary quadratic function is the best, whether the polylines were derived from different or the same geographical feature area(s). The results also show that using the same optimal distance threshold is unreasonable to simplify all polylines from different geographical feature areas. On the other hand, the same geographical feature area polylines could be simplified using the same optimal distance threshold. The uncertainties were assessed by evaluating the automated generalization results for position and geometric accuracy perspectives using polylines from the same geographic feature areas. It is demonstrated that in addition to maintaining the geographical features, the proposed model maintains the shape characteristics of polylines. Limiting the uncertainties would support the realization of completely automatic generalization of polylines and the construction of vector map geodatabases.

Analysis of Affective Discourse in the Change Process of the Employment Relationship Model: Environment Management through Collective Bargaining

This paper covers research whose goal was to analyse affective changes in the process of change in the labour relations model that was consolidated throughout the 1990s. Based on a case study, the focus was on the emotional content expressed by the protagonists inrelation to this collective bargaining framework. In conducting the analysis, we used the wide range of procedures provided by Discourse Analysis (DA). Part of this analysis focused on the protagonists’ emotional management of the early stages of the negotiation. The results let us delve deeper into the affective nature of this process, thereby expanding the light shed by other theoretical and methodological perspectives on this change in the labour relations model.