Application of Video Recognition Technology in Landslide Monitoring System

The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology

Design of rapid monitoring system of geological disaster based on LoRa

According to the characteristics of the geological environment and disasters, this paper uses microelectronics, wireless communication, thin-film solar power supply and other technologies, combined with lightweight process design, a new scheme for rapid geological disaster monitoring system based on LoRa is proposed. The system is based on embedded microprocessor of STM32F103 and SX1278 module of LoRa, which uses self-organizing network design of star-type and constructs a monitoring system with long communication distance and stable and reliable data transmission. The system can realize real-time data collection of multiple monitoring parameters of the disaster body and transmit the monitoring data to the data center or dedicated data receiving terminal through LoRa/GPRS/BeiDou satellite, which can provide data support for expert analysis and decision-making. The system has the features of low power consumption, long transmission distance, ad hoc network, stable and reliable communication, which has wide application prospect in the field of geological disaster monitoring

Design of rapid monitoring system of geological disaster based on LoRa

According to the characteristics of the geological environment and disasters, this paper uses microelectronics, wireless communication, thin-film solar power supply and other technologies, combined with lightweight process design, a new scheme for rapid geological disaster monitoring system based on LoRa is proposed. The system is based on embedded microprocessor of STM32F103 and SX1278 module of LoRa, which uses self-organizing network design of star-type and constructs a monitoring system with long communication distance and stable and reliable data transmission. The system can realize real-time data collection of multiple monitoring parameters of the disaster body and transmit the monitoring data to the data center or dedicated data receiving terminal through LoRa/GPRS/BeiDou satellite, which can provide data support for expert analysis and decision-making. The system has the features of low power consumption, long transmission distance, ad hoc network, stable and reliable communication, which has wide application prospect in the field of geological disaster monitoring

Application of Video Recognition Technology in Landslide Monitoring System

The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology

Design of the Landslide Multi-factor Monitoring System Based on the GNSS Technology

Based on the multi-element monitoring of landslide, this paper adopts the GNSS technology to build the three-dimensional space monitoring system to research the landslide multi-element three- dimensional space monitoring technology. Through collecting the rainfall, soil moisture content, slope, pore water pressure, stress, single point surface deformation etc, the system has many key technologies such as multi-parameter, information acquisition, data fusion analysis and real-time early warning of landslides and integrate various elements by using the professional technology. This research provides an important reference for the landslide disaster prevention

Landslide Displacement Prediction Based on Variational Mode Decomposition and GA–Elman Model

Landslide displacement prediction is an important part of monitoring and early warning systems. Effective displacement prediction is instrumental in reducing the risk of landslide disasters. This paper proposes a displacement prediction model based on variational mode decomposition and a genetic algorithm optimization of the Elman neural network (VMD–GA–Elman). First, using VMD, the landslide displacement sequence is decomposed into the three subsequences of the trend term, the periodic term, and the random term. Then, appropriate influencing factors are selected for each of the three subsequences to construct input datasets; the rationality of the selection of the influencing factors is evaluated using the gray correlation analysis method. The GA–Elman model is used to forecast the trend item, periodic item and random item. Finally, the total displacement is obtained by superimposing the three subsequences to verify the performance of the model. A case study of the Shuizhuyuan landslide (China) is presented for the validation of the developed model. The results show that the model in this paper is in good agreement with the actual situation and has good prediction accuracy; it can, therefore, provide a basis for early warning systems for landslide displacement and deformation

Twentieth Century Walker Circulation Change: Data Analysis and Model Experiments

Recent studies indicate a weakening of the Walker Circulation during the twentieth century. Here, we present evidence from an atmospheric general circulation model (AGCM) forced by the history of observed sea surface temperature (SST) that the Walker Circulation may have intensified rather than weakened. Observed Equatorial Indo-Pacific Sector SST since 1870 exhibited a zonally asymmetric evolution: While the eastern part of the Equatorial Pacific showed only a weak warming, or even cooling in one SST dataset, the western part and the Equatorial Indian Ocean exhibited a rather strong warming. This has resulted in an increase of the SST gradient between the Maritime Continent and the eastern part of the Equatorial Pacific, one driving force of the Walker Circulation. The ensemble experiments with the AGCM, with and without time-varying external forcing, suggest that the enhancement of the SST gradient drove an anomalous atmospheric circulation, with an enhancement of both Walker and Hadley Circulation. Anomalously strong precipitation is simulated over the Indian Ocean and anomalously weak precipitation over the western Pacific, with corresponding changes in the surface wind pattern. Some sensitivity to the forcing SST, however, is noticed. The analysis of twentieth century integrations with global climate models driven with observed radiative forcing obtained from the Coupled Model Intercomparison Project (CMIP) database support the link between the SST gradient and Walker Circulation strength. Furthermore, control integrations with the CMIP models indicate the existence of strong internal variability on centennial timescales. The results suggest that a radiatively forced signal in the Walker Circulation during the twentieth century may have been too weak to be detectable

Beneficial Effects of Partly Milled Highland Barley on the Prevention of High-Fat Diet-Induced Glycometabolic Disorder and the Modulation of Gut Microbiota in Mice

The nutritional functions of highland barley (HB) are superior to those of regular cereals and have attracted increasing attention in recent years. The objective of this study was to investigate whether partly milled highland barley (PHB) can regulate the serum glucose and lipid disorders of mice fed a high-fat diet (HFD) and to further explore their potential gut microbiota modulatory effect. Our results showed that PHB supplementation significantly reduced fasting blood glucose (FBG) and improved oral glucose tolerance. Histological observations confirmed the ability of PHB to alleviate liver and intestine damage. Furthermore, the results of 16S amplicon sequencing revealed that PHB prevented a HFD-induced gut microbiota dysbiosis, enriching some beneficial bacteria, such as Lactobacillus, Bifidobacterium, and Ileibacterium, and reducing several HFD-dependent taxa (norank_f_Desulfovibrionaceae, Blautia, norank_f_Lachnospiraceae, unclassified_f_Lachnospiraceae, and Colidextribacter). In addition, the increase of Lactobacillus and Bifidobacterium presence has a slightly dose-dependent relationship with the amount of the added PHB. Spearman correlation analysis revealed that Lactobacillus and Bifidobacterium were negatively correlated with the blood glucose level of the oral glucose tolerance test. Overall, our results provide important information about the processing of highland barley to retain its hypoglycemic effect and improve its acceptability and biosafety

Ethyl-eicosapentaenoate modulates changes in neurochemistry and brain lipids induced by parkinsonian neurotoxin 1-methyl-4-phenylpyridinium in mouse brain slices

Evidence suggests a link between Parkinson's disease and the dietary intake of omega (n) 123 and n 126 polyunsaturated fatty acids (PUFAs). Presently, we investigated whether an acute dose of parkinsonian neurotoxin 1-methyl-4-phenylpyridinium (MPP+) affects brain n 123 and n 126 PUFA content and expression of fatty acid metabolic enzymes cytosolic phospholipase A2 (cPLA2) and cyclooxygenase-2 (COX-2) in brain slices from C57Bl/6mice. Furthermore, we investigated whether feeding a diet of n 123 PUFA ethyl-eicosapentaenoate (E-EPA) to these mice can attenuate the MPP+ induced changes in brain PUFA content and expression of cPLA2 and COX-2, and attenuate MPP+ induced changes in neurotransmitters and metabolites and apoptotic markers, bax, bcl-2 and caspase-3. MPP+ increased brain content of n 126 PUFAs linoleic acid and arachidonic acid, and increased the mRNA expression of cPLA2. MPP+ also depleted striatal dopamine levels and increased dopamine turnover, and depleted noradrenaline levels in the frontal cortex. The neurotoxin induced increases in bax, bcl-2 and caspase-3 mRNA expression that approached significance. E-EPA by itself increased brain n 123 content, including EPA and docosapentaenoic acid (C22:5, n 123), and increased cortical dopamine. More importantly, E-EPA attenuated the MPP+ induced increase in n 126 fatty acids content, partially attenuated the striatal dopaminergic turnover, and prevented the increases of pro-apoptotic bax and caspase-3 mRNAs. In conclusion, increases in n 126 PUFAs in the acute stage of exposure to parkinsonian neurotoxins may promote pro-inflammatory conditions. EPA may provide modest beneficial effects in Parkinson's disease, but further investigation is warranted.Peer reviewed: YesNRC publication: Ye