Implantable Electrochemical Microsensors for In Vivo Monitoring of Animal Physiological Information

In vivo monitoring of animal physiological information plays a crucial role in promptly alerting humans to potential diseases in animals and aiding in the exploration of mechanisms underlying human diseases.Currently,implantable electrochemical microsensors have emerged as a prominent area of research.These microsensors not only fulfill the technical requirements for monitoring animal physiological information but also offer an ideal platform for integration.They have been extensively studied for their ability to monitor animal physiological information in a minimally invasive manner,characterized by their bloodless,painless features,and exceptional performance.The development of implantable electrochemical microsensors for in vivo monitoring of animal physiological information has witnessed significant scientific and technological advancements through dedicated efforts.This review commenced with a comprehensive discussion of the construction of microsensors,including the materials utilized and the methods employed for fabrication.Following this,we proceeded to explore the various implantation technologies employed for electrochemical microsensors.In addition,a comprehensive overview was provided of the various applications of implantable electrochemical microsensors,specifically in the monitoring of diseases and the investigation of disease mechanisms.Lastly,a concise conclusion was conducted on the recent advancements and significant obstacles pertaining to the practical implementation of implantable electrochemical microsensors.

Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information

New sensing and wireless technologies generate massive data. This paper proposes an efficient Bayesian network to evaluate the slope safety using large-quantity field monitoring information with underlying physical mechanisms. A Bayesian network for a slope involving correlated material properties and dozens of observational points is constructed.

Internet based environmental monitoring information system and its application in Yili Prefecture

With the development of Internet technologies, Internet Based Information System (IBIS) arises with more advantages: Firstly, it is convenient for users to use owing to the introduction of Internet technologies. Secondly, it benefits greatly the data dissemination and data sharing based on Internet. The most important but not the last is that we can establish the information service network supported by its technologies and the facilities of information highway. So, it would be significant to design IBIS to realize the data collection, sharing and dissemination on Internet. There are many factors affecting regional environment. So it is not easy to realize the integrated environmental monitoring. Given this, we designed the Internet based environmental monitoring information system. By the virtue of the Internet based environmental monitoring information system, the management and storage of environmental monitoring data would be easier, which lays the foundation to actualize the environmental monitoring efficiently.

Study on Technologies for Information Monitoring and Quick Response of Agricultural Focuses and Significant Events

This article analyzed the importance of information monitoring and quick response on agricultural focuses and significant events, proposed the workflow and technical framework for information monitoring and quick response based on modern information technologies, and explained key technologies during implementation and the functional structure for prototype system of the technical support platform.

Research on information technology of state monitoring and fault prediction for mechatronics system

The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.Based on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring instruments.The technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

Fuzzy Integral Based Information Fusion for Water Quality Monitoring Using Remote Sensing Data

To improve the monitoring precision of lake chlorophyll a (Chl-a), this paper presents a fusion method based on Choquet Fuzzy Integral (CFI) to estimate the Chl-a concentration. A group of BPNN models are designed. The output of multiple BPNN model is fused by the CFI. Meanwhile, to resolve the over-fitting problem caused by a small number of training sets, we design an algorithm that fully considers neighbor sampling information. A classification experiment of the Chl-a concentration of the Taihu Lake is conducted. The result shows that, the proposed approach is superior to the classification using a single neural network classifier, and the CFI fusion method has higher identification accuracy.

Research on the Correlation Between Oil Menitoring and Vibration Monitoring in Information Collecting and Processing Monitoring

Oil monitoring and vibration monitoring are two principal techniques for mechanical fault diagnosis and condition monitoring at present. They monitor the mechanical condition by different approaches, nevertheless, oil and vibration monitoring are related in information collecting and processing. In the same mechanical system, the information obtained from the same information source can be described with the same expression form. The expressions are constituted of a structure matrix, a relative matrix and a system matrix. For oil and vibration monitoring, the information source is correlation and the collection is independent and complementary. And oil monitoring and vibration monitoring have the same process method when they yield their information. This research has provided a reasonable and useful approach to combine oil monitoring and vibration monitoring.

Study on gas monitoring technology based on information fusion

In view of the deficiency of current gas monitoring systems in coal mine roadwayexcavation, a two-level information fusion technology, which adopted the adaptiveweighted algorithm and the BP neural network technology, was applied to gas monitoring.The results show that the adaptive weighted algorithm can realize self-regulation by decreasingthe weight value of the failed sensor automatically, so as to eliminate the effect ofthe failed sensor and ensure the effectiveness and accuracy of the gas monitoring system.The BP neural network can not only effectively predict the gas gush quantity of the excavationroadway, but also accurately calculate the gas concentration in the region whereone or more sensors have failed, so as to provide the basis for judging the safety status ofthe roadway excavation.The experiments prove the superiority and feasibility of the applicationof information fusion in gas monitoring.

Research on Technology Early-Warning System Based on Dynamic Information Monitoring

Relying on the advanced information technologies, such as information monitoring, data mining, natural language processing etc., the dynamic technology early-warning system is constructed. The system consists of technology information automatic retrieval, technology information monitoring, technology threat evaluation, and crisis response and management subsystem, which implements uninterrupted dynamic monitoring, trace and crisis early-warning to the specific technology. Empirical study testifies that the system improves the accuracy, timeliness and reliability of technology early-warning.

A Study of the electronic information monitoring of bruxism

Objective：Bruxism is the term used for teeth grinding or jaw clenching. An electronic monitor of bruxism was developed to evaluate bruxism duration and frequency. Methods： Ten cases were selected in the Department of Prosthodontics of Jiangsu Stomatological Hospital to evaluate the monitor. A stabilization occlusal splint was fabricated for each of the 10 cases. The vertical dimension for each splint was 0.5 nun lower than mandibular postural position. Some sensors had been prearranged at each splint which could transfer the variation of the biting force into electronic signals. The data of sleeping duration, grinding duration and grinding frequency were recorded with this new type of bruxism monitor, which had been specifically invented to study bruxism. Results：The data from 10 bruxism cases were collected and the results were considered reliable. Subjects nocturnal duration parameters did not change significantly from night-to-night. Conclusion：The bmxism monitor can automatically measure and record bruxism data using an occlusal splint. This device is valuable for diagnosis and evaluation of bruxism.

Quality oriented multimode processes monitoring based on a novel hierarchical common and specific structure with different order information

Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In order to handle such multi-mode process,a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode.In addition,both low and high order information are considered in each layer.The common and specific information within each mode can be captured and separated into several subspaces according to the different order information.The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman(TE)benchmark.Compared with previous methods,superiority of the proposed method is validated by the better monitoring results.

L3SN: A Level-Based, Large-Scale, Longevous Sensor Network System for Agriculture Information Monitoring

We developed L3SN, a scalable, longevous, adaptive, and internet accessible wireless sensor network system for agriculture information monitoring, which is meticulously designed to meet the requirement of thousands hectares coverage, years of time monitoring and the adverse environment. The system architecture, the agriculture sensor device, the mesh protocol, and the web-based information processing platform are introduced. We also presented some implementation experience. The mesh protocol (LayerMesh) is highlighted, in which “stair scheduling” and “distributed dynamic load-balancing” are proposed to response the scalability, longevity and adaptivity requirements. We believe the design of L3SN is useful to many other large-scale, longevous applications such as hydrologic monitoring, geological monitoring etc.

A STUDY OF SOIL CONSERVATION MONITORING INFORMATION SYSTEM BASED ON REMOTELY SENSED DATA FOR A CATCHMENT ON THE LOESS PLATEAU

The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.

Oil monitoring methods based on information theory

To evaluate the wear condition of machines accurately,oil spectrographic entropy,mutual information and ICA analysis methods based on information theory are presented. A full-scale diagnosis utilizing all channels of spectrographic analysis can be obtained. By measuring the complexity and correlativity,the characteristics of wear condition of machines can be shown clearly. The diagnostic quality is improved. The analysis processes of these monitoring methods are given through the explanation of examples. The availability of these methods is validated and further research fields are demonstrated.

Monitoring Information 3D Visualization for Super-Filling Loess Project

The construction of high-filled loess project has some engineering and technical challenges, such as excavation of earth and backfilling of earth are both large, complex construction environment, variety of influence factors. According to this situation, this paper presents a dynamic 3D visualization method for high-filled project based on volume rendering. Through comparative analysis and visual analysis, realized at different times of the Loess fill internal detection data visualization and analysis presented. The results show that this visualization method can directly and accurately display the construction process, help decision makers master construction information and process.

CONDITION MONITOR OF DEEP-HOLE DRILLING BASED ON MULTI-SENSOR INFORMATION FUSION

A condition monitoring method of deep-hole drilling based on multi-sensor information fusion is discussed. The signal of vibration and cutting force are collected when the condition of deep-hole drilling on stainless steel 0Cr17Ni4Cu4Nb is normal or abnormal. Four eigenvectors are extracted on time-domain and frequency-domain analysis of the signals. Then the four eigenvectors are combined and sent to neural networks to dispose. The fusion results indicate that multi-sensor information fusion is superior to single-sensor information, and that cutting force signal can reflect the condition of cutting tool better than vibration signal.

A Monitoring Method for Transmission Tower Foots Displacement Based on Wind-Induced Vibration Response

The displacement of transmission tower feet can seriously affect the safe operation of the tower,and the accuracy of structural health monitoring methods is limited at the present stage.The application of deep learning method provides new ideas for structural health monitoring of towers,but the current amount of tower vibration fault data is restricted to provide adequate training data for Deep Learning(DL).In this paper,we propose a DT-DL based tower foot displacement monitoring method,which firstly simulates the wind-induced vibration response data of the tower under each fault condition by finite element method.Then the vibration signal visualization and Data Transfer(DT)are used to add tower fault data samples to solve the problem of insufficient actual data quantity.Subsequently,the dynamic response test is carried out under different tower fault states,and the tower fault monitoring is carried out by the DL method.Finally,the proposed method is compared with the traditional online monitoring method,and it is found that this method can significantly improve the rate of convergence and recognition accuracy in the recognition process.The results show that the method can effectively identify the tower foot displacement state,which can greatly reduce the accidents that occurred due to the tower foot displacement.

Doppler Radar Fault Judgment System and Remote Monitoring Platform

The Doppler weather radar fault judging system and remote monitoring platform were introduced.Through the real-time scanning of radar alarm information coding,the platform can realize dynamic monitoring and real-time alarm of Doppler radar equipment components,so as to improve the reliability of equipment operation,and truly realize"unattended"remote monitoring.

基于多尺度卷积与Informer混合模型的非侵入式负荷监测方法

针对现有非侵入式负荷监测方法存在的负荷分解准确率低、模型泛化性能差的问题,提出一种多尺度卷积与Informer网络相结合的非侵入式负荷监测方法。采用数据分段优化方法对功率信号进行分段,利用多尺度卷积核获取不同时间尺度的特征序列以及自适应提取多维度功率特征,从而形成特征矩阵;基于Informer网络中的概率稀疏自注意力机制在高维空间中充分捕获特性序列的长期依赖关系,从而提高预测准确率;利用分解值修正方法消除功率分解值中的“虚假”激活状态,以进一步提高分解精度。算例结果验证了所提方法的可行性。