In the era of big data, the analysis and processing of data has many difficult problems, such as difficult integration of heterogeneous data, inability to guarantee timeliness, weak analysis ability and weak visualization ability. In response to these problems, this paper conducts secondary development of the open-source ELK (Elasticsearch, Logstash, Kibana) log analysis system to better analyze and visualize the data. In order to show the effectiveness of the system more clearly, this paper takes the collected operation and maintenance data of a certain server as an example, and presents the important information obtained by searching, summarizing and analyzing the logs in the form of various dynamic charts or visualizations. It can be seen from the results that the system can better and more vividly display data distribution and operation and maintenance and provide a method and tool for data processing and visual presentation, which can help people better grasp information or make auxiliary decision-making.
Small target detection is an importance part of infrared technology. Human visual system properties can improve signal to noise rate and detection rate, etc. In this paper, a small target detection algorithm based on human visual system utilizing distance information is proposed. First, surrounding regions is calculated by weighed sum of each pixel in surrounding regions. The weight is related to distance information between each surrounding pixel and center pixel. Then, the contrast value of center pixel blocks and surrounding regions is calculated. Finally, the contrast value is weighted to the center pixel to get a saliency map. Experiment shows that the proposed has good performance on improving the signal to noise rate and detection rate.
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