In a wireless sensor network, an adversary may crack legal nodes or deploy malicious nodes to launch various attacks. These nodes are collectively called compromised nodes. In this paper, we define a Data Transmission Quality (DTQ) function to differentiate the legitimate nodes and compromised nodes. The DTQ function is defined in a way that it will keep close to constant or change smoothly for legitimate nodes and will keep decreasing for suspicious nodes. The final decision of whether or not a suspicious node is compromised is determined by a group voting procedure. Simulations were conducted to verify the effectiveness of the design.

The main purpose of this study was to analyze the effect of coal mining on the springs in the Yushenfu mining area of China. The results of two springs and hydrological surveys conducted in 1994 and 2015 were compared to study the occurrence and evolution of springs before and after large-scale mining. The mechanism of spring evolution and ecological effects of domain evolution were analyzed by combined groundwater monitoring and evaluation of coal mining intensity. The results show that the maximum amount of single water inflow of spring with sand infiltration recharge was more than 10 L/s, the total amount of single water inflow of spring with mixed infiltration recharge was the highest, and the ecological effect of spring with loess infiltration recharge was the most significant. In the study area, 2580 springs (group) were distributed with a total flow of 4998.9428 L/s before 1994 and 376 residual springs (group) were present with a total flow of 996.392 L/s in 2015. Large-scale mining decreased the regional groundwater level, thus decreasing the amount of spring water. The high intensity of mining decreased the number of springs (group) and area of water and wetland in the study area. This directly affected the watershed ecology; the ecological degradation was significant.

Coal is the major energy source in China. Many coal mines in Southwest China have arranged the excavation roadway system in the Maokou limestone in coal seam floor because of its special hydrogeological conditions. Since karst is widely distributed in Maokou limestone and water-filled karst caves are also developed commonly there, once a strongly water-filled karst cave is exposed during roadway excavation, the water inrush disaster occurs easily. In order to reveal the phenomenon of water inrush disasters from covered karst caves more effectively, the water inrush that occurred during the roadway excavation process of Jiyuan coal mine in northern Guizhou was taken as a research object in this study. Based on the regional geological structure, the hydrogeological condition and the fluid-structure interaction theory, a fluid-structure interaction model of water inrush in the roadway excavation was established, and variation laws of stress field, displacement field and seepage field of surrounding rock during the process of water inrush from karst cave were analyzed. Besides, the influence of different geological conditions on water inrush from karst cave was discussed from aspects of the size of karst cave, the water pressure of karst cave and the thickness of aquiclude.

To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-self, antigen and detector are given. According to the relationship between the antibody-concentration of memory detectors and the intensity of network attack activities, the security situation evaluation method under IOT environment based on artificial immune system is presented. And then according to the situation time series obtained by the mentioned evaluation method, the security situation prediction method based on grey prediction theory is presented for forecasting the intensity and security situation of network attack activities that the IOT environment will be suffered in next step. The experimental results show that IIESSA provides a novel and effective model for perceiving security situation of IOT environment.

The reasonable buried depth of metro station should be investigated for Qingdao with the upper-soft and lower-hard stratum. Strength reduction method has been utilized to study FOS of metro station under different buried depths. As the buried depth increases, the curve of FOS can be divided into three parts as the slowly changed part, the rapidly-increased part, and the gradually-decreased part. Taking FOS = 1 as limitation, the formula of least rock cover thickness has been derived. Based upon the formula, the characteristics of safety distribution changing with buried depth for metro station which behaves as three zones (DI, E, DII) have been discovered. Two typical metro stations have been used to verify the research results.