Real-Time Monitoring Method for Cow Rumination Behavior Based on Edge Computing and Improved MobileNet v3

[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.

Home Monitoring of Estrone-3-Glucuronide (E1-3G) Levels in Two Different Ovarian Stimulation Protocols: A Pilot Study

Background: Studies have shown a strong correlation between the growth of E2 in serum and estrone-3-glucuronide (E1-3G) in urine during ovarian stimulation. Thus, we developed theoretical models for using urinary E1-3G in ovarian stimulation and focused on their experimental verification and analysis. Methods: A prospective, observational pilot study was conducted involving 54 patients who underwent 54 cycles of ovarian stimulation. The goal was to establish the growth rate of urinary E1-3G during the course of stimulation and to determine the daily upper and lower limits of growth rates at which stimulation is appropriate and safe. Controlled ovarian stimulation was performed using two different stimulation protocols—an antagonist protocol in 25 cases and a progestin-primed ovarian stimulation protocol (PPOS) in 29 cases, with fixed doses of gonadotropins. From the second day of stimulation, patients self-measured their daily urine E1-3G levels at home using a portable analyzer. In parallel, a standard ultrasound follow-up protocol accompanied by a determination of E2, LH, and P levels was applied to optimally control stimulation. Results: The average daily growth rates in both groups were about 50%. The daily increase in E1-3G for the antagonist protocol ranged from 14% to 79%, while they were 28% to 79% for the PPOS protocol. Conclusion: This is the first study to analyze the dynamics of E1-3G in two different protocols and to estimate the limits of its increase during the entire course of the stimulation. The results confirm our theoretical model for the viability of using urinary E1-3G for monitoring ovarian stimulation.

A fully integrated electronic fabric-enabled multimodal flexible sensors for real-time wireless pressure-humidity-temperature monitoring

Real-time physiological information monitoring can predict and prevent disease, or improve treatment by early diagnosis. A comprehensive and continuous monitoring of human health requires highly integrated wearable and comfortable sensing devices. To address this need, we propose a low-cost electronic fabric-enabled multifunctional flexible sensing integration platform that includes a flexible pressure sensor for monitoring postural pressure, a humidity sensor for monitoring the humidity of the skin surface, and a flexible temperature sensor for visualizing the ambient temperature around the human body. Thanks to the unique rough surface texture, hierarchical structure, and robust electromechanical features of the MXene-modified nonwoven fabrics, the flexible pressure sensor can achieve a monitoring sensitivity of 1529.1 kPa~(-1) and a pressure range of 150 kPa, which meets the demand for human pressure detection. In addition, the unique porous structure of the fabric and the stacked multilayer structure of MXene enable the humidity sensor to exhibit extremely high monitoring sensitivity, even through clothing, and still be able to detect the humidity on the skin surface.Temperature sensors based on screen-printed thermochromic liquid crystals enable visual monitoring in the range of 0℃–65℃. Through further integration with flexible printed circuit board circuits, we demonstrate a proof-of-concept device that enables real-time monitoring of human physiological information such as physical pressure, humidity, and ambient temperature environment, suggesting that the device provides an excellent platform for the development of commercially viable wearable healthcare monitors.

FY-3D MERSI-Ⅱ影像空间信息增强与湖泊监测应用验证

国产风云三号D星中分辨率成像仪(FY-3D MERSI-Ⅱ)为生态环境监测提供了高频次、多波段、大范围的数据。MERSI-Ⅱ主要提供轨道刈幅的L1级观测产品,而地表反射率及生态参量等下游产品有限。本文开发了顾及传感器成像特性的MERSI-Ⅱ影像空间信息增强方法,充分利用了扫描成像中产生的冗余观测信息,去除Bowtie效应,在保证定量特性的前提下,实现了色调和空间的一致性,将L1级数字信号(DN)转换为几何信息完备、空间质量高的地表反射率数据。湖泊监测产品的精度和可靠性与影像空间分辨率、定位精度及成像质量等密切相关,因此以青藏高原96个湖泊监测应用为例,验证了影像空间信息增强方法的有效性。以Landsat 8陆地成像仪(OLI)水体提取结果作为真值,经本文增强处理的影像在中大型湖泊(≥550 km^(2))面积提取上的平均误差低于3.5%,中小型湖泊(<550 km^(2))提取误差均低于6.5%。综合所有样例湖泊,空间信息增强后的影像在湖泊范围监测应用中平均精度相较于常规影像提升了3.62%。

Remote Sensing Dynamic Monitoring System for Agricultural Disaster in Henan Province Based on Multi-source Satellite Data

Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.

舍内雾化喷洒生物除臭剂工艺在不同清粪工艺猪舍的除臭效果研究

试验旨在研究舍内雾化喷洒生物除臭剂在水泡粪工艺和干清粪工艺猪舍内的除臭效果。分别在句容市某水泡粪工艺育肥场和长兴县某干清粪工艺育肥场开展相关试验,2次试验使用同种生物除臭剂产品,每次试验共10 d时间,第5天开始使用除臭剂,并选取第2~4天作为对照组,第5~9天作为试验组。试验组每天人工在猪舍内喷洒2次、每次喷洒6 L,试验过程中持续监测舍内氨气(NH_(3))、硫化氢(H_(2)S)浓度变化。结果表明:水泡粪工艺猪舍在使用除臭剂处理3 d后,NH_(3)、H_(2)S浓度达到最低值,分别为2.24 mg/kg和0.11 mg/kg,此时的去除率为73.08%和72.50%,相比对照组极显著降低(P<0.01);干清粪工艺猪舍在使用除臭剂处理5 d后,NH_(3)浓度达到最低值,为5.22 mg/kg,去除率为52.65%,处理2 d后H_(2)S浓度达到最低值,为0 mg/kg,去除率为100%,均比对照组极显著降低(P<0.01)。试验结果说明舍内喷洒生物除臭剂对水泡粪和干清粪工艺猪舍内的NH_(3)、H_(2)S浓度均有明显去除效果。

Continuous TDEM for monitoring shale hydraulic fracturing

Monitoring and delineating the spatial distribution of shale fracturing is fundamentally important to shale gas production. Standard monitoring methods, such as time-lapse seismic, cross-well seismic and micro-seismic methods, are expensive, time- consuming, and do not show the changes in the formation with time. The resistivities of hydraulic fracturing fluid and reservoir rocks were measured. The results suggest that the injection fluid and consequently the injected reservoir are characterized by very low resistivity and high chargeability. This allows using of the controlled-source electromagnetic method （CSEM） to monitor shale gas hydraulic fracturing. Based on the geoelectrical model which was proposed according to the well-log and seismic data in the test area the change rule of the reacted electrical field was studied to account for the change of shale resistivity, and then the normalized residual resistivity method for time lapse processing was given. The time-domain electromagnetic method （TDEM） was used to continuously monitor the shale gas fracturing at the Fulin shale gas field in southern China. A high-power transmitter and multi-channel transient electromagnetic receiver array were adopted. 9 h time series of Ex component of 224 sites which were laid out on the surface and over three fracturing stages of a horizontal well at 2800 m depth was recorded. After data processing and calculation of the normalized resistivity residuals, the changes in the Ex signal were determined and a dynamic 3D image of the change in resistivity was constructed. This allows modeling the spatial distribution of the fracturing fluid. The model results suggest that TDEM is promising for monitoring hydraulic fracturing of shale.

Composition analysis of colored dissolved organic matter in Taihu Lake based on three dimension excitation-emission fuorescence matrix and PARAFAC model, and the potential application in water quality monitoring

Taihu Lake is one of the five biggest lakes in China. Surface water samples from 26 sampling sites of Taihu Lake were collected. Furthermore wet chemical analysis （CODCr and BOD5） and measurement of three dimensional excitation-emission matrix （3DEEM） spectra in the laboratory have been conducted. Using parallel factor analysis （PARAFAC） model, three components of colored dissolved organic matter （CDOM） have been identified successfully, based on the analysis of 3DEEM data. The characteristics of the three components also have been described by comparing them to some components of CDOM, identified in earlier researches. Meanwhile, spatial variations of concentration for the three components in Taihu Lake have been analyzed, and the result indicates that the concentration of component 1 depends more on the situation of wastewater pollution and can be used as the indicator of wastewater pollution. The relationship between the concentrations of the three components and results of the wet chemical analysis show that none of the three components can be used as indicators of gross organic matter in water. However, the concentrations of all the three components have obvious linear relationships with the BOD5 value, especially for component 1 （r = 0.72878）. Finally, the potential applications of the composition analysis based on 3DEEM and PARAFAC model in water quality monitoring have been illuminated.

Cavity 3D modeling and correlative techniques based on cavity monitoring

According to the mining method for Dongguashan Copper Mine and Tongkeng Mine in China, and with the help of the cavity monitoring system（CMS） and mining software Surpac, the 3D cavity models were established exactly. A series of correlative techniques for calculating stope over-excavation and under-excavation, stope dilution and ore loss rates, and the blasting design of the pillar with complicated irregular boundaries were developed. These techniques were applied in Dongguashan Copper Mine and Tongkeng Mine successfully. Using these techniques, the dilution rates of stopes 52-2^#, 52-6^#, 52-8^#and 52-10^# of Dongguashan Copper Mine are calculated to be 2.12%, 8.46%, 12-67% and 10.68%, respectively, and the ore loss rates of stopes 52-6^# and 5-8^# are 4.41% and 3.70%, severally. Furthermore, according to the design accomplished by the technique for a pillar of Tongkeng Mine with irregular boundary, the volume, total length of boreholes and the dynamite quantity of the pillar are computed to be 1.2 ×10^4 m^3, 2.98 km and 10.97 t, correspondingly.

Stability and remote real-time monitoring of the slope slide body in the Luoshan mining area

Landslides have occurred frequently in the Luoshan mining area because of disordered mining.This paper discusses the landforms and physiognomy,hydro-meteorology,formation lithology,and geologic structure of the Luoshan mining area.It also describes the factors influencing the slope stability of landslide No.Ⅲ,determines the general parameters and typical section plane,analyzes the stress-strain state of the No.Ⅲ slope,and calculates its safety factors with FLAC3 D under saturated and natural conditions.Based on a stability analysis,a remote real-time monitoring system was applied to the No.Ⅲ slope,and these monitoring data were collected and analyzed.

Monitoring slope deformation using a 3-D laser image scanning system: a case study

An ILRIS-36D 3-D laser image scanning system was used to monitor the Anjialing strip mine slope on Pingshuo in Shanxi province. The basic working principles, performance indexes, features and data collection and processing methods are illus-trated. The point cloud results are analyzed in detail. The rescale range analysis method was used to analyze the deformation char-acteristics of the slope. The results show that the trend of slope displacement is stable and that the degree of landslide danger is low. This work indicates that 3-D laser image scanning can supply multi-parameter, high precision real time data over long distances. These data can be used to study the distortion of the slope quickly and accurately.

Large-scale deformation monitoring in mining area by D-InSAR and 3D laser scanning technology integration

Large-scale deformation can not be detected by traditional D-InSAR technique because of the limit of its detectable deformation gradient,we propose a method that combines SAR data with point cloud data obtained by 3D laser scanning to improve the gradient of deformation detection.The proposed method takes advantage of high-density of 3D laser scanning point cloud data and its high precision of point positioning after 3D modeling.The specifc process can be described as follows:frst,large-scale deformation points in the interferogram are masked out based on interferometric coherence;second,the interferogram with holes is unwrapped to obtain a deformation map with holes,and last,the holes in the deformation map are flled with point cloud data using inverse distance weighting algorithm,which will achieve seamless connection of monitoring region.We took the embankment dam above working face of a certain mining area in Shandong province as an example to study large-scale deformation in mining area using the proposed method.The results show that the maximum absolute error is 64 mm,relative error of maximum subsidence value is 4.95%,and they are consistent with leveling data of ground observation stations,which confrms the feasibility of this method.The method we presented provides new ways and means for achieving large-scale deformation monitoring by D-InSAR in mining area.

The Utilization of Real-Time High Resolution Monitoring Techniques in Karst Carbon Sequestration:A Case Study of the Station in Banzhai Subterranean Stream Catchment

The karst process acts as carbon sequestration for atmospheric CO_2.The amount of karst carbon sequestration (KCS) depends on the discharge of karst catchment and inorganic carbon concentration of the water body.Based on the data from the monitoring station on Banzhai subterranean stream located in Maolan National Nature Reserve of Guizhou province,the process and influence factors of KCS have been analyzed.It shows that the amount of KCS is about 353 t C per year in the catchment of Banzhai subterranean stream,and there is good linear relationship between the strength of KCS and discharge of the stream at various time scales.Therefore,how to monitor the discharge accurately is the key to the estimation of KCS.And stations with real-time monitoring function are very important for KCS calculation because of strong seasonal variability of the karst water cycle.

Assessing a novel modelling approach with high resolution UAV imagery for monitoring health status in priority riparian forests

Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Phytopththora”.Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity.Data obtained by unmanned aerial vehicles(UAVs)may be particularly useful for such tasks due to the high resolution,flexibility of acquisition and cost efficiency of this type of data.In this study,A.glutinosa decline was assessed by considering four categories of tree health status in the field:asymptomatic,dead and defoliation above and below a 50% threshold.A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles-red green blue(RGB)data were analysed using classical random forest(RF)and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony.A total of 34 remote sensing variables were considered,including a set of vegetation indices,texture features from the normalized difference vegetation index(NDVI)and a digital surface model(DSM),topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level.Results:The four categories identified by the RF yielded an overall accuracy of 67%,while aggregation of the legend to three classes(asymptomatic,defoliated,dead)and to two classes(alive,dead)improved the overall accuracy to 72% and 91% respectively.On the other hand,the confusion matrix,computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%,80% and 94% for four-,three-and two-level classifications,respectively.Discussion:The study findings provide forest managers with an alternative robust classification method for the rapid,effective assessment of areas affected and non-affected by the disease,thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forests.

Real-Time Grouting Monitoring and Visualization Analysis System for Dam Foundation Curtain Grouting

A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model(GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.

Design of On-Line Monitoring System for UHVDC Earth Electrode

At present the detecting of ultra high voltage direct current (UHVDC) earth electrode frequently uses manual inspection. This method can't get the real-time operational data of the earth electrodes, and meanwhile, the labor cost is very high. In order to satisfy the security needs of UHVDC, this paper designs an on-line monitoring system for UHVDC earth electrode. By 3G wireless communication-technologies, the system can monitor remotely many kinds of data such as the value of the grounding current, water level of the observation well, soil temperature and humidity near the earth electrode, the micro-climate around the earth electrode site, video data, etc. Through analyzing the datum, the system has broad prospect on fault detection and life evaluation of the UHVDC earth electrode.

A New Protocol for Controlled Ovarian Stimulation Monitoring by Self-Determination of Estrone-3-Glucuronide and Single Ultrasound (COSSESU)

Background: Answering the question of what is the optimal protocol for monitoring controlled ovarian stimulation (COS) still remains a challenge. The rapid introduction of new diagnostic methods and various components of telemedicine makes it possible to reduce the number of patient visits during ovarian stimulation, which will reduce the loss of time, costs, and risk for the patient from COVID-like situations. Methods: The different COS monitoring protocols are examined, thus proposing a new approach consisting of two successive phases. Results: In the first phase, E3G in urine samples is being examined, which is performed by the patient themselves with a small portable analyzer. Based on the results, the specialist prescribes the doses for stimulation. The second phase involves one single determination of the size and number of follicles at the end of stimulation, using TVUS, as well as the dynamics of serum levels of P4 and E2. This proves to be in many cases sufficient. Conclusions: It is of our opinion that on the basis of new diagnostic tests such as E3G in urine and telemedicine, patients are able to independently and actively participate in the treatment process. This new approach to COS monitoring can be successfully implemented in different protocols for ovarian stimulation.

Railway Transport Infrastructure Monitoring by UAVs and Satellites

Improving the rail transport security requires development and implementation of neoteric monitoring and control facilities in conditions of increasing speed and intensity of the train movement and high level of terrorist threat. Use of Earth remote sensing (ERS), permitting to obtain information from large areas with a sufficiently high resolution, can provide significant assistance in solving the mentioned problems. This paper discusses the possibility of using various means of remote sensing such as satellites and unmanned aerial vehicles (UAV), also known as drones, for receiving information in different ranges of the electromagnetic spectrum. The paper states that joint using of both these means gives new possibilities in improving railroad security.

Construction Control and Monitoring of Large Span Continuous Steel Arch Bridge Based on 3G Network

This paper takes the right branch main channel Bridge of Huai River Bridge in Huainan as the engineering background, uses the finite element software Midas and the ANSYS to simulate and analyze the jacking construction of the bridge, and according to the theoretical calculation, the construction monitoring plan is developed, and the stress and deformation of the key section and part of the structure are monitored. Construction monitoring combined with 3 g network and data acquisition module, monitoring data for the real time measurement, the centralized acquisition and wireless transmission, accomplish on-line real-time monitoring of the bridge construction process, effective control of jacking construction and monitoring. The comparison between theoretical analysis and measured results shows that the simulation results are reasonable, and the construction monitoring scheme based on 3G network and data collection can be used as reference.

GF-3 InSAR Achieves Sub-centimeter Level Surface Subsidence Monitoring

The GF-3 satellite was launched on August 10,2016 from the Taiyuan Satellite Launch Center and was put into operation at the end of January,2017.It has acquired nearly 100 thousand C-band multi-polarization ocean and land SAR images,providing data support for many departments covering resource survey,typhoon early warning,disaster assessment,crop yield estimation and polar investigation.Recently,the team led by ZHANG Qingjun from