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Journal articles on the topic 'Trend monitoring systém'

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Published: 28 June 2021
Last updated: 1 February 2022

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1

Svoboda, Jan. "Evaluation of the air quality at the two monitoring sities in Brno related to the synoptic situation." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 53, no. 4 (2005): 139–44. http://dx.doi.org/10.11118/actaun200553040139.

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The main objective of this work was to evaluate influnce of transportation on the air quality using IAQ (index of air quality). The data from one of the AIM station were evaluated. The trend in air quality development in years 1996–2003 was described. In days with adverse IAQ values the probable cause of the phenomenon was determined. It is obvious that adverse IAQ values were recorded during these synoptic situations: centre anticyklone, wedge of high pressure, weak pressure field and warm sector of front systém. The most frequent was the centre anticyklone synoptic situation which is typical (mainly during winter) by air temperature inversion.
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Hegazy, Ibrahim Rizk, and Mansour Rifaat Helmi. "Spatial monitoring of urban growth of Mansoura City, Egypt." International Journal of Low-Carbon Technologies 15, no. 4 (May 3, 2020): 536–42. http://dx.doi.org/10.1093/ijlct/ctaa021.

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Abstract Urbanization is a global trend determined primarily by excessive population growth, particularly in the developing countries such as Egypt. The configuration and boundaries of urbanization and their model can be observed at a distance of space and time. In this research, geographic information system and remote sensing were used to analyze urbanization and trends in the past 30 years of Mansoura City, which is one of the largest medium-sized cities in Egypt. Four Landsat images, obtained in 1985, 1995, 2005 and 2015, were adjusted and compared using the ArcGIS software. The classified images were analyzed to determine urbanization trends in Mansoura city during the three periods 1985–1995, 1995–2005 and 2005–2015. The results of the change disclosure showed areas and trends in urbanization. The urban area has grown by approximately five times over 30 years. The results showed that the eastern direction was predominant during the periods (1985–1995) and (1995–2005) with 53 and 53% of the city total growth, respectively. During the period (2005–2015), the northern trend was dominant with 38% of the city total growth. This research promotes future urban planning strategies by evaluating temporal spatial transformation and urbanization trends.
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Paudel, Bhanu, and Lori M. Brown. "Temporal Changes in Delaware Waters Using Long-Term (1967–2019) Water Temperature Data." Data 6, no. 8 (July 24, 2021): 79. http://dx.doi.org/10.3390/data6080079.

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The present article provides long-term (1967–2019) water temperature data collected from Delaware water quality monitoring sites. In Delaware, there are approximately 140 water quality monitoring sites in Piedmont, Delaware Bay, Chesapeake Bay, and Inland Bay drainage basins. Long-term quarterly (i.e., four times a year: Q1—January–February–March; Q2—April–May–June; Q3—July–August–September; Q4—October–November–December) water temperature data were calculated from each water quality monitoring sites’ continuous monthly data. This study focuses on water quality monitoring sites with significant (p-value identifying linear regression model) increasing or decreasing trends of water temperature. Quarterly water temperature data, statistical analysis, and maps showing increasing and decreasing trend from water quality monitoring sites with significant trends are presented in this article.
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Chudzikiewicz, Andrzej, Anna Stelmach, and Wojciech Wawrzyński. "Selection of signal registration points in the monitoring process and diagnosing the condition of the rail vehicle." Journal of Civil Engineering and Transport 1, no. 1 (December 31, 2019): 7–13. http://dx.doi.org/10.24136/tren.2019.001.

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The article discusses the process of selecting points on a rail vehicle in which sensors recording signals will be located, with a view to their later use in the process of monitoring the condition of the vehicle and in particular elements of the first and second degree suspension system. The number of such points and their location is significant considering the complexity of the monitoring system and thus the costs of its construction and subsequent operation, as well as the possibility of using registered signals in the process of diagnosing the technical condition of the vehicle, bearing in mind the functioning of such a system in on-line mode.
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Pu, Fangling, Zhaozhuo Xu, Hongyu Chen, Xin Xu, and Nengcheng Chen. "A DLM-LSTM Framework for North-South Land Deformation Trend Analysis from Low-Cost GPS Sensor Time Series." Journal of Sensors 2018 (June 6, 2018): 1–11. http://dx.doi.org/10.1155/2018/3054295.

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Landslides endanger regular industrial production and human safety. Displacement trend analysis gives us an explicit way to observe and forecast landslides. Although satellite-borne remote sensing methods such as synthetic aperture radar have gradually replaced manual measurement in detecting deformation trends, they fail to observe displacement in a north-south direction. Wireless low-cost GPS sensors have been developed to assist remote sensing methods in north-south deformation monitoring because of their high temporal resolution and wide usage. In our paper, a DLM-LSTM framework is developed to extract and predict north-south land deformation trends from meter accuracy GPS receivers. A dynamic linear model is introduced to model the relation between measurement and the state vector, including the trend, periodic variation, and autoregressive factors in a discontinuous low-cost latitude time series. The deformation trend with submeter-level accuracy is extracted by a Kalman filter and smoother. With validated input as in previous work, the power of an LSTM network is also shown in its ability to predict deformation trends in submeter-level accuracy. A submeter-level deformation trend is detected from wireless low-cost GPS sensors with meter-level navigation error. The framework will have broad application prospects in geological disaster monitoring.
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Łukasik, Zbigniew, and Anton Ushakov. "Concept «Smart freight wagon»." Journal of Civil Engineering and Transport 2, no. 1 (March 31, 2020): 19–33. http://dx.doi.org/10.24136/tren.2020.002.

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This article discusses the prospects for the implementation of the concept «Smart freight wagon» on the Russian railways. The article discusses a concept for developing in Russia a system for monitoring the operating conditions of rolling stock and transmitting telemetry data on the state of infrastructure under the design names «Smart freight wagon. Also, authors offer the author’s concept of this system improvements based on openHAB smart system model which helps to make the modular system in order to increase fault tolerance and flexibly adapt to the needs of specific customers.
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Lee, Hyun-Woo. "Technical Trend Analysis of a Fault Monitoring System." Journal of Engineering Geology 21, no. 1 (March 31, 2011): 87–95. http://dx.doi.org/10.9720/kseg.2011.21.1.087.

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8

Li, Wen Xing, and Meng Jia. "Vibration Monitoring System Design." Advanced Materials Research 1027 (October 2014): 325–30. http://dx.doi.org/10.4028/www.scientific.net/amr.1027.325.

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Along with the computer software technology, the virtual instrument is gradually become the development direction of the test area. The realizing vibration test which is analyzed by adopting the virtual instrument has become the development trend of vibration test. It firstly introduces relevant simulation technology theory, the principle of fault diagnosis, the significance and the development present situation. Then according to the research for the development current situation of condition monitoring and fault diagnosis at home and abroad, it puts forward the vibration test analysis system composed the necessary sensors, signal disposal device and data acquisition card. At last it uses labwindows software produced in NI to do the development platform.
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9

Chang, Hui-Kuo, Hsing-Chia Kuo, and Yen-Zen Wang. "Novel Grey Model for Diesel Engine Oil Monitoring." Journal of Ship Research 50, no. 01 (March 1, 2006): 31–37. http://dx.doi.org/10.5957/jsr.2006.50.1.31.

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Electronic sensors and data processing systems are increasingly integrated with mechanical systems for continuous condition monitoring and early warning of pending failure. Various predictive algorithms have been applied to sensor data trends. Traditional grey algorithms have been highly useful for data trend prediction but suffer from serious overshoot at inflection points when applied to fluctuating data curves, that is, curves that cannot be accurately represented by a single grey exponential equation. This paper therefore presents an improved grey model (GM), a two-section residual grey model (2S-RGM), and demonstrates 2S-RGM by applying it to data trends in a marine engine oil quality monitoring system. 2S-RGM constantly evaluates data trends and seeks inflection points at which the curve is broken into separate sections, each being treated by an independent GM. 2S-RGM is tested using two sets of published marine diesel engine oil data, one ferrographic and one spectroscopic. Predictive results of 2S-RGM are compared to results of the same data sets applied to six other well-known predictive methodologies. It is demonstrated that 2S-RGM is significantly more accurate, with the additional benefit of avoiding the setup costs of earlier artificial-intelligence-based GM improvements.
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Shi, Xiao Yan, Hong Bao Ye, Dong Li, and Zhi Fu Xu. "Development and Trend of Intelligent Monitoring System for Greenhouse." Advanced Materials Research 1030-1032 (September 2014): 1475–79. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1475.

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Intelligent greenhouse cultivation and management is one of the most important technologies for continuous production of agricultural products. This article deals with the development history, status, key technologies and trend of greenhouse intelligent monitoring system£¬ makes analysis on the existent problems and developing trend so as to provide reference for the growth of China's facility agriculture intellectualization£®
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Tada, Shigeo. "Recent Trend of Remote Monitoring Technology, Cathodic Protection System." Zairyo-to-Kankyo 49, no. 9 (2000): 537–40. http://dx.doi.org/10.3323/jcorr1991.49.537.

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12

Mitratza, Marianna, Jan W. P. F. Kardaun, and Anton E. Kunst. "How large should a cause of death be in order to be included in mortality trend analysis? Deriving a cut-off point from retrospective trend analyses in 21 European countries." BMJ Open 10, no. 1 (January 2020): e031702. http://dx.doi.org/10.1136/bmjopen-2019-031702.

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ObjectivesThe International Classification of Diseases (ICD-10) distinguishes a large number of causes of death (CODs) that could each be studied individually when monitoring time-trends. We aimed to develop recommendations for using the size of CODs as a criterion for their inclusion in long-term trend analysis.DesignRetrospective trend analysis.Setting21 European countries of the WHO Mortality Database.ParticipantsDeaths from CODs (3-position ICD-10 codes) with ≥5 average annual deaths in a 15-year period between 2000 and 2016.Primary and secondary outcome measuresFitting polynomial regression models, we examined for each COD in each country whether or not changes over time were statistically significant (with α=0.05) and we assessed correlates of this outcome. Applying receiver operating characteristicROC curve diagnostics, we derived COD size thresholds for selecting CODs for trends analysis.ResultsAcross all countries, 64.0% of CODs had significant long-term trends. The odds of having a significant trend increased by 18% for every 10% increase of COD size. The independent effect of country was negligible. As compared to circulatory system diseases, the probability of a significant trend was lower for neoplasms and digestive system diseases, and higher for infectious diseases, mental diseases and signs-and-symptoms. We derived a general threshold of around 30 (range: 28–33) annual deaths for inclusion of a COD in trend analysis. The relevant threshold for neoplasms was around 65 (range: 61–70) and for infectious diseases was 20 (range: 19–20).ConclusionsThe likelihood that long-term trends are detected with statistical significance is strongly related to COD size and varies between ICD-10 chapters, but has no independent relation to country. We recommend a general size criterion of 30 annual deaths to select CODs for long-term mortality-trends analysis in European countries.
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13

Zagorowska, Marta, Arne-Marius Ditlefsen, Nina F. Thornhill, and Charlotte Skourup. "Turbomachinery Degradation Monitoring Using Adaptive Trend Analysis." IFAC-PapersOnLine 52, no. 1 (2019): 679–84. http://dx.doi.org/10.1016/j.ifacol.2019.06.141.

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Xiao, Chun, Xue Ping Hao, Li Qiao Li, Wei Li, and Xun Gang Liu. "Research on Data Prediction Methods of Structural Health Monitoring System." Applied Mechanics and Materials 256-259 (December 2012): 1022–28. http://dx.doi.org/10.4028/www.scientific.net/amm.256-259.1022.

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Trend prediction is virtually modeling process for dynamic data. The key to prediction is to establish a model in accordance with actual status, then use the model to predict the trend of object, and infer its behavior in future. Two prediction methods are researched to predict the trend on the observed points of the structure in this paper, which are regression prediction method and grey prediction method. The continuous time strain value of a measured point on Tianxingzhou Yangtze River Bridge is used as data sample for researching. The method of regression analysis is applied for predicting the trend of short-term data, and the method of grey model prediction for predicting long-term data. Regression prediction can assess the health status of the structure and obtain the alarm information effectively by comparing the actual monitoring data with the range of forecast interval. Grey prediction method has great advantages when dealing with poor information. By engineering example this study shows the pros and cons of these two methods, and proves that the method of grey model prediction is more suitable of predicting the trend of object in the structural health monitoring system.
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Sun, Cai Min, Jun Xu, and Jun Wei Yang. "Study on Application of Slopes Stability in Opencast Mines Based on GPS Technology." Applied Mechanics and Materials 501-504 (January 2014): 238–43. http://dx.doi.org/10.4028/www.scientific.net/amm.501-504.238.

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Using GPS technique can monitor geological deformation. Concerning field geological conditions in sinking area, a GPS monitoring network is build up on an open-pit side slope in Qianshui iron mine. By implementing the dynamic monitoring system at regular intervals, the side slope deformation message and its deforming trend can be catch up in time. This paper explains the following procedures for successful completion of a GPS geological deformation project: GPS slope monitoring network design, observation implementing, post-processing of data, and achievements analysis. The results showed that the slope deformation information and development trends can be instantly captured and provide important basic data for Side-slope Stability analysis and reinforcement by aid of GPS technology.
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Gupta, Sonam, Lipika Goel, and Abhay Kumar Agarwal. "A Novel Framework of Health Monitoring Systems." International Journal of Big Data and Analytics in Healthcare 6, no. 1 (January 2021): 1–14. http://dx.doi.org/10.4018/ijbdah.20210101.oa1.

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IoT plays an important role in the healthcare domain for improving the quality of patient care. To analyze the patients' healthcare data, a real-time health-monitoring system is required. The proposed framework in this work is cable of such monitoring and sending alerts on critical circumstances. In this framework, the use of IoT devices makes it possible. This is very helpful in taking care of especially old wards and children in the absence or their caretakers. The function of alerting the caretakers and to inform hospital in critical condition makes this system one of its kind. Readings of patient pulse rates are taken from the pulse rate sensor and the body temperature is measured by MAX30205, a temperature sensor. The data is collected through sensors and sent over the cloud servers. Linear regression is used for further analysis and prediction of pulse and temperature trend lines. Corresponding health repots will be sent to the nearby hospitals and registered mobile numbers. The framework is validated with real-time patient data, and prediction is made regarding the trends.
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Kim, Chuntae, Iruthayapandi Selestin Raja, Jong-Min Lee, Jong Ho Lee, Moon Sung Kang, Seok Hyun Lee, Jin-Woo Oh, and Dong-Wook Han. "Recent Trends in Exhaled Breath Diagnosis Using an Artificial Olfactory System." Biosensors 11, no. 9 (September 14, 2021): 337. http://dx.doi.org/10.3390/bios11090337.

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Artificial olfactory systems are needed in various fields that require real-time monitoring, such as healthcare. This review introduces cases of detection of specific volatile organic compounds (VOCs) in a patient’s exhaled breath and discusses trends in disease diagnosis technology development using artificial olfactory technology that analyzes exhaled human breath. We briefly introduce algorithms that classify patterns of odors (VOC profiles) and describe artificial olfactory systems based on nanosensors. On the basis of recently published research results, we describe the development trend of artificial olfactory systems based on the pattern-recognition gas sensor array technology and the prospects of application of this technology to disease diagnostic devices. Medical technologies that enable early monitoring of health conditions and early diagnosis of diseases are crucial in modern healthcare. By regularly monitoring health status, diseases can be prevented or treated at an early stage, thus increasing the human survival rate and reducing the overall treatment costs. This review introduces several promising technical fields with the aim of developing technologies that can monitor health conditions and diagnose diseases early by analyzing exhaled human breath in real time.
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Carvalho, Beatriz Aguiar da Silva, Ana Gabriella Bandeira Freire Andrade, Andreza Saboia Dantas, Ingrid Medeiros de Figueiredo, Jéssica Alves da Silva, Tatyana Souza Rosendo, and Angelo Giuseppe Roncalli. "Temporal trends of maternal near miss in Brazil between 2000 and 2012." Revista Brasileira de Saúde Materno Infantil 19, no. 1 (March 2019): 115–24. http://dx.doi.org/10.1590/1806-93042019000100007.

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Abstract Objectives: to identify the temporal trends and regional variations in maternal near miss in Brazil. Methods: ecological study of temporal trends. The units of analysis are in the States, the regions and Brazil, between 2000 and 2012, the dependent variable being the maternal near miss rate (MNMR), calculated from the records of the Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH-SUS) (National Health Hospital Information System).Regression analysis using Joinpoint regression software, version 4.1.0. was applied to analyze morbidity trends. Results: the main result of this study was a finding on an increase rate trend in maternal near miss in Brazil, between 2000 and 2012. This trend behaves differently depending on the development level of the region studied, presenting a positively higher increase in less developed regions and states. Conclusions: there is an increasing trend in maternal near miss rates in Brazil. The SIH-SUS may be an important instrument in identifying and monitoring maternal morbidity. Furthermore, investments in more effective public policies are needed to reduce inequalities and improve human development, both of which have influenced the chain of events related to maternal health.
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Supriya, Sai, Priyamvadaa R, and Savita SangappaMulimani. "WIRELESS POWER THEFT MONITORING SYSTEM." International Journal of Research -GRANTHAALAYAH 5, no. 4RACEEE (April 30, 2017): 118–23. http://dx.doi.org/10.29121/granthaalayah.v5.i4raceee.2017.3333.

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Now-a-days in Public Service Sectors, their Automation is the updated trend, which transforms the manpower dependent services to semi-automatic or full-automatic Sectors. Since, because the country is enlightened to globalization, income of people is rising. This “Busy” word has now become vital part of everybody’s life. So, governments prefer not only to give quality service but also the corrupt & error free services to its citizens. So as an upshot, the project proposed which is an advanced system, helps Electricity-Corporations or Electricity-Boards to switch to advancement towards “anti-Power theft” smoothly. This project helps inorder to give quality service to its customer without any kind of problems, along with an aim of reducing recurring theft of energy to a considerable extent.
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20

Kolodiziev, Oleh, Iryna Chmutova, and Vitaliy Lesik. "Use of causal analysis to improve the monitoring of the banking system stability." Banks and Bank Systems 13, no. 2 (June 20, 2018): 62–76. http://dx.doi.org/10.21511/bbs.13(2).2018.06.

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According to the stages of the banking system stability monitoring, the analysis of caus¬al links is used to identify the causes of the crisis trends spreading and the rationale for the most effective levers of regulatory influence on the banking system parameters by the central bank.The research is based on the use of the canonical correlation method for structuring causal links between the indicators for the assessment of the banking system stability, which are grouped into four sub-indices (assessing the intensity of credit and financial interaction in the interbank market, the effectiveness of the banking system functions, structural changes and financial disproportions in the banking system, activities of systemically important banks); the method of regression analysis and the calculation of elasticity coefficients is also used to assess the sensitivity of the banking system stability to changes in parameters that characterize the banking regulation instruments.The article analyzes the results of quantitative and qualitative assessment of the banking system stability (comparison of actual results of the evaluation with the data for previous years and comparison of values of stability indicators with critical values). The causes of detected deviations are determined taking into account the results of applying the canonical correlations method. Regression models have been constructed to confirm the dependence of the banking system stability index on the change in parameters that characterize banking regulation instruments, and to determine the most effective of them. Practical testing of submitted proposals is realized based on the Ukrainian banking system indicators for 2007–2016.
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Watanabe, Takeshi, and Yutaka Doizaki. "Technical Trend for Substation Operation, Monitoring and Maintenance Guidance System." IEEJ Transactions on Power and Energy 119, no. 10 (1999): 1016–19. http://dx.doi.org/10.1541/ieejpes1990.119.10_1016.

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Florkowski, Marek. "Anomaly Detection, Trend Evolution, and Feature Extraction in Partial Discharge Patterns." Energies 14, no. 13 (June 28, 2021): 3886. http://dx.doi.org/10.3390/en14133886.

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In the resilient and reliable electrical power system, the condition of high voltage insulation plays a crucial role. In the field of high voltage insulation integrity, the partial discharge (PD) inception and development trends are essential for assessment criteria in diagnostics systems. The observed trend to employ more and more sophisticated algorithms with machine learning features and artificial intelligence (AI) elements is observed everywhere. The classification and identification of features in PD images is perceived as a critical requirement for an effective high voltage insulation diagnosis. In this context, techniques allowing for anomaly detection, trends observation, and feature extraction in partial discharge patterns are important. In this paper, the application of few algorithms belonging to image processing, machine learning and optical flow is presented. The feature extraction refers to image segmentation and detection of coherent forms in the images. The anomaly detection algorithms can trigger early detection of the trend changes or the appearance of a new discharge form, and hence are suitable for PD monitoring applications. Anomaly detection can also handle transients and disturbances that appear in the PD image as an indication of an abnormal state. The future monitoring systems should be equipped with trend evolution algorithms. In this context, two examples of insulation aging and application of PD-based monitoring are shown. The first one refers to deep convolutional neural networks used for classification of deterioration stages in high voltage insulation. The latter one demonstrates application of optical flow approach for motion detection in partial discharge images. The motivation for the research was the strive to machine-controlled pattern analysis, leading towards intelligent PD-based diagnostics.
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Titchner, Holly A., P. W. Thorne, M. P. McCarthy, S. F. B. Tett, L. Haimberger, and D. E. Parker. "Critically Reassessing Tropospheric Temperature Trends from Radiosondes Using Realistic Validation Experiments." Journal of Climate 22, no. 3 (February 1, 2009): 465–85. http://dx.doi.org/10.1175/2008jcli2419.1.

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Abstract Biases and uncertainties in large-scale radiosonde temperature trends in the troposphere are critically reassessed. Realistic validation experiments are performed on an automatic radiosonde homogenization system by applying it to climate model data with four distinct sets of simulated breakpoint profiles. Knowledge of the “truth” permits a critical assessment of the ability of the system to recover the large-scale trends and a reinterpretation of the results when applied to the real observations. The homogenization system consistently reduces the bias in the daytime tropical, global, and Northern Hemisphere (NH) extratropical trends but underestimates the full magnitude of the bias. Southern Hemisphere (SH) extratropical and all nighttime trends were less well adjusted owing to the sparsity of stations. The ability to recover the trends is dependent on the underlying error structure, and the true trend does not necessarily lie within the range of estimates. The implications are that tropical tropospheric trends in the unadjusted daytime radiosonde observations, and in many current upper-air datasets, are biased cold, but the degree of this bias cannot be robustly quantified. Therefore, remaining biases in the radiosonde temperature record may account for the apparent tropical lapse rate discrepancy between radiosonde data and climate models. Furthermore, the authors find that the unadjusted global and NH extratropical tropospheric trends are biased cold in the daytime radiosonde observations. Finally, observing system experiments show that, if the Global Climate Observing System (GCOS) Upper Air Network (GUAN) were to make climate quality observations adhering to the GCOS monitoring principles, then one would be able to constrain the uncertainties in trends at a more comprehensive set of stations. This reaffirms the importance of running GUAN under the GCOS monitoring principles.
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Chanda, Emmanuel, Victor Munyongwe Mukonka, David Mthembu, Mulakwa Kamuliwo, Sarel Coetzer, and Cecilia Jill Shinondo. "Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia." Journal of Tropical Medicine 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/363520.

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Geographic information systems (GISs) with emerging technologies are being harnessed for studying spatial patterns in vector-borne diseases to reduce transmission. To implement effective vector control, increased knowledge on interactions of epidemiological and entomological malaria transmission determinants in the assessment of impact of interventions is critical. This requires availability of relevant spatial and attribute data to support malaria surveillance, monitoring, and evaluation. Monitoring the impact of vector control through a GIS-based decision support (DSS) has revealed spatial relative change in prevalence of infection and vector susceptibility to insecticides and has enabled measurement of spatial heterogeneity of trend or impact. The revealed trends and interrelationships have allowed the identification of areas with reduced parasitaemia and increased insecticide resistance thus demonstrating the impact of resistance on vector control. The GIS-based DSS provides opportunity for rational policy formulation and cost-effective utilization of limited resources for enhanced malaria vector control.
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Qiu, Dongwei, Tong Wang, Qing Ye, He Huang, Laiyang Wang, Mingxu Duan, and Dean Luo. "A Deformation Prediction Approach for Supertall Building Using Sensor Monitoring System." Journal of Sensors 2019 (April 24, 2019): 1–12. http://dx.doi.org/10.1155/2019/9283584.

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Using high-precision sensors to monitor and predict the deformation trend of supertall buildings is a hot research topic for a long time. And in terms of deformation trend prediction, the main way to realized deformation trend prediction is the deep learning algorithm, but the accuracy of prediction result needs to be improved. To solve the problem described above, firstly, based on the conditional deep belief network (CDBN) model, the levenberg-marquardt (LM) was used to optimize the CDBN model; the LM-CDBN model has been constructed. Then taking CITIC tower, the tallest building in Beijing as the research object, the real-time monitoring data of the shape acceleration array (SAA) as an example, we used LM-CDBN model to analyse and predict the building deformation. Finally, to verify the accuracy and robustness of LM-CDBN model, the prediction results of the LM-CDBN model are compared with the prediction results of the CDBN model, the extreme learning machine (ELM) model, and the unscented Kalman filter-support vector regression (UKF-SVR) model, and we evaluated the result from three aspects: training error, fitness, and stability of prediction results. The results show that the LM-CDBN model has higher precision and fitting degree in the prediction of deformation trend of supertall buildings. And the MRE, MAE, and RMSE of the LM-CDBN model prediction results are only 0.0060, 0.0023mm, and 0.0031mm, and the prediction result was more in line with the actual deformation trend.
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Sparks, Ross Stewart, and Chris Okugami. "Tele-Health Monitoring of Patient Wellness." Journal of Intelligent Systems 25, no. 4 (October 1, 2016): 515–28. http://dx.doi.org/10.1515/jisys-2014-0175.

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AbstractThe vital signs of chronically ill patients are monitored daily. The record flags when a specific vital sign is stable or when it trends into dangerous territory. Patients also self-assess their current state of well-being, i.e. whether they are feeling worse than usual, neither unwell nor very well compared to usual, or are feeling better than usual. This paper examines whether past vital sign data can be used to forecast how well a patient is going to feel the next day. Reliable forecasting of a chronically sick patient’s likely state of health would be useful in regulating the care provided by a community nurse, scheduling care when the patient needs it most. The hypothesis is that the vital signs indicate a trend before a person feels unwell and, therefore, are lead indicators of a patient going to feel unwell. Time series and classification or regression tree methods are used to simplify the process of observing multiple measurements such as body temperature, heart rate, etc., by selecting the vital sign measures, which best forecast well-being. We use machine learning techniques to automatically find the best combination of these vital sign measurements and their rules that forecast the wellness of individual patients. The machine learning models provide rules that can be used to monitor the future wellness of a patient and regulate their care plans.
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Conceição, Mara Beatriz Martins, Antonio Fernando Boing, and Karen Glazer Peres. "Time trends in prostate cancer mortality according to major geographic regions of Brazil: an analysis of three decades." Cadernos de Saúde Pública 30, no. 3 (March 2014): 559–66. http://dx.doi.org/10.1590/0102-311x00005813.

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The aim of this study was to analyze prostate cancer mortality and time trends in Brazil, according to major geographic regions, States, and age brackets. Data on deaths from 1980 to 2010 were obtained from the Mortality Information System. Mortality trends were estimated using Prais-Winsten generalized linear regression. An upward time trend was observed in mortality in all regions of Brazil, with a mean annual increase of 2.8%. The upward trend in mortality occurred in most of the age brackets, with a concentration of deaths in men 70 to 79 years of age (41%) and a significant increase in the 40 to 60-year age bracket. The mortality rate increased significantly in all age brackets in the Northeast, compared to the other regions of Brazil. The study highlighted the importance of redistributing deaths from ill-defined causes in order to correct the mortality rates. The results point to significant regional differences and the need for continuous monitoring of mortality from prostate cancer in Brazil.
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Grigorieva, S. V., N. G. Igoshkina, and O. G. Vasilyeva. "Organization of Skype for Business service monitoring to optimize the services support Department." Voprosy regionalnoj ekonomiki 35, no. 2 (July 29, 2018): 25–31. http://dx.doi.org/10.21499/2078-4023-2018-35-2-25-31.

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This article is devoted to the development of a monitoring system for Skype for Business service to optimize the services support Department. The development of the system was performed using the software of Microsoft Power BI. The developed monitoring system is able to perform the following functions: the ability to monitor the trend in the use of the service; prompt update of data in the system; monitoring of the most frequent errors; determining the trend of errors; collection of information about the quality of calls; collecting impact.
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Kleinert, Anne, Isabell Krisch, Jörn Ungermann, Albert Adibekyan, Berndt Gutschwager, and Christian Monte. "Characterization of blackbody inhomogeneity and its effect on the retrieval results of the GLORIA instrument." Atmospheric Measurement Techniques 11, no. 7 (July 3, 2018): 3871–82. http://dx.doi.org/10.5194/amt-11-3871-2018.

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Abstract. Limb sounding instruments play an important role in the monitoring of climate trends, as they provide a good vertical resolution. Traceability to the International System of Units (SI) via onboard reference or transfer standards is needed to compare trend estimates from multiple instruments. This study investigates the required uncertainty of these radiation standards to properly resolve decadal trends of climate-relevant trace species like ozone, water vapor, and temperature distribution for the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA). Temperature nonuniformities of the onboard reference blackbodies, used for radiometric calibration, have an impact on the calibration uncertainty. The propagation of these nonuniformities through the retrieval is analyzed. A threshold for the maximum tolerable uncertainty of the blackbody temperature is derived, so that climate trends can be significantly identified with GLORIA.
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Oscullo, José, Jaime Cepeda, Carlos Gallardo, and Lenin Haro. "Trend Analysis of Modal Identification based Real-time Power System Oscillations using L1 Trend Filtering." International Journal of Robotics and Control Systems 1, no. 2 (May 8, 2021): 116–30. http://dx.doi.org/10.31763/ijrcs.v1i2.311.

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This paper is looking to show to use of system data collected from wide-area monitoring systems (WAMS). They allow monitoring of the dynamics of power systems. Among the WAMS applications, there is the modal identification algorithm, which identifies critical oscillatory modes from PMU measurements. This application permits using data processors for estimating of frequency, damping, and amplitude of dominant mode oscillations observable in a specific electric signal (e.g., active power, frequency) recorded for the analyzed period. However, since modal identification of real-time measurements is based on an online optimization, the results usually have considerable fluctuations. Thus, it is essential to consider the complementary implementation of trend analysis for acquiring convenient early-warning indicators of oscillatory problems. This consideration allows avoiding erroneous information of the systems oscillatory behavior of the system real-time that modal identification of crude results could deliver. In this paper, the application of a l1 filter for determining the trend analysis of high-dimensional data set resulted from a commercial modal identification is explored. The algorithm is applied to an oscillatory event registered by the WAMS of the Ecuadorian National Interconnected System with promising results.
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Cheng, Li Ping, De Jie Huang, and Jing Xing Zhu. "Design of Intelligent Surface Water Monitoring System." Applied Mechanics and Materials 433-435 (October 2013): 945–49. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.945.

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There are two key issues in the surface water monitoring, one is long-distance data transmission; second is the power to the monitor. The design uses Siemens TC35i module to transmit data, uses clock timing chips to control the working hours of low-power AVR microcontroller and phone modules. So the two problems are solved effectively. The PC-monitor-interface used LabVIEW software is also simple and clear, it can display real-time data; analyzes the trend of the data-curve; warn much earlier. The practical of result shows that the design is simple, good controllability, high reliability.
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Karwur, Satoro Disney, Hesky S. Kolibu, and Verna A. Suoth. "OBJECT DETECTOR PROTOTYPE USING ULTRASONIC SENSOR FOR INDOOR SECURITY MONITORING SYSTEM." JURNAL ILMIAH SAINS 14, no. 2 (October 15, 2014): 100. http://dx.doi.org/10.35799/jis.14.2.2014.6064.

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ABSTRACT A research has been conducted to make an object detector prototype using ultrasonic sensor for indoor security monitoring system. The testing object placed in front of the sensor and the measurement conducted in distance and angle variations. For indoor implementation, graphical display of object detection on computer screen given by blue-to-yellow transition to indicate the nearing object and its reverse to indicate the fading object. The trend of accuracy of the object distance measurement has a declining linear pattern, it means that the accuracy of object detection will decrease if the distance and or angle from the object to the detector are increase. Keywords: object detector, ultrasonic sensor, indoor security monitoring PURWARUPA DETEKTOR OBJEK MENGGUNAKAN SENSOR ULTRASONIK UNTUK SISTEM PEMANTAUAN KEAMANAN DALAM RUANGAN ABSTRAK Sebuah penelitian telah dilakukan untuk membuat purwarupa detektor objek menggunakan sensor ultrasonik untuk sistem pemantauan keamanan dalam ruangan. Objek pengujian diletakkan di depan sensor dan pengukuran dilakukan pada variasi jarak dan sudut. Untuk implementasi dalam ruangan, tampilan grafis pendeteksian objek pada layar komputer diberikan oleh transisi warna biru ke kuning untuk menunjukkan objek yang mendekat dan kebalikannya untuk menunjukkan objek yang menjauh. Tren akurasi pendeteksian objek memiliki pola menurun secara linear, itu berarti bahwa akurasi pendeteksian objek akan berkurang jika jarak dan atau sudut dari objek ke detektor bertambah besar. Kata kunci: detektor objek, sensor ultrasonik, pemantauan keamanan dalam ruangan
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Wang, Zheng Wei, Ping Tang, and Xiao Shi Zheng. "Summary of Remote Monitoring System for CNC Machines." Applied Mechanics and Materials 602-605 (August 2014): 1787–92. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1787.

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With the development of information technology, especially the rapid development of network transmission technology, remote monitoring is becoming more and more popular, remote monitoring system (RMS) for CNC machines will be a trend in the control field. This paper introduces research and application status of RMS for CNC machines interiorly and abroad, summarizes its main features,discusses specific technical routes. Finally,problems and suggestions in the development are presented.
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Barančíková, G. "Changes of humic acids structure on selected key monitoring localities of arable soils." Plant, Soil and Environment 48, No. 1 (December 11, 2011): 40–44. http://dx.doi.org/10.17221/4202-pse.

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Soil fertility is largely determined by the content and quality of soil organic matter. SlovakRepublic monitoring system includes evaluation of soil humus content, basic humic parameters and also chemical structure of humic acids (HA). Changes in humic acids structure on five selected key localities during monitoring period (1994&ndash;2000) are presented in this study. Among soil types, essentially between Chernozem and Planosol, in elemental analysis, optical parameter and 13C NMR parameters significant differences determined by Student&rsquo;s test were observed (Tables 2 and 3). During monitoring period small oxidation trend mainly on Calcaric Fluvisol and Planosol HA expressed by increase of oxygen content and O/C, O/H ratio was observed. Oxidation trends during monitoring period confirm also position of Calcaric Fluvisol and Planosol HA on van Krevelen diagram. Changes in optical parameter E<sup>1%</sup><sub>6</sub>and content of carboxylic groups for the period of monitoring were negligible. Some changes throughout monitoring in <sup>13</sup>C NMR parameters were recorded. On all observed HA considerable decrease of carbon in region 106&ndash;143 ppm, characteristic for aromatic and olefinic carbon with C&ndash;C, C&ndash;H bond, was observed. Spectroscopic parameters are in good agreement with elemental analysis and carboxylic groups. Joint relationships between changes in determined parameters are expressed by significant linear correlations. Predominantly between parameters calculated from <sup>13</sup>C NMR spectra and data of elemental analysis and optical parameter E<sup>1%</sup><sub>6</sub>highly significant linear correlations (R &gt; 0.93) are found (Table 4).&nbsp;
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35

Burt, T. P., N. J. K. Howden, F. Worrall, and M. J. Whelan. "Importance of long-term monitoring for detecting environmental change: lessons from a lowland river in south east England." Biogeosciences 5, no. 6 (November 11, 2008): 1529–35. http://dx.doi.org/10.5194/bg-5-1529-2008.

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Abstract. Rising nitrate concentrations in rivers and groundwater in regions with intensive agriculture have been of concern for several decades. Long records of nitrate concentration are rare; in the UK, few pre-date 1974. Records from the River Stour from 1937 are analysed using moving-windows to explore the effects of window width on trend detection and process inference. Nitrate concentrations rose sharply from the late 1950s in response to widespread ploughing of grassland, but have fallen since the early 1980s, suggesting that widespread nitrogen control measures, which were introduced after the start of the downward trend, may not be the principal driver for recent change. Short windows (5 years) are too noisy; longer windows (10, 15 and 30 years) identify signals (i.e. trends) more reliably. Since system response times can be of the order of 20–30 years, management decisions made on shorter data sets (even up to 15 years) could be misleading.
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36

Burt, T. P., N. J. K. Howden, F. Worrall, and M. J. Whelan. "Importance of long-term monitoring for detecting environmental change: lessons from a lowland river in south east England." Biogeosciences Discussions 5, no. 3 (June 6, 2008): 2369–79. http://dx.doi.org/10.5194/bgd-5-2369-2008.

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Abstract. Rising nitrate concentrations in rivers and groundwater in regions with intensive agriculture have been of concern for several decades. Long records of nitrate concentration are rare; in the UK, few pre-date 1974. Records from the River Stour from 1937 are analysed using "moving-windows", to explore the effects of window width on trend detection and process inference. Nitrate concentrations rose sharply from the late 1950s in response to widespread ploughing of grassland, but have fallen since the early 1980s, suggesting that widespread nitrogen control measures, which were introduced after the start of the downward trend, may not be the principal driver for recent change. Short windows (5 years) are too noisy; longer windows (10, 15 and 30 years) identify signals (i.e. trends) more reliably. Since system response times can be of the order of 20–30 years, management decisions made on shorter data sets (even up to 15 years) could be misleading.
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37

Zhang, Siyu, and R. Ganesan. "Multivariable Trend Analysis for System Monitoring Through Self-Organizing Neural Networks." Journal of Dynamic Systems, Measurement, and Control 119, no. 2 (June 1, 1997): 223–28. http://dx.doi.org/10.1115/1.2801237.

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For precise and reliable fault detection it is essential to consider simultaneously the changes in several diagnostic indices that are extracted from the on-line vibration signal. Existing machine condition monitoring systems consider each diagnostic index separately. Development of an automated diagnostic procedure that considers simultaneously several diagnostic indices is the objective of the present paper. The multivariable trend analysis of on-line vibration signals is deployed as the basis for this procedure. An efficient self-organizing neural network algorithm that is highly suitable to this diagnostic procedure is developed and deployed. Applications to both a bearing system as well as a gearbox system are fully developed and demonstrated.
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JOHNSON, TERRI, XIAOHE ZHANG, and ANDREW BALO. "Assessing Glucose Trend Accuracy with a Novel Continuous Glucose Monitoring System." Diabetes 67, Supplement 1 (May 2018): 950—P. http://dx.doi.org/10.2337/db18-950-p.

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39

Васенко А. Г., Брук В. В., and Свиридов Ю. В. "ГЕОИНФОРМАЦИОННАЯ СИСТЕМА ДЛЯ АНАЛИЗА ДАННЫХ ЭКОЛОГИЧЕСКОГО МОНИТОРИНГА УКРАИНСКОЙ ЧАСТИ ДЕЛЬТЫ ДУНАЯ." Science Review, no. 4(21) (May 31, 2019): 20–24. http://dx.doi.org/10.31435/rsglobal_sr/31052019/6489.

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For forecasting of the change of water quality in Ukrainian part of Danube delta the geographic information system (GIS) of the ecological monitoring had been designed. To this GIS a number of functions had been added including the function of the analysis of the temporary rows of observation results. By means of designed GIS the main trends of the change of the water quality for period, since 2004, have been identified. For majority of the water quality parameters the trends to improvement of water quality have been identified. The trend to deterioration of water quality has been identified for manganese concentration only. Increasing of manganese concentrations existed already in the inlet checkpoint of Ukrainian part of Danube delta (above Reni).
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40

Seidel, Dian J., and Melissa Free. "Measurement Requirements for Climate Monitoring of Upper-Air Temperature Derived from Reanalysis Data." Journal of Climate 19, no. 5 (March 1, 2006): 854–71. http://dx.doi.org/10.1175/jcli3666.1.

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Abstract Using a reanalysis of the climate of the past half century as a model of temperature variations over the next half century, tests of various data collection protocols are made to develop recommendations for observing system requirements for monitoring upper-air temperature. The analysis focuses on accurately estimating monthly climatic data (specifically, monthly average temperature and its standard deviation) and multidecadal trends in monthly temperatures at specified locations, from the surface to 30 hPa. It does not address upper-air network size or station location issues. The effects of reducing the precision of temperature data, incomplete sampling of the diurnal cycle, incomplete sampling of the days of the month, imperfect long-term stability of the observations, and changes in observation schedule are assessed. To ensure accurate monthly climate statistics, observations with at least 0.5-K precision, made at least twice daily, at least once every two or three days are sufficient. Using these same criteria, and maintaining long-term measurement stability to within 0.25 (0.1) K, for periods of 20 to 50 yr, errors in trend estimates can be avoided in at least 90% (95%) of cases. In practical terms, this requires no more than one intervention (e.g., instrument change) over the period of record, and its effect must be to change the measurement bias by no more than 0.25 (0.1) K. The effect of the first intervention dominates the effects of subsequent, uncorrelated interventions. Changes in observation schedule also affect trend estimates. Reducing the number of observations per day, or changing the timing of a single observation per day, has a greater potential to produce errors in trends than reducing the number of days per month on which observations are made. These findings depend on the validity of using reanalysis data to approximate the statistical nature of future climate variations, and on the statistical tests employed. However, the results are based on conservative assumptions, so that adopting observing system requirements based on this analysis should result in a data archive that will meet climate monitoring needs over the next 50 yr.
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41

Lee, Wonjin. "The latest trend in neuromuscular monitoring: return of the electromyography." Anesthesia and Pain Medicine 16, no. 2 (April 30, 2021): 133–37. http://dx.doi.org/10.17085/apm.21014.

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To reduce the risk of residual neuromuscular blockade, neuromuscular monitoring must be performed. Acceleromyography (AMG)-based neuromuscular monitoring was regarded as “clinical gold standard” and widely applied. However, issues related to patient’s posture and overestimation of train-of-four ratio associated with AMG-based neuromuscular monitoring have increased. Recently, electromyography (EMG)-based neuromuscular monitoring is receiving renewed attention, since it overcomes AMG’s weaknesses. However, both AMG-based and EMG-based systems are useful when certain considerations are followed. Ultimately, to assure the patient’s good outcomes, the choice of monitoring system is not as important as the monitoring itself, which should be always implemented in such patients.
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42

Qu, Liang, Lin Zheng, Zhi Guo Bu, Juan Wang, and Ting Zhang. "The Application of Radar Oil Spill Monitoring System in the Management of Marine." Applied Mechanics and Materials 321-324 (June 2013): 747–50. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.747.

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For the characteristics of all-weather monitoring and high accuracy, X-band radar develops into the new technical means of monitoring marine oil spill. This paper presents the principle, workflow and components of radar oil spill monitoring system, as well as its application in marine management and its development trend.
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43

Chuo, Po Chou, Yi Cheng Huang, Min Chie Chiu, and Ho Chih Cheng. "A Quality Monitoring Online System Using an Early Warning Abnormal Trend Distribution: A Thickness Measurement Case Study Using a LVDT." Advanced Materials Research 740 (August 2013): 120–27. http://dx.doi.org/10.4028/www.scientific.net/amr.740.120.

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To assure product quality, an early warning and inspection system to predict the variation (trend) of a products quality (i.e. the product thickness) in the manufacturing process is necessary. Here, a manual online measurement of a production line installed with an online automatic warning system that will prevent manually accumulated errors from occurring is presented. Using this system, a quality trend profile will be made. The abnormal trend distribution will be obtained by randomly selecting the period of the quality trend profile and translating it into a time distribution bar chart. The monitoring online system will be pre-warned via the abnormal trend distribution. A products thickness can be obtained using a linear variable differential transformer (LVDT). The analogue signal will be transmitted to the AD converter of the PLCs analogue input channel. The digital signal will be transmitted from the series port to the remote PC via the web control unit. A profile of the products thickness measured by the LVDT will be monitored online and dynamically exhibited in the web-based remote system by using an embedded Javascript, an HTML, and a web control unit. The upper/lower thresholds will be preset in the product thickness profile. In addition, the quality monitoring system will be pre-warned via the time distribution bar chart when the abnormal trend distribution occurs. Consequently, the web-base monitoring system can be extended to remotely connect to all the LVDT devices.
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44

Sun, Lei, and Xian Wu Hao. "Analysis of Bridge Deflection Based on Time Series." Applied Mechanics and Materials 71-78 (July 2011): 4545–48. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.4545.

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The bridge health monitoring system can collect large amounts of data, but it lacks the trend analysis of monitoring data. This article introduced the method of Time series analysis into the analysis of bridge monitoring data, and adopted ARIMA model in time series analysis of monitoring data, used the least square method for parameter estimation, established the prediction model for bridge deflection, and conducted the goodness of fit test. Take the actual bridge monitoring data as an example, it was demonstrated that the method is feasible in the prediction of bridge condition trend.
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45

Xu, Liang, Zheng Min Qu, Ji Qing Zheng, and Yang Liu. "Concrete Cracks Monitoring of a Practical Bridge by Using Structural Health Monitoring Technique." Key Engineering Materials 648 (June 2015): 1–8. http://dx.doi.org/10.4028/www.scientific.net/kem.648.1.

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Concrete cracks monitoring of a practical bridge was discussed in order to investigate the practical application of structural health monitoring (SHM) technique. Some detail information of the SHM system of a practical bridge were introduced and some key issues for building this monitoring system was discussed. Strain of bridge beam generated near the concrete cracks was applied to assess the change of width of cracks, and the monitoring data were analyzed. The condition of this practical was evaluated from the point of view of the change trend of concrete cracks.
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Xu, Guang Ming, Li Chen, and Xin Gao. "Some Key Issues and Challenges of Building the Structural Health Monitoring System of Bridges." Key Engineering Materials 619 (July 2014): 91–98. http://dx.doi.org/10.4028/www.scientific.net/kem.619.91.

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In view of the issue of bridge structure safety, this study pointed out the necessity and urgency to build the bridge safety operational monitoring system. The basic idea, system composition, current situation of the development and application of structural health monitoring system were summarized. Finally, the key problems and development trend of bride safety monitoring were proposed.
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47

Xiao, Hai Ping, and Lan Lan Chen. "The Research of the Deformation Monitoring System Based on GIS/GPS Integration." Advanced Materials Research 243-249 (May 2011): 5828–31. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5828.

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The research of "3S" integration of the deformation monitoring system, is one of the important development trend of the deformation monitoring technology. This text analyzed the key technology of the application of GPS/GIS integration, realized the effective integration of the mass of datas of GPS and GIS technology, and to establish the GPS/GIS integration of deformation monitoring system provides important technical support.
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Chen, S. S., G. Y. Li, and L. B. He. "The Vibration Monitoring Standards of Desulphurization Fans and the Monitoring and Intelligent System of Identifying Failure." Key Engineering Materials 426-427 (January 2010): 348–51. http://dx.doi.org/10.4028/www.scientific.net/kem.426-427.348.

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A typical fan desulphurization measuring points (failure-prone region), according to measurement data on many occasions, its failure to find the development trend of the equipment malfunction and made more accurate judgments. At the same time, the preparation of the equipment, the corresponding vibration diagnostic criteria and common fault identification intelligent system and continuously updated to facilitate site inspection personnel equipment vibration condition monitoring work and improve their equipment to grasp the operation of the accuracy and efficiency.
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Sun, Wu, Qin Li An, Sheng Zhi Song, and Xin Huang. "Safety Control and Site Monitoring on High Formwork Support System of Fastener-Style Steel Pipe." Applied Mechanics and Materials 578-579 (July 2014): 1200–1203. http://dx.doi.org/10.4028/www.scientific.net/amm.578-579.1200.

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The high formwork system monitoring program of the project example of high formwork support system of fastener-style steel pipe is carried out in detail, including monitoring content , measuring points arrangement, monitoring frequency etc. Based on the analysis of the monitoring data, influential factors of upright tube subsidence and the development trend of high formwork are presented. The site safety control suggestions are given for the high formwork system.
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50

Zhang, Ruixiong, Yuhang Wang, Charles Smeltzer, Hang Qu, William Koshak, and K. Folkert Boersma. "Comparing OMI-based and EPA AQS in situ NO<sub>2</sub> trends: towards understanding surface NO<sub><i>x</i></sub> emission changes." Atmospheric Measurement Techniques 11, no. 7 (July 6, 2018): 3955–67. http://dx.doi.org/10.5194/amt-11-3955-2018.

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Abstract. With the improved spatial resolution of the Ozone Monitoring Instrument (OMI) over earlier instruments and more than 10 years of service, tropospheric NO2 retrievals from OMI have led to many influential studies on the relationships between socioeconomic activities and NOx emissions. Previous studies have shown that the OMI NO2 data show different relative trends compared to in situ measurements. However, the sources of the discrepancies need further investigations. This study focuses on how to appropriately compare relative trends derived from OMI and in situ measurements. We retrieve OMI tropospheric NO2 vertical column densities (VCDs) and obtain the NO2 seasonal trends over the United States, which are compared with coincident in situ surface NO2 measurements from the Air Quality System (AQS) network. The Mann–Kendall method with Sen's slope estimator is applied to derive the NO2 seasonal and annual trends for four regions at coincident sites during 2005–2014. The OMI-based NO2 seasonal relative decreasing trends are generally biased low compared to the in situ trends by up to 3.7 % yr−1, except for the underestimation in the US Midwest and Northeast during December, January, and February (DJF). We improve the OMI retrievals for trend analysis by removing the ocean trend, using the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data in air mass factor (AMF) calculation. We apply a lightning flash filter to exclude lightning-affected data to make proper comparisons. These data processing procedures result in close agreement (within 0.3 % yr−1) between in situ and OMI-based NO2 regional annual relative trends. The remaining discrepancies may result from inherent difference between trends of NO2 tropospheric VCDs and surface concentrations, different spatial sampling of the measurements, chemical nonlinearity, and tropospheric NO2 profile changes. We recommend that future studies apply these procedures (ocean trend removal and MODIS albedo update) to ensure the quality of satellite-based NO2 trend analysis and apply the lightning filter in studying surface NOx emission changes using satellite observations and in comparison with the trends derived from in situ NO2 measurements. With these data processing procedures, we derive OMI-based NO2 regional annual relative trends using all available data for the US West (−2.0 % ± 0.3 yr−1), Midwest (−1.8 % ± 0.4 yr−1), Northeast (−3.1 % ± 0.5 yr−1), and South (−0.9 % ± 0.3 yr−1). The OMI-based annual mean trend over the contiguous United States is −1.5 % ± 0.2 yr−1. It is a factor of 2 lower than that of the AQS in situ data (−3.9 % ± 0.4 yr−1); the difference is mainly due to the fact that the locations of AQS sites are concentrated in urban and suburban regions.
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