Recently, measuring users and community influences on social media networks play significant roles in science and engineering. To address the problems, many researchers have investigated measuring users with these influences by dealing with huge data sets. However, it is hard to enhance the performances of these studies with multiple attributes together with these influences on social networks. This paper has presented a novel model for measuring users with these influences on a social network. In this model, the suggested algorithm combines Knowledge Graph and the learning techniques based on the vote rank mechanism to reflect user interaction activities on the social network. To validate the proposed method, the proposed method has been tested through homogeneous graph with the building knowledge graph based on user interactions together with influences in real-time. Experimental results of the proposed model using six open public data show that the proposed algorithm is an effectiveness in identifying influential nodes.

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For coastal region, the saline intrusion is one of the major issues to be concerned because it has a direct and long-term impact on the socio-economic growth. Rang Dong Textile Industrial Park is specifically designed for the large-scale textile project, located in Rang Dong Town, Nghia Hung District, Nam Dinh Province, with a daily water demand of 170,000m3 per day. The Industrial Park (IP) is located close to the sea, surrounded by 2 big rivers, Day River and Ninh Co River with ambulant water sources. However, the surface water in this region is suffered from the saline intrusion issue. Therefore, in order to supply sufficient water amount for the industrial park, it is important to determine and select the water collector location for the clean water treatment plant in the industrial park. In the present study, the calculation of saline intrusion in the downstream of Day River is simulated with MIKE11 model, which is built based on the salinity data of water in Nhu Tan, Ba Lat, Phu Le & Dong Quy stations. The simulation results show that at the selected location of the water collector, 25km from the sea gate, the salinity maintaining time of water 4‰ per month is almost unaffected; the salinity maintaining time of water 1‰ per month only accounts for 1%-4% days in the month, meeting the water supply demand of the industrial park.