Gongcheng Kexue Yu Jishu/Advanced Engineering Science

In order to relieve the alarm fatigue of security analysts and improve the security operation efficiency, an attacker IP analysis system based on the Ensemble-based Local Outlier Factor algorithm (EBLOF) was proposed in this paper. Firstly, normalized network security alarm logs were extracted and merged, and then the feature engineering was constructed from the attribute dimension and attack behavior dimension of attacker IP. Secondly, inspired by the idea of ensemble learning and traditional LOF anomaly detection algorithm, a robust EBLOF algorithm of finding high-threat attacker IP was constructed in the system. Thirdly, a set of online learning architecture was built by the system, aiming to solve the problem that the machine learning model was difficultly updated online. Through the batch real-time learning technology, the learning architectures ensure that the learning model can be updated online from the system architecture level rather than the algorithm level. Finally, the EBLOF algorithm of this paper was trained on the public anomaly detection data set ODD. The experimental results showed a fact that the algorithm has better robustness than the naive LOF algorithm under different data distributions. The system proposed in the paper was applied in real attack and defense scenarios. Its effectiveness and feasibility were verified by comparing with security operation analysts

CCTS-based solar cells show promising performance in the realm of sunlight-based energy production in this study. Optimizing the buffer layer remains a barrier to improving the efficacy of CCTS-based solar cells. The initial structure is made up of a CCTS absorber layer, a ZnO resistive layer, an AZO transport conducting layer, and a window layer, as well as different buffer layers (CdS, ZnS, and ZnSe) to find the best buffer layer. The second structure is made up of a CCTS absorber layer, a ZnO resistive layer, an AZO transport conductive layer, a window layer, and different buffer layers (CdS, ZnS, and ZnSe) to find the best buffer layer. The second structure consists of the same layers as the first structure, minus the resistive layer ZnO, while the third structure consists of the same layers, minus the window layer AZO. The solar cell in this structure's open circuit (Voc), short circuit current (Jsc), fill factor (FF), and conversion efficiency (PCE) revealed that the first structure has good agreement, and that these buffer layers were used to investigate the effect of buffer thickness as alternative buffer layers. Among these three buffers, cadmium sulphide CdS) is preferable over Zns and ZnSe, and after improving the initial structure, the power conversion efficiency (PCE) was 13.47% for buffer Cds, 13.46%. The simulation showed that for structure MO / CCTS /(CdS)/ZnO / AZO at (3100) nm of absorber layer (CCTS), 40 nm of buffer layer (cds), 10 nm of resistive layer (ZnO), and 60 nm of AZO performs the best for (Voc = 0.573 V, Jsc = 30.344 mAcm-2, FF = 72.57 %, and PCE = 13.91%).

The effect of ethanol on diesel engine performance using B30 fuel has been investigated, namely a mixture of 30% calophyllum inophyllum biodiesel and 70% petrodiesel. The ethanol concentration mixed to B30 was 10% and 20% vol/vol. The experiment was conducted on a single-cylinder four-stroke diesel engine with a natural air system and joined with a generator that functioned as a dynamometer. The test was applied three times to the machine for each load, involving 0, 200, 400, 600, and 800W at a constant rotation speed of 2000 rpm. The experiment reveals that the consistent engine speed method and lamp load produce the same torque (Nm) and effectiveness power (kW) between fuels, impacted by the governor's mechanism. The 20% ethanol (B30E20) has the highest effective thermal efficiency of 28.41% and effectiveness fuel consumption of 0.46 kg/kWh. The addition of 20% ethanol reduced exhaust emissions of carbon monoxide and hydrocarbons up to 0.09% and 27.33 ppm. However, there was an exhaust emissions increase of carbon dioxide up to 8.0%. The exhaust emissions increase of carbon dioxide cannot be considered as a negative consequence because it can be reused (consumption) in the photosynthesis process raw material biofuels.