Intelligent Energy Utilization Analysis Using IUA-SMD Model Based Optimization Technique for Smart Metering Data

Smart metering has gained considerable attention as a research focus due to its reliability and energy-efficient nature compared to traditional electromechanical metering systems. Existing methods primarily focus on data management,rather than emphasizing efficiency. Accurate prediction of electricity consumption is crucial for enabling intelligent grid operations,including resource planning and demandsupply balancing. Smart metering solutions offer users the benefits of effectively interpreting their energy utilization and optimizing costs. Motivated by this,this paper presents an Intelligent Energy Utilization Analysis using Smart Metering Data(IUA-SMD)model to determine energy consumption patterns. The proposed IUA-SMD model comprises three major processes:data Pre-processing,feature extraction,and classification,with parameter optimization. We employ the extreme learning machine(ELM)based classification approach within the IUA-SMD model to derive optimal energy utilization labels. Additionally,we apply the shell game optimization(SGO)algorithm to enhance the classification efficiency of the ELM by optimizing its parameters. The effectiveness of the IUA-SMD model is evaluated using an extensive dataset of smart metering data,and the results are analyzed in terms of accuracy and mean square error(MSE). The proposed model demonstrates superior performance,achieving a maximum accuracy of65.917% and a minimum MSE of0.096. These results highlight the potential of the IUA-SMD model for enabling efficient energy utilization through intelligent analysis of smart metering data.

Tribological behavior of ultra-high molecular weight polyethylene in a hip joint simulator

In this paper effects of various injection molding parameters on tribological properties of ultra-high molecular weight polyethylene （UHMWPE） were investigated. The tribological properties like coefficient of friction and wear rate were obtained from the experimental results of hip simulator which was designed and fabricated in the laboratory. Bovine serum was used as a lubricant in this study. In addition, the hardness of the specimen was also investigated as well. The injection molding parameters that varied for this study are melt temperature, injection velocity and compaction time. The results show that contact loads and melt temperature were mostly influenced the tribological behavior of UHMWPE. A wear mechanism map was developed to study the dominant wear mechanism that influences the wear behavior of UHMWPE. SEM was employed to study the worn out morphologies of UHMWPE. The dominant wear mechanisms that are dominated through our study are ironing, scratching, ploughing, plastic deformation, and fatigue wear.