Establishment of Monitoring and Assessment Index System of Land Degradation of Farmland Ecosystems at Small-scale

The research established land degradation monitoring and assessment in- dex system of farmland ecosystem under influence of human activities, including farming system, measures, mulch residuals, fertilizer pollutions, pesticide pollution, irrigation method, salt content of soils, engineering measures of discharging alkali, agricultural protection forests and poverty. The indices of the system are accessible, and convenient for operation, which is suitable for land managers self-monitoring, re- ducing irrational farming activities, improving farmland productivity and preventing farmland degradation.

Monitoring the Sequential Cropping Index of Arable Land in Zhejiang Province of China Using MODIS-NDVI

The sequential cropping index of arable land is important agricultural information. The aim of this article is to monitor and analyze the parameter, and offer reference for agricultural production. The cropping index of arable land in Zhejiang Province, China from 2001 to 2004 was calculated using the second order difference based MODIS （moderate resolution imagine spectroradimeter） vegetation data from NASA （National Aeronautic and Space Administration） in America and the land use map with a scale of 1：25 000. It was found that the peak of the time series of the NDVI curve indicated that the ground biomass of crops reached the maximum, and fluctuated with the crops growing processes such as sowing, seeding, heading, ripeness, and harvesting within one year. Thus, the sequential cropping index was defined as the number of peaks of the time series of the NDVI curve. The sequential cropping index of all cities in Zhejiang Province, China was worked out. It is seen from the spatial distribution that the cropping index in the southwest Zhejiang Province is larger than that in the northeast. As for the temporal distribution, the sequential cropping index decreased from 2001 to 2003, whereas it increased slightly from 2003 to 2004. However, the index of arable land was relatively low, as far as the geographic position and climatic resource were concerned, and the potential of the sequential cropping index was great.

An improved temperature vegetation dryness index(iTVDI) and its applicability to drought monitoring

Using Moderate Resolution Imaging Spectroradiometer(MODIS) data from the dry season during 2010–2012 over the whole Yunnan Province, an improved temperature vegetation dryness index(iTVDI), in which a parabolic dry-edge equation replaces the traditional linear dry-edge equation, was developed, to reveal the regional drought regime in the dry season. After calculating the correlation coefficient, root-mean-square error, and standard deviation between the iTVDI and observed topsoil moisture at 10 and 20 cm for seven sites, the effectiveness of the new index in depicting topsoil moisture conditions was verified. The drought area indicated by iTVDI mapping was then compared with the drought-affected area reported by the local government. The results indicated that the iTVDI can monitor drought more accurately than the traditional TVDI during the dry season in Yunnan Province. Using iTVDI facilitates drought warning and irrigation scheduling, and the expectation is that this new index can be broadly applied in other areas.

Bispectral index monitoring as an adjunct to nurse-administered combined sedation during endoscopic retrograde cholangiopancreatography

AIM:To determine whether bispectral index (BIS) monitoring is useful for propofol administration for deep sedation during endoscopic retrograde cholangiopancreatography (ERCP). METHODS:Fifty-nine consecutive patients with a variety of reasons for ERCP who underwent the procedure at least twice between 1 July 2010 and 30 November 2010. This was a randomized cross-over study, in which each patient underwent ERCP twice, once with BIS monitoring and once with control monitoring. Whether BIS monitoring was done during the first or second ERCP procedure was random. Patients were intermittently administered a mixed regimen including midazolam, pethidine, and propofol by trained nurses. The nurse used a routine practice to monitor sedation using the Modified Observer's Assessment of Alertness/Sedation (MOAA/S) scale or the BIS monitoring. The total amount of midazolam and propofol used and serious side effects were compared between the BIS and control groups. RESULTS:The mean total propofol dose administered was 53.1 ± 32.2 mg in the BIS group and 54.9 ± 30.8 mg in the control group (P = 0.673). The individual propofol dose received per minute during the ERCP procedure was 2.90 ± 1.83 mg/min in the BIS group and 3.44 ± 2.04 mg in the control group (P = 0.103). The median value of the MOAA/S score during the maintenance phase of sedation was comparable for the two groups. The mean BIS values throughout the procedure (from insertion to removal of the endoscope) were 76.5 ± 8.7 for all 59 patients in using the BIS monitor. No significant differences in the frequency of < 80% oxygen saturation, hypotension (< 80 mmHg), or bradycardia (< 50 beats/min) were observed between the two study groups. Four cases of poor cooperation occurred, in which the procedure should be stopped to add the propofol dose. After adding the propofol, the procedure could be conducted successfully (one case in the BIS group, three cases in the control group). The endoscopist rated patient sedation as excellent for all patients in both groups. All patients in both groups rated their level of satisfaction as high (no discomfort). During the post-procedural follow-up in the recovery area, no cases of clinically significant hypoxic episodes were recorded in either group. No other postoperative side effects related to sedation were observed in either group. CONCLUSION:BIS monitoring trend to slighlty reduce the mean propofol dose. Nurse-administered propofol sedation under the supervision of a gastroenterologist may be considered an alternative under anesthesiologist.

Deformation warning index for reinforced concrete dam based on structural health monitoring data and numerical simulation

The material mechanical parameters of the dam body and foundation will change when a dam is reinforced during the aging process.This causes significant changes in the structural state of the project and makes it difficult to ensure its structural safety.In this study,a new deformation warning index for reinforced concrete dams was developed according to the prototype monitoring data,statistical models,three-dimensional finite element model(FEM)numerical simulation,and the critical conditions of the dam structure.A statistical model was established to separate the water pressure component.Then,a three-dimensional FEM of the reinforced concrete dam was constructed to simulate the water pressure component.Furthermore,the deformation components that affected the mechanical parameters of the dam under the same amount of reservoir water level change were separated and quantified accurately.In addition,the method for inversion of comprehensive mechanical parameters after dam reinforcement was used.The influence mechanisms of the deformation behavior of concrete dams under the reservoir water level and temperature changes were investigated.A new deformation warning index was developed by combining the forward-simulated critical water pressure component and temperature component in the period of extreme temperature decrease with the aging component separated by the statistical model.The new deformation warning index considers the structural state of the dam before and after reinforcement and links the structural strength criterion and the deformation evolution mechanisms.It provides a theoretical foundation and decision support for long-term service and operation management of reinforced dams.

Research on the Seepage Safety Monitoring Indexes of the High Core Rockfill Dam

The study on developing the reasonable safety monitoring indexes plays a most importantly role in the health monitoring of high core rockfill dams. However, researches on this topic are relatively scarce both at home and abroad. In this paper, the characteristics and failure modes of seepage in high core rockfill dam are analyzed firstly. Then, a safety monitoring index based on seepage quantity, which reflects the overall seepage behavior, is developed, using the real-time monitoring data and its safety monitoring model. Moreover, another safety monitoring index based on seepage gradient, reflecting the local seepage behavior, is proposed, combining the spatial layout of osmo- meters and local failure mechanisms of core wall. Additionally, one more safety monitoring index based on permeability coefficient, which considers the overall and local seepage behaviors, is developed, on the basis of establishing the finite element analysis model and real-time seepage coefficient inversion analysis model of high core rockfill dam. A case study on these indexes of Nuozhadu high core rockfill dam is developed, which improves the reliability of seepage safety evaluation of the dam.

A hybrid specific index-related process monitoring strategy based on a novel two-step information extraction method

A two-step information extraction method is presented to capture the specific index-related information more accurately.In the first step,the overall process variables are separated into two sets based on Pearson correlation coefficient.One is process variables strongly related to the specific index and the other is process variables weakly related to the specific index.Through performing principal component analysis(PCA)on the two sets,the directions of latent variables have changed.In other words,the correlation between latent variables in the set with strong correlation and the specific index may become weaker.Meanwhile,the correlation between latent variables in the set with weak correlation and the specific index may be enhanced.In the second step,the two sets are further divided into a subset strongly related to the specific index and a subset weakly related to the specific index from the perspective of latent variables using Pearson correlation coefficient,respectively.Two subsets strongly related to the specific index form a new subspace related to the specific index.Then,a hybrid monitoring strategy based on predicted specific index using partial least squares(PLS)and T2statistics-based method is proposed for specific index-related process monitoring using comprehensive information.Predicted specific index reflects real-time information for the specific index.T2statistics are used to monitor specific index-related information.Finally,the proposed method is applied to Tennessee Eastman(TE).The results indicate the effectiveness of the proposed method.

Dynamic monitoring of serum liver function indexes in patients with COVID-19

BACKGROUND Some patients with the novel 2019 coronavirus disease(COVID-19)display elevated liver enzymes.Some antiviral drugs that can be used against COVID-19 are associated with a risk of hepatotoxicity.AIM To analyze the clinical significance of the dynamic monitoring of the liver function of patients with COVID-19.METHODS This was a retrospective study of patients diagnosed with COVID-19 in January and February 2020 at the Department of Infection,Shantou Central Hospital.The exclusion criteria for all patients were:(1)History of chronic liver disease;(2)History of kidney disease;(3)History of coronary heart disease;(4)History of malignancy;or(5)History of diabetes.The serum levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),γ-glutamyltransferase,and total bilirubin of patients with COVID-19 were measured on days 1,3,7 and 14 after admission,and compared to non-COVID-19 patents.RESULTS Twelve patients with COVID-19(seven men and five women)and twelve controls(eight men and four women)were included.There were one,two,and nine patients with severe,mild,and moderate COVID-19,respectively.There were no differences in age and sex between the two groups(both P>0.05).No significant differences were found in albumin,ALT,AST,γ-glutamyltransferase,or total bilirubin between the controls and the patients with COVID-19 on day 1 of hospitalization(all P>0.05).Serum albumin showed a decreasing trend from days 0 to 7 of hospitalization,reaching the lowest level on day 7.Total bilirubin was higher on day 3 than on day 7.ALT,AST,andγ-glutamyltransferase did not change significantly over time.The severe patient was observed to have ALT levels of 67 U/L and AST levels of 75 U/L on day 7,ALT of 71 U/L and AST of 35 U/L on day 14,and ALT of 210 U/L and AST of 123 U/L on day 21.CONCLUSION Changes in serum liver function indicators are not obvious in the early stage of COVID-19,but clinically significant changes might be observed in severe COVID-19.

The Design and Study on CEO Financial Monitoring Index System Based on Stakeholder Theory

This paper summarizes the current financial monitoring theory and the design of index system, analyzes the possible monitoring indexes relative to stakeholders to achieve their own interests, and then categorizes these indexes into five aspects： the finance, the customer, the process, the employee and the society. After a deep analysis of these indexes, we use the Analytic Hierarchy Process to conform the weight of every index, subsequently build up an effective financial monitoring index system.

A hybrid algorithm for reengineering the refractive index profile of inhomogeneous coatings from optical in-situ broadband monitoring data

Reengineering the refractive index profile of inhomogeneous coatings is a troublesome task. Multiplicity of solutions may significantly reduced by providing additional information. For this reason an in-situ broadband monitoring system was developed to measure the transmittance of the growing film directly at the rotating substrate. For characterization of these coatings, a new model was developed, which significantly reduces the number of parameters. The refractive index profile may be described by a proper number of equally spaced volume fraction values using the Bruggeman effective media approach. A good initial approximation of the refractive index profile can be generated based on deposition rates for both materials recorded with quartz crystal monitor during manufacturing. During the optimization process, a second order minimization algorithm was used to vary the refractive index profile of the whole coating and film thickness of the intermediate stages. Finally, a significantly improved accuracy of the modelled transmittance was achieved.

Study on the Evaluation and Monitoring over In-depth Development of Ecotourism

Qualitative indexes contained in the product standards of in-depth ecotourism development are summarized as:carrying capacity control,protection of natural environment,participation of community residents,education about environment protection,enhancing standard management,clean production,green training,and overall monitoring.Based on the model of grey system theory,the improvement of in-depth ecotourism development was predicted,the construction,evaluation and monitoring model for the in-depth development of ecotourism was established,and finally the index system for the evaluation was set as the General Layer(A),the System Layer(B),the Status Layer(C),and the Variable Layer(D).

Multimode Process Monitoring Based on Fuzzy C-means in Locality Preserving Projection Subspace

For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring strategy based on fuzzy C-means. The high dimensional historical data are transferred to a low dimensional subspace spanned by locality preserving projection. Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operational mode. The distance statistics of each cluster are integrated though the membership values into a novel BID (Bayesian inference distance) monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman benchmark process.

A remote sensing monitoring method for alpine grasslands desertification in the eastern Qinghai–Tibetan Plateau

Alpine grassland is the typical vegetation in the eastern Qinghai–Tibetan Plateau,which has important ecological service functions,and also supports the development of alpine stock farming.In recent years,under both the natural and human disturbance,alpine grasslands in this area have appeared to different degrees of desertification.A diagnosis of the desertification degree serves as the basis for grassland ecological restoration.This study constructs a comprehensive index based on remote sensing called alpine grassland desertification index(AGDI)to monitor the areas and degree of desertification.The most relevant indicators of desertification,namely,vegetation fraction,aboveground biomass,soil moisture,and land surface temperature,were selected to establish AGDI.The geographical detector is used to reselect and assess these indicators.The results show that the overall verification accuracy of AGDI is 82.05%.In particular,the accuracy of identifying severe desertification is the highest.Our study confirms that the desertification of alpine grasslands in the eastern Qinghai–Tibetan Plateau is characterized by fragmentation.Thus,Landsat-8 OLI data with a spatial resolution of 30 m is more suitable than MODIS data for alpine grasslands desertification monitoring.The research results can provide a methodological reference for monitoring desertification of alpine grasslands and other grassland regions in the world.

Development of Wi-Fi Based Home Energy Monitoring System for Green Internet of Things

Green Internet of things （loT） has been heralded as the ＂next big thing＂ waiting to be realized in energy-efficient ubiquitous computing. Green IoT revolves around increased machine-to-machine communications and encompasses energy-efficient wireless embedded sensors and actuators that assist in monitoring and controlling home appliances. Energy efficiency in home applications can be achieved by better monitoring of the specific energy consumption by the appliances. There are many wireless standards that can be adopted for the design of such embedded devices in loT. These communication technologies cater to different requirements and are classified as the short-range and long-range ones. To select the best communication method, this paper surveys various loT communication technologies and discusses the advantages and disadvantages to develop an energy monitoring system. An IoT device based on the Wi-Fi technology system is developed and tested for usage in the home energy monitoring environment. The performance of this system is then evaluated by the measurement of power consumption metrics. In the efficient deep-sleep mode, the system saves up to 0.3 W per cycle with an average power dissipation of less than 0.1 W/s.

Urban Growth Monitoring using Remote Sensing and Geo-Informatics: Case Study of Gandhinagar, Gujarat State (India)

The Gandhinagar town has undergone unprecedented urban growth after assuming the status of a capital of Gujarat state, India in 1971. The Gandhinagar city lies on the western bank of river Sabarmati and city is also known as the “Tree capital of India” because of greenery with 54% green cover. The urban sprawl in Gandhinagar town was analyzed using multi-temporal Landsat TM data from 1981 to 2015. Spectral indices namely Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI) and Built-up Index (BUI) were generated from the Landsat TM bands covering visible Red (R), Near Infrared (NIR) and Short Wave Infrared (SWIR) wavelength regions. Spectral variations in built-up, open spaces, urban vegetation and water areas were studied by generating two-dimensional spectral plots of NDBI and BUI. The spectral response of built up areas like Urban-dense and urban-sparse classes are quite distinct from other cover types like open spaces, urban vegetation and water. The results indicate that the normalized difference built-up index (NDBI) and Built-up Index (BUI) were very useful for mapping urban built-up areas in Gandhinagar town using Landsat Thematic Mapper (TM) data. The built-up area in Gandhinagar increased from 1100.1 ha during Jan 1989 to 1907.3 ha during Jan 2015 which indicates about 73 per cent increase in the built-up area during the period of 26 years. The urban vegetation which includes parks and gardens in the city has also shown increasing trend during the period of 1989 to 2015. However, the area under open spaces has decreased as the development of built-up area has increased as per development plan of the Gandhinagar town.

A Multi-scale Perspective on Drought Monitoring and Assessment for the Pearl River Basin

It is accepted that climate change has a great impact on water cycle and regional water balance,and thus it would change the formation and evolution conditions of drought in some degree. By using data at 42 meteorological stations of the Pearl River Basin,the Standardized Precipitation Evapotranspiration Index（ SPEI） at different time scales was calculated. Based on the SPEIs of 1- 12 months,a newly proposed index for drought--Joint Drought Index（ JDI） was established under the multi-scale perspective through the copula function. Since short-term SPEIs are essential for the identification of emerging droughts and long-term SPEIs are useful for prolonged droughts,the JDI,which integrates all the usefull informations of drought and can thus form an overall judgement,is superior than the single SPEI in drought monitoring. By the forcast evaluation system and comparison to the actual drought,the accuracy and effectiveness of JDI in drought monitoring were verified. In general,JDI can be used as a new ideal index for future drought monitoring and assessment. Additionly,we analyzed the spatio-temperal characteristics of drought across the Pearl River Basin using the JDI. The results indicate that mild drought was the most frequent drought occurred in the Pearl River Basin over the past half century,and moderate drought followed. Severe drought and extreme drought would appear occasionally while exceptional drought could hardly be found. A dry-wet-dry interdecadal variation pattern had been found from the 1960 s to the 2000 s. Since the 21 stcentury,an obvious trend toward drought can be observed in the whole basin,especially in the Xijiang subbasin,which,consequently,poses an increasing challenge for the water resource planning and management.

A novel multimode process monitoring method integrating LCGMM with modified LFDA

Complex processes often work with multiple operation regions, it is critical to develop effective monitoring approaches to ensure the safety of chemical processes. In this work, a discriminant local consistency Gaussian mixture model(DLCGMM) for multimode process monitoring is proposed for multimode process monitoring by integrating LCGMM with modified local Fisher discriminant analysis(MLFDA). Different from Fisher discriminant analysis(FDA) that aims to discover the global optimal discriminant directions, MLFDA is capable of uncovering multimodality and local structure of the data by exploiting the posterior probabilities of observations within clusters calculated from the results of LCGMM. This may enable MLFDA to capture more meaningful discriminant information hidden in the high-dimensional multimode observations comparing to FDA. Contrary to most existing multimode process monitoring approaches, DLCGMM performs LCGMM and MFLDA iteratively, and the optimal subspaces with multi-Gaussianity and the optimal discriminant projection vectors are simultaneously achieved in the framework of supervised and unsupervised learning. Furthermore, monitoring statistics are established on each cluster that represents a specific operation condition and two global Bayesian inference-based fault monitoring indexes are established by combining with all the monitoring results of all clusters. The efficiency and effectiveness of the proposed method are evaluated through UCI datasets, a simulated multimode model and the Tennessee Eastman benchmark process.

Overview of Grassland Degradation Research Based on Remote Sensing Monitoring

In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal characteristics and driving factors of grassland degradation and in order to deeply understand the research status of grassland degradation monitoring methods and evaluation index system, this paper mainly investigates the research progress of grassland degradation remote sensing monitoring methods and evaluation indicators. Furthermore, this paper summarizes the more commonly used remote sensing monitoring methods and evaluation methods, analyzes the problems existing in the evaluation indicators of grassland degradation, and points out the research direction of the evaluation indicators in the future. Finally, a comprehensive remote sensing monitoring and evaluation system are established in this paper. Research findings: because of the variety of grassland degradation types and the emergence of remote sensing monitoring and evaluation methods, establishing a comprehensive remote sensing monitoring and evaluation system to classify and summarize the research methods of different grassland degradation can lay a foundation for the development of grassland degradation evaluation and monitoring in the future and provide research ideas. It is the trend of grassland degradation remote sensing research in the future.

Analysis on the noises from continuously monitoring GPS sites

In this paper, we analyze the time series of site coordinates of 27 continuously monitoring GPS sites covered by the Crustal Movement Observation Network of China over the whole country. The data are obtained in the period from the beginning of the observation to the November of 2005. On the basis of data processing, we analyze the power spectrum density of coordinate component noise at each site and calculate the spectral indexes manifesting the noise property of each component. The spectral indexes indicate that for most sites, the noise of time series of each coordinate component can be addressed by the model of white noise ＋ flicker noise; and for a small amount of sites, it can be described by the model of white noise ＋ flicker noise ＋ random walk noise. We also quantitatively estimate each noise component in the model by using the criterion of maximum likelihood estimation. The result shows that the white noise in the time series of GPS site coordinates does not constitute the main part of noise. Therefore, the error estimation of site movement parameters is usually too small, or too optimistic if we consider the white noise only. Correspondingly, if this factor is not fully considered in explaining these movement parameters, it might mislead the readers.

Vision-Based Learning Status Monitoring on Color and Depth Live Facial Videos

This study analyzes live facial videos for recognizing nonverbal learning-related facial movements and head poses to discover the learning status of students. First, color and depth facial videos captured by a Kinect are analyzed for face tracking using a three-dimensional （3D） active appearance model （AAM）. Second, the facial feature vector sequences are used to train hidden Markov models （HMMs） to recognize seven learning-related facial movements （smile, blink, frown, shake, nod, yawn, and talk）. The final stage involves the analysis of the facial movement vector sequence to evaluate three status scores （understanding, interaction, and consciousness）, each represents the learning status of a student and is helpful to both teachers and students for improving teaching and learning. Five teaching activities demonstrate that the proposed learning status analysis system promotes the interpersonal communication between teachers and students.