A component-based system for agricultural drought monitoring by remote sensing.

PubMed

Dong, Heng; Li, Jun; Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

A component-based system for agricultural drought monitoring by remote sensing

PubMed Central

Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China’s Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring. PMID:29236700

Monitoring operational data production applying Big Data tooling

NASA Astrophysics Data System (ADS)

Som de Cerff, Wim; de Jong, Hotze; van den Berg, Roy; Bos, Jeroen; Oosterhoff, Rijk; Klein Ikkink, Henk Jan; Haga, Femke; Elsten, Tom; Verhoef, Hans; Koutek, Michal; van de Vegte, John

2015-04-01

Within the KNMI Deltaplan programme for improving the KNMI operational infrastructure an new fully automated system for monitoring the KNMI operational data production systems is being developed: PRISMA (PRocessflow Infrastructure Surveillance and Monitoring Application). Currently the KNMI operational (24/7) production systems consist of over 60 applications, running on different hardware systems and platforms. They are interlinked for the production of numerous data products, which are delivered to internal and external customers. All applications are individually monitored by different applications, complicating root cause and impact analysis. Also, the underlying hardware and network is monitored separately using Zabbix. Goal of the new system is to enable production chain monitoring, which enables root cause analysis (what is the root cause of the disruption) and impact analysis (what other products will be effected). The PRISMA system will make it possible to dispose all the existing monitoring applications, providing one interface for monitoring the data production. For modeling the production chain, the Neo4j Graph database is used to store and query the model. The model can be edited through the PRISMA web interface, but is mainly automatically provided by the applications and systems which are to be monitored. The graph enables us to do root case and impact analysis. The graph can be visualized in the PRISMA web interface on different levels. Each 'monitored object' in the model will have a status (OK, error, warning, unknown). This status is derived by combing all log information available. For collecting and querying the log information Splunk is used. The system is developed using Scrum, by a multi-disciplinary team consisting of analysts, developers, a tester and interaction designer. In the presentation we will focus on the lessons learned working with the 'Big data' tooling Splunk and Neo4J.

Self-calibrating models for dynamic monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1996-01-01

A method for automatically building qualitative and semi-quantitative models of dynamic systems, and using them for monitoring and fault diagnosis, is developed and demonstrated. The qualitative approach and semi-quantitative method are applied to monitoring observation streams, and to design of non-linear control systems.

Dynamic data filtering system and method

DOEpatents

Bickford, Randall L; Palnitkar, Rahul M

2014-04-29

A computer-implemented dynamic data filtering system and method for selectively choosing operating data of a monitored asset that modifies or expands a learned scope of an empirical model of normal operation of the monitored asset while simultaneously rejecting operating data of the monitored asset that is indicative of excessive degradation or impending failure of the monitored asset, and utilizing the selectively chosen data for adaptively recalibrating the empirical model to more accurately monitor asset aging changes or operating condition changes of the monitored asset.

40 CFR Table 4 to Subpart Ffff of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2012 CFR

2012-07-01

... Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment... Construction On or Before December 9, 2004 Pt. 60, Subpt. FFFF, Table 4 Table 4 to Subpart FFFF of Part 60—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...

40 CFR Table 4 to Subpart Ffff of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2013 CFR

2013-07-01

... Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment... Construction On or Before December 9, 2004 Pt. 60, Subpt. FFFF, Table 4 Table 4 to Subpart FFFF of Part 60—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...

40 CFR Table 4 to Subpart Ffff of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2014 CFR

2014-07-01

... Emission Monitoring Systems (CEMS) 4 Table 4 to Subpart FFFF of Part 60 Protection of Environment... Construction On or Before December 9, 2004 Pt. 60, Subpt. FFFF, Table 4 Table 4 to Subpart FFFF of Part 60—Model Rule—Requirements for Continuous Emission Monitoring Systems (CEMS) As stated in § 60.3039, you...

Optimized Temporal Monitors for SystemC

NASA Technical Reports Server (NTRS)

Tabakov, Deian; Rozier, Kristin Y.; Vardi, Moshe Y.

2012-01-01

SystemC is a modeling language built as an extension of C++. Its growing popularity and the increasing complexity of designs have motivated research efforts aimed at the verification of SystemC models using assertion-based verification (ABV), where the designer asserts properties that capture the design intent in a formal language such as PSL or SVA. The model then can be verified against the properties using runtime or formal verification techniques. In this paper we focus on automated generation of runtime monitors from temporal properties. Our focus is on minimizing runtime overhead, rather than monitor size or monitor-generation time. We identify four issues in monitor generation: state minimization, alphabet representation, alphabet minimization, and monitor encoding. We conduct extensive experimentation and identify a combination of settings that offers the best performance in terms of runtime overhead.

40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?

Code of Federal Regulations, 2011 CFR

2011-07-01

... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the continuous emission monitoring systems used? You must use data from the continuous emission monitoring...

40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?

Code of Federal Regulations, 2010 CFR

2010-07-01

... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the continuous emission monitoring systems used? You must use data from the continuous emission monitoring...

[The regional model of three-level system of of medical social monitoring of children and adolescents: the pilot project in the Republic of Tatarstan].

PubMed

Al'bitskii, V Iu; Ustinova, N V; Farrakhov, A Z; Shavaliev, R F; Kulikov O V; Plaksina, L V

2014-01-01

The absence of system of medical social monitoring of children being in difficult life situations is one of main causes of preventable losses of health and life of children and adolescents. The plan of activities of the working group No3 under the Coordination council under the President of the Russian Federation of the national strategy realization of actions in interest of children for 2012-2017 includes a point: "The development and implementation of standard model of medical social monitoring of children and adolescents in the subjects of the Russian Federation". The implementation of this task is assigned to the Department of social pediatrics of The research center of children health of Moscow and the Ministry of Health of the Republic of Tatarstan. The research methods included analysis and generalization of advanced experience of medical social monitoring of children population; expertise technique; modeling. The regional model of three-level system of medical social monitoring of children population is developed and implemented. The model includes level I (consulting rooms of medical social care of children polyclinics, feldsher obstetric stations, first-aid centers), level II--inter-municipal (departments of medical social monitoring in central district hospitals, medical institutions, clinical diagnostic centers) and level III--regional (the Republican center of medical social monitoring of children and adolescents). The immediate tasks necessary for effective functioning of system of medical social monitoring were determined. Within the framework of implementation of the pilot project the legal and normative legislative acts were developed to regulate functioning of regional model of three-level system of medical social care. The other documents necessary for effective functioning of this system were elaborated. The practical significance of this system is in the implementation of effective three-level model of medical social monitoring of children and adolescents supporting decrease of morbidity, mortality and "risk behaviors" suicidal included. The model is to prevent child neglect and homelessness and cruel treatment of children and adolescents.

Object-oriented Approach to High-level Network Monitoring and Management

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi

2000-01-01

An absolute prerequisite for the management of large investigating methods to build high-level monitoring computer networks is the ability to measure their systems that are built on top of existing monitoring performance. Unless we monitor a system, we cannot tools. Due to the heterogeneous nature of the hope to manage and control its performance. In this underlying systems at NASA Langley Research Center, paper, we describe a network monitoring system that we use an object-oriented approach for the design, we are currently designing and implementing. Keeping, first, we use UML (Unified Modeling Language) to in mind the complexity of the task and the required model users' requirements. Second, we identify the flexibility for future changes, we use an object-oriented existing capabilities of the underlying monitoring design methodology. The system is built using the system. Third, we try to map the former with the latter. APIs offered by the HP OpenView system.

General Purpose Data-Driven Online System Health Monitoring with Applications to Space Operations

NASA Technical Reports Server (NTRS)

Iverson, David L.; Spirkovska, Lilly; Schwabacher, Mark

2010-01-01

Modern space transportation and ground support system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional parameter limit checking, or model-based or rule-based methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults, failures, or precursors of significant failures. The Inductive Monitoring System (IMS) is a general purpose, data-driven system health monitoring software tool that has been successfully applied to several aerospace applications and is under evaluation for anomaly detection in vehicle and ground equipment for next generation launch systems. After an introduction to IMS application development, we discuss these NASA online monitoring applications, including the integration of IMS with complementary model-based and rule-based methods. Although the examples presented in this paper are from space operations applications, IMS is a general-purpose health-monitoring tool that is also applicable to power generation and transmission system monitoring.

System of Monitoring the Quality of Higher Education in UK Universities: Experience for Ukraine

ERIC Educational Resources Information Center

Krasilnikova, Hanna

2014-01-01

The article deals with the experience of the use of the system of internal monitoring of the quality of higher education in UK Universities. There has been analyzed the existing model of the system of higher education monitoring at the level of a higher education institution within the scope of the British higher education model, discovered by a…

On predicting monitoring system effectiveness

NASA Astrophysics Data System (ADS)

Cappello, Carlo; Sigurdardottir, Dorotea; Glisic, Branko; Zonta, Daniele; Pozzi, Matteo

2015-03-01

While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

Failure monitoring in dynamic systems: Model construction without fault training data

NASA Technical Reports Server (NTRS)

Smyth, P.; Mellstrom, J.

1993-01-01

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maxwell, Don E; Ezell, Matthew A; Becklehimer, Jeff

While sites generally have systems in place to monitor the health of Cray computers themselves, often the cooling systems are ignored until a computer failure requires investigation into the source of the failure. The Liebert XDP units used to cool the Cray XE/XK models as well as the Cray proprietary cooling system used for the Cray XC30 models provide data useful for health monitoring. Unfortunately, this valuable information is often available only to custom solutions not accessible by a center-wide monitoring system or is simply ignored entirely. In this paper, methods and tools used to harvest the monitoring data availablemore » are discussed, and the implementation needed to integrate the data into a center-wide monitoring system at the Oak Ridge National Laboratory is provided.« less

An experimental work on wireless structural health monitoring system applying on a submarine model scale

NASA Astrophysics Data System (ADS)

Nugroho, W. H.; Purnomo, N. J. H.; Soedarto, T.

2016-11-01

This paper presents an experimental work to monitor the health of submarine hull structures using strain sensors and wireless communication technology. The monitored - submarine hull was built in a hydro elastic model scale 1: 30 with a steel bar backbone and tested on water tank of Indonesian Hydrodynamic Laboratory (IHL). Specifically, this health monitoring system for the submarine model was developed using wireless modems, data communication software and conventional strain sensors. This system was used to monitor the loads on a steel bar backbone of the running submarine model from the edge of the water tank. Commands were issued from a notebook to instruct the health monitoring system to acquire data from sensors mounted externally to the steel bar. Data from measurements made on the structure are then transmitted wirelessly back to a notebook computer for processing and analysis. The results of the tank test have been validated and showed no loss of communication signal over an area of the tank. This work also presents a potential use of involving complete automation of this system with an in-service structure coupled with an on-line warning/damage detection capability.

40 CFR Table 6 to Subpart Bbbb of... - Model Rule-Requirements for Validating Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2010 CFR

2010-07-01

... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment...—Requirements for Validating Continuous Emission Monitoring Systems (CEMS) For the following continuous emission monitoring systems Use the following methods in appendix A of this part to validate poollutant concentratin...

40 CFR Table 6 to Subpart Bbbb of... - Model Rule-Requirements for Validating Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2011 CFR

2011-07-01

... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment...—Requirements for Validating Continuous Emission Monitoring Systems (CEMS) For the following continuous emission monitoring systems Use the following methods in appendix A of this part to validate poollutant concentratin...

40 CFR 60.3038 - What continuous emission monitoring systems must I install?

Code of Federal Regulations, 2012 CFR

2012-07-01

... systems must I install? 60.3038 Section 60.3038 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install... carbon monoxide and for oxygen. You must monitor the oxygen concentration at each location where you...

40 CFR 60.3038 - What continuous emission monitoring systems must I install?

Code of Federal Regulations, 2014 CFR

2014-07-01

... systems must I install? 60.3038 Section 60.3038 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install... carbon monoxide and for oxygen. You must monitor the oxygen concentration at each location where you...

40 CFR 60.3038 - What continuous emission monitoring systems must I install?

Code of Federal Regulations, 2013 CFR

2013-07-01

... systems must I install? 60.3038 Section 60.3038 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... December 9, 2004 Model Rule-Monitoring § 60.3038 What continuous emission monitoring systems must I install... carbon monoxide and for oxygen. You must monitor the oxygen concentration at each location where you...

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

Development of a model protection and dynamic response monitoring system for the national transonic facility

NASA Technical Reports Server (NTRS)

Young, Clarence P., Jr.; Balakrishna, S.; Kilgore, W. Allen

1995-01-01

A state-of-the-art, computerized mode protection and dynamic response monitoring system has been developed for the NASA Langley Research Center National Transonic Facility (NTF). This report describes the development of the model protection and shutdown system (MPSS). A technical description of the system is given along with discussions on operation and capabilities of the system. Applications of the system to vibration problems are presented to demonstrate the system capabilities, typical applications, versatility, and investment research return derived from the system to date. The system was custom designed for the NTF but can be used at other facilities or for other dynamic measurement/diagnostic applications. Potential commercial uses of the system are described. System capability has been demonstrated for forced response testing and for characterizing and quantifying bias errors for onboard inertial model attitude measurement devices. The system is installed in the NTF control room and has been used successfully for monitoring, recording and analyzing the dynamic response of several model systems tested in the NTF.

A Prototype Educational Delivery System Using Water Quality Monitoring as a Model.

ERIC Educational Resources Information Center

Glazer, Richard B.

This report describes the model educational delivery system used by Ulster County Community College in its water quality monitoring program. The educational delivery system described in the report encompasses the use of behavioral objectives as its foundation and builds upon this foundation to form a complete system whose outcomes can be measured,…

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Biswas, Gautam; Aaseng, Gordon; Narasimhan, Sriam; Pattipati, Krishna

2005-01-01

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Structural Health Monitoring Using High-Density Fiber Optic Strain Sensor and Inverse Finite Element Methods

NASA Technical Reports Server (NTRS)

Vazquez, Sixto L.; Tessler, Alexander; Quach, Cuong C.; Cooper, Eric G.; Parks, Jeffrey; Spangler, Jan L.

2005-01-01

In an effort to mitigate accidents due to system and component failure, NASA s Aviation Safety has partnered with industry, academia, and other governmental organizations to develop real-time, on-board monitoring capabilities and system performance models for early detection of airframe structure degradation. NASA Langley is investigating a structural health monitoring capability that uses a distributed fiber optic strain system and an inverse finite element method for measuring and modeling structural deformations. This report describes the constituent systems that enable this structural monitoring function and discusses results from laboratory tests using the fiber strain sensor system and the inverse finite element method to demonstrate structural deformation estimation on an instrumented test article

A Novel Series Connected Batteries State of High Voltage Safety Monitor System for Electric Vehicle Application

PubMed Central

Jiaxi, Qiang; Lin, Yang; Jianhui, He; Qisheng, Zhou

2013-01-01

Batteries, as the main or assistant power source of EV (Electric Vehicle), are usually connected in series with high voltage to improve the drivability and energy efficiency. Today, more and more batteries are connected in series with high voltage, if there is any fault in high voltage system (HVS), the consequence is serious and dangerous. Therefore, it is necessary to monitor the electric parameters of HVS to ensure the high voltage safety and protect personal safety. In this study, a high voltage safety monitor system is developed to solve this critical issue. Four key electric parameters including precharge, contact resistance, insulation resistance, and remaining capacity are monitored and analyzed based on the equivalent models presented in this study. The high voltage safety controller which integrates the equivalent models and control strategy is developed. By the help of hardware-in-loop system, the equivalent models integrated in the high voltage safety controller are validated, and the online electric parameters monitor strategy is analyzed and discussed. The test results indicate that the high voltage safety monitor system designed in this paper is suitable for EV application. PMID:24194677

A novel series connected batteries state of high voltage safety monitor system for electric vehicle application.

PubMed

Jiaxi, Qiang; Lin, Yang; Jianhui, He; Qisheng, Zhou

2013-01-01

Batteries, as the main or assistant power source of EV (Electric Vehicle), are usually connected in series with high voltage to improve the drivability and energy efficiency. Today, more and more batteries are connected in series with high voltage, if there is any fault in high voltage system (HVS), the consequence is serious and dangerous. Therefore, it is necessary to monitor the electric parameters of HVS to ensure the high voltage safety and protect personal safety. In this study, a high voltage safety monitor system is developed to solve this critical issue. Four key electric parameters including precharge, contact resistance, insulation resistance, and remaining capacity are monitored and analyzed based on the equivalent models presented in this study. The high voltage safety controller which integrates the equivalent models and control strategy is developed. By the help of hardware-in-loop system, the equivalent models integrated in the high voltage safety controller are validated, and the online electric parameters monitor strategy is analyzed and discussed. The test results indicate that the high voltage safety monitor system designed in this paper is suitable for EV application.

Evaluating model accuracy for model-based reasoning

NASA Technical Reports Server (NTRS)

Chien, Steve; Roden, Joseph

1992-01-01

Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2014 CFR

2014-07-01

... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...

40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2012 CFR

2012-07-01

... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...

40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2013 CFR

2013-07-01

... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...

The Aviation System Monitoring and Modeling (ASMM) Project: A Documentation of its History and Accomplishments: 1999-2005

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Editor)

2007-01-01

The Aviation System Monitoring and Modeling (ASMM) Project was one of the projects within NASA s Aviation Safety Program from 1999 through 2005. The objective of the ASMM Project was to develop the technologies to enable the aviation industry to undertake a proactive approach to the management of its system-wide safety risks. The ASMM Project entailed four interdependent elements: (1) Data Analysis Tools Development - develop tools to convert numerical and textual data into information; (2) Intramural Monitoring - test and evaluate the data analysis tools in operational environments; (3) Extramural Monitoring - gain insight into the aviation system performance by surveying its front-line operators; and (4) Modeling and Simulations - provide reliable predictions of the system-wide hazards, their causal factors, and their operational risks that may result from the introduction of new technologies, new procedures, or new operational concepts. This report is a documentation of the history of this highly successful project and of its many accomplishments and contributions to improved safety of the aviation system.

Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network.

PubMed

Şimşir, Mehmet; Bayır, Raif; Uyaroğlu, Yılmaz

2016-01-01

Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors) encounter previously defined and undefined faults under operation. It may inevitably lead to the interruption of the electromechanical system operation; hence, economic losses take place at certain times. Therefore, in order to maintain system operation sustainability, the motor should be precisely monitored and the faults are diagnosed considering various significant motor parameters. In this study, the artificial feedforward backpropagation neural network approach is proposed to real-time monitor and diagnose the faults of the hub motor by measuring seven main system parameters. So as to construct a necessary model, we trained the model, using a data set consisting of 4160 samples where each has 7 parameters, by the MATLAB environment until the best model is obtained. The results are encouraging and meaningful for the specific motor and the developed model may be applicable to other types of hub motors. The prosperous model of the whole system was embedded into Arduino Due microcontroller card and the mobile real-time monitoring and fault diagnosis system prototype for hub motor was designed and manufactured.

Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network

PubMed Central

Şimşir, Mehmet; Bayır, Raif; Uyaroğlu, Yılmaz

2016-01-01

Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors) encounter previously defined and undefined faults under operation. It may inevitably lead to the interruption of the electromechanical system operation; hence, economic losses take place at certain times. Therefore, in order to maintain system operation sustainability, the motor should be precisely monitored and the faults are diagnosed considering various significant motor parameters. In this study, the artificial feedforward backpropagation neural network approach is proposed to real-time monitor and diagnose the faults of the hub motor by measuring seven main system parameters. So as to construct a necessary model, we trained the model, using a data set consisting of 4160 samples where each has 7 parameters, by the MATLAB environment until the best model is obtained. The results are encouraging and meaningful for the specific motor and the developed model may be applicable to other types of hub motors. The prosperous model of the whole system was embedded into Arduino Due microcontroller card and the mobile real-time monitoring and fault diagnosis system prototype for hub motor was designed and manufactured. PMID:26819590

Monitoring is not enough: on the need for a model-based approach to migratory bird management

USGS Publications Warehouse

Nichols, J.D.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

2000-01-01

Informed management requires information about system state and about effects of potential management actions on system state. Population monitoring can provide the needed information about system state, as well as information that can be used to investigate effects of management actions. Three methods for investigating effects of management on bird populations are (1) retrospective analysis, (2) formal experimentation and constrained-design studies, and (3) adaptive management. Retrospective analyses provide weak inferences, regardless of the quality of the monitoring data. The active use of monitoring data in experimental or constrained-design studies or in adaptive management is recommended. Under both approaches, learning occurs via the comparison of estimates from the monitoring program with predictions from competing management models.

Health monitoring system for transmission shafts based on adaptive parameter identification

NASA Astrophysics Data System (ADS)

Souflas, I.; Pezouvanis, A.; Ebrahimi, K. M.

2018-05-01

A health monitoring system for a transmission shaft is proposed. The solution is based on the real-time identification of the physical characteristics of the transmission shaft i.e. stiffness and damping coefficients, by using a physical oriented model and linear recursive identification. The efficacy of the suggested condition monitoring system is demonstrated on a prototype transient engine testing facility equipped with a transmission shaft capable of varying its physical properties. Simulation studies reveal that coupling shaft faults can be detected and isolated using the proposed condition monitoring system. Besides, the performance of various recursive identification algorithms is addressed. The results of this work recommend that the health status of engine dynamometer shafts can be monitored using a simple lumped-parameter shaft model and a linear recursive identification algorithm which makes the concept practically viable.

40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?

Code of Federal Regulations, 2013 CFR

2013-07-01

... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the... systems for sulfur dioxide, nitrogen oxides, and carbon monoxide to demonstrate continuous compliance with...

40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?

Code of Federal Regulations, 2014 CFR

2014-07-01

... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the... systems for sulfur dioxide, nitrogen oxides, and carbon monoxide to demonstrate continuous compliance with...

40 CFR 60.1725 - How are the data from the continuous emission monitoring systems used?

Code of Federal Regulations, 2012 CFR

2012-07-01

... emission monitoring systems used? 60.1725 Section 60.1725 Protection of Environment ENVIRONMENTAL... Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1725 How are the data from the... systems for sulfur dioxide, nitrogen oxides, and carbon monoxide to demonstrate continuous compliance with...

Online Monitoring System of Air Distribution in Pulverized Coal-Fired Boiler Based on Numerical Modeling

NASA Astrophysics Data System (ADS)

Żymełka, Piotr; Nabagło, Daniel; Janda, Tomasz; Madejski, Paweł

2017-12-01

Balanced distribution of air in coal-fired boiler is one of the most important factors in the combustion process and is strongly connected to the overall system efficiency. Reliable and continuous information about combustion airflow and fuel rate is essential for achieving optimal stoichiometric ratio as well as efficient and safe operation of a boiler. Imbalances in air distribution result in reduced boiler efficiency, increased gas pollutant emission and operating problems, such as corrosion, slagging or fouling. Monitoring of air flow trends in boiler is an effective method for further analysis and can help to appoint important dependences and start optimization actions. Accurate real-time monitoring of the air distribution in boiler can bring economical, environmental and operational benefits. The paper presents a novel concept for online monitoring system of air distribution in coal-fired boiler based on real-time numerical calculations. The proposed mathematical model allows for identification of mass flow rates of secondary air to individual burners and to overfire air (OFA) nozzles. Numerical models of air and flue gas system were developed using software for power plant simulation. The correctness of the developed model was verified and validated with the reference measurement values. The presented numerical model for real-time monitoring of air distribution is capable of giving continuous determination of the complete air flows based on available digital communication system (DCS) data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, K.; Tsai, H.; Decision and Information Sciences

The technical basis for extending the Model 9977 shipping package periodic maintenance beyond the one-year interval to a maximum of five years is based on the performance of the O-ring seals and the environmental conditions. The DOE Packaging Certification Program (PCP) has tasked Argonne National Laboratory to develop a Radio-Frequency Identification (RFID) temperature monitoring system for use by the facility personnel at DAF/NTS. The RFID temperature monitoring system, depicted in the figure below, consists of the Mk-1 RFId tags, a reader, and a control computer mounted on a mobile platform that can operate as a stand-alone system, or it canmore » be connected to the local IT network. As part of the Conditions of Approval of the CoC, the user must complete the prescribed training to become qualified and be certified for operation of the RFID temperature monitoring system. The training course will be administered by Argonne National Laboratory on behalf of the Headquarters Certifying Official. This is a complete documentation package for the RFID temperature monitoring system of the Model 9977 packagings at NTS. The documentation package will be used for training and certification. The table of contents are: Acceptance Testing Procedure of MK-1 RFID Tags for DOE/EM Nuclear Materials Management Applications; Acceptance Testing Result of MK-1 RFID Tags for DOE/EM Nuclear Materials Management Applications; Performance Test of the Single Bolt Seal Sensor for the Model 9977 Packaging; Calibration of Built-in Thermistors in RFID Tags for Nevada Test Site; Results of Calibration of Built-in Thermistors in RFID Tags; Results of Thermal Calibration of Second Batch of MK-I RFID Tags; Procedure for Installing and Removing MK-1 RFID Tag on Model 9977 Drum; User Guide for RFID Reader and Software for Temperature Monitoring of Model 9977 Drums at NTS; Software Quality Assurance Plan (SQAP) for the ARG-US System; Quality Category for the RFID Temperature Monitoring System; The Documentation Package for the RFID Temperature Monitoring System; Software Test Plan and Results for ARG-US OnSite; Configuration Management Plan (CMP) for the ARG-US System; Requirements Management Plan for the ARG-US System; and Design Management Plan for ARG-US.« less

Environmental exposure modeling and monitoring of human pharmaceutical concentrations in the environment

USGS Publications Warehouse

Versteeg, D.J.; Alder, A. C.; Cunningham, V. L.; Kolpin, D.W.; Murray-Smith, R.; Ternes, T.

2005-01-01

Human pharmaceuticals are receiving increased attention as environmental contaminants. This is due to their biological activity and the number of monitoring programs focusing on analysis of these compounds in various environmental media and compartments. Risk assessments are needed to understand the implications of reported concentrations; a fundamental part of the risk assessment is an assessment of environmental exposures. The purpose of this chapter is to provide guidance on the use of predictive tools (e.g., models) and monitoring data in exposure assessments for pharmaceuticals in the environment. Methods to predict environmental concentrations from equations based on first principles are presented. These equations form the basis of existing GIS (geographic information systems)-based systems for understanding the spatial distribution of pharmaceuticals in the environment. The pharmaceutical assessment and transport (PhATE), georeferenced regional exposure assessment tool for European rivers (GREAT-ER), and geographical information system (GIS)-ROUT models are reviewed and recommendations are provided concerning the design and execution of monitoring studies. Model predictions and monitoring data are compared to evaluate the relative utility of each approach in environmental exposure assessments. In summary, both models and monitoring data can be used to define representative exposure concentrations of pharmaceuticals in the environment in support of environmental risk assessments.

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

PubMed

Dėdelė, Audrius; Miškinytė, Auksė

2015-09-01

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

Monitoring Distributed Systems: A Relational Approach.

DTIC Science & Technology

1982-12-01

relationship, and time. The first two have been are modeled directly in the relational model. The third is perhaps the most fundamental , for without the system ...of another, newly created file. The approach adopted here applies to object-based operatin systems , and will support capability addressing at the...in certainties. -- Francis Bacon, in The Advancement of Learning The thesis of this research is that monitoring distributed systems is fundamentally a

A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter. Appendix D

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Hindson, William; Sanderfer, Dwight; Deb, Somnath; Domagala, Chuck

2001-01-01

Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.

Modeling of Global BEAM Structure for Evaluation of MMOD Impacts to Support Development of a Health Monitoring System

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Vassilakos, Gregory J.

2015-01-01

This report summarizes the initial modeling of the global response of the Bigelow Expandable Activity Module (BEAM) to micrometeorite and orbital debris(MMOD) impacts using a structural, nonlinear, transient dynamic, finite element code. These models complement the on-orbit deployment of the Distributed Impact Detection System (DIDS) to support structural health monitoring studies. Two global models were developed. The first focused exclusively on impacts on the soft-goods (fabric-envelop) portion of BEAM. The second incorporates the bulkhead to support understanding of bulkhead impacts. These models were exercised for random impact locations and responses monitored at the on-orbit sensor locations. The report concludes with areas for future study.

Synergy of Earth Observation and In-Situ Monitoring Data for Flood Hazard Early Warning System

NASA Astrophysics Data System (ADS)

Brodsky, Lukas; Kodesova, Radka; Spazierova, Katerina

2010-12-01

In this study, we demonstrate synergy of EO and in-situ monitoring data for early warning flood hazard system in the Czech Republic developed within ESA PECS project FLOREO. The development of the demonstration system is oriented to support existing monitoring activities, especially snow melt and surface water runoff contributing to flooding events. The system consists of two main parts accordingly, the first is snow cover and snow melt monitoring driven mainly by EO data and the other is surface water runoff modeling and monitoring driven by synergy of in-situ and EO data.

Protocol and Demonstrations of Probabilistic Reliability Assessment for Structural Health Monitoring Systems (Preprint)

DTIC Science & Technology

2011-11-01

assessment to quality of localization/characterization estimates. This protocol includes four critical components: (1) a procedure to identify the...critical factors impacting SHM system performance; (2) a multistage or hierarchical approach to SHM system validation; (3) a model -assisted evaluation...Lindgren, E. A ., Buynak, C. F., Steffes, G., Derriso, M., “ Model -assisted Probabilistic Reliability Assessment for Structural Health Monitoring

Health Monitoring of a Planetary Rover Using Hybrid Particle Petri Nets

NASA Technical Reports Server (NTRS)

Gaudel, Quentin; Ribot, Pauline; Chanthery, Elodie; Daigle, Matthew J.

2016-01-01

This paper focuses on the application of a Petri Net-based diagnosis method on a planetary rover prototype.The diagnosis is performed by using a model-based method in the context of health management of hybrid systems.In system health management, the diagnosis task aims at determining the current health state of a system and the fault occurrences that lead to this state. The Hybrid Particle Petri Nets (HPPN) formalism is used to model hybrid systems behavior and degradation, and to define the generation of diagnosers to monitor the health states of such systems under uncertainty. At any time, the HPPN-based diagnoser provides the current diagnosis represented by a distribution of beliefs over the health states. The health monitoring methodology is demonstrated on the K11 rover. A hybrid model of the K11 is proposed and experimental results show that the approach is robust to real system data and constraints.

Discipline Monitoring System: A School Self-Study Project for Montgomery County Public Schools.

ERIC Educational Resources Information Center

Richardson, William M.; Splaine, Pam

The Discipline Monitoring System (DMS) is a computer-assisted model allowing individual secondary schools to analyze their disciplinary actions. The Montgomery County Public Schools (Maryland) adopted this model to manipulate the following data: who is suspended, who is referred, who makes referrals, characteristics of these persons, and events…

76 FR 43906 - Approval and Promulgation of State Implementation Plan Revisions; Infrastructure Requirements for...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-22

... emissions inventories, monitoring, and modeling, to assure attainment and maintenance of the standards... NAAQS required the deployment of a system of new monitors to measure ambient levels of that new... requirements, including emissions inventories, monitoring, and modeling to assure attainment and maintenance of...

[Theoretical model study about the application risk of high risk medical equipment].

PubMed

Shang, Changhao; Yang, Fenghui

2014-11-01

Research for establishing a risk monitoring theoretical model of high risk medical equipment at applying site. Regard the applying site as a system which contains some sub-systems. Every sub-system consists of some risk estimating indicators. After quantizing of each indicator, the quantized values are multiplied with corresponding weight and then the products are accumulated. Hence, the risk estimating value of each subsystem is attained. Follow the calculating method, the risk estimating values of each sub-system are multiplied with corresponding weights and then the product is accumulated. The cumulative sum is the status indicator of the high risk medical equipment at applying site. The status indicator reflects the applying risk of the medical equipment at applying site. Establish a risk monitoring theoretical model of high risk medical equipment at applying site. The model can monitor the applying risk of high risk medical equipment at applying site dynamically and specially.

Analyses of the most influential factors for vibration monitoring of planetary power transmissions in pellet mills by adaptive neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Milovančević, Miloš; Nikolić, Vlastimir; Anđelković, Boban

2017-01-01

Vibration-based structural health monitoring is widely recognized as an attractive strategy for early damage detection in civil structures. Vibration monitoring and prediction is important for any system since it can save many unpredictable behaviors of the system. If the vibration monitoring is properly managed, that can ensure economic and safe operations. Potentials for further improvement of vibration monitoring lie in the improvement of current control strategies. One of the options is the introduction of model predictive control. Multistep ahead predictive models of vibration are a starting point for creating a successful model predictive strategy. For the purpose of this article, predictive models of are created for vibration monitoring of planetary power transmissions in pellet mills. The models were developed using the novel method based on ANFIS (adaptive neuro fuzzy inference system). The aim of this study is to investigate the potential of ANFIS for selecting the most relevant variables for predictive models of vibration monitoring of pellet mills power transmission. The vibration data are collected by PIC (Programmable Interface Controller) microcontrollers. The goal of the predictive vibration monitoring of planetary power transmissions in pellet mills is to indicate deterioration in the vibration of the power transmissions before the actual failure occurs. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of vibration monitoring. It was also used to select the minimal input subset of variables from the initial set of input variables - current and lagged variables (up to 11 steps) of vibration. The obtained results could be used for simplification of predictive methods so as to avoid multiple input variables. It was preferable to used models with less inputs because of overfitting between training and testing data. While the obtained results are promising, further work is required in order to get results that could be directly applied in practice.

Ecological monitoring in a discrete-time prey-predator model.

PubMed

Gámez, M; López, I; Rodríguez, C; Varga, Z; Garay, J

2017-09-21

The paper is aimed at the methodological development of ecological monitoring in discrete-time dynamic models. In earlier papers, in the framework of continuous-time models, we have shown how a systems-theoretical methodology can be applied to the monitoring of the state process of a system of interacting populations, also estimating certain abiotic environmental changes such as pollution, climatic or seasonal changes. In practice, however, there may be good reasons to use discrete-time models. (For instance, there may be discrete cycles in the development of the populations, or observations can be made only at discrete time steps.) Therefore the present paper is devoted to the development of the monitoring methodology in the framework of discrete-time models of population ecology. By monitoring we mean that, observing only certain component(s) of the system, we reconstruct the whole state process. This may be necessary, e.g., when in a complex ecosystem the observation of the densities of certain species is impossible, or too expensive. For the first presentation of the offered methodology, we have chosen a discrete-time version of the classical Lotka-Volterra prey-predator model. This is a minimal but not trivial system where the methodology can still be presented. We also show how this methodology can be applied to estimate the effect of an abiotic environmental change, using a component of the population system as an environmental indicator. Although this approach is illustrated in a simplest possible case, it can be easily extended to larger ecosystems with several interacting populations and different types of abiotic environmental effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model-based monitoring of stormwater runoff quality.

PubMed

Birch, Heidi; Vezzaro, Luca; Mikkelsen, Peter Steen

2013-01-01

Monitoring of micropollutants (MP) in stormwater is essential to evaluate the impacts of stormwater on the receiving aquatic environment. The aim of this study was to investigate how different strategies for monitoring of stormwater quality (combining a model with field sampling) affect the information obtained about MP discharged from the monitored system. A dynamic stormwater quality model was calibrated using MP data collected by automatic volume-proportional sampling and passive sampling in a storm drainage system on the outskirts of Copenhagen (Denmark) and a 10-year rain series was used to find annual average (AA) and maximum event mean concentrations. Use of this model reduced the uncertainty of predicted AA concentrations compared to a simple stochastic method based solely on data. The predicted AA concentration, obtained by using passive sampler measurements (1 month installation) for calibration of the model, resulted in the same predicted level but with narrower model prediction bounds than by using volume-proportional samples for calibration. This shows that passive sampling allows for a better exploitation of the resources allocated for stormwater quality monitoring.

Real-time human collaboration monitoring and intervention

DOEpatents

Merkle, Peter B.; Johnson, Curtis M.; Jones, Wendell B.; Yonas, Gerold; Doser, Adele B.; Warner, David J.

2010-07-13

A method of and apparatus for monitoring and intervening in, in real time, a collaboration between a plurality of subjects comprising measuring indicia of physiological and cognitive states of each of the plurality of subjects, communicating the indicia to a monitoring computer system, with the monitoring computer system, comparing the indicia with one or more models of previous collaborative performance of one or more of the plurality of subjects, and with the monitoring computer system, employing the results of the comparison to communicate commands or suggestions to one or more of the plurality of subjects.

Application of Multiregressive Linear Models, Dynamic Kriging Models and Neural Network Models to Predictive Maintenance of Hydroelectric Power Systems

NASA Astrophysics Data System (ADS)

Lucifredi, A.; Mazzieri, C.; Rossi, M.

2000-05-01

Since the operational conditions of a hydroelectric unit can vary within a wide range, the monitoring system must be able to distinguish between the variations of the monitored variable caused by variations of the operation conditions and those due to arising and progressing of failures and misoperations. The paper aims to identify the best technique to be adopted for the monitoring system. Three different methods have been implemented and compared. Two of them use statistical techniques: the first, the linear multiple regression, expresses the monitored variable as a linear function of the process parameters (independent variables), while the second, the dynamic kriging technique, is a modified technique of multiple linear regression representing the monitored variable as a linear combination of the process variables in such a way as to minimize the variance of the estimate error. The third is based on neural networks. Tests have shown that the monitoring system based on the kriging technique is not affected by some problems common to the other two models e.g. the requirement of a large amount of data for their tuning, both for training the neural network and defining the optimum plane for the multiple regression, not only in the system starting phase but also after a trivial operation of maintenance involving the substitution of machinery components having a direct impact on the observed variable. Or, in addition, the necessity of different models to describe in a satisfactory way the different ranges of operation of the plant. The monitoring system based on the kriging statistical technique overrides the previous difficulties: it does not require a large amount of data to be tuned and is immediately operational: given two points, the third can be immediately estimated; in addition the model follows the system without adapting itself to it. The results of the experimentation performed seem to indicate that a model based on a neural network or on a linear multiple regression is not optimal, and that a different approach is necessary to reduce the amount of work during the learning phase using, when available, all the information stored during the initial phase of the plant to build the reference baseline, elaborating, if it is the case, the raw information available. A mixed approach using the kriging statistical technique and neural network techniques could optimise the result.

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Markerless video analysis for movement quantification in pediatric epilepsy monitoring.

PubMed

Lu, Haiping; Eng, How-Lung; Mandal, Bappaditya; Chan, Derrick W S; Ng, Yen-Ling

2011-01-01

This paper proposes a markerless video analytic system for quantifying body part movements in pediatric epilepsy monitoring. The system utilizes colored pajamas worn by a patient in bed to extract body part movement trajectories, from which various features can be obtained for seizure detection and analysis. Hence, it is non-intrusive and it requires no sensor/marker to be attached to the patient's body. It takes raw video sequences as input and a simple user-initialization indicates the body parts to be examined. In background/foreground modeling, Gaussian mixture models are employed in conjunction with HSV-based modeling. Body part detection follows a coarse-to-fine paradigm with graph-cut-based segmentation. Finally, body part parameters are estimated with domain knowledge guidance. Experimental studies are reported on sequences captured in an Epilepsy Monitoring Unit at a local hospital. The results demonstrate the feasibility of the proposed system in pediatric epilepsy monitoring and seizure detection.

Object-oriented model-driven control

NASA Technical Reports Server (NTRS)

Drysdale, A.; Mcroberts, M.; Sager, J.; Wheeler, R.

1994-01-01

A monitoring and control subsystem architecture has been developed that capitalizes on the use of modeldriven monitoring and predictive control, knowledge-based data representation, and artificial reasoning in an operator support mode. We have developed an object-oriented model of a Controlled Ecological Life Support System (CELSS). The model based on the NASA Kennedy Space Center CELSS breadboard data, tracks carbon, hydrogen, and oxygen, carbodioxide, and water. It estimates and tracks resorce-related parameters such as mass, energy, and manpower measurements such as growing area required for balance. We are developing an interface with the breadboard systems that is compatible with artificial reasoning. Initial work is being done on use of expert systems and user interface development. This paper presents an approach to defining universally applicable CELSS monitor and control issues, and implementing appropriate monitor and control capability for a particular instance: the KSC CELSS Breadboard Facility.

Systemic Case Formulation, Individualized Process Monitoring, and State Dynamics in a Case of Dissociative Identity Disorder.

PubMed

Schiepek, Günter K; Stöger-Schmidinger, Barbara; Aichhorn, Wolfgang; Schöller, Helmut; Aas, Benjamin

2016-01-01

Objective: The aim of this case report is to demonstrate the feasibility of a systemic procedure (synergetic process management) including modeling of the idiographic psychological system and continuous high-frequency monitoring of change dynamics in a case of dissociative identity disorder. The psychotherapy was realized in a day treatment center with a female client diagnosed with borderline personality disorder (BPD) and dissociative identity disorder. Methods: A three hour long co-creative session at the beginning of the treatment period allowed for modeling the systemic network of the client's dynamics of cognitions, emotions, and behavior. The components (variables) of this idiographic system model (ISM) were used to create items for an individualized process questionnaire for the client. The questionnaire was administered daily through an internet-based monitoring tool (Synergetic Navigation System, SNS), to capture the client's individual change process continuously throughout the therapy and after-care period. The resulting time series were reflected by therapist and client in therapeutic feedback sessions. Results: For the client it was important to see how the personality states dominating her daily life were represented by her idiographic system model and how the transitions between each state could be explained and understood by the activating and inhibiting relations between the cognitive-emotional components of that system. Continuous monitoring of her cognitions, emotions, and behavior via SNS allowed for identification of important triggers, dynamic patterns, and psychological mechanisms behind seemingly erratic state fluctuations. These insights enabled a change in management of the dynamics and an intensified trauma-focused therapy. Conclusion: By making use of the systemic case formulation technique and subsequent daily online monitoring, client and therapist continuously refer to detailed visualizations of the mental and behavioral network and its dynamics (e.g., order transitions). Effects on self-related information processing, on identity development, and toward a more pronounced autonomy in life (instead of feeling helpless against the chaoticity of state dynamics) were evident in the presented case and documented by the monitoring system.

Use of microcomputers for planning and managing silviculture habitat relationships.

Treesearch

B.G. Marcot; R.S. McNay; R.E. Page

1988-01-01

Microcomputers aid in monitoring, modeling, and decision support for integrating objectives of silviculture and wildlife habitat management. Spreadsheets, data bases, statistics, and graphics programs are described for use in monitoring. Stand growth models, modeling languages, area and geobased information systems, and optimization models are discussed for use in...

Infrared Laser System for Extended Area Monitoring of Air Pollution

NASA Technical Reports Server (NTRS)

Snowman, L. R.; Gillmeister, R. J.

1971-01-01

An atmospheric pollution monitoring system using a spectrally scanning laser has been developed by the General Electric Company. This paper will report on an evaluation of a breadboard model, and will discuss applications of the concept to various ambient air monitoring situations. The system is adaptable to other tunable lasers. Operating in the middle infrared region, the system uses retroreflectors to measure average concentrations over long paths at low, safe power levels. The concept shows promise of meeting operational needs in ambient air monitoring and providing new data for atmospheric research.

FPGA-based firmware model for extended measurement systems with data quality monitoring

NASA Astrophysics Data System (ADS)

Wojenski, A.; Pozniak, K. T.; Mazon, D.; Chernyshova, M.

2017-08-01

Modern physics experiments requires construction of advanced, modular measurement systems for data processing and registration purposes. Components are often designed in one of the common mechanical and electrical standards, e.g. VME or uTCA. The paper is focused on measurement systems using FPGAs as data processing blocks, especially for plasma diagnostics using GEM detectors with data quality monitoring aspects. In the article is proposed standardized model of HDL FPGA firmware implementation, for use in a wide range of different measurement system. The effort was made in term of flexible implementation of data quality monitoring along with source data dynamic selection. In the paper is discussed standard measurement system model followed by detailed model of FPGA firmware for modular measurement systems. Considered are both: functional blocks and data buses. In the summary, necessary blocks and signal lines are described. Implementation of firmware following the presented rules should provide modular design, with ease of change different parts of it. The key benefit is construction of universal, modular HDL design, that can be applied in different measurement system with simple adjustments.

On the matter of the reliability of the chemical monitoring system based on the modern control and monitoring devices

NASA Astrophysics Data System (ADS)

Andriushin, A. V.; Dolbikova, N. S.; Kiet, S. V.; Merzlikina, E. I.; Nikitina, I. S.

2017-11-01

The reliability of the main equipment of any power station depends on the correct water chemistry. In order to provide it, it is necessary to monitor the heat carrier quality, which, in its turn, is provided by the chemical monitoring system. Thus, the monitoring system reliability plays an important part in providing reliability of the main equipment. The monitoring system reliability is determined by the reliability and structure of its hardware and software consisting of sensors, controllers, HMI and so on [1,2]. Workers of a power plant dealing with the measuring equipment must be informed promptly about any breakdowns in the monitoring system, in this case they are able to remove the fault quickly. A computer consultant system for personnel maintaining the sensors and other chemical monitoring equipment can help to notice faults quickly and identify their possible causes. Some technical solutions for such a system are considered in the present paper. The experimental results were obtained on the laboratory and experimental workbench representing a physical model of a part of the chemical monitoring system.

A comparative analysis of modeled and monitored ambient hazardous air pollutants in Texas: a novel approach using concordance correlation.

PubMed

Lupo, Philip J; Symanski, Elaine

2009-11-01

Often, in studies evaluating the health effects of hazardous air pollutants (HAPs), researchers rely on ambient air levels to estimate exposure. Two potential data sources are modeled estimates from the U.S. Environmental Protection Agency (EPA) Assessment System for Population Exposure Nationwide (ASPEN) and ambient air pollutant measurements from monitoring networks. The goal was to conduct comparisons of modeled and monitored estimates of HAP levels in the state of Texas using traditional approaches and a previously unexploited method, concordance correlation analysis, to better inform decisions regarding agreement. Census tract-level ASPEN estimates and monitoring data for all HAPs throughout Texas, available from the EPA Air Quality System, were obtained for 1990, 1996, and 1999. Monitoring sites were mapped to census tracts using U.S. Census data. Exclusions were applied to restrict the monitored data to measurements collected using a common sampling strategy with minimal missing values over time. Comparisons were made for 28 HAPs in 38 census tracts located primarily in urban areas throughout Texas. For each pollutant and by year of assessment, modeled and monitored air pollutant annual levels were compared using standard methods (i.e., ratios of model-to-monitor annual levels). Concordance correlation analysis was also used, which assesses linearity and agreement while providing a formal method of statistical inference. Forty-eight percent of the median model-to-monitor values fell between 0.5 and 2, whereas only 17% of concordance correlation coefficients were significant and greater than 0.5. On the basis of concordance correlation analysis, the findings indicate there is poorer agreement when compared with the previously applied ad hoc methods to assess comparability between modeled and monitored levels of ambient HAPs.

Physical factors that influence patients' privacy perception toward a psychiatric behavioral monitoring system: a qualitative study.

PubMed

Zakaria, Nasriah; Ramli, Rusyaizila

2018-01-01

Psychiatric patients have privacy concerns when it comes to technology intervention in the hospital setting. In this paper, we present scenarios for psychiatric behavioral monitoring systems to be placed in psychiatric wards to understand patients' perception regarding privacy. Psychiatric behavioral monitoring refers to systems that are deemed useful in measuring clinical outcomes, but little research has been done on how these systems will impact patients' privacy. We conducted a case study in one teaching hospital in Malaysia. We investigated the physical factors that influence patients' perceived privacy with respect to a psychiatric monitoring system. The eight physical factors identified from the information system development privacy model, a comprehensive model for designing a privacy-sensitive information system, were adapted in this research. Scenario-based interviews were conducted with 25 patients in a psychiatric ward for 3 months. Psychiatric patients were able to share how physical factors influence their perception of privacy. Results show how patients responded to each of these dimensions in the context of a psychiatric behavioral monitoring system. Some subfactors under physical privacy are modified to reflect the data obtained in the interviews. We were able to capture the different physical factors that influence patient privacy.

The KATE shell: An implementation of model-based control, monitor and diagnosis

NASA Technical Reports Server (NTRS)

Cornell, Matthew

1987-01-01

The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

Monitoring Effective Doses Received By Air Crews With A Space Weather Application

NASA Astrophysics Data System (ADS)

Lantos, P.

To fulfil new requirements of the European Community concerning monitoring of effective doses received by air crews, the French Aviation Authority has developed an operational system called Sievert. The SIEVERT system is analysed as an exam- ple of Space Weather application. One of its characteristics is to calculate the dose received on-board each flight on the basis of the specific and detailled flight given by companies. Operational models will be used. As input to the models, the system needs monitoring of galactic cosmic rays and of solar flare particles. The French neu- tron monitors located in Kerguelen Islands (South Indian Ocean) and Terre Adélie (Antarctica) will be used for this purpose. Particular attention will be devoted to evo- lution of the system in conjunction with new measurements available in the frame of a permanent validation process.

78 FR 14450 - Approval and Promulgation of Implementation Plans; Tennessee; 110(a)(1) and (2) Infrastructure...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-06

... to address basic SIP requirements, including emissions inventories, monitoring, and modeling to... basic structural SIP elements such as modeling, monitoring, and emissions inventories that are designed...): Emission limits and other control measures. 110(a)(2)(B): Ambient air quality monitoring/data system. 110(a...

Novel diffuse optics system for continuous tissue viability monitoring: extended recovery in vivo testing in a porcine flap model

NASA Astrophysics Data System (ADS)

Lee, Seung Yup; Pakela, Julia M.; Hedrick, Taylor L.; Vishwanath, Karthik; Helton, Michael C.; Chung, Yooree; Kolodziejski, Noah J.; Stapels, Christopher J.; McAdams, Daniel R.; Fernandez, Daniel E.; Christian, James F.; O'Reilly, Jameson; Farkas, Dana; Ward, Brent B.; Feinberg, Stephen E.; Mycek, Mary-Ann

2017-02-01

In reconstructive surgery, tissue perfusion/vessel patency is critical to the success of microvascular free tissue flaps. Early detection of flap failure secondary to compromise of vascular perfusion would significantly increase the chances of flap salvage. We have developed a compact, clinically-compatible monitoring system to enable automated, minimally-invasive, continuous, and quantitative assessment of flap viability/perfusion. We tested the system's continuous monitoring capability during extended non-recovery surgery using an in vivo porcine free flap model. Initial results indicated that the system could assess flap viability/perfusion in a quantitative and continuous manner. With proven performance, the compact form constructed with cost-effective components would make this system suitable for clinical translation.

Towards Comprehensive Variation Models for Designing Vehicle Monitoring Systems

NASA Technical Reports Server (NTRS)

McAdams, Daniel A.; Tumer, Irem Y.; Clancy, Daniel (Technical Monitor)

2002-01-01

When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes in a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. This crucial roadblock makes their implementation in real vehicles (e.g., helicopter transmissions and aircraft engines) difficult, making their operation costly and unreliable. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. Using such models, we develop a methodology to account for design and manufacturing variations, and explore the changes in the vibration response to determine its stochastic nature. We explore the potential of the methodology using a nonlinear cam-follower model, where the spring stiffness values are assumed to follow a normal distribution. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle monitoring systems.

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Toward Failure Modeling In Complex Dynamic Systems: Impact of Design and Manufacturing Variations

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; McAdams, Daniel A.; Clancy, Daniel (Technical Monitor)

2001-01-01

When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes during a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the. modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle vibration monitoring systems.

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

40 CFR 60.1735 - Am I exempt from any appendix B or appendix F requirements to evaluate continuous emission...

Code of Federal Regulations, 2012 CFR

2012-07-01

... appendix F requirements to evaluate continuous emission monitoring systems? 60.1735 Section 60.1735... Combustion Units Constructed on or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1735... to also evaluate your oxygen (or carbon dioxide) continuous emission monitoring system. Therefore...

A Model for Field Deployment of Wireless Sensor Networks (WSNs) within the Domain of Microclimate Habitat Monitoring

ERIC Educational Resources Information Center

Sanborn, Mark

2011-01-01

Wireless sensor networks (WSNs) represent a class of miniaturized information systems designed to monitor physical environments. These smart monitoring systems form collaborative networks utilizing autonomous sensing, data-collection, and processing to provide real-time analytics of observed environments. As a fundamental research area in…

Strategic system development toward biofuel, desertification, and crop production monitoring in continental scales using satellite-based photosynthesis models

NASA Astrophysics Data System (ADS)

Kaneko, Daijiro

2013-10-01

The author regards fundamental root functions as underpinning photosynthesis activities by vegetation and as affecting environmental issues, grain production, and desertification. This paper describes the present development of monitoring and near real-time forecasting of environmental projects and crop production by approaching established operational monitoring step-by-step. The author has been developing a thematic monitoring structure (named RSEM system) which stands on satellite-based photosynthesis models over several continents for operational supports in environmental fields mentioned above. Validation methods stand not on FLUXNET but on carbon partitioning validation (CPV). The models demand continuing parameterization. The entire frame system has been built using Reanalysis meteorological data, but model accuracy remains insufficient except for that of paddy rice. The author shall accomplish the system that incorporates global environmental forces. Regarding crop production applications, industrialization in developing countries achieved through direct investment by economically developed nations raises their income, resulting in increased food demand. Last year, China began to import rice as it had in the past with grains of maize, wheat, and soybeans. Important agro-potential countries make efforts to cultivate new crop lands in South America, Africa, and Eastern Europe. Trends toward less food sustainability and stability are continuing, with exacerbation by rapid social and climate changes. Operational monitoring of carbon sequestration by herbaceous and bore plants converges with efforts at bio-energy, crop production monitoring, and socio-environmental projects such as CDM A/R, combating desertification, and bio-diversity.

Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

NASA Astrophysics Data System (ADS)

Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

2013-09-01

In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making.

PubMed

Peterson, James T; Freeman, Mary C

2016-12-01

Stream ecosystems provide multiple, valued services to society, including water supply, waste assimilation, recreation, and habitat for diverse and productive biological communities. Managers striving to sustain these services in the face of changing climate, land uses, and water demands need tools to assess the potential effectiveness of alternative management actions, and often, the resulting tradeoffs between competing objectives. Integrating predictive modeling with monitoring data in an adaptive management framework provides a process by which managers can reduce model uncertainties and thus improve the scientific bases for subsequent decisions. We demonstrate an integration of monitoring data with a dynamic, metapopulation model developed to assess effects of streamflow alteration on fish occupancy in a southeastern US stream system. Although not extensive (collected over three years at nine sites), the monitoring data allowed us to assess and update support for alternative population dynamic models using model probabilities and Bayes rule. We then use the updated model weights to estimate the effects of water withdrawal on stream fish communities and demonstrate how feedback in the form of monitoring data can be used to improve water resource decision making. We conclude that investment in more strategic monitoring, guided by a priori model predictions under alternative hypotheses and an adaptive sampling design, could substantially improve the information available to guide decision-making and management for ecosystem services from lotic systems. Published by Elsevier Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perkins, Casey J.; Brigantic, Robert T.; Keating, Douglas H.

There is a need to develop and demonstrate technical approaches for verifying potential future agreements to limit and reduce total warhead stockpiles. To facilitate this aim, warhead monitoring systems employ both concepts of operations (CONOPS) and technologies. A systems evaluation approach can be used to assess the relative performance of CONOPS and technologies in their ability to achieve monitoring system objectives which include: 1) confidence that a treaty accountable item (TAI) initialized by the monitoring system is as declared; 2) confidence that there is no undetected diversion from the monitoring system; and 3) confidence that a TAI is dismantled asmore » declared. Although there are many quantitative methods that can be used to assess system performance for the above objectives, this paper focuses on a simulation perspective primarily for the ability to support analysis of the probabilities that are used to define operating characteristics of CONOPS and technologies. This paper describes a discrete event simulation (DES) model, comprised of three major sub-models: including TAI lifecycle flow, monitoring activities, and declaration behavior. The DES model seeks to capture all processes and decision points associated with the progressions of virtual TAIs, with notional characteristics, through the monitoring system from initialization through dismantlement. The simulation updates TAI progression (i.e., whether the generated test objects are accepted and rejected at the appropriate points) all the way through dismantlement. Evaluation of TAI lifecycles primarily serves to assess how the order, frequency, and combination of functions in the CONOPS affect system performance as a whole. It is important, however, to note that discrete event simulation is also capable (at a basic level) of addressing vulnerabilities in the CONOPS and interdependencies between individual functions as well. This approach is beneficial because it does not rely on complex mathematical models, but instead attempts to recreate the real world system as a decision and event driven simulation. Finally, because the simulation addresses warhead confirmation, chain of custody, and warhead dismantlement in a modular fashion, a discrete-event model could be easily adapted to multiple CONOPS for the exploration of a large number of “what if” scenarios.« less

A bio-inspired memory model for structural health monitoring

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhu, Yong

2009-04-01

Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system.

A Hybrid Stochastic-Neuro-Fuzzy Model-Based System for In-Flight Gas Turbine Engine Diagnostics

DTIC Science & Technology

2001-04-05

Margin (ADM) and (ii) Fault Detection Margin (FDM). Key Words: ANFIS, Engine Health Monitoring , Gas Path Analysis, and Stochastic Analysis Adaptive Network...The paper illustrates the application of a hybrid Stochastic- Fuzzy -Inference Model-Based System (StoFIS) to fault diagnostics and prognostics for both...operational history monitored on-line by the engine health management (EHM) system. To capture the complex functional relationships between different

The skill of ECMWF long range Forecasting System to drive impact models for health and hydrology in Africa

NASA Astrophysics Data System (ADS)

Di Giuseppe, F.; Tompkins, A. M.; Lowe, R.; Dutra, E.; Wetterhall, F.

2012-04-01

As the quality of numerical weather prediction over the monthly to seasonal leadtimes steadily improves there is an increasing motivation to apply these fruitfully to the impacts sectors of health, water, energy and agriculture. Despite these improvements, the accuracy of fields such as temperature and precipitation that are required to drive sectoral models can still be poor. This is true globally, but particularly so in Africa, the region of focus in the present study. In the last year ECMWF has been particularly active through EU research founded projects in demonstrating the capability of its longer range forecasting system to drive impact modeling systems in this region. A first assessment on the consequences of the documented errors in ECMWF forecasting system is therefore presented here looking at two different application fields which we found particularly critical for Africa - vector-born diseases prevention and hydrological monitoring. A new malaria community model (VECTRI) has been developed at ICTP and tested for the 3 target regions participating in the QWECI project. The impacts on the mean malaria climate is assessed using the newly realized seasonal forecasting system (Sys4) with the dismissed system 3 (Sys3) which had the same model cycle of the up-to-date ECMWF re-analysis product (ERA-Interim). The predictive skill of Sys4 to be employed for malaria monitoring and forecast are also evaluated by aggregating the fields to country level. As a part of the DEWFORA projects, ECMWF is also developing a system for drought monitoring and forecasting over Africa whose main meteorological input is precipitation. Similarly to what is done for the VECTRI model, the skill of seasonal forecasts of precipitation is, in this application, translated into the capability of predicting drought while ERA-Interim is used in monitoring. On a monitoring level, the near real-time update of ERA-Interim could compensate the lack of observations in the regions. However, ERA-Interim suffers from biases and drifts that limit its application for drought monitoring purposes in some regions.

Zebrafish as a model system to study toxicology.

PubMed

Dai, Yu-Jie; Jia, Yong-Fang; Chen, Na; Bian, Wan-Ping; Li, Qin-Kai; Ma, Yan-Bo; Chen, Yan-Ling; Pei, De-Sheng

2014-01-01

Monitoring and assessing the effects of contaminants in the aquatic eco-environment is critical in protecting human health and the environment. The zebrafish has been widely used as a prominent model organism in different fields because of its small size, low cost, diverse adaptability, short breeding cycle, high fecundity, and transparent embryos. Recent studies have demonstrated that zebrafish sensitivity can aid in monitoring environmental contaminants, especially with the application of transgenic technology in this area. The present review provides a brief overview of recent studies on wild-type and transgenic zebrafish as a model system to monitor toxic heavy metals, endocrine disruptors, and organic pollutants for toxicology. The authors address the new direction of developing high-throughput detection of genetically modified transparent zebrafish to open a new window for monitoring environmental pollutants. © 2013 SETAC.

Environmental noise forecasting based on support vector machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

2018-01-01

As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

40 CFR Table 7 to Subpart Bbbb of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2013 CFR

2013-07-01

... Emission Monitoring Systems (CEMS) 7 Table 7 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 7 Table 7 to Subpart BBBB of Part 60—Model Rule... sulfur dioxide emissions of the municipal waste combustion unit 4. Carbon Monoxide 125 percent of the...

40 CFR Table 7 to Subpart Bbbb of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2012 CFR

2012-07-01

... Emission Monitoring Systems (CEMS) 7 Table 7 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 7 Table 7 to Subpart BBBB of Part 60—Model Rule... sulfur dioxide emissions of the municipal waste combustion unit 4. Carbon Monoxide 125 percent of the...

40 CFR Table 7 to Subpart Bbbb of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2014 CFR

2014-07-01

... Emission Monitoring Systems (CEMS) 7 Table 7 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 7 Table 7 to Subpart BBBB of Part 60—Model Rule... sulfur dioxide emissions of the municipal waste combustion unit 4. Carbon Monoxide 125 percent of the...

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope.

PubMed

Lin, Hsueh-Chun; Hong, Yao-Ming; Kan, Yao-Chiang

2012-01-01

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.

A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application.

PubMed

Mostafa, Salama A; Mustapha, Aida; Mohammed, Mazin Abed; Ahmad, Mohd Sharifuddin; Mahmoud, Moamin A

2018-04-01

Autonomous agents are being widely used in many systems, such as ambient assisted-living systems, to perform tasks on behalf of humans. However, these systems usually operate in complex environments that entail uncertain, highly dynamic, or irregular workload. In such environments, autonomous agents tend to make decisions that lead to undesirable outcomes. In this paper, we propose a fuzzy-logic-based adjustable autonomy (FLAA) model to manage the autonomy of multi-agent systems that are operating in complex environments. This model aims to facilitate the autonomy management of agents and help them make competent autonomous decisions. The FLAA model employs fuzzy logic to quantitatively measure and distribute autonomy among several agents based on their performance. We implement and test this model in the Automated Elderly Movements Monitoring (AEMM-Care) system, which uses agents to monitor the daily movement activities of elderly users and perform fall detection and prevention tasks in a complex environment. The test results show that the FLAA model improves the accuracy and performance of these agents in detecting and preventing falls. Copyright © 2018 Elsevier B.V. All rights reserved.

Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

ERIC Educational Resources Information Center

Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

2011-01-01

In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

Determination of recharge fraction of injection water in combined abstraction-injection wells using continuous radon monitoring.

PubMed

Lee, Kil Yong; Kim, Yong-Chul; Cho, Soo Young; Kim, Seong Yun; Yoon, Yoon Yeol; Koh, Dong Chan; Ha, Kyucheol; Ko, Kyung-Seok

2016-12-01

The recharge fractions of injection water in combined abstraction-injection wells (AIW) were determined using continuous radon monitoring and radon mass balance model. The recharge system consists of three combined abstraction-injection wells, an observation well, a collection tank, an injection tank, and tubing for heating and transferring used groundwater. Groundwater was abstracted from an AIW and sprayed on the water-curtain heating facility and then the used groundwater was injected into the same AIW well by the recharge system. Radon concentrations of fresh groundwater in the AIWs and of used groundwater in the injection tank were measured continuously using a continuous radon monitoring system. Radon concentrations of fresh groundwater in the AIWs and used groundwater in the injection tank were in the ranges of 10,830-13,530 Bq/m 3 and 1500-5600 Bq/m 3 , respectively. A simple radon mass balance model was developed to estimate the recharge fraction of used groundwater in the AIWs. The recharge fraction in the 3 AIWs was in the range of 0.595-0.798. The time series recharge fraction could be obtained using the continuous radon monitoring system with a simple radon mass balance model. The results revealed that the radon mass balance model using continuous radon monitoring was effective for determining the time series recharge fractions in AIWs as well as for characterizing the recharge system. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coma Patient Monitoring System Using Image Processing

NASA Astrophysics Data System (ADS)

Sankalp, Meenu

2011-12-01

COMA PATIENT MONITORING SYSTEM provides high quality healthcare services in the near future. To provide more convenient and comprehensive medical monitoring in big hospitals since it is tough job for medical personnel to monitor each patient for 24 hours.. The latest development in patient monitoring system can be used in Intensive Care Unit (ICU), Critical Care Unit (CCU), and Emergency Rooms of hospital. During treatment, the patient monitor is continuously monitoring the coma patient to transmit the important information. Also in the emergency cases, doctor are able to monitor patient condition efficiently to reduce time consumption, thus it provides more effective healthcare system. So due to importance of patient monitoring system, the continuous monitoring of the coma patient can be simplified. This paper investigates about the effects seen in the patient using "Coma Patient Monitoring System" which is a very advanced product related to physical changes in body movement of the patient and gives Warning in form of alarm and display on the LCD in less than one second time. It also passes a sms to a person sitting at the distant place if there exists any movement in any body part of the patient. The model for the system uses Keil software for the software implementation of the developed system.

Benchmarking the performance of a land data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

The application of land data assimilation systems to operational agricultural drought monitoring requires the development of (at least) three separate system sub-components: 1) a retrieval model to invert satellite-derived observations into soil moisture estimates, 2) a prognostic soil water balance...

Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework

NASA Astrophysics Data System (ADS)

Alameddine, Ibrahim; Karmakar, Subhankar; Qian, Song S.; Paerl, Hans W.; Reckhow, Kenneth H.

2013-10-01

The total maximum daily load program aims to monitor more than 40,000 standard violations in around 20,000 impaired water bodies across the United States. Given resource limitations, future monitoring efforts have to be hedged against the uncertainties in the monitored system, while taking into account existing knowledge. In that respect, we have developed a hierarchical spatiotemporal Bayesian model that can be used to optimize an existing monitoring network by retaining stations that provide the maximum amount of information, while identifying locations that would benefit from the addition of new stations. The model assumes the water quality parameters are adequately described by a joint matrix normal distribution. The adopted approach allows for a reduction in redundancies, while emphasizing information richness rather than data richness. The developed approach incorporates the concept of entropy to account for the associated uncertainties. Three different entropy-based criteria are adopted: total system entropy, chlorophyll-a standard violation entropy, and dissolved oxygen standard violation entropy. A multiple attribute decision making framework is adopted to integrate the competing design criteria and to generate a single optimal design. The approach is implemented on the water quality monitoring system of the Neuse River Estuary in North Carolina, USA. The model results indicate that the high priority monitoring areas identified by the total system entropy and the dissolved oxygen violation entropy criteria are largely coincident. The monitoring design based on the chlorophyll-a standard violation entropy proved to be less informative, given the low probabilities of violating the water quality standard in the estuary.

Statistically Qualified Neuro-Analytic system and Method for Process Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

1998-11-04

An apparatus and method for monitoring a process involves development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two steps: deterministic model adaption and stochastic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics,augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation emor minimization technique. Stochastic model adaptation involves qualifying any remaining uncertaintymore » in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system.« less

Field test of an alternative longwall gate road design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, R.M.; Vandergrift, T.L.; McDonnell, J.P.

1994-01-01

The US Bureau of Mines (USBM) MULSIM/ML modeling technique has been used to analyze anticipated stress distributions for a proposed alternative longwall gate road design for a western Colorado coal mine. The model analyses indicated that the alternative gate road design would reduce stresses in the headgate entry. To test the validity of the alternative gate road design under actual mining conditions, a test section of the alternative system was incorporated into a subsequent set of gate roads developed at the mine. The alternative gate road test section was instrumented with borehole pressure cells, as part of an ongoing USBMmore » research project to monitor ground pressure changes as longwall mining progressed. During the excavation of the adjacent longwall panels, the behavior of the alternative gate road system was monitored continuously using the USBM computer-assisted Ground Control Management System. During these field tests, the alternative gate road system was first monitored and evaluated as a headgate, and later monitored and evaluated as a tailgate. The results of the field tests confirmed the validity of using the MULSIM/NL modeling technique to evaluate mine designs.« less

IMS radionuclide monitoring after the announced nuclear test of the DPRK on 3 September 2017

NASA Astrophysics Data System (ADS)

Kusmierczyk-Michulec, J.; Kalinowski, M.; Bourgouin, P.; Boxue, L.; Gheddou, A.; Klingberg, F.; Leppaenen, A. P.; Schoeppner, M.; Werzi, R.; Wang, J.

2017-12-01

The International Monitoring System (IMS) developed by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) is a global system of monitoring stations, using four complementary technologies: seismic, hydroacoustic, infrasound and radionuclide. The radionuclide network comprises 80 stations, out of which 40 are to be equipped with noble gas systems. The aim of radionuclide stations is a global monitoring of radioactive aerosols, radioactive noble gases and atmospheric transport modelling (ATM). To investigate the transport of radionuclide emissions, the Provisional Technical Secretariat (PTS) operates an Atmospheric Transport Modelling (ATM) system based on the Lagrangian Particle Dispersion Model FLEXPART. The air mass trajectory provides a "link" between a radionuclide release and a detection confirmed by radionuclide measurements. The aim of this study is to demonstrate the RN analysis and the application of ATM to investigate the episodes of elevated levels of radioxenon observed by IMS stations after the sixth nuclear test, announced by the Democratic People's Republic of Korea (DPRK) at the Punggye-ri Nuclear Test Site on 3 September 2017. A comparison to the previous tests will be presented.

A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

PubMed Central

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-01-01

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing. PMID:24803190

A space weather forecasting system with multiple satellites based on a self-recognizing network.

PubMed

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-05-05

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

Bayesian Inference for Signal-Based Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.

2015-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. SIG-VISA (Signal-based Vertically Integrated Seismic Analysis) is a system for global seismic monitoring through Bayesian inference on seismic signals. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of recent geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a global network of stations. We demonstrate recent progress in scaling up SIG-VISA to efficiently process the data stream of global signals recorded by the International Monitoring System (IMS), including comparisons against existing processing methods that show increased sensitivity from our signal-based model and in particular the ability to locate events (including aftershock sequences that can tax analyst processing) precisely from waveform correlation effects. We also provide a Bayesian analysis of an alleged low-magnitude event near the DPRK test site in May 2010 [1] [2], investigating whether such an event could plausibly be detected through automated processing in a signal-based monitoring system. [1] Zhang, Miao and Wen, Lianxing. "Seismological Evidence for a Low-Yield Nuclear Test on 12 May 2010 in North Korea". Seismological Research Letters, January/February 2015. [2] Richards, Paul. "A Seismic Event in North Korea on 12 May 2010". CTBTO SnT 2015 oral presentation, video at https://video-archive.ctbto.org/index.php/kmc/preview/partner_id/103/uiconf_id/4421629/entry_id/0_ymmtpps0/delivery/http

A conductive grating sensor for online quantitative monitoring of fatigue crack.

PubMed

Li, Peiyuan; Cheng, Li; Yan, Xiaojun; Jiao, Shengbo; Li, Yakun

2018-05-01

Online quantitative monitoring of crack damage due to fatigue is a critical challenge for structural health monitoring systems assessing structural safety. To achieve online quantitative monitoring of fatigue crack, a novel conductive grating sensor based on the principle of electrical potential difference is proposed. The sensor consists of equidistant grating channels to monitor the fatigue crack length and conductive bars to provide the circuit path. An online crack monitoring system is established to verify the sensor's capability. The experimental results prove that the sensor is suitable for online quantitative monitoring of fatigue crack. A finite element model for the sensor is also developed to optimize the sensitivity of crack monitoring, which is defined by the rate of sensor resistance change caused by the break of the first grating channel. Analysis of the model shows that the sensor sensitivity can be enhanced by reducing the number of grating channels and increasing their resistance and reducing the resistance of the conductive bar.

A conductive grating sensor for online quantitative monitoring of fatigue crack

NASA Astrophysics Data System (ADS)

Li, Peiyuan; Cheng, Li; Yan, Xiaojun; Jiao, Shengbo; Li, Yakun

2018-05-01

Online quantitative monitoring of crack damage due to fatigue is a critical challenge for structural health monitoring systems assessing structural safety. To achieve online quantitative monitoring of fatigue crack, a novel conductive grating sensor based on the principle of electrical potential difference is proposed. The sensor consists of equidistant grating channels to monitor the fatigue crack length and conductive bars to provide the circuit path. An online crack monitoring system is established to verify the sensor's capability. The experimental results prove that the sensor is suitable for online quantitative monitoring of fatigue crack. A finite element model for the sensor is also developed to optimize the sensitivity of crack monitoring, which is defined by the rate of sensor resistance change caused by the break of the first grating channel. Analysis of the model shows that the sensor sensitivity can be enhanced by reducing the number of grating channels and increasing their resistance and reducing the resistance of the conductive bar.

Physical factors that influence patients’ privacy perception toward a psychiatric behavioral monitoring system: a qualitative study

PubMed Central

Zakaria, Nasriah; Ramli, Rusyaizila

2018-01-01

Background Psychiatric patients have privacy concerns when it comes to technology intervention in the hospital setting. In this paper, we present scenarios for psychiatric behavioral monitoring systems to be placed in psychiatric wards to understand patients’ perception regarding privacy. Psychiatric behavioral monitoring refers to systems that are deemed useful in measuring clinical outcomes, but little research has been done on how these systems will impact patients’ privacy. Methods We conducted a case study in one teaching hospital in Malaysia. We investigated the physical factors that influence patients’ perceived privacy with respect to a psychiatric monitoring system. The eight physical factors identified from the information system development privacy model, a comprehensive model for designing a privacy-sensitive information system, were adapted in this research. Scenario-based interviews were conducted with 25 patients in a psychiatric ward for 3 months. Results Psychiatric patients were able to share how physical factors influence their perception of privacy. Results show how patients responded to each of these dimensions in the context of a psychiatric behavioral monitoring system. Conclusion Some subfactors under physical privacy are modified to reflect the data obtained in the interviews. We were able to capture the different physical factors that influence patient privacy. PMID:29343963

Development of an operational African Drought Monitor prototype

NASA Astrophysics Data System (ADS)

Chaney, N.; Sheffield, J.; Wood, E. F.; Lettenmaier, D. P.

2011-12-01

Droughts have severe economic, environmental, and social impacts. However, timely detection and monitoring can minimize these effects. Based on previous drought monitoring over the continental US, a drought monitor has been developed for Africa. Monitoring drought in data sparse regions such as Africa is difficult due to a lack of historical or real-time observational data at a high spatial and temporal resolution. As a result, a land surface model is used to estimate hydrologic variables, which are used as surrogate observations for monitoring drought. The drought monitoring system consists of two stages: the first is to create long-term historical background simulations against which current conditions can be compared. The second is the real-time estimation of current hydrological conditions that results in an estimated drought index value. For the first step, a hybrid meteorological forcing dataset was created that assimilates reanalysis and observational datasets from 1950 up to real-time. Furthermore, the land surface model (currently the VIC land surface model is being used) was recalibrated against spatially disaggregated runoff fields derived from over 500 GRDC stream gauge measurements over Africa. The final result includes a retrospective database from 1950 to real-time of soil moisture, evapotranspiration, river discharge at the GRDC gauged sites (etc.) at a 1/4 degree spatial resolution, and daily temporal resolution. These observation-forced simulations are analyzed to detect and track historical drought events according to a drought index that is calculated from the soil moisture fields and river discharge relative to their seasonal climatology. The real-time monitoring requires the use of remotely sensed and weather-model analysis estimates of hydrological model forcings. For the current system, NOAA's Global Forecast System (GFS) is used along with remotely sensed precipitation from the NASA TMPA system. The historical archive of these data is evaluated against the data set used to create the background simulations. Real-time adjustments are used to preserve consistency between the historical and real-time data. The drought monitor will be presented together with the web-interface that has been developed for the scientific community to access and retrieve the data products. This system will be deployed for operational use at AGRHYMET in Niamey, Niger before the end of 2011.

40 CFR Table 6 to Subpart Bbbb of... - Model Rule-Requirements for Validating Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2014 CFR

2014-07-01

... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 6 Table 6 to Subpart BBBB of Part 60—Model Rule... levels Use the following methods in appendix A of this part to measure oxygen (or carbon dioxide) 1...

40 CFR Table 6 to Subpart Bbbb of... - Model Rule-Requirements for Validating Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2012 CFR

2012-07-01

... Continuous Emission Monitoring Systems (CEMS) 6 Table 6 to Subpart BBBB of Part 60 Protection of Environment... or Before August 30, 1999 Pt. 60, Subpt. BBBB, Table 6 Table 6 to Subpart BBBB of Part 60—Model Rule... levels Use the following methods in appendix A of this part to measure oxygen (or carbon dioxide) 1...

Monitoring apparatus and method for battery power supply

DOEpatents

Martin, Harry L.; Goodson, Raymond E.

1983-01-01

A monitoring apparatus and method are disclosed for monitoring and/or indicating energy that a battery power source has then remaining and/or can deliver for utilization purposes as, for example, to an electric vehicle. A battery mathematical model forms the basis for monitoring with a capacity prediction determined from measurement of the discharge current rate and stored battery parameters. The predicted capacity is used to provide a state-of-charge indication. Self-calibration over the life of the battery power supply is enacted through use of a feedback voltage based upon the difference between predicted and measured voltages to correct the battery mathematical model. Through use of a microprocessor with central information storage of temperature, current and voltage, system behavior is monitored, and system flexibility is enhanced.

Contract Monitoring in Agent-Based Systems: Case Study

NASA Astrophysics Data System (ADS)

Hodík, Jiří; Vokřínek, Jiří; Jakob, Michal

Monitoring of fulfilment of obligations defined by electronic contracts in distributed domains is presented in this paper. A two-level model of contract-based systems and the types of observations needed for contract monitoring are introduced. The observations (inter-agent communication and agents’ actions) are collected and processed by the contract observation and analysis pipeline. The presented approach has been utilized in a multi-agent system for electronic contracting in a modular certification testing domain.

A Coupled model for ERT monitoring of contaminated sites

NASA Astrophysics Data System (ADS)

Wang, Yuling; Zhang, Bo; Gong, Shulan; Xu, Ya

2018-02-01

The performance of electrical resistivity tomography (ERT) system is usually investigated using a fixed resistivity distribution model in numerical simulation study. In this paper, a method to construct a time-varying resistivity model by coupling water transport, solute transport and constant current field is proposed for ERT monitoring of contaminated sites. Using the proposed method, a monitoring model is constructed for a contaminated site with a pollution region on the surface and ERT monitoring results at different time is calculated by the finite element method. The results show that ERT monitoring profiles can effectively reflect the increase of the pollution area caused by the diffusion of pollutants, but the extent of the pollution is not exactly the same as the actual situation. The model can be extended to any other case and can be used to scheme design and results analysis for ERT monitoring.

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

USGS Publications Warehouse

Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

2015-01-01

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Development of an In-Situ Decommissioning Sensor Network Test Bed for Structural Condition Monitoring - 12156

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeigler, Kristine E.; Ferguson, Blythe A.

2012-07-01

The Savannah River National Laboratory (SRNL) has established an In Situ Decommissioning (ISD) Sensor Network Test Bed, a unique, small scale, configurable environment, for the assessment of prospective sensors on actual ISD system material, at minimal cost. The Department of Energy (DOE) is presently implementing permanent entombment of contaminated, large nuclear structures via ISD. The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. Validation of ISD system performance models and verification of actual system conditions can be achieved through the development a system of sensors to monitor the materials andmore » condition of the structure. The ISD Sensor Network Test Bed has been designed and deployed to addresses the DOE-Environmental Management Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building at the Savannah River Site. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of groutable thermistors for temperature and moisture monitoring, strain gauges for crack growth monitoring, tilt-meters for settlement monitoring, and a communication system for data collection. Baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment. The Sensor Network Test Bed at SRNL uses COTS sensors on concrete blocks from the outer wall of the P Reactor Building to measure conditions expected to occur in ISD structures. Knowledge and lessons learned gained from installation, testing, and monitoring of the equipment will be applied to sensor installation in a meso-scale test bed at FIU and in future ISD structures. The initial data collected from the sensors installed on the P Reactor Building blocks define the baseline materials condition of the P Reactor ISD external concrete structure. Continued monitoring of the blocks will enable evaluation of the effects of aging on the P Reactor ISD structure. The collected data will support validation of the material degradation model and assessment of the condition of the ISD structure over time. The following are recommendations for continued development of the ISD Sensor Network Test Bed: - Establish a long-term monitoring program using the concrete blocks with existing sensor and/or additional sensors for trending the concrete materials and structural condition; - Continue development of a stand-alone test bed sensor system that is self-powered and provides wireless transmission of data to a user-accessible dashboard; - Develop and implement periodic NDE/DE characterization of the concrete blocks to provide verification and validation for the measurements obtained through the sensor system and concrete degradation model(s). (authors)« less

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

General-Purpose Monitoring during Speech Production

ERIC Educational Resources Information Center

Ries, Stephanie; Janssen, Niels; Dufau, Stephane; Alario, F.-Xavier; Burle, Boris

2011-01-01

The concept of "monitoring" refers to our ability to control our actions on-line. Monitoring involved in speech production is often described in psycholinguistic models as an inherent part of the language system. We probed the specificity of speech monitoring in two psycholinguistic experiments where electroencephalographic activities were…

The monocular visual imaging technology model applied in the airport surface surveillance

NASA Astrophysics Data System (ADS)

Qin, Zhe; Wang, Jian; Huang, Chao

2013-08-01

At present, the civil aviation airports use the surface surveillance radar monitoring and positioning systems to monitor the aircrafts, vehicles and the other moving objects. Surface surveillance radars can cover most of the airport scenes, but because of the terminals, covered bridges and other buildings geometry, surface surveillance radar systems inevitably have some small segment blind spots. This paper presents a monocular vision imaging technology model for airport surface surveillance, achieving the perception of scenes of moving objects such as aircrafts, vehicles and personnel location. This new model provides an important complement for airport surface surveillance, which is different from the traditional surface surveillance radar techniques. Such technique not only provides clear objects activities screen for the ATC, but also provides image recognition and positioning of moving targets in this area. Thereby it can improve the work efficiency of the airport operations and avoid the conflict between the aircrafts and vehicles. This paper first introduces the monocular visual imaging technology model applied in the airport surface surveillance and then the monocular vision measurement accuracy analysis of the model. The monocular visual imaging technology model is simple, low cost, and highly efficient. It is an advanced monitoring technique which can make up blind spot area of the surface surveillance radar monitoring and positioning systems.

ASSESSMENT OF DYNAMIC PRA TECHNIQUES WITH INDUSTRY AVERAGE COMPONENT PERFORMANCE DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yadav, Vaibhav; Agarwal, Vivek; Gribok, Andrei V.

In the nuclear industry, risk monitors are intended to provide a point-in-time estimate of the system risk given the current plant configuration. Current risk monitors are limited in that they do not properly take into account the deteriorating states of plant equipment, which are unit-specific. Current approaches to computing risk monitors use probabilistic risk assessment (PRA) techniques, but the assessment is typically a snapshot in time. Living PRA models attempt to address limitations of traditional PRA models in a limited sense by including temporary changes in plant and system configurations. However, information on plant component health are not considered. Thismore » often leaves risk monitors using living PRA models incapable of conducting evaluations with dynamic degradation scenarios evolving over time. There is a need to develop enabling approaches to solidify risk monitors to provide time and condition-dependent risk by integrating traditional PRA models with condition monitoring and prognostic techniques. This paper presents estimation of system risk evolution over time by integrating plant risk monitoring data with dynamic PRA methods incorporating aging and degradation. Several online, non-destructive approaches have been developed for diagnosing plant component conditions in nuclear industry, i.e., condition indication index, using vibration analysis, current signatures, and operational history [1]. In this work the component performance measures at U.S. commercial nuclear power plants (NPP) [2] are incorporated within the various dynamic PRA methodologies [3] to provide better estimates of probability of failures. Aging and degradation is modeled within the Level-1 PRA framework and is applied to several failure modes of pumps and can be extended to a range of components, viz. valves, generators, batteries, and pipes.« less

Field application of smart SHM using field programmable gate array technology to monitor an RC bridge in New Mexico

NASA Astrophysics Data System (ADS)

Azarbayejani, M.; Jalalpour, M.; El-Osery, A. I.; Reda Taha, M. M.

2011-08-01

In this paper, an innovative field application of a structural health monitoring (SHM) system using field programmable gate array (FPGA) technology and wireless communication is presented. The new SHM system was installed to monitor a reinforced concrete (RC) bridge on Interstate 40 (I-40) in Tucumcari, New Mexico. This newly installed system allows continuous remote monitoring of this bridge using solar power. Details of the SHM component design and installation are discussed. The integration of FPGA and solar power technologies make it possible to remotely monitor infrastructure with limited access to power. Furthermore, the use of FPGA technology enables smart monitoring where data communication takes place on-need (when damage warning signs are met) and on-demand for periodic monitoring of the bridge. Such a system enables a significant cut in communication cost and power demands which are two challenges during SHM operation. Finally, a three-dimensional finite element (FE) model of the bridge was developed and calibrated using a static loading field test. This model is then used for simulating damage occurrence on the bridge. Using the proposed automation process for SHM will reduce human intervention significantly and can save millions of dollars currently spent on prescheduled inspection of critical infrastructure worldwide.

An Integrated Modeling and Simulation Methodology for Intelligent Systems Design and Testing

DTIC Science & Technology

2002-08-01

simulation and actual execution. KEYWORDS: Model Continuity, Modeling, Simulation, Experimental Frame, Real Time Systems , Intelligent Systems...the methodology for a stand-alone real time system. Then it will scale up to distributed real time systems . For both systems, step-wise simulation...MODEL CONTINUITY Intelligent real time systems monitor, respond to, or control, an external environment. This environment is connected to the digital

Environment quality monitoring using ARM processor

NASA Astrophysics Data System (ADS)

Vinaya, C. H.; Krishna Thanikanti, Vamsi; Ramasamy, Sudha

2017-11-01

This paper of air quality monitoring system describes a model of sensors network to continuously monitoring the environment with low cost developed model. At present time all over the world turned into a great revolution in industrial domain and on the other hand environment get polluting in a dangerous value. There are so many technologies present to reduce the polluting contents but still there is no completely reduction of that pollution. Even there are different methods to monitor the pollution content; these are much costly that not everyone can adapt those methods or devices. Now we are proposing a sensors connected network to monitor the environment continuously and displaying the pollutant gases percentage in air surroundings and can transmit the results to our mobiles by message. The advantage of this system is easy to design, establish at area to monitor, maintenance and most cost effective as well.

Model-Based Sensor Placement for Component Condition Monitoring and Fault Diagnosis in Fossil Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mobed, Parham; Pednekar, Pratik; Bhattacharyya, Debangsu

Design and operation of energy producing, near “zero-emission” coal plants has become a national imperative. This report on model-based sensor placement describes a transformative two-tier approach to identify the optimum placement, number, and type of sensors for condition monitoring and fault diagnosis in fossil energy system operations. The algorithms are tested on a high fidelity model of the integrated gasification combined cycle (IGCC) plant. For a condition monitoring network, whether equipment should be considered at a unit level or a systems level depends upon the criticality of the process equipment, its likeliness to fail, and the level of resolution desiredmore » for any specific failure. Because of the presence of a high fidelity model at the unit level, a sensor network can be designed to monitor the spatial profile of the states and estimate fault severity levels. In an IGCC plant, besides the gasifier, the sour water gas shift (WGS) reactor plays an important role. In view of this, condition monitoring of the sour WGS reactor is considered at the unit level, while a detailed plant-wide model of gasification island, including sour WGS reactor and the Selexol process, is considered for fault diagnosis at the system-level. Finally, the developed algorithms unify the two levels and identifies an optimal sensor network that maximizes the effectiveness of the overall system-level fault diagnosis and component-level condition monitoring. This work could have a major impact on the design and operation of future fossil energy plants, particularly at the grassroots level where the sensor network is yet to be identified. In addition, the same algorithms developed in this report can be further enhanced to be used in retrofits, where the objectives could be upgrade (addition of more sensors) and relocation of existing sensors.« less

Initial Evaluation of Signal-Based Bayesian Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Russell, S.

2016-12-01

We present SIGVISA (Signal-based Vertically Integrated Seismic Analysis), a next-generation system for global seismic monitoring through Bayesian inference on seismic signals. Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a network of stations. We report results from an evaluation of SIGVISA monitoring the western United States for a two-week period following the magnitude 6.0 event in Wells, NV in February 2008. During this period, SIGVISA detects more than twice as many events as NETVISA, and three times as many as SEL3, while operating at the same precision; at lower precisions it detects up to five times as many events as SEL3. At the same time, signal-based monitoring reduces mean location errors by a factor of four relative to detection-based systems. We provide evidence that, given only IMS data, SIGVISA detects events that are missed by regional monitoring networks, indicating that our evaluations may even underestimate its performance. Finally, SIGVISA matches or exceeds the detection rates of existing systems for de novo events - events with no nearby historical seismicity - and detects through automated processing a number of such events missed even by the human analysts generating the LEB.

Model-based design and experimental verification of a monitoring concept for an active-active electromechanical aileron actuation system

NASA Astrophysics Data System (ADS)

Arriola, David; Thielecke, Frank

2017-09-01

Electromechanical actuators have become a key technology for the onset of power-by-wire flight control systems in the next generation of commercial aircraft. The design of robust control and monitoring functions for these devices capable to mitigate the effects of safety-critical faults is essential in order to achieve the required level of fault tolerance. A primary flight control system comprising two electromechanical actuators nominally operating in active-active mode is considered. A set of five signal-based monitoring functions are designed using a detailed model of the system under consideration which includes non-linear parasitic effects, measurement and data acquisition effects, and actuator faults. Robust detection thresholds are determined based on the analysis of parametric and input uncertainties. The designed monitoring functions are verified experimentally and by simulation through the injection of faults in the validated model and in a test-rig suited to the actuation system under consideration, respectively. They guarantee a robust and efficient fault detection and isolation with a low risk of false alarms, additionally enabling the correct reconfiguration of the system for an enhanced operational availability. In 98% of the performed experiments and simulations, the correct faults were detected and confirmed within the time objectives set.

Approach to in-process tool wear monitoring in drilling: Application of Kalman filter theory

NASA Astrophysics Data System (ADS)

He, Ning; Zhang, Youzhen; Pan, Liangxian

1993-05-01

The two parameters often used in adaptive control, tool wear and wear rate, are the important factors affecting machinability. In this paper, it is attempted to use the modern cybernetics to solve the in-process tool wear monitoring problem by applying the Kalman filter theory to monitor drill wear quantitatively. Based on the experimental results, a dynamic model, a measuring model and a measurement conversion model suitable for Kalman filter are established. It is proved that the monitoring system possesses complete observability but does not possess complete controllability. A discriminant for selecting the characteristic parameters is put forward. The thrust force Fz is selected as the characteristic parameter in monitoring the tool wear by this discriminant. The in-process Kalman filter drill wear monitoring system composed of force sensor microphotography and microcomputer is well established. The results obtained by the Kalman filter, the common indirect measuring method and the real drill wear measured by the aid of microphotography are compared. The result shows that the Kalman filter has high precision of measurement and the real time requirement can be satisfied.

System and Method for Monitoring Distributed Asset Data

NASA Technical Reports Server (NTRS)

Gorinevsky, Dimitry (Inventor)

2015-01-01

A computer-based monitoring system and monitoring method implemented in computer software for detecting, estimating, and reporting the condition states, their changes, and anomalies for many assets. The assets are of same type, are operated over a period of time, and outfitted with data collection systems. The proposed monitoring method accounts for variability of working conditions for each asset by using regression model that characterizes asset performance. The assets are of the same type but not identical. The proposed monitoring method accounts for asset-to-asset variability; it also accounts for drifts and trends in the asset condition and data. The proposed monitoring system can perform distributed processing of massive amounts of historical data without discarding any useful information where moving all the asset data into one central computing system might be infeasible. The overall processing is includes distributed preprocessing data records from each asset to produce compressed data.

Effects of blind spot monitoring systems on police-reported lane-change crashes.

PubMed

Cicchino, Jessica B

2018-06-21

To examine the effectiveness of blind spot monitoring systems in preventing police-reported lane-change crashes. Poisson regression was used to compare crash involvement rates per insured vehicle year in police-reported lane-change crashes in 26 U.S. states during 2009-2015 between vehicles with blind spot monitoring and the same vehicle models without the optional system, controlling for other factors that can affect crash risk. Crash involvement rates in lane-change crashes were 14% lower (95% confidence limits -24% to -2%) among vehicles with blind spot monitoring than those without. Blind spot monitoring systems are effective in preventing police-reported lane-change crashes when considering crashes of all severities. If every U.S. vehicle in 2015 were equipped with blind spot monitoring that performed like the study systems, it is estimated that about 50,000 crashes could have been prevented.

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; 4 Blyth, Eleanor; de Roo, Ad; Doell. Petra; Ek, Mike; Famiglietti, James;

Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

NASA Astrophysics Data System (ADS)

Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; Blyth, Eleanor; de Roo, Ad; DöLl, Petra; Ek, Mike; Famiglietti, James; Gochis, David; van de Giesen, Nick; Houser, Paul; Jaffé, Peter R.; Kollet, Stefan; Lehner, Bernhard; Lettenmaier, Dennis P.; Peters-Lidard, Christa; Sivapalan, Murugesu; Sheffield, Justin; Wade, Andrew; Whitehead, Paul

2011-05-01

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (˜10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a "grand challenge" to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

PubMed

Housh, Mashor; Ohar, Ziv

2017-03-01

The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Protocol for Reliability Assessment of Structural Health Monitoring Systems Incorporating Model-assisted Probability of Detection (MAPOD) Approach

DTIC Science & Technology

2011-09-01

a quality evaluation with limited data, a model -based assessment must be...that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a ...affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range

Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure.

PubMed

Ding, You-Liang; Wang, Gao-Xin; Sun, Peng; Wu, Lai-Yi; Yue, Qing

2015-01-01

Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the performance deterioration during the long-time service of the bridge, a Structural Health Monitoring (SHM) system has been implemented on this bridge by the application of modern techniques in sensing, testing, computing, and network communication. The SHM system includes various sensors as well as corresponding data acquisition and transmission equipment for automatic data collection. Furthermore, an evaluation system of structural safety has been developed for the real-time condition assessment of this bridge. The mathematical correlation models describing the overall structural behavior of the bridge can be obtained with the support of the health monitoring system, which includes cross-correlation models for accelerations, correlation models between temperature and static strains of steel truss arch, and correlation models between temperature and longitudinal displacements of piers. Some evaluation results using the mean value control chart based on mathematical correlation models are presented in this paper to show the effectiveness of this SHM system in detecting the bridge's abnormal behaviors under the varying environmental conditions such as high-speed trains and environmental temperature.

Formal verification of medical monitoring software using Z language: a representative sample.

PubMed

Babamir, Seyed Morteza; Borhani, Mehdi

2012-08-01

Medical monitoring systems are useful aids assisting physicians in keeping patients under constant surveillance; however, taking sound decision by the systems is a physician concern. As a result, verification of the systems behavior in monitoring patients is a matter of significant. The patient monitoring is undertaken by software in modern medical systems; so, software verification of modern medial systems have been noticed. Such verification can be achieved by the Formal Languages having mathematical foundations. Among others, the Z language is a suitable formal language has been used to formal verification of systems. This study aims to present a constructive method to verify a representative sample of a medical system by which the system is visually specified and formally verified against patient constraints stated in Z Language. Exploiting our past experience in formal modeling Continuous Infusion Insulin Pump (CIIP), we think of the CIIP system as a representative sample of medical systems in proposing our present study. The system is responsible for monitoring diabetic's blood sugar.

Building Construction Progress Monitoring Using Unmanned Aerial System (uas), Low-Cost Photogrammetry, and Geographic Information System (gis)

NASA Astrophysics Data System (ADS)

Bognot, J. R.; Candido, C. G.; Blanco, A. C.; Montelibano, J. R. Y.

2018-05-01

Monitoring the progress of building's construction is critical in construction management. However, measuring the building construction's progress are still manual, time consuming, error prone, and impose tedious process of analysis leading to delays, additional costings and effort. The main goal of this research is to develop a methodology for building construction progress monitoring based on 3D as-built model of the building from unmanned aerial system (UAS) images, 4D as-planned model (with construction schedule integrated) and, GIS analysis. Monitoring was done by capturing videos of the building with a camera-equipped UAS. Still images were extracted, filtered, bundle-adjusted, and 3D as-built model was generated using open source photogrammetric software. The as-planned model was generated from digitized CAD drawings using GIS. The 3D as-built model was aligned with the 4D as-planned model of building formed from extrusion of building elements, and integration of the construction's planned schedule. The construction progress is visualized via color-coding the building elements in the 3D model. The developed methodology was conducted and applied from the data obtained from an actual construction site. Accuracy in detecting `built' or `not built' building elements ranges from 82-84 % and precision of 50-72 %. Quantified progress in terms of the number of building elements are 21.31% (November 2016), 26.84 % (January 2017) and 44.19 % (March 2017). The results can be used as an input for progress monitoring performance of construction projects and improving related decision-making process.

Wastewater quality monitoring system using sensor fusion and machine learning techniques.

PubMed

Qin, Xusong; Gao, Furong; Chen, Guohua

2012-03-15

A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

ENSEMBLE and AMET: Two Systems and Approaches to a Harmonized, Simplified and Efficient Facility for Air Quality Models Development and Evaluation

EPA Science Inventory

The complexity of air quality modeling systems, air quality monitoring data make ad-hoc systems for model evaluation important aids to the modeling community. Among those are the ENSEMBLE system developed by the EC-Joint Research Center, and the AMET software developed by the US-...

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

NASA Technical Reports Server (NTRS)

White, Kristopher D.; Case, Jonathan L.

2013-01-01

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

NASA Astrophysics Data System (ADS)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.

The role of population monitoring in the management of North American waterfowl

USGS Publications Warehouse

Nichols, J.D.; Williams, B.K.; Johnson, F.A.

2000-01-01

Despite the effort and expense devoted to large-scale monitoring programs, few existing programs have been designed with specific objectives in mind and few permit strong inferences about the dynamics of monitored systems. The waterfowl population monitoring programs of the U.S. Fish and Wildlife Service, Canadian Wildlife Service and state and provincial agencies provide a nice example with respect to program objectives, design and implementation. The May Breeding Grounds Survey provides an estimate of system state (population size) that serves two primary purposes in the adaptive management process: identifying the appropriate time-specific management actions and updating the information state (model weights) by providing a basis for evaluating predictions of competing models. Other waterfowl monitoring programs (e.g., banding program, hunter questionnaire survey, parts collection survey, winter survey) provide estimates of vital rates (rates of survival, reproduction and movement) associated with system dynamics and variables associated with management objectives (e.g., harvest). The reliability of estimates resulting from monitoring programs depends strongly on whether considerations about spatial variation and detection probability have been adequately incorporated into program design and implementation. Certain waterfowl surveys again provide nice examples of monitoring programs that incorporate these considerations.

Autonomous System for Monitoring the Integrity of Composite Fan Housings

NASA Technical Reports Server (NTRS)

Qing, Xinlin P.; Aquino, Christopher; Kumar, Amrita

2010-01-01

A low-cost and reliable system assesses the integrity of composite fan-containment structures. The system utilizes a network of miniature sensors integrated with the structure to scan the entire structural area for any impact events and resulting structural damage, and to monitor degradation due to usage. This system can be used to monitor all types of composite structures on aircraft and spacecraft, as well as automatically monitor in real time the location and extent of damage in the containment structures. This diagnostic information is passed to prognostic modeling that is being developed to utilize the information and provide input on the residual strength of the structure, and maintain a history of structural degradation during usage. The structural health-monitoring system would consist of three major components: (1) sensors and a sensor network, which is permanently bonded onto the structure being monitored; (2) integrated hardware; and (3) software to monitor in-situ the health condition of in-service structures.

Systems, methods and computer-readable media for modeling cell performance fade of rechargeable electrochemical devices

DOEpatents

Gering, Kevin L

2013-08-27

A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware periodically samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics of the electrochemical cell. The computing system also develops a mechanistic level model of the electrochemical cell to determine performance fade characteristics of the electrochemical cell and analyzing the mechanistic level model to estimate performance fade characteristics over aging of a similar electrochemical cell. The mechanistic level model uses first constant-current pulses applied to the electrochemical cell at a first aging period and at three or more current values bracketing a first exchange current density. The mechanistic level model also is based on second constant-current pulses applied to the electrochemical cell at a second aging period and at three or more current values bracketing the second exchange current density.

The adaptive safety analysis and monitoring system

NASA Astrophysics Data System (ADS)

Tu, Haiying; Allanach, Jeffrey; Singh, Satnam; Pattipati, Krishna R.; Willett, Peter

2004-09-01

The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

An Online Risk Monitor System (ORMS) to Increase Safety and Security Levels in Industry

NASA Astrophysics Data System (ADS)

Zubair, M.; Rahman, Khalil Ur; Hassan, Mehmood Ul

2013-12-01

The main idea of this research is to develop an Online Risk Monitor System (ORMS) based on Living Probabilistic Safety Assessment (LPSA). The article highlights the essential features and functions of ORMS. The basic models and modules such as, Reliability Data Update Model (RDUM), running time update, redundant system unavailability update, Engineered Safety Features (ESF) unavailability update and general system update have been described in this study. ORMS not only provides quantitative analysis but also highlights qualitative aspects of risk measures. ORMS is capable of automatically updating the online risk models and reliability parameters of equipment. ORMS can support in the decision making process of operators and managers in Nuclear Power Plants.

Attention focussing and anomaly detection in real-time systems monitoring

NASA Technical Reports Server (NTRS)

Doyle, Richard J.; Chien, Steve A.; Fayyad, Usama M.; Porta, Harry J.

1993-01-01

In real-time monitoring situations, more information is not necessarily better. When faced with complex emergency situations, operators can experience information overload and a compromising of their ability to react quickly and correctly. We describe an approach to focusing operator attention in real-time systems monitoring based on a set of empirical and model-based measures for determining the relative importance of sensor data.

Experimental Validation of a Resilient Monitoring and Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wen-Chiao Lin; Kris R. E. Villez; Humberto E. Garcia

2014-05-01

Complex, high performance, engineering systems have to be closely monitored and controlled to ensure safe operation and protect public from potential hazards. One of the main challenges in designing monitoring and control algorithms for these systems is that sensors and actuators may be malfunctioning due to malicious or natural causes. To address this challenge, this paper addresses a resilient monitoring and control (ReMAC) system by expanding previously developed resilient condition assessment monitoring systems and Kalman filter-based diagnostic methods and integrating them with a supervisory controller developed here. While the monitoring and diagnostic algorithms assess plant cyber and physical health conditions,more » the supervisory controller selects, from a set of candidates, the best controller based on the current plant health assessments. To experimentally demonstrate its enhanced performance, the developed ReMAC system is then used for monitoring and control of a chemical reactor with a water cooling system in a hardware-in-the-loop setting, where the reactor is computer simulated and the water cooling system is implemented by a machine condition monitoring testbed at Idaho National Laboratory. Results show that the ReMAC system is able to make correct plant health assessments despite sensor malfunctioning due to cyber attacks and make decisions that achieve best control actions despite possible actuator malfunctioning. Monitoring challenges caused by mismatches between assumed system component models and actual measurements are also identified for future work.« less

Display/control requirements for automated VTOL aircraft

NASA Technical Reports Server (NTRS)

Hoffman, W. C.; Kleinman, D. L.; Young, L. R.

1976-01-01

A systematic design methodology for pilot displays in advanced commercial VTOL aircraft was developed and refined. The analyst is provided with a step-by-step procedure for conducting conceptual display/control configurations evaluations for simultaneous monitoring and control pilot tasks. The approach consists of three phases: formulation of information requirements, configuration evaluation, and system selection. Both the monitoring and control performance models are based upon the optimal control model of the human operator. Extensions to the conventional optimal control model required in the display design methodology include explicit optimization of control/monitoring attention; simultaneous monitoring and control performance predictions; and indifference threshold effects. The methodology was applied to NASA's experimental CH-47 helicopter in support of the VALT program. The CH-47 application examined the system performance of six flight conditions. Four candidate configurations are suggested for evaluation in pilot-in-the-loop simulations and eventual flight tests.

Instantaneous angular speed monitoring of gearboxes under non-cyclic stationary load conditions

NASA Astrophysics Data System (ADS)

Stander, C. J.; Heyns, P. S.

2005-07-01

Recent developments in the condition monitoring and asset management market have led to the commercialisation of online vibration-monitoring systems. These systems are primarily utilised to monitor large mineral mining equipment such as draglines, continuous miners and hydraulic shovels. Online monitoring systems make diagnostic information continuously available for asset management, production outsourcing and maintenance alliances with equipment manufacturers. However, most online vibration-monitoring systems are based on conventional vibration-monitoring technologies, which are prone to giving false equipment deterioration warnings on gears that operate under fluctuating load conditions. A simplified mathematical model of a gear system was developed to illustrate the feasibility of monitoring the instantaneous angular speed (IAS) as a means of monitoring the condition of gears that are subjected to fluctuating load conditions. A distinction is made between cyclic stationary load modulation and non-cyclic stationary load modulation. It is shown that rotation domain averaging will suppress the modulation caused by non-cyclic stationary load conditions but will not suppress the modulation caused by cyclic stationary load conditions. An experimental investigation on a test rig indicated that the IAS of a gear shaft could be monitored with a conventional shaft encoder to indicate a deteriorating gear fault condition.

Health Monitoring for Airframe Structural Characterization

NASA Technical Reports Server (NTRS)

Munns, Thomas E.; Kent, Renee M.; Bartolini, Antony; Gause, Charles B.; Borinski, Jason W.; Dietz, Jason; Elster, Jennifer L.; Boyd, Clark; Vicari, Larry; Ray, Asok;

Bridge deterioration models to support Indiana's bridge management system.

DOT National Transportation Integrated Search

2016-02-01

An effective bridge management system that is equipped with reliable deterioration models enables agency engineers to carry out : monitoring and long-term programming of bridge repair actions. At the project level, deterioration models help the agenc...

Introducing a new monitoring manual for home fortification and strengthening capacity to monitor nutrition interventions.

PubMed

Jefferds, Maria Elena D; Flores-Ayala, Rafael

2015-12-01

Lack of monitoring capacity is a key barrier for nutrition interventions and limits programme management, decision making and programme effectiveness in many low-income and middle-income countries. A 2011 global assessment reported lack of monitoring capacity was the top barrier for home fortification interventions, such as micronutrient powders or lipid-based nutrient supplements. A Manual for Developing and Implementing Monitoring Systems for Home Fortification Interventions was recently disseminated. It is comprehensive and describes monitoring concepts and frameworks and includes monitoring tools and worksheets. The monitoring manual describes the steps of developing and implementing a monitoring system for home fortification interventions, including identifying and engaging stakeholders; developing a programme description including logic model and logical framework; refining the purpose of the monitoring system, identifying users and their monitoring needs; describing the design of the monitoring system; developing indicators; describing the core components of a comprehensive monitoring plan; and considering factors related to stage of programme development, sustainability and scale up. A fictional home fortification example is used throughout the monitoring manual to illustrate these steps. The monitoring manual is a useful tool to support the development and implementation of home fortification intervention monitoring systems. In the context of systematic capacity gaps to design, implement and monitor nutrition interventions in many low-income and middle-income countries, the dissemination of new tools, such as monitoring manuals may have limited impact without additional attention to strengthening other individual, organisational and systems levels capacities. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Implementation of the Geological Hazard Monitoring and Early Warning System Based on Multi - source Data -A Case Study of Deqin Tibetan County, Yunnan Province

NASA Astrophysics Data System (ADS)

Zhao, Junsan; Chen, Guoping; Yuan, Lei

2017-04-01

The new technologies, such as 3D laser scanning, InSAR, GNSS, unmanned aerial vehicle and Internet of things, will provide much more data resources for the surveying and monitoring, as well as the development of Early Warning System (EWS). This paper provides the solutions of the design and implementation of a geological disaster monitoring and early warning system (GDMEWS), which includes landslides and debris flows hazard, based on the multi-sources of the date by use of technologies above mentioned. The complex and changeable characteristics of the GDMEWS are described. The architecture of the system, composition of the multi-source database, development mode and service logic, the methods and key technologies of system development are also analyzed. To elaborate the process of the implementation of the GDMEWS, Deqin Tibetan County is selected as a case study area, which has the unique terrain and diverse types of typical landslides and debris flows. Firstly, the system functional requirements, monitoring and forecasting models of the system are discussed. Secondly, the logic relationships of the whole process of disaster including pre-disaster, disaster rescue and post-disaster reconstruction are studied, and the support tool for disaster prevention, disaster reduction and geological disaster management are developed. Thirdly, the methods of the multi - source monitoring data integration and the generation of the mechanism model of Geological hazards and simulation are expressed. Finally, the construction of the GDMEWS is issued, which will be applied to management, monitoring and forecasting of whole disaster process in real-time and dynamically in Deqin Tibetan County. Keywords: multi-source spatial data; geological disaster; monitoring and warning system; Deqin Tibetan County

A cloud-based information repository for bridge monitoring applications

NASA Astrophysics Data System (ADS)

Jeong, Seongwoon; Zhang, Yilan; Hou, Rui; Lynch, Jerome P.; Sohn, Hoon; Law, Kincho H.

2016-04-01

This paper describes an information repository to support bridge monitoring applications on a cloud computing platform. Bridge monitoring, with instrumentation of sensors in particular, collects significant amount of data. In addition to sensor data, a wide variety of information such as bridge geometry, analysis model and sensor description need to be stored. Data management plays an important role to facilitate data utilization and data sharing. While bridge information modeling (BrIM) technologies and standards have been proposed and they provide a means to enable integration and facilitate interoperability, current BrIM standards support mostly the information about bridge geometry. In this study, we extend the BrIM schema to include analysis models and sensor information. Specifically, using the OpenBrIM standards as the base, we draw on CSI Bridge, a commercial software widely used for bridge analysis and design, and SensorML, a standard schema for sensor definition, to define the data entities necessary for bridge monitoring applications. NoSQL database systems are employed for data repository. Cloud service infrastructure is deployed to enhance scalability, flexibility and accessibility of the data management system. The data model and systems are tested using the bridge model and the sensor data collected at the Telegraph Road Bridge, Monroe, Michigan.

Model-based reasoning for power system management using KATE and the SSM/PMAD

NASA Technical Reports Server (NTRS)

Morris, Robert A.; Gonzalez, Avelino J.; Carreira, Daniel J.; Mckenzie, F. D.; Gann, Brian

1993-01-01

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Characterization of Model-Based Reasoning Strategies for Use in IVHM Architectures

NASA Technical Reports Server (NTRS)

Poll, Scott; Iverson, David; Patterson-Hine, Ann

2003-01-01

Open architectures are gaining popularity for Integrated Vehicle Health Management (IVHM) applications due to the diversity of subsystem health monitoring strategies in use and the need to integrate a variety of techniques at the system health management level. The basic concept of an open architecture suggests that whatever monitoring or reasoning strategy a subsystem wishes to deploy, the system architecture will support the needs of that subsystem and will be capable of transmitting subsystem health status across subsystem boundaries and up to the system level for system-wide fault identification and diagnosis. There is a need to understand the capabilities of various reasoning engines and how they, coupled with intelligent monitoring techniques, can support fault detection and system level fault management. Researchers in IVHM at NASA Ames Research Center are supporting the development of an IVHM system for liquefying-fuel hybrid rockets. In the initial stage of this project, a few readily available reasoning engines were studied to assess candidate technologies for application in next generation launch systems. Three tools representing the spectrum of model-based reasoning approaches, from a quantitative simulation based approach to a graph-based fault propagation technique, were applied to model the behavior of the Hybrid Combustion Facility testbed at Ames. This paper summarizes the characterization of the modeling process for each of the techniques.

Fuzzy Petri nets to model vision system decisions within a flexible manufacturing system

NASA Astrophysics Data System (ADS)

Hanna, Moheb M.; Buck, A. A.; Smith, R.

1994-10-01

The paper presents a Petri net approach to modelling, monitoring and control of the behavior of an FMS cell. The FMS cell described comprises a pick and place robot, vision system, CNC-milling machine and 3 conveyors. The work illustrates how the block diagrams in a hierarchical structure can be used to describe events at different levels of abstraction. It focuses on Fuzzy Petri nets (Fuzzy logic with Petri nets) including an artificial neural network (Fuzzy Neural Petri nets) to model and control vision system decisions and robot sequences within an FMS cell. This methodology can be used as a graphical modelling tool to monitor and control the imprecise, vague and uncertain situations, and determine the quality of the output product of an FMS cell.

78 FR 37133 - National Emission Standards for Hazardous Air Pollutants From Petroleum Refineries

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-20

... systems that would allow owners and operators at existing sources to monitor quarterly using a leak action... option, which requires monitoring monthly at a leak action level defined as a total strippable... monitoring alternative and the modeling indicates that quarterly monitoring at the lower leak action level...

40 CFR 60.5225 - What are the monitoring and calibration requirements for compliance with my operating limits?

Code of Federal Regulations, 2012 CFR

2012-07-01

... SOURCES Emission Guidelines and Compliance Times for Existing Sewage Sludge Incineration Units Model Rule... monitoring system according to your monitoring plan required under § 60.4880. Additionally: (i) For carrier gas flow rate monitors (for activated carbon injection), during the performance test conducted...

Cabin Atmosphere Monitoring System (CAMS), pre-prototype model development continuation

NASA Technical Reports Server (NTRS)

Bursack, W. W.; Harris, W. A.

1975-01-01

The development of the Cabin Atmosphere Monitoring System (CAMS) is described. Attention was directed toward improving stability and reliability of the design using flight application guidelines. Considerable effort was devoted to the development of a temperature-stable RF/DC generator used for excitation of the quadrupole mass filter. Minor design changes were made in the preprototype model. Specific gas measurement examples are included along with a discussion of the measurement rationale employed.

Mapping the information landscape: Discerning peaks and valleys for ecological monitoring

USGS Publications Warehouse

Moniz, L.J.; Nichols, J.D.; Nichols, J.M.

2007-01-01

We investigate previously unreported phenomena that have a potentially significant impact on the design of surveillance monitoring programs for ecological systems. Ecological monitoring practitioners have long recognized that different species are differentially informative of a system?s dynamics, as codified in the well-known concepts of indicator or keystone species. Using a novel combination of analysis techniques from nonlinear dynamics, we describe marked variation among spatial sites in information content with respect to system dynamics in the entire region. We first observed these phenomena in a spatially extended predator?prey model, but we observed strikingly similar features in verified water-level data from a NOAA/NOS Great Lakes monitoring program. We suggest that these features may be widespread and the design of surveillance monitoring programs should reflect knowledge of their existence.

The Application of Lidar to Synthetic Vision System Integrity

NASA Technical Reports Server (NTRS)

Campbell, Jacob L.; UijtdeHaag, Maarten; Vadlamani, Ananth; Young, Steve

2003-01-01

One goal in the development of a Synthetic Vision System (SVS) is to create a system that can be certified by the Federal Aviation Administration (FAA) for use at various flight criticality levels. As part of NASA s Aviation Safety Program, Ohio University and NASA Langley have been involved in the research and development of real-time terrain database integrity monitors for SVS. Integrity monitors based on a consistency check with onboard sensors may be required if the inherent terrain database integrity is not sufficient for a particular operation. Sensors such as the radar altimeter and weather radar, which are available on most commercial aircraft, are currently being investigated for use in a real-time terrain database integrity monitor. This paper introduces the concept of using a Light Detection And Ranging (LiDAR) sensor as part of a real-time terrain database integrity monitor. A LiDAR system consists of a scanning laser ranger, an inertial measurement unit (IMU), and a Global Positioning System (GPS) receiver. Information from these three sensors can be combined to generate synthesized terrain models (profiles), which can then be compared to the stored SVS terrain model. This paper discusses an initial performance evaluation of the LiDAR-based terrain database integrity monitor using LiDAR data collected over Reno, Nevada. The paper will address the consistency checking mechanism and test statistic, sensitivity to position errors, and a comparison of the LiDAR-based integrity monitor to a radar altimeter-based integrity monitor.

Real-time monitoring of process parameters in rice wine fermentation by a portable spectral analytical system combined with multivariate analysis.

PubMed

Ouyang, Qin; Zhao, Jiewen; Pan, Wenxiu; Chen, Quansheng

2016-01-01

A portable and low-cost spectral analytical system was developed and used to monitor real-time process parameters, i.e. total sugar content (TSC), alcohol content (AC) and pH during rice wine fermentation. Various partial least square (PLS) algorithms were implemented to construct models. The performance of a model was evaluated by the correlation coefficient (Rp) and the root mean square error (RMSEP) in the prediction set. Among the models used, the synergy interval PLS (Si-PLS) was found to be superior. The optimal performance by the Si-PLS model for the TSC was Rp = 0.8694, RMSEP = 0.438; the AC was Rp = 0.8097, RMSEP = 0.617; and the pH was Rp = 0.9039, RMSEP = 0.0805. The stability and reliability of the system, as well as the optimal models, were verified using coefficients of variation, most of which were found to be less than 5%. The results suggest this portable system is a promising tool that could be used as an alternative method for rapid monitoring of process parameters during rice wine fermentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conceptual ecological models to support detection of ecological change on Alaska National Wildlife Refuges

USGS Publications Warehouse

Woodward, Andrea; Beever, Erik A.

2011-01-01

More than 31 million hectares of land are protected and managed in 16 refuges by the U.S. Fish and Wildlife Service (USFWS) in Alaska. The vastness and isolation of Alaskan refuges give rise to relatively intact and complete ecosystems. The potential for these lands to provide habitat for trust species is likely to be altered, however, due to global climate change, which is having dramatic effects at high latitudes. The ability of USFWS to effectively manage these lands in the future will be enhanced by a regional inventory and monitoring program that integrates and supplements monitoring currently being implemented by individual refuges. Conceptual models inform monitoring programs in a number of ways, including summarizing important ecosystem components and processes as well as facilitating communication, discussion and debate about the nature of the system and important management issues. This process can lead to hypotheses regarding future changes, likely results of alternative management actions, identification of monitoring indicators, and ultimately, interpretation of monitoring results. As a first step towards developing a monitoring program, the 16 refuges in Alaska each created a conceptual model of their refuge and the landscape context. Models include prominent ecosystem components, drivers, and processes by which components are linked or altered. The Alaska refuge system also recognizes that designing and implementing monitoring at regional and ecoregional extents has numerous scientific, fiscal, logistical, and political advantages over monitoring conducted exclusively at refuge-specific scales. Broad-scale monitoring is particularly advantageous for examining phenomena such as climate change because effects are best interpreted at broader spatial extents. To enable an ecoregional perspective, a rationale was developed for deriving ecoregional boundaries for four ecoregions (Polar, Interior Alaska, Bering Coast, and North Pacific Coast) from the Unified Ecoregions of Alaska. Ecoregional models were then developed to illustrate resources and processes that operate at spatial scales larger than individual refuges within each ecoregion. Conceptual models also were developed for adjacent marine areas, designated as the North Pacific, Bering Sea, and Beaufort-Chukchi Sea Marine Ecoregions. Although many more conceptual models will be required to support development of a regional monitoring program, these definitions of ecoregions and associated conceptual models are an important foundation.

Microbial load monitor

NASA Technical Reports Server (NTRS)

Caplin, R. S.; Royer, E. R.

1977-01-01

Design analysis of a microbial load monitor system flight engineering model was presented. Checkout of the card taper and media pump system was fabricated as well as the final two incubating reading heads, the sample receiving and card loading device assembly, related sterility testing, and software. Progress in these areas was summarized.

TRANSMAP : an integrated, real time environmental monitoring and forecasting system for highways and waterways in RI

DOT National Transportation Integrated Search

2001-12-01

This report summarizes the work accomplished during the second year of a three-year project to develop a state of the art, integrated environmental monitoring and modeling system to provide data and information to support the operation, management, a...

A survey of fuzzy logic monitoring and control utilisation in medicine.

PubMed

Mahfouf, M; Abbod, M F; Linkens, D A

2001-01-01

Intelligent systems have appeared in many technical areas, such as consumer electronics, robotics and industrial control systems. Many of these intelligent systems are based on fuzzy control strategies which describe complex systems mathematical models in terms of linguistic rules. Since the 1980s new techniques have appeared from which fuzzy logic has been applied extensively in medical systems. The justification for such intelligent systems driven solutions is that biological systems are so complex that the development of computerised systems within such environments is not always a straightforward exercise. In practice, a precise model may not exist for biological systems or it may be too difficult to model. In most cases fuzzy logic is considered to be an ideal tool as human minds work from approximate data, extract meaningful information and produce crisp solutions. This paper surveys the utilisation of fuzzy logic control and monitoring in medical sciences with an analysis of its possible future penetration.

The thermal impact of aquifer thermal energy storage (ATES) systems: a case study in the Netherlands, combining monitoring and modeling

NASA Astrophysics Data System (ADS)

Visser, Philip W.; Kooi, Henk; Stuyfzand, Pieter J.

2015-05-01

Results are presented of a comprehensive thermal impact study on an aquifer thermal energy storage (ATES) system in Bilthoven, the Netherlands. The study involved monitoring of the thermal impact and modeling of the three-dimensional temperature evolution of the storage aquifer and over- and underlying units. Special attention was paid to non-uniformity of the background temperature, which varies laterally and vertically in the aquifer. Two models were applied with different levels of detail regarding initial conditions and heterogeneity of hydraulic and thermal properties: a fine-scale heterogeneity model which construed the lateral and vertical temperature distribution more realistically, and a simplified model which represented the aquifer system with only a limited number of homogeneous layers. Fine-scale heterogeneity was shown to be important to accurately model the ATES-impacted vertical temperature distribution and the maximum and minimum temperatures in the storage aquifer, and the spatial extent of the thermal plumes. The fine-scale heterogeneity model resulted in larger thermally impacted areas and larger temperature anomalies than the simplified model. The models showed that scattered and scarce monitoring data of ATES-induced temperatures can be interpreted in a useful way by groundwater and heat transport modeling, resulting in a realistic assessment of the thermal impact.

Predictive monitoring and diagnosis of periodic air pollution in a subway station.

PubMed

Kim, YongSu; Kim, MinJung; Lim, JungJin; Kim, Jeong Tai; Yoo, ChangKyoo

2010-11-15

The purpose of this study was to develop a predictive monitoring and diagnosis system for the air pollutants in a subway system using a lifting technique with a multiway principal component analysis (MPCA) which monitors the periodic patterns of the air pollutants and diagnoses the sources of the contamination. The basic purpose of this lifting technique was to capture the multivariate and periodic characteristics of all of the indoor air samples collected during each day. These characteristics could then be used to improve the handling of strong periodic fluctuations in the air quality environment in subway systems and will allow important changes in the indoor air quality to be quickly detected. The predictive monitoring approach was applied to a real indoor air quality dataset collected by telemonitoring systems (TMS) that indicated some periodic variations in the air pollutants and multivariate relationships between the measured variables. Two monitoring models--global and seasonal--were developed to study climate change in Korea. The proposed predictive monitoring method using the lifted model resulted in fewer false alarms and missed faults due to non-stationary behavior than that were experienced with the conventional methods. This method could be used to identify the contributions of various pollution sources. Copyright © 2010 Elsevier B.V. All rights reserved.

Real time sound analysis for medical remote monitoring.

PubMed

Istrate, Dan; Binet, Morgan; Cheng, Sreng

2008-01-01

The increase of aging population in Europe involves more people living alone at home with an increased risk of home accidents or falls. In order to prevent or detect a distress situation in the case of an elderly people living alone, a remote monitoring system based on the sound environment analysis can be used. We have already proposed a system which monitors the sound environment, identifies everyday life sounds and distress expressions in order to participate to an alarm decision. This first system uses a classical sound card on a PC or embedded PC allowing only one channel monitor. In this paper, we propose a new architecture of the remote monitoring system, which relies on a real time multichannel implementation based on an USB acquisition card. This structure allows monitoring eight channels in order to cover all the rooms of an apartment. More than that, the SNR estimation leads currently to the adaptation of the recognition models to environment.

Studies and analyses of the space shuttle main engine

NASA Technical Reports Server (NTRS)

Tischer, Alan E.; Glover, R. C.

1987-01-01

The primary objectives were to: evaluate ways to maximize the information yield from the current Space Shuttle Main Engine (SSME) condition monitoring sensors, identify additional sensors or monitoring capabilities which would significantly improve SSME data, and provide continuing support of the Main Engine Cost/Operations (MECO) model. In the area of SSME condition monitoring, the principal tasks were a review of selected SSME failure data, a general survey of condition monitoring, and an evaluation of the current engine monitoring system. A computerized data base was developed to assist in modeling engine failure information propagations. Each of the above items is discussed in detail. Also included is a brief discussion of the activities conducted in support of the MECO model.

Small scale monitoring of a bioremediation barrier using miniature electrical resistivity tomography

NASA Astrophysics Data System (ADS)

Sentenac, Philippe; Hogson, Tom; Keenan, Helen; Kulessa, Bernd

2015-04-01

The aim of this study was to assess, in the laboratory, the efficiency of a barrier of oxygen release compound (ORC) to block and divert a diesel plume migration in a scaled aquifer model using miniature electrical resistivity tomography (ERT) as the monitoring system. Two plumes of contaminant (diesel) were injected in a soil model made of local sand and clay. The diesel plumes migration was imaged and monitored using a miniature resistivity array system that has proved to be accurate in soil resistivity variations in small-scaled models of soil. ERT results reflected the lateral spreading and diversion of the diesel plumes in the unsaturated zone. One of the contaminant plumes was partially blocked by the ORC barrier and a diversion and reorganisation of the diesel in the soil matrix was observed. The technique of time-lapse ERT imaging showed that a dense non-aqueous phase liquid (DNAPL) contaminant like diesel can be monitored through a bioremediation barrier and the technique is well suited to monitor the efficiency of the barrier. Therefore, miniature ERT as a small-scale modelling tool could complement conventional techniques, which require more expensive and intrusive site investigation prior to remediation.

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model

PubMed Central

Li, Xiaoqing; Wang, Yu

2018-01-01

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing technology. PMID:29351254

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

PubMed

Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

2018-01-19

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing technology.

Prognostics using Engineering and Environmental Parameters as Applied to State of Health (SOH) Radionuclide Aerosol Sampler Analyzer (RASA) Real-Time Monitoring

NASA Astrophysics Data System (ADS)

Hutchenson, K. D.; Hartley-McBride, S.; Saults, T.; Schmidt, D. P.

2006-05-01

The International Monitoring System (IMS) is composed in part of radionuclide particulate and gas monitoring systems. Monitoring the operational status of these systems is an important aspect of nuclear weapon test monitoring. Quality data, process control techniques, and predictive models are necessary to detect and predict system component failures. Predicting failures in advance provides time to mitigate these failures, thus minimizing operational downtime. The Provisional Technical Secretariat (PTS) requires IMS radionuclide systems be operational 95 percent of the time. The United States National Data Center (US NDC) offers contributing components to the IMS. This effort focuses on the initial research and process development using prognostics for monitoring and predicting failures of the RASA two (2) days into the future. The predictions, using time series methods, are input to an expert decision system, called SHADES (State of Health Airflow and Detection Expert System). The results enable personnel to make informed judgments about the health of the RASA system. Data are read from a relational database, processed, and displayed to the user in a GIS as a prototype GUI. This procedure mimics the real time application process that could be implemented as an operational system, This initial proof-of-concept effort developed predictive models focused on RASA components for a single site (USP79). Future work shall include the incorporation of other RASA systems, as well as their environmental conditions that play a significant role in performance. Similarly, SHADES currently accommodates specific component behaviors at this one site. Future work shall also include important environmental variables that play an important part of the prediction algorithms.

How conduit models can be used to interpret volcano monitoring data

NASA Astrophysics Data System (ADS)

Thomas, M. E.; Neuberg, J. W.; Karl, S.; Collinson, A.; Pascal, K.

2012-04-01

During the last decade there have been major advances in the field of volcano monitoring, but to be able to take full advantage of these advances it is vital to link the monitoring data with the physical processes that give rise to the recorded signals. To obtain a better understanding of these physical processes it is necessary to understand the conditions of the system at depth. This can be achieved through numerical modelling. We present the results of conduit models representative of a silicic volcanic system and demonstrate how processes identified and interpreted from these models may manifest in the recorded monitoring data. Links are drawn to seismicity, deformation, and gas emissions. A key point is how these data compliment each other, and through utilising conduit models we are able to interpret how these different data may be recorded in response to a particular process. This is an invaluable tool as it is far easier to draw firm conclusions on what is happening at a volcano if there are several different data sets that suggest the same processes are occurring. Some of these interpretations appear useful in forecasting potentially catastrophic changes in eruptive behaviour, such as a dome collapse leading to violent explosive behaviour, and the role of monitoring data in this capacity will also be addressed.

Virtual expansion of the technical vision system for smart vehicles based on multi-agent cooperation model

NASA Astrophysics Data System (ADS)

Krapukhina, Nina; Senchenko, Roman; Kamenov, Nikolay

2017-12-01

Road safety and driving in dense traffic flows poses some challenges in receiving information about surrounding moving object, some of which can be in the vehicle's blind spot. This work suggests an approach to virtual monitoring of the objects in a current road scene via a system with a multitude of cooperating smart vehicles exchanging information. It also describes the intellectual agent model, and provides methods and algorithms of identifying and evaluating various characteristics of moving objects in video flow. Authors also suggest ways for integrating the information from the technical vision system into the model with further expansion of virtual monitoring for the system's objects. Implementation of this approach can help to expand the virtual field of view for a technical vision system.

A knowledge-based flight status monitor for real-time application in digital avionics systems

NASA Technical Reports Server (NTRS)

Duke, E. L.; Disbrow, J. D.; Butler, G. F.

1989-01-01

The Dryden Flight Research Facility of the National Aeronautics and Space Administration (NASA) Ames Research Center (Ames-Dryden) is the principal NASA facility for the flight testing and evaluation of new and complex avionics systems. To aid in the interpretation of system health and status data, a knowledge-based flight status monitor was designed. The monitor was designed to use fault indicators from the onboard system which are telemetered to the ground and processed by a rule-based model of the aircraft failure management system to give timely advice and recommendations in the mission control room. One of the important constraints on the flight status monitor is the need to operate in real time, and to pursue this aspect, a joint research activity between NASA Ames-Dryden and the Royal Aerospace Establishment (RAE) on real-time knowledge-based systems was established. Under this agreement, the original LISP knowledge base for the flight status monitor was reimplemented using the intelligent knowledge-based system toolkit, MUSE, which was developed under RAE sponsorship. Details of the flight status monitor and the MUSE implementation are presented.

Space Shuttle Main Engine: Advanced Health Monitoring System

NASA Technical Reports Server (NTRS)

Singer, Chirs

1999-01-01

The main gola of the Space Shuttle Main Engine (SSME) Advanced Health Management system is to improve flight safety. To this end the new SSME has robust new components to improve the operating margen and operability. The features of the current SSME health monitoring system, include automated checkouts, closed loop redundant control system, catastropic failure mitigation, fail operational/ fail-safe algorithms, and post flight data and inspection trend analysis. The features of the advanced health monitoring system include: a real time vibration monitor system, a linear engine model, and an optical plume anomaly detection system. Since vibration is a fundamental measure of SSME turbopump health, it stands to reason that monitoring the vibration, will give some idea of the health of the turbopumps. However, how is it possible to avoid shutdown, when it is not necessary. A sensor algorithm has been developed which has been exposed to over 400 test cases in order to evaluate the logic. The optical plume anomaly detection (OPAD) has been developed to be a sensitive monitor of engine wear, erosion, and breakage.

Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure

PubMed Central

Wu, Lai-Yi

2015-01-01

Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the performance deterioration during the long-time service of the bridge, a Structural Health Monitoring (SHM) system has been implemented on this bridge by the application of modern techniques in sensing, testing, computing, and network communication. The SHM system includes various sensors as well as corresponding data acquisition and transmission equipment for automatic data collection. Furthermore, an evaluation system of structural safety has been developed for the real-time condition assessment of this bridge. The mathematical correlation models describing the overall structural behavior of the bridge can be obtained with the support of the health monitoring system, which includes cross-correlation models for accelerations, correlation models between temperature and static strains of steel truss arch, and correlation models between temperature and longitudinal displacements of piers. Some evaluation results using the mean value control chart based on mathematical correlation models are presented in this paper to show the effectiveness of this SHM system in detecting the bridge's abnormal behaviors under the varying environmental conditions such as high-speed trains and environmental temperature. PMID:26451387

[The Development of Information Centralization and Management Integration System for Monitors Based on Wireless Sensor Network].

PubMed

Xu, Xiu; Zhang, Honglei; Li, Yiming; Li, Bin

2015-07-01

Developed the information centralization and management integration system for monitors of different brands and models with wireless sensor network technologies such as wireless location and wireless communication, based on the existing wireless network. With adaptive implementation and low cost, the system which possesses the advantages of real-time, efficiency and elaboration is able to collect status and data of the monitors, locate the monitors, and provide services with web server, video server and locating server via local network. Using an intranet computer, the clinical and device management staffs can access the status and parameters of monitors. Applications of this system provide convenience and save human resource for clinical departments, as well as promote the efficiency, accuracy and elaboration for the device management. The successful achievement of this system provides solution for integrated and elaborated management of the mobile devices including ventilator and infusion pump.

Health State Utilities Associated with Glucose Monitoring Devices.

PubMed

Matza, Louis S; Stewart, Katie D; Davies, Evan W; Hellmund, Richard; Polonsky, William H; Kerr, David

2017-03-01

Glucose monitoring is important for patients with diabetes treated with insulin. Conventional glucose monitoring requires a blood sample, typically obtained by pricking the finger. A new sensor-based system called "flash glucose monitoring" monitors glucose levels with a sensor worn on the arm, without requiring blood samples. To estimate the utility difference between these two glucose monitoring approaches for use in cost-utility models. In time trade-off interviews, general population participants in the United Kingdom (London and Edinburgh) valued health states that were drafted and refined on the basis of literature, clinician input, and a pilot study. The health states had identical descriptions of diabetes and insulin treatment, differing only in glucose monitoring approach. A total of 209 participants completed the interviews (51.7% women; mean age = 42.1 years). Mean utilities were 0.851 ± 0.140 for conventional monitoring and 0.882 ± 0.121 for flash monitoring (significant difference between the mean utilities; t = 8.3; P < 0.0001). Of the 209 participants, 78 (37.3%) had a higher utility for flash monitoring, 2 (1.0%) had a higher utility for conventional monitoring, and 129 (61.7%) had the same utility for both health states. The flash glucose monitoring system was associated with a significantly greater utility than the conventional monitoring system. This difference may be useful in cost-utility models comparing the value of glucose monitoring devices for patients with diabetes. This study adds to the literature on treatment process utilities, suggesting that time trade-off methods may be used to quantify preferences among medical devices. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Rater Accuracy and Training Group Effects in Expert- and Supervisor-Based Monitoring Systems

ERIC Educational Resources Information Center

Baird, Jo-Anne; Meadows, Michelle; Leckie, George; Caro, Daniel

2017-01-01

This study evaluated rater accuracy with rater-monitoring data from high stakes examinations in England. Rater accuracy was estimated with cross-classified multilevel modelling. The data included face-to-face training and monitoring of 567 raters in 110 teams, across 22 examinations, giving a total of 5500 data points. Two rater-monitoring systems…

A feasibility study on the predictive emission monitoring system applied to the Hsinta power plant of Taiwan Power Company.

PubMed

Chien, T W; Chu, H; Hsu, W C; Tseng, T K; Hsu, C H; Chen, K Y

2003-08-01

The continuous emission monitoring system (CEMS) can monitor flue gas emissions continuously and instantaneously. However, it has the disadvantages of enormous cost, easily producing errors in sampling periods of bad weather, lagging response in variable ambient environments, and missing data in daily zero and span tests and maintenance. The concept of a predictive emission monitoring system (PEMS) is to use the operating parameters of combustion equipment through thermodynamic or statistical methods to construct a mathematic model that can predict emissions by a computer program. The goal of this study is to set up a PEMS in a gas-fired combined cycle power generation unit at the Hsinta station of Taiwan Power Co. The emissions to be monitored include nitrogen oxides (NOx) and oxygen (O2) in flue gas. The major variables of the predictive model were determined based on the combustion theory. The data of these variables then were analyzed to establish a regression model. From the regression results, the influences of these variables are discussed and the predicted values are compared with the CEMS data for accuracy. In addition, according to the cost information, the capital and operation and maintenance costs for a PEMS can be much lower than those for a CEMS.

Transregional Collaborative Research Centre 32: Patterns in Soil-Vegetation-Atmosphere-Systems

NASA Astrophysics Data System (ADS)

Masbou, M.; Simmer, C.; Kollet, S.; Boessenkool, K.; Crewell, S.; Diekkrüger, B.; Huber, K.; Klitzsch, N.; Koyama, C.; Vereecken, H.

2012-04-01

The soil-vegetation-atmosphere system is characterized by non-linear exchanges of mass, momentum and energy with complex patterns, structures and processes that act at different temporal and spatial scales. Under the TR32 framework, the characterisation of these structures and patterns will lead to a deeper qualitative and quantitative understanding of the SVA system, and ultimately to better predictions of the SVA state. Research in TR32 is based on three methodological pillars: Monitoring, Modelling and Data Assimilation. Focusing our research on the Rur Catchment (Germany), patterns are monitored since 2006 continuously using existing and novel geophysical and remote sensing techniques from the local to the catchment scale based on ground penetrating radar methods, induced polarization, radiomagnetotellurics, electrical resistivity tomography, boundary layer scintillometry, lidar techniques, cosmic-ray, microwave radiometry, and precipitation radars with polarization diversity. Modelling approaches involve development of scaled consistent coupled model platform: high resolution numerical weather prediction (NWP; 400m) and hydrological models (few meters). In the second phase (2011-2014), the focus is on the integration of models from the groundwater to the atmosphere for both the m- and km-scale and the extension of the experimental monitoring in respect to vegetation. The coupled modelling platform is based on the atmospheric model COSMO, the land surface model CLM and the hydrological model ParFlow. A scale consistent two-way coupling is performed using the external OASIS coupler. Example work includes the transfer of laboratory methods to the field; the measurements of patterns of soil-carbon, evapotranspiration and respiration measured in the field; catchment-scale modeling of exchange processes and the setup of an atmospheric boundary layer monitoring network. These modern and predominantly non-invasive measurement techniques are exploited in combination with advanced modelling systems by data assimilation to yield improved numerical models for the prediction of water-, energy and CO2-transfer by accounting for the patterns occurring at various scales.

mHealthMon: toward energy-efficient and distributed mobile health monitoring using parallel offloading.

PubMed

Ahnn, Jong Hoon; Potkonjak, Miodrag

2013-10-01

Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient's sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application's quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobile health monitoring application, in various mobile health monitoring scenarios applying a realistic mobility model.

Phasor Measurement Unit and Its Application in Modern Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Jian; Makarov, Yuri V.; Dong, Zhao Yang

2010-06-01

The introduction of phasor measuring units (PMUs) in power systems significantly improves the possibilities for monitoring and analyzing power system dynamics. Synchronized measurements make it possible to directly measure phase angles between corresponding phasors in different locations within the power system. Improved monitoring and remedial action capabilities allow network operators to utilize the existing power system in a more efficient way. Improved information allows fast and reliable emergency actions, which reduces the need for relatively high transmission margins required by potential power system disturbances. In this chapter, the applications of PMU in modern power systems are presented. Specifically, the topicsmore » touched in this chapter include state estimation, voltage and transient stability, oscillation monitoring, event and fault detection, situation awareness, and model validation. A case study using Characteristic Ellipsoid method based on PMU to monitor power system dynamic is presented.« less

A Seamless Framework for Global Water Cycle Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

2013-12-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

A robust quantitative near infrared modeling approach for blend monitoring.

PubMed

Mohan, Shikhar; Momose, Wataru; Katz, Jeffrey M; Hossain, Md Nayeem; Velez, Natasha; Drennen, James K; Anderson, Carl A

2018-01-30

This study demonstrates a material sparing Near-Infrared modeling approach for powder blend monitoring. In this new approach, gram scale powder mixtures are subjected to compression loads to simulate the effect of scale using an Instron universal testing system. Models prepared by the new method development approach (small-scale method) and by a traditional method development (blender-scale method) were compared by simultaneously monitoring a 1kg batch size blend run. Both models demonstrated similar model performance. The small-scale method strategy significantly reduces the total resources expended to develop Near-Infrared calibration models for on-line blend monitoring. Further, this development approach does not require the actual equipment (i.e., blender) to which the method will be applied, only a similar optical interface. Thus, a robust on-line blend monitoring method can be fully developed before any large-scale blending experiment is viable, allowing the blend method to be used during scale-up and blend development trials. Copyright © 2017. Published by Elsevier B.V.

Real-time monitoring of a microbial electrolysis cell using an electrical equivalent circuit model.

PubMed

Hussain, S A; Perrier, M; Tartakovsky, B

2018-04-01

Efforts in developing microbial electrolysis cells (MECs) resulted in several novel approaches for wastewater treatment and bioelectrosynthesis. Practical implementation of these approaches necessitates the development of an adequate system for real-time (on-line) monitoring and diagnostics of MEC performance. This study describes a simple MEC equivalent electrical circuit (EEC) model and a parameter estimation procedure, which enable such real-time monitoring. The proposed approach involves MEC voltage and current measurements during its operation with periodic power supply connection/disconnection (on/off operation) followed by parameter estimation using either numerical or analytical solution of the model. The proposed monitoring approach is demonstrated using a membraneless MEC with flow-through porous electrodes. Laboratory tests showed that changes in the influent carbon source concentration and composition significantly affect MEC total internal resistance and capacitance estimated by the model. Fast response of these EEC model parameters to changes in operating conditions enables the development of a model-based approach for real-time monitoring and fault detection.

Raspberry Pi in-situ network monitoring system of groundwater flow and temperature integrated with OpenGeoSys

NASA Astrophysics Data System (ADS)

Park, Chan-Hee; Lee, Cholwoo

2016-04-01

Raspberry Pi series is a low cost, smaller than credit-card sized computers that various operating systems such as linux and recently even Windows 10 are ported to run on. Thanks to massive production and rapid technology development, the price of various sensors that can be attached to Raspberry Pi has been dropping at an increasing speed. Therefore, the device can be an economic choice as a small portable computer to monitor temporal hydrogeological data in fields. In this study, we present a Raspberry Pi system that measures a flow rate, and temperature of groundwater at sites, stores them into mysql database, and produces interactive figures and tables such as google charts online or bokeh offline for further monitoring and analysis. Since all the data are to be monitored on internet, any computers or mobile devices can be good monitoring tools at convenience. The measured data are further integrated with OpenGeoSys, one of the hydrogeological models that is also ported to the Raspberry Pi series. This leads onsite hydrogeological modeling fed by temporal sensor data to meet various needs.

Development of a multi-ensemble Prediction Model for China

NASA Astrophysics Data System (ADS)

Brasseur, G. P.; Bouarar, I.; Petersen, A. K.

2016-12-01

As part of the EU-sponsored Panda and MarcoPolo Projects, a multi-model prediction system including 7 models has been developed. Most regional models use global air quality predictions provided by the Copernicus Atmospheric Monitoring Service and downscale the forecast at relatively high spatial resolution in eastern China. The paper will describe the forecast system and show examples of forecasts produced for several Chinese urban areas and displayed on a web site developed by the Dutch Meteorological service. A discussion on the accuracy of the predictions based on a detailed validation process using surface measurements from the Chinese monitoring network will be presented.

On the role of model-based monitoring for adaptive planning under uncertainty

NASA Astrophysics Data System (ADS)

Raso, Luciano; Kwakkel, Jan; Timmermans, Jos; Haasnoot, Mariolijn

2016-04-01

Adaptive plans, designed to anticipate and respond to an unfolding uncertain future, have found a fertile application domain in the planning of deltas that are exposed to rapid socioeconomic development and climate change. Adaptive planning, under the moniker of adaptive delta management, is used in the Dutch Delta Program for developing a nation-wide plan to prepare for uncertain climate change and socio-economic developments. Scientifically, adaptive delta management relies heavily on Dynamic Adaptive Policy Pathways. Currently, in the Netherlands the focus is shifting towards implementing the adaptive delta plan. This shift is especially relevant because the efficacy of adaptive plans hinges on monitoring on-going developments and ensuring that actions are indeed taken if and when necessary. In the design of an effective monitoring system for an adaptive plan, three challenges have to be confronted: • Shadow of the past: The development of adaptive plans and the design of their monitoring system relies heavily on current knowledge of the system, and current beliefs about plausible future developments. A static monitoring system is therefore exposed to the exact same uncertainties one tries to address through adaptive planning. • Inhibition of learning: Recent applications of adaptive planning tend to overlook the importance of learning and new information, and fail to account for this explicitly in the design of adaptive plans. • Challenge of surprise: Adaptive policies are designed in light of the current foreseen uncertainties. However, developments that are not considered during the design phase as being plausible could still substantially affect the performance of adaptive policies. The shadow of the past, the inhibition of learning, and the challenge of surprise taken together suggest that there is a need for redesigning the concepts of monitoring and evaluation to support the implementation of adaptive plans. Innovations from control theory, triggered by the challenge of uncertainty in operational control, may offer solutions from which monitoring for adaptive planning can benefit. Specifically: (i) in control, observations are incorporated into the model through data assimilation, updating the present state, boundary conditions, and parameters based on new observations, diminishing the shadow of the past; (ii) adaptive control is a way to modify the characteristics of the internal model, incorporating new knowledge on the system, countervailing the inhibition of learning; and (iii) in closed-loop control, a continuous system update equips the controller with "inherent robustness", i.e. to capacity to adapts to new conditions even when these were not initially considered. We aim to explore how inherent robustness addresses the challenge of surprise. Innovations in model-based control might help to improve and adapt the models used to support adaptive delta management to new information (reducing uncertainty). Moreover, this would offer a starting point for using these models not only in the design of adaptive plans, but also as part of the monitoring. The proposed research requires multidisciplinary cooperation between control theory, the policy sciences, and integrated assessment modeling.

Metric Ranking of Invariant Networks with Belief Propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tao, Changxia; Ge, Yong; Song, Qinbao

The management of large-scale distributed information systems relies on the effective use and modeling of monitoring data collected at various points in the distributed information systems. A promising approach is to discover invariant relationships among the monitoring data and generate invariant networks, where a node is a monitoring data source (metric) and a link indicates an invariant relationship between two monitoring data. Such an invariant network representation can help system experts to localize and diagnose the system faults by examining those broken invariant relationships and their related metrics, because system faults usually propagate among the monitoring data and eventually leadmore » to some broken invariant relationships. However, at one time, there are usually a lot of broken links (invariant relationships) within an invariant network. Without proper guidance, it is difficult for system experts to manually inspect this large number of broken links. Thus, a critical challenge is how to effectively and efficiently rank metrics (nodes) of invariant networks according to the anomaly levels of metrics. The ranked list of metrics will provide system experts with useful guidance for them to localize and diagnose the system faults. To this end, we propose to model the nodes and the broken links as a Markov Random Field (MRF), and develop an iteration algorithm to infer the anomaly of each node based on belief propagation (BP). Finally, we validate the proposed algorithm on both realworld and synthetic data sets to illustrate its effectiveness.« less

Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches.

PubMed

Suzuki, Noriyuki; Murasawa, Kaori; Sakurai, Takeo; Nansai, Keisuke; Matsuhashi, Keisuke; Moriguchi, Yuichi; Tanabe, Kiyoshi; Nakasugi, Osami; Morita, Masatoshi

2004-11-01

A spatially resolved and geo-referenced dynamic multimedia environmental fate model, G-CIEMS (Grid-Catchment Integrated Environmental Modeling System) was developed on a geographical information system (GIS). The case study for Japan based on the air grid cells of 5 x 5 km resolution and catchments with an average area of 9.3 km2, which corresponds to about 40,000 air grid cells and 38,000 river segments/catchment polygons, were performed for dioxins, benzene, 1,3-butadiene, and di-(2-ethyhexyl)phthalate. The averaged concentration of the model and monitoring output were within a factor of 2-3 for all the media. Outputs from G-CIEMS and the generic model were essentially comparable when identical parameters were employed, whereas the G-CIEMS model gave explicit information of distribution of chemicals in the environment. Exposure-weighted averaged concentrations (EWAC) in air were calculated to estimate the exposure ofthe population, based on the results of generic, G-CIEMS, and monitoring approaches. The G-CIEMS approach showed significantly better agreement with the monitoring-derived EWAC than the generic model approach. Implication for the use of a geo-referenced modeling approach in the risk assessment scheme is discussed as a generic-spatial approach, which can be used to provide more accurate exposure estimation with distribution information, using generally available data sources for a wide range of chemicals.

Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Sheffield, J.; Lobell, D. B.; Wood, E. F.

2010-12-01

Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including objective quantification and tracking of their spatial-temporal characteristics. Further we present strategies for merging various sources of information, including bias correction of satellite precipitation and assimilation of remotely sensed soil moisture, which can augment the monitoring in regions where satellite precipitation is most uncertain. Ongoing work is adding a drought forecast component based on a successful implementation over the U.S. and agricultural productivity estimates based on output from crop yield models. The forecast component uses seasonal global climate forecasts from the NCEP Climate Forecast System (CFS). These are merged with observed climatology in a Bayesian framework to produce ensemble atmospheric forcings that better capture the uncertainties. At the same time, the system bias corrects and downscales the monthly CFS data. We show some initial seasonal (up to 6-month lead) hydrologic forecast results for the African system. Agricultural monitoring is based on the precipitation, temperature and soil moisture from the system to force statistical and process based crop yield models. We demonstrate the feasibility of monitoring major crop types across the world and show a strategy for providing predictions of yields within our drought forecast mode.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

Monitoring real-time navigation processes using the automated reasoning tool (ART)

NASA Technical Reports Server (NTRS)

Maletz, M. C.; Culbert, C. J.

1985-01-01

An expert system is described for monitoring and controlling navigation processes in real-time. The ART-based system features data-driven computation, accommodation of synchronous and asynchronous data, temporal modeling for individual time intervals and chains of time intervals, and hypothetical reasoning capabilities that consider alternative interpretations of the state of navigation processes. The concept is illustrated in terms of the NAVEX system for monitoring and controlling the high speed ground navigation console for Mission Control at Johnson Space Center. The reasoning processes are outlined, including techniques used to consider alternative data interpretations. Installation of the system has permitted using a single operator, instead of three, to monitor the ascent and entry phases of a Shuttle mission.

Implementation of medical monitor system based on networks

NASA Astrophysics Data System (ADS)

Yu, Hui; Cao, Yuzhen; Zhang, Lixin; Ding, Mingshi

2006-11-01

In this paper, the development trend of medical monitor system is analyzed and portable trend and network function become more and more popular among all kinds of medical monitor devices. The architecture of medical network monitor system solution is provided and design and implementation details of medical monitor terminal, monitor center software, distributed medical database and two kind of medical information terminal are especially discussed. Rabbit3000 system is used in medical monitor terminal to implement security administration of data transfer on network, human-machine interface, power management and DSP interface while DSP chip TMS5402 is used in signal analysis and data compression. Distributed medical database is designed for hospital center according to DICOM information model and HL7 standard. Pocket medical information terminal based on ARM9 embedded platform is also developed to interactive with center database on networks. Two kernels based on WINCE are customized and corresponding terminal software are developed for nurse's routine care and doctor's auxiliary diagnosis. Now invention patent of the monitor terminal is approved and manufacture and clinic test plans are scheduled. Applications for invention patent are also arranged for two medical information terminals.

EPA'S ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM: AVAILABILITY OF BROAD-SCALE ENVIRONMENTAL DATA AND OPPORTUNITIES FOR USE IN ENVIRONMENTAL MODELING APPLICATIONS

EPA Science Inventory

The Environmental Monitoring and Assessment Program (EMAP) has collected a suite of environmental data over a four year period from estuarine system in the mid-Atlantic and Gulf of Mexico. ata are currently available for secondary users including environmental modelers. he data w...

Research of diagnosis sensors fault based on correlation analysis of the bridge structural health monitoring system

NASA Astrophysics Data System (ADS)

Hu, Shunren; Chen, Weimin; Liu, Lin; Gao, Xiaoxia

2010-03-01

Bridge structural health monitoring system is a typical multi-sensor measurement system due to the multi-parameters of bridge structure collected from the monitoring sites on the river-spanning bridges. Bridge structure monitored by multi-sensors is an entity, when subjected to external action; there will be different performances to different bridge structure parameters. Therefore, the data acquired by each sensor should exist countless correlation relation. However, complexity of the correlation relation is decided by complexity of bridge structure. Traditionally correlation analysis among monitoring sites is mainly considered from physical locations. unfortunately, this method is so simple that it cannot describe the correlation in detail. The paper analyzes the correlation among the bridge monitoring sites according to the bridge structural data, defines the correlation of bridge monitoring sites and describes its several forms, then integrating the correlative theory of data mining and signal system to establish the correlation model to describe the correlation among the bridge monitoring sites quantificationally. Finally, The Chongqing Mashangxi Yangtze river bridge health measurement system is regards as research object to diagnosis sensors fault, and simulation results verify the effectiveness of the designed method and theoretical discussions.

Flow dynamics in hyper-saline aquifers: hydro-geophysical monitoring and modeling

NASA Astrophysics Data System (ADS)

Haaken, Klaus; Piero Deidda, Gian; Cassiani, Giorgio; Deiana, Rita; Putti, Mario; Paniconi, Claudio; Scudeler, Carlotta; Kemna, Andreas

2017-03-01

Saline-freshwater interaction in porous media is a phenomenon of practical interest particularly for the management of water resources in arid and semi-arid environments, where precious freshwater resources are threatened by seawater intrusion and where storage of freshwater in saline aquifers can be a viable option. Saline-freshwater interactions are controlled by physico-chemical processes that need to be accurately modeled. This in turn requires monitoring of these systems, a non-trivial task for which spatially extensive, high-resolution non-invasive techniques can provide key information. In this paper we present the field monitoring and numerical modeling components of an approach aimed at understanding complex saline-freshwater systems. The approach is applied to a freshwater injection experiment carried out in a hyper-saline aquifer near Cagliari (Sardinia, Italy). The experiment was monitored using time-lapse cross-hole electrical resistivity tomography (ERT). To investigate the flow dynamics, coupled numerical flow and transport modeling of the experiment was carried out using an advanced three-dimensional (3-D) density-driven flow-transport simulator. The simulation results were used to produce synthetic ERT inversion results to be compared against real field ERT results. This exercise demonstrates that the evolution of the freshwater bulb is strongly influenced by the system's (even mild) hydraulic heterogeneities. The example also highlights how the joint use of ERT imaging and gravity-dependent flow and transport modeling give fundamental information for this type of study.

Simulation of car movement along circular path

NASA Astrophysics Data System (ADS)

Fedotov, A. I.; Tikhov-Tinnikov, D. A.; Ovchinnikova, N. I.; Lysenko, A. V.

2017-10-01

Under operating conditions, suspension system performance changes which negatively affects vehicle stability and handling. The paper aims to simulate the impact of changes in suspension system performance on vehicle stability and handling. Methods. The paper describes monitoring of suspension system performance, testing of vehicle stability and handling, analyzes methods of suspension system performance monitoring under operating conditions. The mathematical model of a car movement along a circular path was developed. Mathematical tools describing a circular movement of a vehicle along a horizontal road were developed. Turning car movements were simulated. Calculation and experiment results were compared. Simulation proves the applicability of a mathematical model for assessment of the impact of suspension system performance on vehicle stability and handling.

Predictive Monitoring for Improved Management of Glucose Levels

PubMed Central

Reifman, Jaques; Rajaraman, Srinivasan; Gribok, Andrei; Ward, W. Kenneth

2007-01-01

Background Recent developments and expected near-future improvements in continuous glucose monitoring (CGM) devices provide opportunities to couple them with mathematical forecasting models to produce predictive monitoring systems for early, proactive glycemia management of diabetes mellitus patients before glucose levels drift to undesirable levels. This article assesses the feasibility of data-driven models to serve as the forecasting engine of predictive monitoring systems. Methods We investigated the capabilities of data-driven autoregressive (AR) models to (1) capture the correlations in glucose time-series data, (2) make accurate predictions as a function of prediction horizon, and (3) be made portable from individual to individual without any need for model tuning. The investigation is performed by employing CGM data from nine type 1 diabetic subjects collected over a continuous 5-day period. Results With CGM data serving as the gold standard, AR model-based predictions of glucose levels assessed over nine subjects with Clarke error grid analysis indicated that, for a 30-minute prediction horizon, individually tuned models yield 97.6 to 100.0% of data in the clinically acceptable zones A and B, whereas cross-subject, portable models yield 95.8 to 99.7% of data in zones A and B. Conclusions This study shows that, for a 30-minute prediction horizon, data-driven AR models provide sufficiently-accurate and clinically-acceptable estimates of glucose levels for timely, proactive therapy and should be considered as the modeling engine for predictive monitoring of patients with type 1 diabetes mellitus. It also suggests that AR models can be made portable from individual to individual with minor performance penalties, while greatly reducing the burden associated with model tuning and data collection for model development. PMID:19885110

A proactive system for maritime environment monitoring.

PubMed

Moroni, Davide; Pieri, Gabriele; Tampucci, Marco; Salvetti, Ovidio

2016-01-30

The ability to remotely detect and monitor oil spills is becoming increasingly important due to the high demand of oil-based products. Indeed, shipping routes are becoming very crowded and the likelihood of oil slick occurrence is increasing. In this frame, a fully integrated remote sensing system can be a valuable monitoring tool. We propose an integrated and interoperable system able to monitor ship traffic and marine operators, using sensing capabilities from a variety of electronic sensors, along with geo-positioning tools, and through a communication infrastructure. Our system is capable of transferring heterogeneous data, freely and seamlessly, between different elements of the information system (and their users) in a consistent and usable form. The system also integrates a collection of decision support services providing proactive functionalities. Such services demonstrate the potentiality of the system in facilitating dynamic links among different data, models and actors, as indicated by the performed field tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Glucose Monitoring in Individuals With Diabetes Using a Long-Term Implanted Sensor/Telemetry System and Model.

PubMed

Lucisano, Joseph Y; Routh, Timothy L; Lin, Joe T; Gough, David A

2017-09-01

The use of a fully implanted first-generation prototype sensor/telemetry system is described for long-term monitoring of subcutaneous tissue glucose in a small cohort of people with diabetes. Sensors are based on a membrane containing immobilized glucose oxidase and catalase coupled to oxygen electrodes and a telemetry system, integrated as an implant. The devices remained implanted for up to 180 days, with signals transmitted every 2 min to external receivers. The data include signal recordings from glucose clamps and spontaneous glucose excursions, matched, respectively, to reference blood glucose and finger-stick values. The sensor signals indicate dynamic tissue glucose, for which there is no independent standard, and a model describing the relationship between blood glucose and the signal is, therefore, included. The values of all model parameters have been estimated, including the permeability of adjacent tissues to glucose, and equated to conventional mass transfer parameters. As a group, the sensor calibration varied randomly at an average rate of -2.6%/week. Statistical correlation indicated strong association between the sensor signals and reference glucose values. Continuous long-term glucose monitoring in individuals with diabetes is feasible with this system. All therapies for diabetes are based on glucose control, and therefore, require glucose monitoring. This fully implanted long-term sensor/telemetry system may facilitate a new era of management of the disease.

Glucose Monitoring in Individuals with Diabetes using a Long-Term Implanted Sensor/Telemetry System and Model

PubMed Central

Lucisano, Joseph Y.; Routh, Timothy L.; Lin, Joe T.; Gough, David A.

2017-01-01

Objective The use of a fully implanted, first-generation prototype sensor/telemetry system is described for long-term monitoring of subcutaneous tissue glucose in a small cohort of people with diabetes. Methods Sensors are based on a membrane containing immobilized glucose oxidase and catalase coupled to oxygen electrodes and a telemetry system, integrated as an implant. The devices remained implanted for up to 180 days, with signals transmitted every 2 minutes to external receivers. Results The data include signal recordings from glucose clamps and spontaneous glucose excursions, matched respectively to reference blood glucose and finger-stick values. The sensor signals indicate dynamic tissue glucose, for which there is no independent standard, and a model describing the relationship between blood glucose and the signal is therefore included. The values of all model parameters have been estimated, including the permeability of adjacent tissues to glucose, and equated to conventional mass transfer parameters. As a group, the sensor calibration varied randomly at an average rate of −2.6%/week. Statistical correlation indicated strong association between the sensor signals and reference glucose values. Conclusions Continuous, long-term glucose monitoring in individuals with diabetes is feasible with this system. Significance All therapies for diabetes are based on glucose control and therefore require glucose monitoring. This fully implanted, long-term sensor/telemetry system may facilitate a new era of management of the disease. PMID:27775510

Monitoring issues from a modeling perspective

NASA Technical Reports Server (NTRS)

Mahlman, Jerry D.

1993-01-01

Recognition that earth's climate and biogeophysical conditions are likely changing due to human activities has led to a heightened awareness of the need for improved long-term global monitoring. The present long-term measurement efforts tend to be spotty in space, inadequately calibrated in time, and internally inconsistent with respect to other instruments and measured quantities. In some cases, such as most of the biosphere, most chemicals, and much of the ocean, even a minimal monitoring program is not available. Recently, it has become painfully evident that emerging global change issues demand information and insights that the present global monitoring system simply cannot supply. This is because a monitoring system must provide much more than a statement of change at a given level of statistical confidence. It must describe changes in diverse parts of the entire earth system on regional to global scales. It must be able to provide enough input to allow an integrated physical characterization of the changes that have occurred. Finally, it must allow a separation of the observed changes into their natural and anthropogenic parts. The enormous policy significance of global change virtually guarantees an unprecedented level of scrutiny of the changes in the earth system and why they are happening. These pressures create a number of emerging challenges and opportunities. For example, they will require a growing partnership between the observational programs and the theory/modeling community. Without this partnership, the scientific community will likely fall short in the monitoring effort. The monitoring challenge before us is not to solve the problem now, but rather to set appropriate actions in motion so as to create the required framework for solution. Each individual piece needs to establish its role in the large problem and how the required interactions are to take place. Below, we emphasize some of the needs and opportunities that could and should be addressed through participation by the theoreticians and modelers in the global change monitoring effort.

An overview: modern techniques for railway vehicle on-board health monitoring systems

NASA Astrophysics Data System (ADS)

Li, Chunsheng; Luo, Shihui; Cole, Colin; Spiryagin, Maksym

2017-07-01

Health monitoring systems with low-cost sensor networks and smart algorithms are always needed in both passenger trains and heavy haul trains due to the increasing need for reliability and safety in the railway industry. This paper focuses on an overview of existing approaches applied for railway vehicle on-board health monitoring systems. The approaches applied in the data measurement systems and the data analysis systems in railway on-board health monitoring systems are presented in this paper, including methodologies, theories and applications. The pros and cons of the various approaches are analysed to determine appropriate benchmarks for an effective and efficient railway vehicle on-board health monitoring system. According to this review, inertial sensors are the most popular due to their advantages of low cost, robustness and low power consumption. Linearisation methods are required for the model-based methods which would inevitably introduce error to the estimation results, and it is time-consuming to include all possible conditions in the pre-built database required for signal-based methods. Based on this review, future development trends in the design of new low-cost health monitoring systems for railway vehicles are discussed.

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Monitoring Biogeochemical Processes in Coral Reef Environments with Remote Sensing: A Cross-Disciplinary Approach.

NASA Astrophysics Data System (ADS)

Perez, D.; Phinn, S. R.; Roelfsema, C. M.; Shaw, E. C.; Johnston, L.; Iguel, J.; Camacho, R.

2017-12-01

Primary production and calcification are important to measure and monitor over time, because of their fundamental roles in the carbon cycling and accretion of habitat structure for reef ecosystems. However, monitoring biogeochemical processes in coastal environments has been difficult due to complications in resolving differences in water optical properties from biological productivity and other sources (sediment, dissolved organics, etc.). This complicates application of algorithms developed for satellite image data from open ocean conditions, and requires alternative approaches. This project applied a cross-disciplinary approach, using established methods for monitoring productivity in terrestrial environments to coral reef systems. Availability of regularly acquired high spatial (< 5m pixels), multispectral satellite imagery has improved mapping and monitoring capabilities for shallow, marine environments such as seagrass and coral reefs. There is potential to further develop optical models for remote sensing applications to estimate and monitor reef system processes, such as primary productivity and calcification. This project collected field measurements of spectral absorptance and primary productivity and calcification rates for two reef systems: Heron Reef, southern Great Barrier Reef and Saipan Lagoon, Commonwealth of the Northern Mariana Islands. Field data were used to parameterize a light-use efficiency (LUE) model, estimating productivity from absorbed photosynthetically active radiation. The LUE model has been successfully applied in terrestrial environments for the past 40 years, and could potentially be used in shallow, marine environments. The model was used in combination with a map of benthic community composition produced from objective based image analysis of WorldView 2 imagery. Light-use efficiency was measured for functional groups: coral, algae, seagrass, and sediment. However, LUE was overestimated for sediment, which led to overestimation of productivity for the mapped area. This was due to differences in spatial and temporal resolution of field data used in the model. The limitations and application of the LUE model to coral reef environments will be presented.

Hydrogeologic characterization of an arid zone Radioactive Waste Management Site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ginanni, J.M.; O`Neill, L.J.; Hammermeister, D.P.

1994-06-01

An in-depth subsurface site characterization and monitoring program for the soil water migration pathway has been planned, implemented, and completed to satisfy data requirements for a waiver from groundwater monitoring, for an exemption from liner leachate collections systems, and for different regulatory driven performance assessments. A traditional scientific approach has been taken to focus characterization and monitoring efforts. This involved developing a conceptual model of the hydrogeologic system and defining and testing hypotheses about this model. Specific hypotheses tested included: that the system was hydrologically heterogenous and anisotropic, and that recharge was very low or negligible. Mineralogical, physical, and hydrologicmore » data collected to test hypotheses has shown the hydrologic system to be remarkably homogenous and isotropic rather than heterogenous and anisotropic. Both hydrodynamic and environmental tracer approaches for estimating recharge have led to the conclusion that recharge from the Area 5 RWMS is not occurring in the upper region of the vadose zone, and that recharge at depth is extremely small or negligible. This demonstration of ``no migration of hazardous constituents to the water table satisfies a key requirement for both the groundwater monitoring waiver and the exemption from liner leachate collection systems. Data obtained from testing hypotheses concerning the soil water migration pathway have been used to refine the conceptual model of the hydrogeologic system of the site. These data suggest that the soil gas and atmospheric air pathways may be more important for transporting contaminants to the accessible environment than the soil water pathway. New hypotheses have been developed about these pathways, and characterization and monitoring activities designed to collect data to test these hypotheses.« less

Database and interactive monitoring system for the photonics and electronics of RPC Muon Trigger in CMS experiment

NASA Astrophysics Data System (ADS)

Wiacek, Daniel; Kudla, Ignacy M.; Pozniak, Krzysztof T.; Bunkowski, Karol

2005-02-01

The main task of the RPC (Resistive Plate Chamber) Muon Trigger monitoring system design for the CMS (Compact Muon Solenoid) experiment (at LHC in CERN Geneva) is the visualization of data that includes the structure of electronic trigger system (e.g. geometry and imagery), the way of its processes and to generate automatically files with VHDL source code used for programming of the FPGA matrix. In the near future, the system will enable the analysis of condition, operation and efficiency of individual Muon Trigger elements, registration of information about some Muon Trigger devices and present previously obtained results in interactive presentation layer. A broad variety of different database and programming concepts for design of Muon Trigger monitoring system was presented in this article. The structure and architecture of the system and its principle of operation were described. One of ideas for building this system is use object-oriented programming and design techniques to describe real electronics systems through abstract object models stored in database and implement these models in Java language.

Environmental Monitoring for Situation Assessment using Mobile and Fixed Sensors

NASA Technical Reports Server (NTRS)

Fikes, Richard

2004-01-01

This project was co-led by Dr. Sheila McIlraith and Prof. Richard Fikes. Substantial research results and published papers describing those results were produced in multiple technology areas, including the following: 1) Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net; 2) A Formal Theory of Testing for Dynamical Systems; 3) Diagnosing Hybrid Systems Using a Bayesian Model Selection Approach.

Architecture for reactive planning of robot actions

NASA Astrophysics Data System (ADS)

Riekki, Jukka P.; Roening, Juha

1995-01-01

In this article, a reactive system for planning robot actions is described. The described hierarchical control system architecture consists of planning-executing-monitoring-modelling elements (PEMM elements). A PEMM element is a goal-oriented, combined processing and data element. It includes a planner, an executor, a monitor, a modeler, and a local model. The elements form a tree-like structure. An element receives tasks from its ancestor and sends subtasks to its descendants. The model knowledge is distributed into the local models, which are connected to each other. The elements can be synchronized. The PEMM architecture is strictly hierarchical. It integrated planning, sensing, and modelling into a single framework. A PEMM-based control system is reactive, as it can cope with asynchronous events and operate under time constraints. The control system is intended to be used primarily to control mobile robots and robot manipulators in dynamic and partially unknown environments. It is suitable especially for applications consisting of physically separated devices and computing resources.

A real-time posture monitoring method for rail vehicle bodies based on machine vision

NASA Astrophysics Data System (ADS)

Liu, Dongrun; Lu, Zhaijun; Cao, Tianpei; Li, Tian

2017-06-01

Monitoring vehicle operation conditions has become significantly important in modern high-speed railway systems. However, the operational impact of monitoring the roll angle of vehicle bodies has principally been limited to tilting trains, while few studies have focused on monitoring the running posture of vehicle bodies during operation. We propose a real-time posture monitoring method to fulfil real-time monitoring requirements, by taking rail surfaces and centrelines as detection references. In realising the proposed method, we built a mathematical computational model based on space coordinate transformations to calculate attitude angles of vehicles in operation and vertical and lateral vibration displacements of single measuring points. Moreover, comparison and verification of reliability between system and field results were conducted. Results show that monitoring of the roll angles of car bodies obtained through the system exhibit variation trends similar to those converted from the dynamic deflection of bogie secondary air springs. The monitoring results of two identical conditions were basically the same, highlighting repeatability and good monitoring accuracy. Therefore, our monitoring results were reliable in reflecting posture changes in running railway vehicles.

SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting

NASA Astrophysics Data System (ADS)

Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

2014-12-01

Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

Bar-Chart-Monitor System For Wind Tunnels

NASA Technical Reports Server (NTRS)

Jung, Oscar

1993-01-01

Real-time monitor system provides bar-chart displays of significant operating parameters developed for National Full-Scale Aerodynamic Complex at Ames Research Center. Designed to gather and process sensory data on operating conditions of wind tunnels and models, and displays data for test engineers and technicians concerned with safety and validation of operating conditions. Bar-chart video monitor displays data in as many as 50 channels at maximum update rate of 2 Hz in format facilitating quick interpretation.

Hybrid Modeling Improves Health and Performance Monitoring

NASA Technical Reports Server (NTRS)

2007-01-01

Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

Formal Verification of the Runway Safety Monitor

NASA Technical Reports Server (NTRS)

Siminiceanu, Radu; Ciardo, Gianfranco

2006-01-01

The Runway Safety Monitor (RSM) designed by Lockheed Martin is part of NASA's effort to reduce runway accidents. We developed a Petri net model of the RSM protocol and used the model checking functions of our tool SMART to investigate a number of safety properties in RSM. To mitigate the impact of state-space explosion, we built a highly discretized model of the system, obtained by partitioning the monitored runway zone into a grid of smaller volumes and by considering scenarios involving only two aircraft. The model also assumes that there are no communication failures, such as bad input from radar or lack of incoming data, thus it relies on a consistent view of reality by all participants. In spite of these simplifications, we were able to expose potential problems in the RSM conceptual design. Our findings were forwarded to the design engineers, who undertook corrective action. Additionally, the results stress the efficiency attained by the new model checking algorithms implemented in SMART, and demonstrate their applicability to real-world systems.

Process-based monitoring and modeling of Karst springs - Linking intrinsic to specific vulnerability.

PubMed

Epting, Jannis; Page, Rebecca M; Auckenthaler, Adrian; Huggenberger, Peter

2018-06-01

The presented work illustrates to what extent field investigations as well as monitoring and modeling approaches are necessary to understand the high discharge dynamics and vulnerability of Karst springs. In complex settings the application of 3D geological models is essential for evaluating the vulnerability of Karst systems. They allow deriving information on catchment characteristics, as the geometry of aquifers and aquitards as well as their displacements along faults. A series of Karst springs in northwestern Switzerland were compared and Karst system dynamics with respect to qualitative and quantitative issues were evaluated. The main objective of the studies was to combine information of catchment characteristics and data from novel monitoring systems (physicochemical and microbiological parameters) to assess the intrinsic vulnerability of Karst springs to microbiological contamination with simulated spring discharges derived from numerical modeling (linear storage models). The numerically derived relation of fast and slow groundwater flow components enabled us to relate different sources of groundwater recharge and to characterize the dynamics of the Karst springs. Our study illustrates that comparably simple model-setups were able to reproduce the overall dynamic intrinsic vulnerability of several Karst systems and that one of the most important processes involved was the temporal variation of groundwater recharge (precipitation, evapotranspiration and snow melt). Furthermore, we make a first attempt on how to link intrinsic to specific vulnerability of Karst springs, which involves activities within the catchment area as human impacts from agriculture and settlements. Likewise, by a more detailed representation of system dynamics the influence of surface water, which is impacted by release events from storm sewers, infiltrating into the Karst system, could be considered. Overall, we demonstrate that our approach can be the basis for a more flexible and differentiated management and monitoring of raw-water quality of Karst springs. Copyright © 2017 Elsevier B.V. All rights reserved.

Availability analysis of mechanical systems with condition-based maintenance using semi-Markov and evaluation of optimal condition monitoring interval

NASA Astrophysics Data System (ADS)

Kumar, Girish; Jain, Vipul; Gandhi, O. P.

2018-03-01

Maintenance helps to extend equipment life by improving its condition and avoiding catastrophic failures. Appropriate model or mechanism is, thus, needed to quantify system availability vis-a-vis a given maintenance strategy, which will assist in decision-making for optimal utilization of maintenance resources. This paper deals with semi-Markov process (SMP) modeling for steady state availability analysis of mechanical systems that follow condition-based maintenance (CBM) and evaluation of optimal condition monitoring interval. The developed SMP model is solved using two-stage analytical approach for steady-state availability analysis of the system. Also, CBM interval is decided for maximizing system availability using Genetic Algorithm approach. The main contribution of the paper is in the form of a predictive tool for system availability that will help in deciding the optimum CBM policy. The proposed methodology is demonstrated for a centrifugal pump.

Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System

NASA Astrophysics Data System (ADS)

Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.

2008-12-01

The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so that they can cover an even wider net of data sources. The goal is to develop the means to link together the upper level and lower level ontologies and to have these registered within the GEOSS Registry. Actual operational ontologies that would link to models or link to data collections containing input variables required by models would have to be nested underneath this top level ontology, analogous to the mapping that has been carried out among ontologies within GEON.

Real time hydro-metereological hazards monitoring system for the Ravenna municipality

NASA Astrophysics Data System (ADS)

Bertoni, W.; Cattarossi, A.; Gonella, M.

2003-04-01

The Ravenna municipality (Italy, Emilia Romagna region), through a cooperative agreement with ENI S.p.A’s., AGIP division, is carrying out a research study for the development of a real time monitoring system of hydro-meteorological conditions. The system aims to support the city Crisis Response Unit to provide more efficient support all over the municipal territory that is the largest in Italy with more than 700 km2. The support unit, a GIS computer based application, directly links to a broad range of sources, gathering real time information from a Local Area Model (meteorological data), a Wave Model (sea hydrodynamic circulation), monitoring stations, located partially on the Adriatic sea (AGIP offshore platform, SIMN) and partially over the Ravenna inland (SPDS, SIN). In the first phase, now completed and undergoing testing, this vast and diversified collection of data feeds a number of statistical models with up to 72 hours of forecast capabilities. The GIS application displays actual and forecast sea conditions offshore of Ravenna littorals in addition to actual and forecast flood conditions along the Ravenna Province inland. Model generated data are used for the forecast, which is then calibrated using the measured data. When the predefined warning limits are exceeded, end users are alerted via prerecorded phone messages, SMS, or visually through the direct or remote interaction with the GIS system (remotely accessible via portable computers). In the second stage, the statistical approach will be substituted by a more deterministic approach. A coupled hydrologic-hydraulic model will be used to forecast water stages along rivers and runoff volume along major watersheds. Moreover, already functioning capabilities allows direct control of remote monitoring points (stream and rain gages, etc.) The entire Real Time Monitoring System was developed on a GIS platform. The GEOdatabase, a relational database based on MSDE technology, is the core of the application which revolves around the conceptualization of a Hydro Data Model, a standardized way to store hydraulic based data such as watershed delineation, hydrologic network, monitoring points and time series data. Recent advancement in GIS software technologies and ready to use hydro-meteorological data offer an unprecedented opportunity to customize the GIS application and provide a powerful application to prevent and defeat flood hazards.

Quantification of alcohol drinking patterns in mice.

PubMed

Eisenhardt, Manuela; Leixner, Sarah; Spanagel, Rainer; Bilbao, Ainhoa

2015-11-01

The use of mice in alcohol research provides an excellent model system for a better understanding of the genetics and neurobiology of alcohol addiction. Almost 60 years ago, alcohol researchers began to test strains of mice for alcohol preference and intake. In particular, various voluntary alcohol drinking paradigms in the home cage were developed. In mouse models of voluntary oral alcohol consumption, animals have concurrent access to water and either one or several concentrated alcohol solutions in their home cages. Although these models have high face validity, many experimental conditions require a more precise monitoring of alcohol consumption in mice in order to capture the role of specific strains or genes, or any other manipulation on alcohol drinking behavior. Therefore, we have developed a fully automated, highly precise monitoring system for alcohol drinking in mice in the home cage. This system is now commercially available. We show that this drinkometer system allows for detecting differences in drinking behavior (i) in transgenic mice, (ii) following alcohol deprivation, and (iii) following stress applications that are usually not detected by classical home-cage drinking paradigms. In conclusion, our drinkometer system allows disturbance-free and high resolution monitoring of alcohol drinking behavior. In particular, micro-drinking and circadian drinking patterns can be monitored in genetically modified and inbred strains of mice after environmental and pharmacological manipulation, and therefore this system represents an improvement in measuring behavioral features that are of relevance for the development of alcohol use disorders. © 2015 Society for the Study of Addiction.

Monitoring and analysis of liquid storage in LNG tank based on different support springs

NASA Astrophysics Data System (ADS)

He, Hua; Sun, Jianping; Li, Ke; Wu, Zheng; Chen, Qidong; Chen, Guodong; Cao, Can

2018-04-01

With the rapid development of social modernization, LNG vehicles are springing up in daily life. However, it is difficult to monitor and judge the liquid storage tanks accurately and quickly. Based on this, this paper presents a new method of liquid storage monitoring, LNG tank on-line vibration monitoring system. By collecting the vibration frequency of LNG tank and tank liquid and supporting spring system, the liquid storage quality in the tank can be calculated. In this experiment, various vibration modes of the tank spring system are fully taken into account. The vibration effects of different types of support springs on the LNG tank system were investigated. The results show that the spring model has a great influence on the test results. This study provides a technical reference for the selection of suitable support springs for liquid storage monitoring.

Hydroacoustic propagation grids for the CTBT knowledge databaes BBN technical memorandum W1303

DOE Office of Scientific and Technical Information (OSTI.GOV)

J. Angell

1998-05-01

The Hydroacoustic Coverage Assessment Model (HydroCAM) has been used to develop components of the hydroacoustic knowledge database required by operational monitoring systems, particularly the US National Data Center (NDC). The database, which consists of travel time, amplitude correction and travel time standard deviation grids, is planned to support source location, discrimination and estimation functions of the monitoring network. The grids will also be used under the current BBN subcontract to support an analysis of the performance of the International Monitoring System (IMS) and national sensor systems. This report describes the format and contents of the hydroacoustic knowledgebase grids, and themore » procedures and model parameters used to generate these grids. Comparisons between the knowledge grids, measured data and other modeled results are presented to illustrate the strengths and weaknesses of the current approach. A recommended approach for augmenting the knowledge database with a database of expected spectral/waveform characteristics is provided in the final section of the report.« less

Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

NASA Astrophysics Data System (ADS)

Gómez A, Héctor F.; Martínez-Tomás, Rafael; Arias Tapia, Susana A.; Rincón Zamorano, Mariano

2014-04-01

Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge

NASA Technical Reports Server (NTRS)

Yap, Keng C.

2010-01-01

This viewgraph presentation reviews Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge. The Wing Leading Edge Impact Detection System (WLE IDS) and the Impact Analysis Process are also described to monitor WLE debris threats. The contents include: 1) Risk Management via SHM; 2) Hardware Overview; 3) Instrumentation; 4) Sensor Configuration; 5) Debris Hazard Monitoring; 6) Ascent Response Summary; 7) Response Signal; 8) Distribution of Flight Indications; 9) Probabilistic Risk Analysis (PRA); 10) Model Correlation; 11) Impact Tests; 12) Wing Leading Edge Modeling; 13) Ascent Debris PRA Results; and 14) MM/OD PRA Results.

Africa-Wide Monitoring of Small Surface Water Bodies Using Multisource Satellite Data: A Monitoring System for FEWS NET

NASA Astrophysics Data System (ADS)

Velpuri, N. M.; Senay, G. B.; Rowland, J.; Budde, M. E.; Verdin, J. P.

2015-12-01

Continental Africa has the largest volume of water stored in wetlands, large lakes, reservoirs and rivers, yet it suffers with problems such as water availability and access. Furthermore, African countries are amongst the most vulnerable to the impact of natural hazards such as droughts and floods. With climate change intensifying the hydrologic cycle and altering the distribution and frequency of rainfall, the problem of water availability and access is bound to increase. The U.S Geological Survey Famine Early Warning Systems Network (FEWS NET), funded by the U.S. Agency for International Development, has initiated a large-scale project to monitor small to medium surface water bodies in Africa. Under this project, multi-source satellite data and hydrologic modeling techniques are integrated to monitor these water bodies in Africa. First, small water bodies are mapped using satellite data such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat, and high resolution Google Earth imagery. Stream networks and watersheds for each water body are identified using Shuttle Radar Topography Mission (SRTM) digital elevation data. Finally, a hydrologic modeling approach that uses satellite-derived precipitation estimates and evapotranspiration data calculated from global data assimilation system climate parameters is applied to model water levels. This approach has been implemented to monitor nearly 300 small water bodies located in 10 countries in sub-Saharan Africa. Validation of modeled scaled depths with field-installed gauge data in East Africa demonstrated the ability of the model to capture both the spatial patterns and seasonal variations. Modeled scaled estimates captured up to 60% of the observed gauge variability with an average RMSE of 22%. Current and historic data (since 2001) on relative water level, precipitation, and evapotranspiration for each water body is made available in near real time. The water point monitoring network will be further expanded to cover other pastoral regions of sub-Saharan Africa. This project provides timely information on water availability that supports FEWS NET monitoring activities in Africa. Information on water availability produced in this study would further increase the resilience of local communities to floods and droughts.

Fiber optic sensor design for chemical process and environmental monitoring

NASA Astrophysics Data System (ADS)

Mahendran, R. S.; Harris, D.; Wang, L.; Machavaram, V. R.; Chen, R.; Kukureka, St. N.; Fernando, G. F.

2007-07-01

Cure monitoring is a term that is used to describe the cross-linking reactions in a thermosetting resin system. Advanced fiber reinforced composites are being used increasingly in a number of industrial sectors including aerospace, marine, sport, automotive and civil engineering. There is a general realization that the processing conditions that are used to manufacture the composites can have a major influence on its hot-wet mechanical properties. This paper is concerned with the design and demonstration of a number of sensor designs for in-situ cure monitoring of a model thermosetting resin system. Simple fixtures were constructed to enable a pair of cleaved optical fibers with a defined gap between the end-faces to be held in position. The resin system was introduced into this gap and the cure kinetics were followed by transmission infrared spectroscopy. A semi-empirical model was used to describe the cure process using the data obtained at different cure temperatures. The same sensor system was used to detect the ingress of moisture in the cured resin system.

The Challenges of Developing a Framework for Global Water Cycle Monitoring and Prediction (Alfred Wegener Medal Lecture)

NASA Astrophysics Data System (ADS)

Wood, Eric F.

2014-05-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ("From Observations to Decisions") recognizes that "water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity", and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the developments at Princeton University towards a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. At every step there are scientific challenges whose solutions are only partially being solved. In addition there are challenges in delivering such systems as "climate services", especially to societies with low technical capacity such as rural agriculturalists in sub-Saharan Africa, but whose needs for such information are great. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

Intelligent Engine Systems Work Element 1.3: Sub System Health Management

NASA Technical Reports Server (NTRS)

Ashby, Malcolm; Simpson, Jeffrey; Singh, Anant; Ferguson, Emily; Frontera, mark

2005-01-01

The objectives of this program were to develop health monitoring systems and physics-based fault detection models for engine sub-systems including the start, lubrication, and fuel. These models will ultimately be used to provide more effective sub-system fault identification and isolation to reduce engine maintenance costs and engine down-time. Additionally, the bearing sub-system health is addressed in this program through identification of sensing requirements, a review of available technologies and a demonstration of a demonstration of a conceptual monitoring system for a differential roller bearing. This report is divided into four sections; one for each of the subtasks. The start system subtask is documented in section 2.0, the oil system is covered in section 3.0, bearing in section 4.0, and the fuel system is presented in section 5.0.

Design and Realization of Online Monitoring System of Distributed New Energy and Renewable Energy

NASA Astrophysics Data System (ADS)

Tang, Yanfen; Zhou, Tao; Li, Mengwen; Zheng, Guotai; Li, Hao

2018-01-01

Aimed at difficult centralized monitoring and management of current distributed new energy and renewable energy generation projects due to great varieties, different communication protocols and large-scale difference, this paper designs a online monitoring system of new energy and renewable energy characterized by distributed deployment, tailorable functions, extendible applications and fault self-healing performance. This system is designed based on international general standard for grid information data model, formulates unified data acquisition and transmission standard for different types of new energy and renewable energy generation projects, and can realize unified data acquisition and real-time monitoring of new energy and renewable energy generation projects, such as solar energy, wind power, biomass energy, etc. within its jurisdiction. This system has applied in Beijing. At present, 576 projects are connected to the system. Good effect is achieved and stability and reliability of the system have been validated.

78 FR 14681 - Approval and Promulgation of Implementation Plans; Kentucky; 110(a)(1) and (2) Infrastructure...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-07

..., and modeling to assure attainment and maintenance for that new NAAQS. Section 110(a) of the CAA... structural SIP requirements such as modeling, monitoring, and emissions inventories that are designed to... limits and other control measures. 110(a)(2)(B): Ambient air quality monitoring/data system. 110(a)(2)(C...

RBC aggregation based system for long-term photoplethysmography (PPG): new prospects for PPG applications

NASA Astrophysics Data System (ADS)

Shvartsman, Leonid D.; Tverskoy, Boris

2015-03-01

We present system for long-term continuous PPG monitoring, and physical model for PPG analysis. The system is based on ideology of light scattering modulated by the process of RBC aggregation. OXIRATE's system works in reflection geometry. The sensor is tiny, completely mobile phone compatible, it can be placed nearly everywhere on the body surface. These technical features allow all-night comfortable PPG monitoring that was performed and analyzed. We can define various sleep stages on the basis of different reproducible time-behavior of PPG signal. Our system of PPG monitoring was used also for reflection pulse oximetry and for extreme PPG studies, such as diving.

Mapping, Monitoring and Modeling Submersed Aquatic Vegetation Species and Communities

NASA Astrophysics Data System (ADS)

Hartis, Brett Michael

Aquatic macrophyte communities are critically important habitat species in aquatic systems worldwide. None are more important than those found beneath the water's surface, commonly referred to as submersed aquatic vegetation (SAV). Although vital to such systems, many native submersed plants have shown near irreversible declines in recent decades as water quality impairment, habitat destruction, and encroachment by invasive species have increased. In the past, aquatic plant science has emphasized the restoration and protection of native species and the management of invasive species. Comparatively little emphasis has been directed toward adequately mapping and monitoring these resources to track their viability over time. Modeling the potential intrusion of certain invasive plant species has also been given little attention, likely because aquatic systems in general can be difficult to assess. In recent years, scientists and resource managers alike have begun paying more attention to mapping SAV communities and to address the spread of invasive species across various regions. This research attempts to provide new, cutting-edge techniques to improve SAV mapping and monitoring efforts in coastal regions, at both community and individual species levels, while also providing insights about the establishment potential of Hydrilla verticillata, a noxious, highly invasive submersed plant. Technological advances in satellite remote sensing, interpolation and spatial analysis in geographic information systems, and state-of-the-art climate envelope modeling techniques were used to further assess the dynamic nature of SAV on various scales. This work contributes to the growing science of mapping, monitoring, and modeling of SAV

Cost-Effectiveness of Remote Cardiac Monitoring With the CardioMEMS Heart Failure System.

PubMed

Schmier, Jordana K; Ong, Kevin L; Fonarow, Gregg C

2017-07-01

Heart failure (HF) is a leading cause of cardiovascular mortality in the United States and presents a substantial economic burden. A recently approved implantable wireless pulmonary artery pressure remote monitor, the CardioMEMS HF System, has been shown to be effective in reducing hospitalizations among New York Heart Association (NYHA) class III HF patients. The objective of this study was to estimate the cost-effectiveness of this remote monitoring technology compared to standard of care treatment for HF. A Markov cohort model relying on the CHAMPION (CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients) clinical trial for mortality and hospitalization data, published sources for cost data, and a mix of CHAMPION data and published sources for utility data, was developed. The model compares outcomes over 5 years for implanted vs standard of care patients, allowing patients to accrue costs and utilities while they remain alive. Sensitivity analyses explored uncertainty in input parameters. The CardioMEMS HF System was found to be cost-effective, with an incremental cost-effectiveness ratio of $44,832 per quality-adjusted life year (QALY). Sensitivity analysis found the model was sensitive to the device cost and to whether mortality benefits were sustained, although there were no scenarios in which the cost/QALY exceeded $100,000. Compared with standard of care, the CardioMEMS HF System was cost-effective when leveraging trial data to populate the model. © 2017 Wiley Periodicals, Inc.

Information technologies in optimization process of monitoring of software and hardware status

NASA Astrophysics Data System (ADS)

Nikitin, P. V.; Savinov, A. N.; Bazhenov, R. I.; Ryabov, I. V.

2018-05-01

The article describes a model of a hardware and software monitoring system for a large company that provides customers with software as a service (SaaS solution) using information technology. The main functions of the monitoring system are: provision of up-todate data for analyzing the state of the IT infrastructure, rapid detection of the fault and its effective elimination. The main risks associated with the provision of these services are described; the comparative characteristics of the software are given; author's methods of monitoring the status of software and hardware are proposed.

Estimating linear temporal trends from aggregated environmental monitoring data

USGS Publications Warehouse

Erickson, Richard A.; Gray, Brian R.; Eager, Eric A.

2017-01-01

Trend estimates are often used as part of environmental monitoring programs. These trends inform managers (e.g., are desired species increasing or undesired species decreasing?). Data collected from environmental monitoring programs is often aggregated (i.e., averaged), which confounds sampling and process variation. State-space models allow sampling variation and process variations to be separated. We used simulated time-series to compare linear trend estimations from three state-space models, a simple linear regression model, and an auto-regressive model. We also compared the performance of these five models to estimate trends from a long term monitoring program. We specifically estimated trends for two species of fish and four species of aquatic vegetation from the Upper Mississippi River system. We found that the simple linear regression had the best performance of all the given models because it was best able to recover parameters and had consistent numerical convergence. Conversely, the simple linear regression did the worst job estimating populations in a given year. The state-space models did not estimate trends well, but estimated population sizes best when the models converged. We found that a simple linear regression performed better than more complex autoregression and state-space models when used to analyze aggregated environmental monitoring data.

A distributed cloud-based cyberinfrastructure framework for integrated bridge monitoring

NASA Astrophysics Data System (ADS)

Jeong, Seongwoon; Hou, Rui; Lynch, Jerome P.; Sohn, Hoon; Law, Kincho H.

2017-04-01

This paper describes a cloud-based cyberinfrastructure framework for the management of the diverse data involved in bridge monitoring. Bridge monitoring involves various hardware systems, software tools and laborious activities that include, for examples, a structural health monitoring (SHM), sensor network, engineering analysis programs and visual inspection. Very often, these monitoring systems, tools and activities are not coordinated, and the collected information are not shared. A well-designed integrated data management framework can support the effective use of the data and, thereby, enhance bridge management and maintenance operations. The cloud-based cyberinfrastructure framework presented herein is designed to manage not only sensor measurement data acquired from the SHM system, but also other relevant information, such as bridge engineering model and traffic videos, in an integrated manner. For the scalability and flexibility, cloud computing services and distributed database systems are employed. The information stored can be accessed through standard web interfaces. For demonstration, the cyberinfrastructure system is implemented for the monitoring of the bridges located along the I-275 Corridor in the state of Michigan.

Mathematical model of unmanned aerial vehicle used for endurance autonomous monitoring

NASA Astrophysics Data System (ADS)

Chelaru, Teodor-Viorel; Chelaru, Adrian

2014-12-01

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system, based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.

Design and implementation of a remote UAV-based mobile health monitoring system

NASA Astrophysics Data System (ADS)

Li, Songwei; Wan, Yan; Fu, Shengli; Liu, Mushuang; Wu, H. Felix

2017-04-01

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

40 CFR Table 7 to Subpart Bbbb of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2010 CFR

2010-07-01

...—Requirements for Continuous Emission Monitoring Systems (CEMS) For the following pollutants Use the following span values for CEMS Use the following performance specifications in appendix B of this part for your CEMS If needed to meet minimum data requirements, use the folloiwng alternate methods in appendix A of...

40 CFR Table 7 to Subpart Bbbb of... - Model Rule-Requirements for Continuous Emission Monitoring Systems (CEMS)

Code of Federal Regulations, 2011 CFR

2011-07-01

...—Requirements for Continuous Emission Monitoring Systems (CEMS) For the following pollutants Use the following span values for CEMS Use the following performance specifications in appendix B of this part for your CEMS If needed to meet minimum data requirements, use the folloiwng alternate methods in appendix A of...

Statistically qualified neuro-analytic failure detection method and system

DOEpatents

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

2002-03-02

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

Operations and maintenance manual, atmospheric contaminant sensor. Addendum 1: Carbon monoxide monitor model 204

NASA Technical Reports Server (NTRS)

1972-01-01

An instrument for monitoring the carbon monoxide content of the ambient atmosphere is described. The subjects discussed are: (1) theory of operation, (2) system features, (3) controls and monitors, (4) operational procedures, and (5) maintenance and troubleshooting. Block drawings and circuit diagrams are included to clarify the text.

Systems identification and application systems development for monitoring the physiological and health status of crewmen in space

NASA Technical Reports Server (NTRS)

Leonard, J. I.; Furukawa, S.; Vannordstrand, P. C.

1975-01-01

The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems.

Amplifying human ability through autonomics and machine learning in IMPACT

NASA Astrophysics Data System (ADS)

Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

2017-05-01

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

Deploying Server-side File System Monitoring at NERSC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uselton, Andrew

2009-05-01

The Franklin Cray XT4 at the NERSC center was equipped with the server-side I/O monitoring infrastructure Cerebro/LMT, which is described here in detail. Insights gained from the data produced include a better understanding of instantaneous data rates during file system testing, file system behavior during regular production time, and long-term average behaviors. Information and insights gleaned from this monitoring support efforts to proactively manage the I/O infrastructure on Franklin. A simple model for I/O transactions is introduced and compared with the 250 million observations sent to the LMT database from August 2008 to February 2009.

Working Group 1: Software System Design and Implementation for Environmental Modeling

EPA Science Inventory

ISCMEM Working Group One Presentation, presentation with the purpose of fostering the exchange of information about environmental modeling tools, modeling frameworks, and environmental monitoring databases.

Simultaneous, noninvasive, in vivo, continuous monitoring of hematocrit, vascular volume, hemoglobin oxygen saturation, pulse rate and breathing rate in humans and other animal models using a single light source

NASA Astrophysics Data System (ADS)

Dent, Paul; Tun, Sai Han; Fillioe, Seth; Deng, Bin; Satalin, Josh; Nieman, Gary; Wilcox, Kailyn; Searles, Quinn; Narsipur, Sri; Peterson, Charles M.; Goodisman, Jerry; Mostrom, James; Steinmann, Richard; Chaiken, J.

2018-02-01

We previously reported a new algorithm "PV[O]H" for continuous, noninvasive, in vivo monitoring of hematocrit changes in blood and have since shown its utility for monitoring in humans during 1) hemodialysis, 2) orthostatic perturbations and 3) during blood loss and fluid replacement in a rat model. We now show that the algorithm is sensitive to changes in hemoglobin oxygen saturation. We document the phenomenology of the effect and explain the effect using new results obtained from humans and rat models. The oxygen sensitivity derives from the differential absorption of autofluorescence originating in the static tissues by oxy and deoxy hemoglobin. Using this approach we show how to perform simultaneous, noninvasive, in vivo, continuous monitoring of hematocrit, vascular volume, hemoglobin oxygen saturation, pulse rate and breathing rate in mammals using a single light source. We suspect that monitoring of changes in this suite of vital signs can be provided with improved time response, sensitivity and precision compared to existing methodologies. Initial results also offer a more detailed glimpse into the systemic oxygen transport in the circulatory system of humans.

Generic particulate-monitoring system for retrofit to Hanford exhaust stacks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Camman, J.W.; Carbaugh, E.H.

1982-11-01

Evaluations of 72 sampling and monitoring systems were performed at Hanford as the initial phase of a program to upgrade such systems. Each evaluation included determination of theoretical sampling efficiencies for particle sizes ranging from 0.5 to 10 micrometers aerodynamic equivalent diameter, addressing anisokinetic bias, sample transport line losses, and collector device efficiency. Upgrades needed to meet current Department of Energy guidance for effluent sampling and monitoring were identified, and a cost for each upgrade was estimated. A relative priority for each system's upgrade was then established based on evaluation results, current operational status, and future plans for the facilitymore » being exhausted. Common system upgrade requirements lead to the development of a generic design for common components of an exhaust stack sampling and monitoring system for airborne radioactive particulates. The generic design consists of commercially available off-the-shelf components to the extent practical and will simplify future stack sampling and monitoring system design, fabrication, and installation efforts. Evaluation results and their significance to system upgrades are empasized. A brief discussion of the analytical models used and experience to date with the upgrade program is included. Development of the generic stack sampling and monitoring system design is outlined. Generic system design features and limitations are presented. Requirements for generic system retrofitting to existing exhaust stacks are defined and benefits derived from generic system application are discussed.« less

Predictive Modeling of Cardiac Ischemia

NASA Technical Reports Server (NTRS)

Anderson, Gary T.

1996-01-01

The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.

Model-Based Anomaly Detection for a Transparent Optical Transmission System

NASA Astrophysics Data System (ADS)

Bengtsson, Thomas; Salamon, Todd; Ho, Tin Kam; White, Christopher A.

In this chapter, we present an approach for anomaly detection at the physical layer of networks where detailed knowledge about the devices and their operations is available. The approach combines physics-based process models with observational data models to characterize the uncertainties and derive the alarm decision rules. We formulate and apply three different methods based on this approach for a well-defined problem in optical network monitoring that features many typical challenges for this methodology. Specifically, we address the problem of monitoring optically transparent transmission systems that use dynamically controlled Raman amplification systems. We use models of amplifier physics together with statistical estimation to derive alarm decision rules and use these rules to automatically discriminate between measurement errors, anomalous losses, and pump failures. Our approach has led to an efficient tool for systematically detecting anomalies in the system behavior of a deployed network, where pro-active measures to address such anomalies are key to preventing unnecessary disturbances to the system's continuous operation.

Advanced Pulse Oximetry System for Remote Monitoring and Management

PubMed Central

Pak, Ju Geon; Park, Kee Hyun

2012-01-01

Pulse oximetry data such as saturation of peripheral oxygen (SpO2) and pulse rate are vital signals for early diagnosis of heart disease. Therefore, various pulse oximeters have been developed continuously. However, some of the existing pulse oximeters are not equipped with communication capabilities, and consequently, the continuous monitoring of patient health is restricted. Moreover, even though certain oximeters have been built as network models, they focus on exchanging only pulse oximetry data, and they do not provide sufficient device management functions. In this paper, we propose an advanced pulse oximetry system for remote monitoring and management. The system consists of a networked pulse oximeter and a personal monitoring server. The proposed pulse oximeter measures a patient's pulse oximetry data and transmits the data to the personal monitoring server. The personal monitoring server then analyzes the received data and displays the results to the patient. Furthermore, for device management purposes, operational errors that occur in the pulse oximeter are reported to the personal monitoring server, and the system configurations of the pulse oximeter, such as thresholds and measurement targets, are modified by the server. We verify that the proposed pulse oximetry system operates efficiently and that it is appropriate for monitoring and managing a pulse oximeter in real time. PMID:22933841

Advanced pulse oximetry system for remote monitoring and management.

PubMed

Pak, Ju Geon; Park, Kee Hyun

2012-01-01

Pulse oximetry data such as saturation of peripheral oxygen (SpO(2)) and pulse rate are vital signals for early diagnosis of heart disease. Therefore, various pulse oximeters have been developed continuously. However, some of the existing pulse oximeters are not equipped with communication capabilities, and consequently, the continuous monitoring of patient health is restricted. Moreover, even though certain oximeters have been built as network models, they focus on exchanging only pulse oximetry data, and they do not provide sufficient device management functions. In this paper, we propose an advanced pulse oximetry system for remote monitoring and management. The system consists of a networked pulse oximeter and a personal monitoring server. The proposed pulse oximeter measures a patient's pulse oximetry data and transmits the data to the personal monitoring server. The personal monitoring server then analyzes the received data and displays the results to the patient. Furthermore, for device management purposes, operational errors that occur in the pulse oximeter are reported to the personal monitoring server, and the system configurations of the pulse oximeter, such as thresholds and measurement targets, are modified by the server. We verify that the proposed pulse oximetry system operates efficiently and that it is appropriate for monitoring and managing a pulse oximeter in real time.

Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation.

PubMed

Bravo, Mercedes A; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J; Bell, Michelle L

2012-07-01

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of Accuracy of Six Blood Glucose Monitoring Systems and Modeling of Possibly Related Insulin Dosing Errors.

PubMed

Baumstark, Annette; Jendrike, Nina; Pleus, Stefan; Haug, Cornelia; Freckmann, Guido

2017-10-01

Self-monitoring of blood glucose (BG) is an essential part of diabetes therapy. Accurate and reliable results from BG monitoring systems (BGMS) are important especially when they are used to calculate insulin doses. This study aimed at assessing system accuracy of BGMS and possibly related insulin dosing errors. System accuracy of six different BGMS (Accu-Chek ® Aviva Nano, Accu-Chek Mobile, Accu-Chek Performa Nano, CONTOUR ® NEXT LINK 2.4, FreeStyle Lite, OneTouch ® Verio ® IQ) was assessed in comparison to a glucose oxidase and a hexokinase method. Study procedures and analysis were based on ISO 15197:2013/EN ISO 15197:2015, clause 6.3. In addition, insulin dosing error was modeled. In the comparison against the glucose oxidase method, five out of six BGMS fulfilled ISO 15197:2013 accuracy criteria. Up to 14.3%/4.3%/0.3% of modeled doses resulted in errors exceeding ±0.5/±1.0/±1.5 U and missing the modeled target by 20 mg/dL/40 mg/dL/60 mg/dL, respectively. Compared against the hexokinase method, five out of six BGMS fulfilled ISO 15197:2013 accuracy criteria. Up to 25.0%/10.5%/3.2% of modeled doses resulted in errors exceeding ±0.5/±1.0/±1.5 U, respectively. Differences in system accuracy were found, even among BGMS that fulfilled the minimum system accuracy criteria of ISO 15197:2013. In the error model, considerable insulin dosing errors resulted for some of the investigated systems. Diabetes patients on insulin therapy should be able to rely on their BGMS' readings; therefore, they require highly accurate BGMS, in particular, when making therapeutic decisions.

Development of GUI Type On-Line Condition Monitoring Program for a Turboprop Engine Using Labview

NASA Astrophysics Data System (ADS)

Kong, Changduk; Kim, Keonwoo

2011-12-01

Recently, an aero gas turbine health monitoring system has been developed for precaution and maintenance action against faults or performance degradations of the advanced propulsion system which occurs in severe environments such as high altitude, foreign object damage particles, hot and heavy rain and snowy atmospheric conditions. However to establish this health monitoring system, the online condition monitoring program is firstly required, and the program must monitor the engine performance trend through comparison between measured engine performance data and base performance results calculated by base engine performance model. This work aims to develop a GUI type on-line condition monitoring program for the PT6A-67 turboprop engine of a high altitude and long endurance operation UAV using LabVIEW. The base engine performance of the on-line condition monitoring program is simulated using component maps inversely generated from the limited performance deck data provided by engine manufacturer. The base engine performance simulation program is evaluated because analysis results by this program agree well with the performance deck data. The proposed on-line condition program can monitor the real engine performance as well as the trend through precise comparison between clean engine performance results calculated by the base performance simulation program and measured engine performance signals. In the development phase of this monitoring system, a signal generation module is proposed to evaluate the proposed online monitoring system. For user friendly purpose, all monitoring program are coded by LabVIEW, and monitoring examples are demonstrated using the proposed GUI type on-condition monitoring program.

A New Real - Time Fault Detection Methodology for Systems Under Test. Phase 1

NASA Technical Reports Server (NTRS)

Johnson, Roger W.; Jayaram, Sanjay; Hull, Richard A.

1998-01-01

The purpose of this research is focussed on the identification/demonstration of critical technology innovations that will be applied to various applications viz. Detection of automated machine Health Monitoring (BM, real-time data analysis and control of Systems Under Test (SUT). This new innovation using a High Fidelity Dynamic Model-based Simulation (BFDMS) approach will be used to implement a real-time monitoring, Test and Evaluation (T&E) methodology including the transient behavior of the system under test. The unique element of this process control technique is the use of high fidelity, computer generated dynamic models to replicate the behavior of actual Systems Under Test (SUT). It will provide a dynamic simulation capability that becomes the reference truth model, from which comparisons are made with the actual raw/conditioned data from the test elements.

NASA's Carbon Monitoring System Flux-Pilot Project: A Multi-Component Analysis System for Carbon-Cycle Research and Monitoring

NASA Technical Reports Server (NTRS)

Pawson, S.; Gunson, M.; Potter, C.; Jucks, K.

2012-01-01

The importance of greenhouse gas increases for climate motivates NASA s observing strategy for CO2 from space, including the forthcoming Orbiting Carbon Observatory (OCO-2) mission. Carbon cycle monitoring, including attribution of atmospheric concentrations to regional emissions and uptake, requires a robust modeling and analysis infrastructure to optimally extract information from the observations. NASA's Carbon-Monitoring System Flux-Pilot Project (FPP) is a prototype for such analysis, combining a set of unique tools to facilitate analysis of atmospheric CO2 along with fluxes between the atmosphere and the terrestrial biosphere or ocean. NASA's analysis system is unique, in that it combines information and expertise from the land, oceanic, and atmospheric branches of the carbon cycle and includes some estimates of uncertainty. Numerous existing space-based missions provide information of relevance to the carbon cycle. This study describes the components of the FPP framework, assessing the realism of computed fluxes, thus providing the basis for research and monitoring applications. Fluxes are computed using data-constrained terrestrial biosphere models and physical ocean models, driven by atmospheric observations and assimilating ocean-color information. Use of two estimates provides a measure of uncertainty in the fluxes. Along with inventories of other emissions, these data-derived fluxes are used in transport models to assess their consistency with atmospheric CO2 observations. Closure is achieved by using a four-dimensional data assimilation (inverse) approach that adjusts the terrestrial biosphere fluxes to make them consistent with the atmospheric CO2 observations. Results will be shown, illustrating the year-to-year variations in land biospheric and oceanic fluxes computed in the FPP. The signals of these surface-flux variations on atmospheric CO2 will be isolated using forward modeling tools, which also incorporate estimates of transport error. The results will be discussed in the context of interannual variability of observed atmospheric CO2 distributions.

Automated monitor and control for deep space network subsystems

NASA Technical Reports Server (NTRS)

Smyth, P.

1989-01-01

The problem of automating monitor and control loops for Deep Space Network (DSN) subsystems is considered and an overview of currently available automation techniques is given. The use of standard numerical models, knowledge-based systems, and neural networks is considered. It is argued that none of these techniques alone possess sufficient generality to deal with the demands imposed by the DSN environment. However, it is shown that schemes that integrate the better aspects of each approach and are referenced to a formal system model show considerable promise, although such an integrated technology is not yet available for implementation. Frequent reference is made to the receiver subsystem since this work was largely motivated by experience in developing an automated monitor and control loop for the advanced receiver.

Model-based monitoring and diagnosis of a satellite-based instrument

NASA Technical Reports Server (NTRS)

Bos, Andre; Callies, Jorg; Lefebvre, Alain

1995-01-01

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

Model-based monitoring and diagnosis of a satellite-based instrument

NASA Astrophysics Data System (ADS)

Bos, Andre; Callies, Jorg; Lefebvre, Alain

1995-05-01

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

Designing hydrologic monitoring networks to maximize predictability of hydrologic conditions in a data assimilation system: a case study from South Florida, U.S.A

NASA Astrophysics Data System (ADS)

Flores, A. N.; Pathak, C. S.; Senarath, S. U.; Bras, R. L.

2009-12-01

Robust hydrologic monitoring networks represent a critical element of decision support systems for effective water resource planning and management. Moreover, process representation within hydrologic simulation models is steadily improving, while at the same time computational costs are decreasing due to, for instance, readily available high performance computing resources. The ability to leverage these increasingly complex models together with the data from these monitoring networks to provide accurate and timely estimates of relevant hydrologic variables within a multiple-use, managed water resources system would substantially enhance the information available to resource decision makers. Numerical data assimilation techniques provide mathematical frameworks through which uncertain model predictions can be constrained to observational data to compensate for uncertainties in the model forcings and parameters. In ensemble-based data assimilation techniques such as the ensemble Kalman Filter (EnKF), information in observed variables such as canal, marsh and groundwater stages are propagated back to the model states in a manner related to: (1) the degree of certainty in the model state estimates and observations, and (2) the cross-correlation between the model states and the observable outputs of the model. However, the ultimate degree to which hydrologic conditions can be accurately predicted in an area of interest is controlled, in part, by the configuration of the monitoring network itself. In this proof-of-concept study we developed an approach by which the design of an existing hydrologic monitoring network is adapted to iteratively improve the predictions of hydrologic conditions within an area of the South Florida Water Management District (SFWMD). The objective of the network design is to minimize prediction errors of key hydrologic states and fluxes produced by the spatially distributed Regional Simulation Model (RSM), developed specifically to simulate the hydrologic conditions in several intensively managed and hydrologically complex watersheds within the SFWMD system. In a series of synthetic experiments RSM is used to generate the notionally true hydrologic state and the relevant observational data. The EnKF is then used as the mechanism to fuse RSM hydrologic estimates with data from the candidate network. The performance of the candidate network is measured by the prediction errors of the EnKF estimates of hydrologic states, relative to the notionally true scenario. The candidate network is then adapted by relocating existing observational sites to unobserved areas where predictions of local hydrologic conditions are most uncertain and the EnKF procedure repeated. Iteration of the monitoring network continues until further improvements in EnKF-based predictions of hydrologic conditions are negligible.

CCTV Coverage Index Based on Surveillance Resolution and Its Evaluation Using 3D Spatial Analysis

PubMed Central

Choi, Kyoungah; Lee, Impyeong

2015-01-01

We propose a novel approach to evaluating how effectively a closed circuit television (CCTV) system can monitor a targeted area. With 3D models of the target area and the camera parameters of the CCTV system, the approach produces surveillance coverage index, which is newly defined in this study as a quantitative measure for surveillance performance. This index indicates the proportion of the space being monitored with a sufficient resolution to the entire space of the target area. It is determined by computing surveillance resolution at every position and orientation, which indicates how closely a specific object can be monitored with a CCTV system. We present full mathematical derivation for the resolution, which depends on the location and orientation of the object as well as the geometric model of a camera. With the proposed approach, we quantitatively evaluated the surveillance coverage of a CCTV system in an underground parking area. Our evaluation process provided various quantitative-analysis results, compelling us to examine the design of the CCTV system prior to its installation and understand the surveillance capability of an existing CCTV system. PMID:26389909

Event-driven simulation in SELMON: An overview of EDSE

NASA Technical Reports Server (NTRS)

Rouquette, Nicolas F.; Chien, Steve A.; Charest, Leonard, Jr.

1992-01-01

EDSE (event-driven simulation engine), a model-based event-driven simulator implemented for SELMON, a tool for sensor selection and anomaly detection in real-time monitoring is described. The simulator is used in conjunction with a causal model to predict future behavior of the model from observed data. The behavior of the causal model is interpreted as equivalent to the behavior of the physical system being modeled. An overview of the functionality of the simulator and the model-based event-driven simulation paradigm on which it is based is provided. Included are high-level descriptions of the following key properties: event consumption and event creation, iterative simulation, synchronization and filtering of monitoring data from the physical system. Finally, how EDSE stands with respect to the relevant open issues of discrete-event and model-based simulation is discussed.

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

NASA Technical Reports Server (NTRS)

Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.

1998-01-01

Control of air contaminants is a crucial factor in the safety considerations of crewed space flight. Indoor air quality needs to be closely monitored during long range missions such as a Mars mission, and also on large complex space structures such as the International Space Station. This work mainly pertains to the detection and simulation of air contaminants in the space station, though much of the work is easily extended to buildings, and issues of ventilation systems. Here we propose a method with which to track the presence of contaminants using an accurate physical model, and also develop a robust procedure that would raise alarms when certain tolerance levels are exceeded. A part of this research concerns the modeling of air flow inside a spacecraft, and the consequent dispersal pattern of contaminants. Our objective is to also monitor the contaminants on-line, so we develop a state estimation procedure that makes use of the measurements from a sensor system and determines an optimal estimate of the contamination in the system as a function of time and space. The real-time optimal estimates in turn are used to detect faults in the system and also offer diagnoses as to their sources. This work is concerned with the monitoring of air contaminants aboard future generation spacecraft and seeks to satisfy NASA's requirements as outlined in their Strategic Plan document (Technology Development Requirements, 1996).

View west of load dispatch model board; section covers substations ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View west of load dispatch model board; section covers substations from edgerly (right) to thorndale and west yard (left). Instruments at bottom of center board section formerly monitored energy usage and were replaced by a computerized monitoring system. - Thirtieth Street Station, Load Dispatch Center, Thirtieth & Market Streets, Railroad Station, Amtrak (formerly Pennsylvania Railroad Station), Philadelphia, Philadelphia County, PA

Remote sensing of snow and ice

NASA Technical Reports Server (NTRS)

Rango, A.

1979-01-01

This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.

Multi-Level Modeling of Complex Socio-Technical Systems - Phase 1

DTIC Science & Technology

2013-06-06

is to detect anomalous organizational outcomes, diagnose the causes of these anomalies , and decide upon appropriate compensation schemes. All of...monitor process outcomes. The purpose of this monitoring is to detect anomalous process outcomes, diagnose the causes of these anomalies , and decide upon...monitor work outcomes in terms of performance. The purpose of this monitoring is to detect anomalous work outcomes, diagnose the causes of these anomalies

Intelligent model-based diagnostics for vehicle health management

NASA Astrophysics Data System (ADS)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Monitoring and evaluating civil structures using measured vibration

NASA Astrophysics Data System (ADS)

Straser, Erik G.; Kiremidjian, Anne S.

1996-04-01

The need for a rapid assessment of the state of critical and conventional civil structures, such as bridges, control centers, airports, and hospitals, among many, has been amply demonstrated during recent natural disasters. Research is underway at Stanford University to develop a state-of-the-art automated damage monitoring system for long term and extreme event monitoring based on both ambient and forced response measurements. Such research requires a multi-disciplinary approach harnessing the talents and expertise of civil, electrical, and mechanical engineering to arrive at a novel hardware and software solution. Recent advances in silicon micro-machining and microprocessor design allow for the economical integration of sensing, processing, and communication components. Coupling these technological advances with parameter identification algorithms allows for the realization of extreme event damage monitoring systems for civil structures. This paper addresses the first steps toward the development of a near real-time damage diagnostic and monitoring system based on structural response to extreme events. Specifically, micro-electro-mechanical- structures (MEMS) and microcontroller embedded systems (MES) are demonstrated to be an effective platform for the measurement and analysis of civil structures. Experimental laboratory tests with small scale model specimens and a preliminary sensor module are used to evaluate hardware and obtain structural response data from input accelerograms. A multi-step analysis procedure employing ordinary least squares (OLS), extended Kalman filtering (EKF), and a substructuring approach is conducted to extract system characteristics of the model. Results from experimental tests and system identification (SI) procedures as well as fundamental system design issues are presented.

Early warning, warning or alarm systems for natural hazards? A generic classification.

NASA Astrophysics Data System (ADS)

Sättele, Martina; Bründl, Michael; Straub, Daniel

2013-04-01

Early warning, warning and alarm systems have gained popularity in recent years as cost-efficient measures for dangerous natural hazard processes such as floods, storms, rock and snow avalanches, debris flows, rock and ice falls, landslides, flash floods, glacier lake outburst floods, forest fires and even earthquakes. These systems can generate information before an event causes loss of property and life. In this way, they mainly mitigate the overall risk by reducing the presence probability of endangered objects. These systems are typically prototypes tailored to specific project needs. Despite their importance there is no recognised system classification. This contribution classifies warning and alarm systems into three classes: i) threshold systems, ii) expert systems and iii) model-based expert systems. The result is a generic classification, which takes the characteristics of the natural hazard process itself and the related monitoring possibilities into account. The choice of the monitoring parameters directly determines the system's lead time. The classification of 52 active systems moreover revealed typical system characteristics for each system class. i) Threshold systems monitor dynamic process parameters of ongoing events (e.g. water level of a debris flow) and incorporate minor lead times. They have a local geographical coverage and a predefined threshold determines if an alarm is automatically activated to warn endangered objects, authorities and system operators. ii) Expert systems monitor direct changes in the variable disposition (e.g crack opening before a rock avalanche) or trigger events (e.g. heavy rain) at a local scale before the main event starts and thus offer extended lead times. The final alarm decision incorporates human, model and organisational related factors. iii) Model-based expert systems monitor indirect changes in the variable disposition (e.g. snow temperature, height or solar radiation that influence the occurrence probability of snow avalanches) or trigger events (e.g. heavy snow fall) to predict spontaneous hazard events in advance. They encompass regional or national measuring networks and satisfy additional demands such as the standardisation of the measuring stations. The developed classification and the characteristics, which were revealed for each class, yield a valuable input to quantifying the reliability of warning and alarm systems. Importantly, this will facilitate to compare them with well-established standard mitigation measures such as dams, nets and galleries within an integrated risk management approach.

Mass and stiffness estimation using mobile devices for structural health monitoring

NASA Astrophysics Data System (ADS)

Le, Viet; Yu, Tzuyang

2015-04-01

In the structural health monitoring (SHM) of civil infrastructure, dynamic methods using mass, damping, and stiffness for characterizing structural health have been a traditional and widely used approach. Changes in these system parameters over time indicate the progress of structural degradation or deterioration. In these methods, capability of predicting system parameters is essential to their success. In this paper, research work on the development of a dynamic SHM method based on perturbation analysis is reported. The concept is to use externally applied mass to perturb an unknown system and measure the natural frequency of the system. Derived theoretical expressions for mass and stiffness prediction are experimentally verified by a building model. Dynamic responses of the building model perturbed by various masses in free vibration were experimentally measured by a mobile device (cell phone) to extract the natural frequency of the building model. Single-degreeof- freedom (SDOF) modeling approach was adopted for the sake of using a cell phone. From the experimental result, it is shown that the percentage error of predicted mass increases when the mass ratio increases, while the percentage error of predicted stiffness decreases when the mass ratio increases. This work also demonstrated the potential use of mobile devices in the health monitoring of civil infrastructure.

A Low Cost Automated Monitoring System for Landslides Using Dual Frequency GPS

NASA Astrophysics Data System (ADS)

Mills, H.; Edwards, S.

2006-12-01

Landslides are an existing and permanent threat to societies across the globe, generating financial and human losses whenever and wherever they occur. Drawing together the strands of science that provide increased understanding of landslide triggers through accurate modelling is therefore vital for the development of mitigation and management strategies. Together with climatic and geomorphological data a key input here is information on the precise location and timing of landslide events. However, the detailed monitoring of landslides and precursor movements is generally limited to episodic campaigns where limiting factors include equipment and mobilisation costs, time constraints and spatial resolution. This research has developed a geodetic tool of benefit to scientists involved in the development of closely coupled models that seek to explain trigger mechanisms such as rainfall duration and intensity and changes in groundwater pressure to actual real land movements. A fully automated low cost dual frequency GPS station for the continuous in-situ monitoring of landslide sites has been developed. System configuration combines a dual frequency GPS receiver, PC board with a GPRS modem and power supply to deliver 24hr/365day operation capability. Individual components have been chosen to provide the highest accuracies while minimising power consumption resulting in a system around half that of equivalent commercial systems. Measurement point-costs can be further reduced through the use of antenna switching and multi antenna arrays. Continuous data is delivered via mobile phone uplink and processed automatically using geodetic software. The developed system has been extensively tested on a purpose built platform capable of simulating ground movements. Co-mounted antennas have allowed direct comparisons with more expensive geodetic GPS receivers. The system is capable of delivering precise 3D coordinates with a 9 mm rms. The system can be up-scaled resulting in the increased spatial density of monitoring and yielding more detailed information on landslide movements for improved downstream modelling and monitoring.

Pathogen Treatment Guidance and Monitoring Approaches fro ...

EPA Pesticide Factsheets

On-site non-potable water reuse is increasingly used to augment water supplies, but traditional fecal indicator approaches for defining and monitoring exposure risks are limited when applied to these decentralized options. This session emphasizes risk-based modeling to define pathogen log-reduction requirements coupled with alternative targets for monitoring enabled by genomic sequencing (i.e., the microbiome of reuse systems). 1. Discuss risk-based modeling to define pathogen log-reduction requirements 2. Review alternative targets for monitoring 3. Gain an understanding of how new tools can help improve successful development of sustainable on-site non-potable water reuse Presented at the Water Wastewater Equipment Treatment & Transport Show.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rainer, Leo I.; Hoeschele, Marc A.; Apte, Michael G.

This report addresses the results of detailed monitoring completed under Program Element 6 of Lawrence Berkeley National Laboratory's High Performance Commercial Building Systems (HPCBS) PIER program. The purpose of the Energy Simulations and Projected State-Wide Energy Savings project is to develop reasonable energy performance and cost models for high performance relocatable classrooms (RCs) across California climates. A key objective of the energy monitoring was to validate DOE2 simulations for comparison to initial DOE2 performance projections. The validated DOE2 model was then used to develop statewide savings projections by modeling base case and high performance RC operation in the 16 Californiamore » climate zones. The primary objective of this phase of work was to utilize detailed field monitoring data to modify DOE2 inputs and generate performance projections based on a validated simulation model. Additional objectives include the following: (1) Obtain comparative performance data on base case and high performance HVAC systems to determine how they are operated, how they perform, and how the occupants respond to the advanced systems. This was accomplished by installing both HVAC systems side-by-side (i.e., one per module of a standard two module, 24 ft by 40 ft RC) on the study RCs and switching HVAC operating modes on a weekly basis. (2) Develop projected statewide energy and demand impacts based on the validated DOE2 model. (3) Develop cost effectiveness projections for the high performance HVAC system in the 16 California climate zones.« less

Rotor Smoothing and Vibration Monitoring Results for the US Army VMEP

DTIC Science & Technology

2009-06-01

individual component CI detection thresholds, and development of models for diagnostics, prognostics , and anomaly detection . Figure 16 VMEP Server...and prognostics are of current interest. Development of those systems requires large amounts of data (collection, monitoring , manipulation) to capture...development of automated systems and for continuous updating of algorithms to improve detection , classification, and prognostic performance. A test

An efficient recursive least square-based condition monitoring approach for a rail vehicle suspension system

NASA Astrophysics Data System (ADS)

Liu, X. Y.; Alfi, S.; Bruni, S.

2016-06-01

A model-based condition monitoring strategy for the railway vehicle suspension is proposed in this paper. This approach is based on recursive least square (RLS) algorithm focusing on the deterministic 'input-output' model. RLS has Kalman filtering feature and is able to identify the unknown parameters from a noisy dynamic system by memorising the correlation properties of variables. The identification of suspension parameter is achieved by machine learning of the relationship between excitation and response in a vehicle dynamic system. A fault detection method for the vertical primary suspension is illustrated as an instance of this condition monitoring scheme. Simulation results from the rail vehicle dynamics software 'ADTreS' are utilised as 'virtual measurements' considering a trailer car of Italian ETR500 high-speed train. The field test data from an E464 locomotive are also employed to validate the feasibility of this strategy for the real application. Results of the parameter identification performed indicate that estimated suspension parameters are consistent or approximate with the reference values. These results provide the supporting evidence that this fault diagnosis technique is capable of paving the way for the future vehicle condition monitoring system.

A web accessible scientific workflow system for vadoze zone performance monitoring: design and implementation examples

NASA Astrophysics Data System (ADS)

Mattson, E.; Versteeg, R.; Ankeny, M.; Stormberg, G.

2005-12-01

Long term performance monitoring has been identified by DOE, DOD and EPA as one of the most challenging and costly elements of contaminated site remedial efforts. Such monitoring should provide timely and actionable information relevant to a multitude of stakeholder needs. This information should be obtained in a manner which is auditable, cost effective and transparent. Over the last several years INL staff has designed and implemented a web accessible scientific workflow system for environmental monitoring. This workflow environment integrates distributed, automated data acquisition from diverse sensors (geophysical, geochemical and hydrological) with server side data management and information visualization through flexible browser based data access tools. Component technologies include a rich browser-based client (using dynamic javascript and html/css) for data selection, a back-end server which uses PHP for data processing, user management, and result delivery, and third party applications which are invoked by the back-end using webservices. This system has been implemented and is operational for several sites, including the Ruby Gulch Waste Rock Repository (a capped mine waste rock dump on the Gilt Edge Mine Superfund Site), the INL Vadoze Zone Research Park and an alternative cover landfill. Implementations for other vadoze zone sites are currently in progress. These systems allow for autonomous performance monitoring through automated data analysis and report generation. This performance monitoring has allowed users to obtain insights into system dynamics, regulatory compliance and residence times of water. Our system uses modular components for data selection and graphing and WSDL compliant webservices for external functions such as statistical analyses and model invocations. Thus, implementing this system for novel sites and extending functionality (e.g. adding novel models) is relatively straightforward. As system access requires a standard webbrowser and uses intuitive functionality, stakeholders with diverse degrees of technical insight can use this system with little or no training.

Health Monitoring of a Satellite System

NASA Technical Reports Server (NTRS)

Chen, Robert H.; Ng, Hok K.; Speyer, Jason L.; Guntur, Lokeshkumar S.; Carpenter, Russell

2004-01-01

A health monitoring system based on analytical redundancy is developed for satellites on elliptical orbits. First, the dynamics of the satellite including orbital mechanics and attitude dynamics is modelled as a periodic system. Then, periodic fault detection filters are designed to detect and identify the satellite's actuator and sensor faults. In addition, parity equations are constructed using the algebraic redundant relationship among the actuators and sensors. Furthermore, a residual processor is designed to generate the probability of each of the actuator and sensor faults by using a sequential probability test. Finally, the health monitoring system, consisting of periodic fault detection lters, parity equations and residual processor, is evaluated in the simulation in the presence of disturbances and uncertainty.

Atmospheric transport modelling in support of CTBT verification—overview and basic concepts

NASA Astrophysics Data System (ADS)

Wotawa, Gerhard; De Geer, Lars-Erik; Denier, Philippe; Kalinowski, Martin; Toivonen, Harri; D'Amours, Real; Desiato, Franco; Issartel, Jean-Pierre; Langer, Matthias; Seibert, Petra; Frank, Andreas; Sloan, Craig; Yamazawa, Hiromi

Under the provisions of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), a global monitoring system comprising different verification technologies is currently being set up. The network will include 80 radionuclide (RN) stations distributed all over the globe that measure treaty-relevant radioactive species. While the seismic subsystem cannot distinguish between chemical and nuclear explosions, RN monitoring would provide the "smoking gun" of a possible treaty violation. Atmospheric transport modelling (ATM) will be an integral part of CTBT verification, since it provides a geo-temporal location capability for the RN technology. In this paper, the basic concept for the future ATM software system to be installed at the International Data Centre is laid out. The system is based on the operational computation of multi-dimensional source-receptor sensitivity fields for all RN samples by means of adjoint tracer transport modelling. While the source-receptor matrix methodology has already been applied in the past, the system that we suggest will be unique and unprecedented, since it is global, real-time and aims at uncovering source scenarios that are compatible with measurements. Furthermore, it has to deal with source dilution ratios that are by orders of magnitude larger than in typical transport model applications. This new verification software will need continuous scientific attention, and may well provide a prototype system for future applications in areas of environmental monitoring, emergency response and verification of other international agreements and treaties.

An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

NASA Astrophysics Data System (ADS)

Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

2013-12-01

One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.

Information processing requirements for on-board monitoring of automatic landing

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Karmarkar, J. S.

1977-01-01

A systematic procedure is presented for determining the information processing requirements for on-board monitoring of automatic landing systems. The monitoring system detects landing anomalies through use of appropriate statistical tests. The time-to-correct aircraft perturbations is determined from covariance analyses using a sequence of suitable aircraft/autoland/pilot models. The covariance results are used to establish landing safety and a fault recovery operating envelope via an event outcome tree. This procedure is demonstrated with examples using the NASA Terminal Configured Vehicle (B-737 aircraft). The procedure can also be used to define decision height, assess monitoring implementation requirements, and evaluate alternate autoland configurations.

A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

NASA Astrophysics Data System (ADS)

Khader, A. I.; Rosenberg, D. E.; McKee, M.

2013-05-01

Groundwater contaminated with nitrate poses a serious health risk to infants when this contaminated water is used for culinary purposes. To avoid this health risk, people need to know whether their culinary water is contaminated or not. Therefore, there is a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management options. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision-maker and the expected outcomes from these alternatives. The alternatives include (i) ignore the health risk of nitrate-contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, contaminant transport processes, and climate (Khader, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine, where methemoglobinemia (blue baby syndrome) is the main health problem associated with the principal contaminant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs include healthcare for methemoglobinemia, purchase of bottled water, and installation and maintenance of the groundwater monitoring system. At current methemoglobinemia and bottled water costs of 150/person and 0.6/baby/day, the decision tree results show that the expected cost of establishing the proposed groundwater quality monitoring network exceeds the expected costs of the uninformed alternatives and there is no value to the information the monitoring system provides. However, the monitoring system will be preferred to ignoring the health risk or using alternative sources if the methemoglobinemia cost rises to 300/person or the bottled water cost increases to 2.3/baby/day. Similarly, the monitoring system has value if the system can more accurately report actual aquifer concentrations and the public more fully abides by manager recommendations to use/not use the aquifer. The system also has value if it will serve a larger population or if its installation costs can be reduced, for example using a smaller number of monitoring wells. The VOI analysis shows how monitoring system design, accuracy, installation and operating costs, public awareness of health risks, costs of alternatives, and demographics together affect the value of implementing a system to monitor groundwater quality.

A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

NASA Astrophysics Data System (ADS)

Khader, A.; Rosenberg, D.; McKee, M.

2012-12-01

Nitrate pollution poses a health risk for infants whose freshwater drinking source is groundwater. This risk creates a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision maker and the expected outcomes from these alternatives. The alternatives include: (i) ignore the health risk of nitrate contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, pollution transport processes, and climate (Khader and McKee, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine where methemoglobinemia is the main health problem associated with the principal pollutant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not-use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs include healthcare for methemoglobinemia, purchase of bottled water, and installation and maintenance of the groundwater monitoring system. At current methemoglobinemia and bottled water costs of 150 $/person and 0.6 $/baby/day, the decision tree results show that the expected cost of establishing the proposed groundwater quality monitoring network exceeds the expected costs of the uninformed alternatives and there is not value to the information the monitoring system provides. However, the monitoring system will be preferred to ignoring the health risk or using alternative sources if the methemoglobinemia cost rises to 300 $/person or the bottled water cost increases to 2.3 $/baby/day. Similarly, the monitoring system has value if the system can more accurately report actual aquifer concentrations and the public more fully abides by managers' recommendations to use/not use the aquifer. The system also has value if it will serve a larger population or if its installation costs can be reduced, for example using a smaller number of monitoring wells. The VOI analysis shows how monitoring system design, accuracy, installation and operating costs, public awareness of health risks, costs of alternatives, and demographics together affect the value of implementing a system to monitor groundwater quality.

A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

NASA Astrophysics Data System (ADS)

Marécal, V.; Peuch, V.-H.; Andersson, C.; Andersson, S.; Arteta, J.; Beekmann, M.; Benedictow, A.; Bergström, R.; Bessagnet, B.; Cansado, A.; Chéroux, F.; Colette, A.; Coman, A.; Curier, R. L.; Denier van der Gon, H. A. C.; Drouin, A.; Elbern, H.; Emili, E.; Engelen, R. J.; Eskes, H. J.; Foret, G.; Friese, E.; Gauss, M.; Giannaros, C.; Guth, J.; Joly, M.; Jaumouillé, E.; Josse, B.; Kadygrov, N.; Kaiser, J. W.; Krajsek, K.; Kuenen, J.; Kumar, U.; Liora, N.; Lopez, E.; Malherbe, L.; Martinez, I.; Melas, D.; Meleux, F.; Menut, L.; Moinat, P.; Morales, T.; Parmentier, J.; Piacentini, A.; Plu, M.; Poupkou, A.; Queguiner, S.; Robertson, L.; Rouïl, L.; Schaap, M.; Segers, A.; Sofiev, M.; Thomas, M.; Timmermans, R.; Valdebenito, Á.; van Velthoven, P.; van Versendaal, R.; Vira, J.; Ung, A.

2015-03-01

This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. The paper gives an overall picture of its status at the end of MACC-II (summer 2014). This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs and PAN + PAN precursors) over 8 vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performances of the system are assessed daily, weekly and 3 monthly (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the median ensemble to forecast regional ozone pollution events. The time period of this case study is also used to illustrate that the median ensemble generally outperforms each of the individual models and that it is still robust even if two of the seven models are missing. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10 and show an overall improvement over time. The change of the skills of the ensemble over the past two summers for ozone and the past two winters for PM10 are discussed in the paper. While the evolution of the ozone scores is not significant, there are improvements of PM10 over the past two winters that can be at least partly attributed to new developments on aerosols in the seven individual models. Nevertheless, the year to year changes in the models and ensemble skills are also linked to the variability of the meteorological conditions and of the set of observations used to calculate the statistical indicators. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

An overheight vehicle bridge collision monitoring system using piezoelectric transducers

NASA Astrophysics Data System (ADS)

Song, G.; Olmi, C.; Gu, H.

2007-04-01

With increasing traffic volume follows an increase in the number of overheight truck collisions with highway bridges. The detection of collision impact and evaluation of the impact level is a critical issue in the maintenance of a concrete bridge. In this paper, an overheight collision detection and evaluation system is developed for concrete bridge girders using piezoelectric transducers. An electric circuit is designed to detect the impact and to activate a digital camera to take photos of the offending truck. Impact tests and a health monitoring test were conducted on a model concrete bridge girder by using three piezoelectric transducers embedded before casting. From the experimental data of the impact test, it can be seen that there is a linear relation between the output of sensor energy and the impact energy. The health monitoring results show that the proposed damage index indicates the level of damage inside the model concrete bridge girder. The proposed overheight truck-bridge collision detection and evaluation system has the potential to be applied to the safety monitoring of highway bridges.

Exploiting analytics techniques in CMS computing monitoring

NASA Astrophysics Data System (ADS)

Bonacorsi, D.; Kuznetsov, V.; Magini, N.; Repečka, A.; Vaandering, E.

2017-10-01

The CMS experiment has collected an enormous volume of metadata about its computing operations in its monitoring systems, describing its experience in operating all of the CMS workflows on all of the Worldwide LHC Computing Grid Tiers. Data mining efforts into all these information have rarely been done, but are of crucial importance for a better understanding of how CMS did successful operations, and to reach an adequate and adaptive modelling of the CMS operations, in order to allow detailed optimizations and eventually a prediction of system behaviours. These data are now streamed into the CERN Hadoop data cluster for further analysis. Specific sets of information (e.g. data on how many replicas of datasets CMS wrote on disks at WLCG Tiers, data on which datasets were primarily requested for analysis, etc) were collected on Hadoop and processed with MapReduce applications profiting of the parallelization on the Hadoop cluster. We present the implementation of new monitoring applications on Hadoop, and discuss the new possibilities in CMS computing monitoring introduced with the ability to quickly process big data sets from mulltiple sources, looking forward to a predictive modeling of the system.

A Distributed Web-based Solution for Ionospheric Model Real-time Management, Monitoring, and Short-term Prediction

NASA Astrophysics Data System (ADS)

Kulchitsky, A.; Maurits, S.; Watkins, B.

2006-12-01

With the widespread availability of the Internet today, many people can monitor various scientific research activities. It is important to accommodate this interest providing on-line access to dynamic and illustrative Web-resources, which could demonstrate different aspects of ongoing research. It is especially important to explain and these research activities for high school and undergraduate students, thereby providing more information for making decisions concerning their future studies. Such Web resources are also important to clarify scientific research for the general public, in order to achieve better awareness of research progress in various fields. Particularly rewarding is dissemination of information about ongoing projects within Universities and research centers to their local communities. The benefits of this type of scientific outreach are mutual, since development of Web-based automatic systems is prerequisite for many research projects targeting real-time monitoring and/or modeling of natural conditions. Continuous operation of such systems provide ongoing research opportunities for the statistically massive validation of the models, as well. We have developed a Web-based system to run the University of Alaska Fairbanks Polar Ionospheric Model in real-time. This model makes use of networking and computational resources at the Arctic Region Supercomputing Center. This system was designed to be portable among various operating systems and computational resources. Its components can be installed across different computers, separating Web servers and computational engines. The core of the system is a Real-Time Management module (RMM) written Python, which facilitates interactions of remote input data transfers, the ionospheric model runs, MySQL database filling, and PHP scripts for the Web-page preparations. The RMM downloads current geophysical inputs as soon as they become available at different on-line depositories. This information is processed to provide inputs for the next ionospheic model time step and then stored in a MySQL database as the first part of the time-specific record. The RMM then performs synchronization of the input times with the current model time, prepares a decision on initialization for the next model time step, and monitors its execution. Then, as soon as the model completes computations for the next time step, RMM visualizes the current model output into various short-term (about 1-2 hours) forecasting products and compares prior results with available ionospheric measurements. The RMM places prepared images into the MySQL database, which can be located on a different computer node, and then proceeds to the next time interval continuing the time-loop. The upper-level interface of this real-time system is the a PHP-based Web site (http://www.arsc.edu/SpaceWeather/new). This site provides general information about the Earth polar and adjacent mid-latitude ionosphere, allows for monitoring of the current developments and short-term forecasts, and facilitates access to the comparisons archive stored in the database.

[Establishment of model of traditional Chinese medicine injections post-marketing safety monitoring].

PubMed

Guo, Xin-E; Zhao, Yu-Bin; Xie, Yan-Ming; Zhao, Li-Cai; Li, Yan-Feng; Hao, Zhe

2013-09-01

To establish a nurse based post-marketing safety surveillance model for traditional Chinese medicine injections (TCMIs). A TCMIs safety monitoring team and a research hospital team engaged in the research, monitoring processes, and quality control processes were established, in order to achieve comprehensive, timely, accurate and real-time access to research data, to eliminate errors in data collection. A triage system involving a study nurse, as the first point of contact, clinicians and clinical pharmacists was set up in a TCM hospital. Following the specified workflow involving labeling of TCM injections and using improved monitoring forms it was found that there were no missing reports at the ratio of error was zero. A research nurse as the first and main point of contact in post-marketing safety monitoring of TCM as part of a triage model, ensures that research data collected has the characteristics of authenticity, accuracy, timeliness, integrity, and eliminate errors during the process of data collection. Hospital based monitoring is a robust and operable process.

Incorporation of Monitoring Systems to Model Irrigated Cotton at a Landscape Level

USDA-ARS?s Scientific Manuscript database

Advances in computer speed, industry IT core capabilities, and available soils and weather information have resulted in the need for “cropping system models” that address in detail the spatial and temporal water, energy and carbon balance of the system at a landscape scale. Many of these models have...

SIG-VISA: Signal-based Vertically Integrated Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Mayeda, K. M.; Myers, S. C.; Russell, S.

2013-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software; however, while such detections may constitute a useful summary of station activity, they discard large amounts of information present in the original recorded signal. We present SIG-VISA (Signal-based Vertically Integrated Seismic Analysis), a system for seismic monitoring through Bayesian inference on seismic signals. By directly modeling the recorded signal, our approach incorporates additional information unavailable to detection-based methods, enabling higher sensitivity and more accurate localization using techniques such as waveform matching. SIG-VISA's Bayesian forward model of seismic signal envelopes includes physically-derived models of travel times and source characteristics as well as Gaussian process (kriging) statistical models of signal properties that combine interpolation of historical data with extrapolation of learned physical trends. Applying Bayesian inference, we evaluate the model on earthquakes as well as the 2009 DPRK test event, demonstrating a waveform matching effect as part of the probabilistic inference, along with results on event localization and sensitivity. In particular, we demonstrate increased sensitivity from signal-based modeling, in which the SIGVISA signal model finds statistical evidence for arrivals even at stations for which the IMS station processing failed to register any detection.

Multileaf collimator tracking integrated with a novel x-ray imaging system and external surrogate monitoring

NASA Astrophysics Data System (ADS)

Krauss, Andreas; Fast, Martin F.; Nill, Simeon; Oelfke, Uwe

2012-04-01

We have previously developed a tumour tracking system, which adapts the aperture of a Siemens 160 MLC to electromagnetically monitored target motion. In this study, we exploit the use of a novel linac-mounted kilovoltage x-ray imaging system for MLC tracking. The unique in-line geometry of the imaging system allows the detection of target motion perpendicular to the treatment beam (i.e. the directions usually featuring steep dose gradients). We utilized the imaging system either alone or in combination with an external surrogate monitoring system. We equipped a Siemens ARTISTE linac with two flat panel detectors, one directly underneath the linac head for motion monitoring and the other underneath the patient couch for geometric tracking accuracy assessments. A programmable phantom with an embedded metal marker reproduced three patient breathing traces. For MLC tracking based on x-ray imaging alone, marker position was detected at a frame rate of 7.1 Hz. For the combined external and internal motion monitoring system, a total of only 85 x-ray images were acquired prior to or in between the delivery of ten segments of an IMRT beam. External motion was monitored with a potentiometer. A correlation model between external and internal motion was established. The real-time component of the MLC tracking procedure then relied solely on the correlation model estimations of internal motion based on the external signal. Geometric tracking accuracies were 0.6 mm (1.1 mm) and 1.8 mm (1.6 mm) in directions perpendicular and parallel to the leaf travel direction for the x-ray-only (the combined external and internal) motion monitoring system in spite of a total system latency of ˜0.62 s (˜0.51 s). Dosimetric accuracy for a highly modulated IMRT beam-assessed through radiographic film dosimetry-improved substantially when tracking was applied, but depended strongly on the respective geometric tracking accuracy. In conclusion, we have for the first time integrated MLC tracking with x-ray imaging in the in-line geometry and demonstrated highly accurate respiratory motion tracking.

View west within the periphery of the load dispatch model ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View west within the periphery of the load dispatch model board, operator's console is at lower center and button board is at lower right of the photograph; section of model board shown covers substation from Perryman (left) to Frankford (right); instruments at right center of photograph formerly monitored energy usage and were replaced by computerized monitoring system. - Thirtieth Street Station, Load Dispatch Center, Thirtieth & Market Streets, Railroad Station, Amtrak (formerly Pennsylvania Railroad Station), Philadelphia, Philadelphia County, PA

Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net

NASA Technical Reports Server (NTRS)

Lerner, Uri; Moses, Brooks; Scott, Maricia; McIlraith, Sheila; Keller, Daphne

2005-01-01

The Reverse Water Gas Shift system (RWGS) is a complex physical system designed to produce oxygen from the carbon dioxide atmosphere on Mars. If sent to Mars, it would operate without human supervision, thus requiring a reliable automated system for monitoring and control. The RWGS presents many challenges typical of real-world systems, including: noisy and biased sensors, nonlinear behavior, effects that are manifested over different time granularities, and unobservability of many important quantities. In this paper we model the RWGS using a hybrid (discrete/continuous) Dynamic Bayesian Network (DBN), where the state at each time slice contains 33 discrete and 184 continuous variables. We show how the system state can be tracked using probabilistic inference over the model. We discuss how to deal with the various challenges presented by the RWGS, providing a suite of techniques that are likely to be useful in a wide range of applications. In particular, we describe a general framework for dealing with nonlinear behavior using numerical integration techniques, extending the successful Unscented Filter. We also show how to use a fixed-point computation to deal with effects that develop at different time scales, specifically rapid changes occuring during slowly changing processes. We test our model using real data collected from the RWGS, demonstrating the feasibility of hybrid DBNs for monitoring complex real-world physical systems.

Impasse-driven tutoring for reactive skill acquisition

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.; Johnson, W. Lewis

1993-01-01

We are interested in developing effective performance-oriented training for the operation of systems that are used for monitor and control purposes. We have focused on one such system, the communications Link Monitor and Control (LMC) system used in NASA's Deep Space Network (DSN), which is a worldwide system for navigating, tracking and communicating with unmanned interplanetary spacecraft. The tasks in this domain are procedural in nature and require reactive, goal-oriented skills; we have previously described a cognitive model for problem solving that accounts for both novice and expert levels of behavior as well as how skill is acquired. Our cognitive modeling work in this task domain led us to make a number of predictions about tutoring that have influenced the design of the system described in this paper.

Environmental Monitoring Using Sensor Networks

NASA Astrophysics Data System (ADS)

Yang, J.; Zhang, C.; Li, X.; Huang, Y.; Fu, S.; Acevedo, M. F.

2008-12-01

Environmental observatories, consisting of a variety of sensor systems, computational resources and informatics, are important for us to observe, model, predict, and ultimately help preserve the health of the nature. The commoditization and proliferation of coin-to-palm sized wireless sensors will allow environmental monitoring with unprecedented fine spatial and temporal resolution. Once scattered around, these sensors can identify themselves, locate their positions, describe their functions, and self-organize into a network. They communicate through wireless channel with nearby sensors and transmit data through multi-hop protocols to a gateway, which can forward information to a remote data server. In this project, we describe an environmental observatory called Texas Environmental Observatory (TEO) that incorporates a sensor network system with intertwined wired and wireless sensors. We are enhancing and expanding the existing wired weather stations to include wireless sensor networks (WSNs) and telemetry using solar-powered cellular modems. The new WSNs will monitor soil moisture and support long-term hydrologic modeling. Hydrologic models are helpful in predicting how changes in land cover translate into changes in the stream flow regime. These models require inputs that are difficult to measure over large areas, especially variables related to storm events, such as soil moisture antecedent conditions and rainfall amount and intensity. This will also contribute to improve rainfall estimations from meteorological radar data and enhance hydrological forecasts. Sensor data are transmitted from monitoring site to a Central Data Collection (CDC) Server. We incorporate a GPRS modem for wireless telemetry, a single-board computer (SBC) as Remote Field Gateway (RFG) Server, and a WSN for distributed soil moisture monitoring. The RFG provides effective control, management, and coordination of two independent sensor systems, i.e., a traditional datalogger-based wired sensor system and the WSN-based wireless sensor system. The RFG also supports remote manipulation of the devices in the field such as the SBC, datalogger, and WSN. Sensor data collected from the distributed monitoring stations are stored in a database (DB) Server. The CDC Server acts as an intermediate component to hide the heterogeneity of different devices and support data validation required by the DB Server. Daemon programs running on the CDC Server pre-process the data before it is inserted into the database, and periodically perform synchronization tasks. A SWE-compliant data repository is installed to enable data exchange, accepting data from both internal DB Server and external sources through the OGC web services. The web portal, i.e. TEO Online, serves as a user-friendly interface for data visualization, analysis, synthesis, modeling, and K-12 educational outreach activities. It also provides useful capabilities for system developers and operators to remotely monitor system status and remotely update software and system configuration, which greatly simplifies the system debugging and maintenance tasks. We also implement Sensor Observation Services (SOS) at this layer, conforming to the SWE standard to facilitate data exchange. The standard SensorML/O&M data representation makes it easy to integrate our sensor data into the existing Geographic Information Systems (GIS) web services and exchange the data with other organizations.

Water quality real-time monitoring system via biological detection based on video analysis

NASA Astrophysics Data System (ADS)

Xin, Chen; Fei, Yuan

2017-11-01

With the development of society, water pollution has become the most serious problem in China. Therefore, real-time water quality monitoring is an important part of human activities and water pollution prevention. In this paper, the behavior of zebrafish was monitored by computer vision. Firstly, the moving target was extracted by the method of saliency detection, and tracked by fitting the ellipse model. Then the motion parameters were extracted by optical flow method, and the data were monitored in real time by means of Hinkley warning and threshold warning. We achieved classification warning through a number of dimensions by comprehensive toxicity index. The experimental results show that the system can achieve more accurate real-time monitoring.

New generation of meteorology cameras

NASA Astrophysics Data System (ADS)

Janout, Petr; Blažek, Martin; Páta, Petr

2017-12-01

A new generation of the WILLIAM (WIde-field aLL-sky Image Analyzing Monitoring system) camera includes new features such as monitoring of rain and storm clouds during the day observation. Development of the new generation of weather monitoring cameras responds to the demand for monitoring of sudden weather changes. However, new WILLIAM cameras are ready to process acquired image data immediately, release warning against sudden torrential rains, and send it to user's cell phone and email. Actual weather conditions are determined from image data, and results of image processing are complemented by data from sensors of temperature, humidity, and atmospheric pressure. In this paper, we present the architecture, image data processing algorithms of mentioned monitoring camera and spatially-variant model of imaging system aberrations based on Zernike polynomials.

Evaluating Conceptual Site Models with Multicomponent Reactive Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, Z.; Heffner, D.; Price, V.; Temples, T. J.; Nicholson, T. J.

2005-05-01

Modeling ground-water flow and multicomponent reactive chemical transport is a useful approach for testing conceptual site models and assessing the design of monitoring networks. A graded approach with three conceptual site models is presented here with a field case of tetrachloroethene (PCE) transport and biodegradation near Charleston, SC. The first model assumed a one-layer homogeneous aquifer structure with semi-infinite boundary conditions, in which an analytical solution of the reactive solute transport can be obtained with BIOCHLOR (Aziz et al., 1999). Due to the over-simplification of the aquifer structure, this simulation cannot reproduce the monitoring data. In the second approach we used GMS to develop the conceptual site model, a layer-cake multi-aquifer system, and applied a numerical module (MODFLOW and RT3D within GMS) to solve the flow and reactive transport problem. The results were better than the first approach but still did not fit the plume well because the geological structures were still inadequately defined. In the third approach we developed a complex conceptual site model by interpreting log and seismic survey data with Petra and PetraSeis. We detected a major channel and a younger channel, through the PCE source area. These channels control the local ground-water flow direction and provide a preferential chemical transport pathway. Results using the third conceptual site model agree well with the monitoring concentration data. This study confirms that the bias and uncertainty from inadequate conceptual models are much larger than those introduced from an inadequate choice of model parameter values (Neuman and Wierenga, 2003; Meyer et al., 2004). Numerical modeling in this case provides key insight into the hydrogeology and geochemistry of the field site for predicting contaminant transport in the future. Finally, critical monitoring points and performance indicator parameters are selected for future monitoring to confirm system performance.

Distributed architecture and distributed processing mode in urban sewage treatment

NASA Astrophysics Data System (ADS)

Zhou, Ruipeng; Yang, Yuanming

2017-05-01

Decentralized rural sewage treatment facility over the broad area, a larger operation and management difficult, based on the analysis of rural sewage treatment model based on the response to these challenges, we describe the principle, structure and function in networking technology and network communications technology as the core of distributed remote monitoring system, through the application of case analysis to explore remote monitoring system features in a decentralized rural sewage treatment facilities in the daily operation and management. Practice shows that the remote monitoring system to provide technical support for the long-term operation and effective supervision of the facilities, and reduced operating, maintenance and supervision costs for development.

Performance monitoring in the medial frontal cortex and related neural networks: From monitoring self actions to understanding others' actions.

PubMed

Ninomiya, Taihei; Noritake, Atsushi; Ullsperger, Markus; Isoda, Masaki

2018-04-27

Action is a key channel for interacting with the outer world. As such, the ability to monitor actions and their consequences - regardless as to whether they are self-generated or other-generated - is of crucial importance for adaptive behavior. The medial frontal cortex (MFC) has long been studied as a critical node for performance monitoring in nonsocial contexts. Accumulating evidence suggests that the MFC is involved in a wide range of functions necessary for one's own performance monitoring, including error detection, and monitoring and resolving response conflicts. Recent studies, however, have also pointed to the importance of the MFC in performance monitoring under social conditions, ranging from monitoring and understanding others' actions to reading others' mental states, such as their beliefs and intentions (i.e., mentalizing). Here we review the functional roles of the MFC and related neural networks in performance monitoring in both nonsocial and social contexts, with an emphasis on the emerging field of a social systems neuroscience approach using macaque monkeys as a model system. Future work should determine the way in which the MFC exerts its monitoring function via interactions with other brain regions, such as the superior temporal sulcus in the mentalizing system and the ventral premotor cortex in the mirror system. Copyright © 2018. Published by Elsevier B.V.

Experimental study on distributed optical fiber-based approach monitoring saturation line in levee engineering

NASA Astrophysics Data System (ADS)

Su, Huaizhi; Li, Hao; Kang, Yeyuan; Wen, Zhiping

2018-02-01

Seepage is one of key factors which affect the levee engineering safety. The seepage danger without timely detection and rapid response may likely lead to severe accidents such as seepage failure, slope instability, and even levee break. More than 90 percent of levee break events are caused by the seepage. It is very important for seepage behavior identification to determine accurately saturation line in levee engineering. Furthermore, the location of saturation line has a major impact on slope stability in levee engineering. Considering the structure characteristics and service condition of levee engineering, the distributed optical fiber sensing technology is introduced to implement the real-time observation of saturation line in levee engineering. The distributed optical fiber temperature sensor system (DTS)-based monitoring principle of saturation line in levee engineering is investigated. An experimental platform, which consists of DTS, heating system, water-supply system, auxiliary analysis system and levee model, is designed and constructed. The monitoring experiment of saturation line in levee model is implemented on this platform. According to the experimental results, the numerical relationship between moisture content and thermal conductivity in porous medium is identified. A line heat source-based distributed optical fiber method obtaining the thermal conductivity in porous medium is developed. A DTS-based approach is proposed to monitor the saturation line in levee engineering. The embedment pattern of optical fiber for monitoring saturation line is presented.

Monitoring and modeling of microbial and biological water quality

USDA-ARS?s Scientific Manuscript database

Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

Hyperspectral Imaging of Functional Patterns for Disease Assessment and Treatment Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demos, S; Hattery, D; Hassan, M

2003-12-05

We have designed and built a six-band multi-spectral NIR imaging system used in clinical testing on cancer patients. From our layered tissue model, we create blood volume and blood oxygenation images for patient treatment monitoring.

Monitoring Bloom Dynamics of a Common Coastal Bioluminescent Ctenophore

DTIC Science & Technology

2010-09-30

photodiodes. IMPACT/APPLICATIONS More frequent and more rapidly developing jellyfish blooms, especially Mnemiopsis leidyi as well as Harmful Algal...To meet the need for a bioluminescent jellyfish monitoring and forecasting system, predictive models will depend upon dense networks of sensor

Identifying atmospheric monitoring needs for Space Station Freedom

NASA Technical Reports Server (NTRS)

Casserly, Dennis M.

1989-01-01

The atmospheric monitoring needs for Space Station Freedom were identified by examining the following from an industrial hygiene perspective: the experiences of past missions; ground based tests of proposed life support systems; the unique experimental and manufacturing facilities; the contaminant load model; metabolic production; and a fire. A target list of compounds to be monitored is presented and information is provided relative to the frequency of analysis, concentration ranges, and locations for monitoring probes.

Spatiotemporal data visualisation for homecare monitoring of elderly people.

PubMed

Juarez, Jose M; Ochotorena, Jose M; Campos, Manuel; Combi, Carlo

2015-10-01

Elderly people who live alone can be assisted by home monitoring systems that identify risk scenarios such as falls, fatigue symptoms or burglary. Given that these systems have to manage spatiotemporal data, human intervention is required to validate automatic alarms due to the high number of false positives and the need for context interpretation. The goal of this work was to provide tools to support human action, to identify such potential risk scenarios based on spatiotemporal data visualisation. We propose the MTA (multiple temporal axes) model, a visual representation of temporal information of the activity of a single person at different locations. The main goal of this model is to visualize the behaviour of a person in their home, facilitating the identification of health-risk scenarios and repetitive patterns. We evaluate the model's insight capacity compared with other models using a standard evaluation protocol. We also test its practical suitability of the MTA graphical model in a commercial home monitoring system. In particular, we implemented 8VISU, a visualization tool based on MTA. MTA proved to be more than 90% accurate in identify non-risk scenarios, independently of the length of the record visualised. When the spatial complexity was increased (e.g. number of rooms) the model provided good accuracy form up to 5 rooms. Therefore, user preferences and user performance seem to be balanced. Moreover, it also gave high sensitivity levels (over 90%) for 5-8 rooms. Fall is the most recurrent incident for elderly people. The MTA model outperformed the other models considered in identifying fall scenarios (66% of correctness) and was the second best for burglary and fatigue scenarios (36% of correctness). Our experiments also confirm the hypothesis that cyclic models are the most suitable for fatigue scenarios, the Spiral and MTA models obtaining most positive identifications. In home monitoring systems, spatiotemporal visualization is a useful tool for identifying risk and preventing home accidents in elderly people living alone. The MTA model helps the visualisation in different stages of the temporal data analysis process. In particular, its explicit representation of space and movement is useful for identifying potential scenarios of risk, while the spiral structure can be used for the identification of recurrent patterns. The results of the experiments and the experience using the visualization tool 8VISU proof the potential of the MTA graphical model to mine temporal data and to support caregivers using home monitoring infrastructures. Copyright © 2015 Elsevier B.V. All rights reserved.

Informing Drought Preparedness and Response with the South Asia Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Ghatak, D.; Matin, M. A.; Qamer, F. M.; Adhikary, B.; Bajracharya, B.; Nelson, J.; Pulla, S. T.; Ellenburg, W. L.

2017-12-01

Decision-relevant drought monitoring in South Asia is a challenge from both a scientific and an institutional perspective. Scientifically, climatic diversity, inconsistent in situ monitoring, complex hydrology, and incomplete knowledge of atmospheric processes mean that monitoring and prediction are fraught with uncertainty. Institutionally, drought monitoring efforts need to align with the information needs and decision-making processes of relevant agencies at national and subnational levels. Here we present first results from an emerging operational drought monitoring and forecast system developed and supported by the NASA SERVIR Hindu-Kush Himalaya hub. The system has been designed in consultation with end users from multiple sectors in South Asian countries to maximize decision-relevant information content in the monitoring and forecast products. Monitoring of meteorological, agricultural, and hydrological drought is accomplished using the South Asia Land Data Assimilation System, a platform that supports multiple land surface models and meteorological forcing datasets to characterize uncertainty, and subseasonal to seasonal hydrological forecasts are produced by driving South Asia LDAS with downscaled meteorological fields drawn from an ensemble of global dynamically-based forecast systems. Results are disseminated to end users through a Tethys online visualization platform and custom communications that provide user oriented, easily accessible, timely, and decision-relevant scientific information.

The SysMan monitoring service and its management environment

NASA Astrophysics Data System (ADS)

Debski, Andrzej; Janas, Ekkehard

1996-06-01

Management of modern information systems is becoming more and more complex. There is a growing need for powerful, flexible and affordable management tools to assist system managers in maintaining such systems. It is at the same time evident that effective management should integrate network management, system management and application management in a uniform way. Object oriented OSI management architecture with its four basic modelling concepts (information, organization, communication and functional models) together with widely accepted distribution platforms such as ANSA/CORBA, constitutes a reliable and modern framework for the implementation of a management toolset. This paper focuses on the presentation of concepts and implementation results of an object oriented management toolset developed and implemented within the framework of the ESPRIT project 7026 SysMan. An overview is given of the implemented SysMan management services including the System Management Service, Monitoring Service, Network Management Service, Knowledge Service, Domain and Policy Service, and the User Interface. Special attention is paid to the Monitoring Service which incorporates the architectural key entity responsible for event management. Its architecture and building components, especially filters, are emphasized and presented in detail.

a Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

NASA Astrophysics Data System (ADS)

Park, Young-Tack; Kim, Jae-Hoon; Park, Hyun-Soo

1997-06-01

Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

Integrating remotely sensed fires for predicting deforestation for REDD.

PubMed

Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

2017-06-01

Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

Operational Monitoring and Forecasting in Regional Seas: the Aegean Sea example

NASA Astrophysics Data System (ADS)

Nittis, K.; Perivoliotis, L.; Zervakis, V.; Papadopoulos, A.; Tziavos, C.

2003-04-01

The increasing economic activities in the coastal zone and the associated pressure on the marine environment have raised the interest on monitoring systems able to provide supporting information for its effective management and protection. Such an integrated monitoring, forecasting and information system is being developed during the past years in the Aegean Sea. Its main component is the POSEIDON network that provides real-time data for meteorological and surface oceanographic parameters (waves, currents, hydrological and biochemical data) from 11 fixed oceanographic buoys. The numerical forecasting system is composed by an ETA atmospheric model, a WAM wave model and a POM hydrodynamic model that provide every day 72 hours forecasts. The system is operational since May 2000 and its products are published through Internet while a sub-set is also available through cellular telephony. New type of observing platforms will be available in the near future through a number of EU funded research projects. The Mediterranean Moored Multi-sensor Array (M3A) that was developed for the needs of the Mediterranean Forecasting System and was tested during 2000-2001 will be operational in 2004 during the MFSTEP project. The M3A system incorporates sensors for optical and chemical measurements (Oxygen, Turbidity, Chlorophyll-a, Nutrients and PAR) in the euphotic zone (0-100m) together with sensors for physical parameters (Temperature, Salinity, Current speed and direction) at the 0-500m layer. A Ferry-Box system will also operate during 2004 in the southern Aegean Sea, providing surface data for physical and bio-chemical properties. The ongoing modeling efforts include coupling with larger scale circulation models of the Mediterranean, high-resolution downscaling to coastal areas of the Aegean Sea and development of multi-variate data assimilation methods.

Making intelligent systems team players. A guide to developing intelligent monitoring systems

NASA Technical Reports Server (NTRS)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Crack identification for rigid pavements using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bahaddin Ersoz, Ahmet; Pekcan, Onur; Teke, Turker

2017-09-01

Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation of existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based pavement monitoring systems have been in-use in assessing the remaining life of in-service pavements. Although such systems produce accurate results, their use can be expensive and data processing can be time consuming, which make them infeasible considering the demand for quick pavement evaluation. To overcome such problems, Unmanned Aerial Vehicles (UAVs) can be used as an alternative as they are relatively cheaper and easier-to-use. In this study, we propose a UAV based pavement crack identification system for monitoring rigid pavements’ existing conditions. The system consists of recently introduced image processing algorithms used together with conventional machine learning techniques, both of which are used to perform detection of cracks on rigid pavements’ surface and their classification. Through image processing, the distinct features of labelled crack bodies are first obtained from the UAV based images and then used for training of a Support Vector Machine (SVM) model. The performance of the developed SVM model was assessed with a field study performed along a rigid pavement exposed to low traffic and serious temperature changes. Available cracks were classified using the UAV based system and obtained results indicate it ensures a good alternative solution for pavement monitoring applications.

Model-based reasoning in SSF ECLSS

NASA Technical Reports Server (NTRS)

Miller, J. K.; Williams, George P. W., Jr.

1992-01-01

The interacting processes and reconfigurable subsystems of the Space Station Freedom Environmental Control and Life Support System (ECLSS) present a tremendous technical challenge to Freedom's crew and ground support. ECLSS operation and problem analysis is time-consuming for crew members and difficult for current computerized control, monitoring, and diagnostic software. These challenges can be at least partially mitigated by the use of advanced techniques such as Model-Based Reasoning (MBR). This paper will provide an overview of MBR as it is being applied to Space Station Freedom ECLSS. It will report on work being done to produce intelligent systems to help design, control, monitor, and diagnose Freedom's ECLSS. Specifically, work on predictive monitoring, diagnosability, and diagnosis, with emphasis on the automated diagnosis of the regenerative water recovery and air revitalization processes will be discussed.

Embedded Diagnostic/Prognostic Reasoning and Information Continuity for Improved Avionics Maintenance

DTIC Science & Technology

2006-01-01

enabling technologies such as built-in-test, advanced health monitoring algorithms, reliability and component aging models, prognostics methods, and...deployment and acceptance. This framework and vision is consistent with the onboard PHM ( Prognostic and Health Management) as well as advanced... monitored . In addition to the prognostic forecasting capabilities provided by monitoring system power, multiple confounding errors by electronic

Fir sawyer beetle-Siberian fir interaction modeling: resistance of fir stands to insect outbreaks

Treesearch

Tamara M. Ovtchinnikova; Victor V. Kiselev

1991-01-01

Entomological monitoring is part of a total ecological monitoring system. Its purpose is the identification, prognosis, and estimation of forest ecosystem impacts induced by insects. The entomological monitoring of a forest is based on a clear understanding of the role played by insects in forest ecosystems. The patterns of insect population dynamics in space and time...

Monitoring of biofilm-associated Legionella pneumophila on different substrata in model cooling tower system.

PubMed

Türetgen, Irfan; Cotuk, Aysin

2007-02-01

Cooling towers have the potential to develop infectious concentrations of Legionella pneumophila. Legionella counts increases where biofilm and warm water temperatures are present. In this study, biofilm associated L. pneumophila and heterotrophic bacteria were compared in terms of material dependence. Model cooling tower system was experimentally infected by L. pneumophila standard strain and monthly monitored. Different materials were tested for a period of 180 days. The lowest L. pneumophila and heterotrophic plate counts were measured on plastic polymers, whereas L. pneumophila and heterotrophic bacteria were accumulated rapidly on galvanized steel surfaces. It can be concluded that selection of plastic polymers, as a manufacturing material, are suitable for recirculating water systems.

Monitoring of services with non-relational databases and map-reduce framework

NASA Astrophysics Data System (ADS)

Babik, M.; Souto, F.

2012-12-01

Service Availability Monitoring (SAM) is a well-established monitoring framework that performs regular measurements of the core site services and reports the corresponding availability and reliability of the Worldwide LHC Computing Grid (WLCG) infrastructure. One of the existing extensions of SAM is Site Wide Area Testing (SWAT), which gathers monitoring information from the worker nodes via instrumented jobs. This generates quite a lot of monitoring data to process, as there are several data points for every job and several million jobs are executed every day. The recent uptake of non-relational databases opens a new paradigm in the large-scale storage and distributed processing of systems with heavy read-write workloads. For SAM this brings new possibilities to improve its model, from performing aggregation of measurements to storing raw data and subsequent re-processing. Both SAM and SWAT are currently tuned to run at top performance, reaching some of the limits in storage and processing power of their existing Oracle relational database. We investigated the usability and performance of non-relational storage together with its distributed data processing capabilities. For this, several popular systems have been compared. In this contribution we describe our investigation of the existing non-relational databases suited for monitoring systems covering Cassandra, HBase and MongoDB. Further, we present our experiences in data modeling and prototyping map-reduce algorithms focusing on the extension of the already existing availability and reliability computations. Finally, possible future directions in this area are discussed, analyzing the current deficiencies of the existing Grid monitoring systems and proposing solutions to leverage the benefits of the non-relational databases to get more scalable and flexible frameworks.

Continuous gravimetric monitoring as an integrative tool for exploring hydrological processes in the Lomme Karst System (Belgium)

NASA Astrophysics Data System (ADS)

Watlet, A.; Van Camp, M. J.; Poulain, A.; Hallet, V.; Rochez, G.; Quinif, Y.; Meus, P.; Kaufmann, O.; Francis, O.

2016-12-01

Karst systems are highly heterogeneous which makes their hydrology difficult to understand. Geophysical techniques offer non-invasive and integrative methods that help interpreting such systems as a whole. Among these techniques, gravimetry has been increasingly used in the last decade to characterize the hydrological behavior of complex systems, e.g. karst environments or volcanoes. We present a continuous microgravimetric monitoring of 3 years in the karstic area of Rochefort (Belgium), that shows multiple occurrences of caves and karstic features. The gravity record includes measurements of a GWR superconducting gravimeter, a Micro-g LaCoste gPhone and an absolute FG5 gravimeter. Together with meteorological measurements and a surface/in-cave hydrogeological monitoring, we were able to improve the knowledge of hydrological processes. On the one hand, the data allowed identifying seasonal groundwater content changes in the unsaturated zone of the karst area, most likely to be linked to temporary groundwater storage occurring in the most karstified layers closed to the surface. Combined with additional geological information, modelling of the gravity signal based on the vertical potential of the gravitational attraction was then particularly useful to estimate the seasonal recharge leading to the temporary subsurface groundwater storage. On the other hand, the gravity monitoring of flash floods occurring in deeper layers after intense rainfall events informed on the effective porosity gradient of the limestones. Modelling was then helpful to identify the hydrogeological role played by the cave galleries with respect to the hosting limestones during flash floods. These results are also compared with measurements of an in-cave gravimetric monitoring performed with a gPhone spring gravimeter. An Electrical Resistivity Tomography monitoring is also conducted at site and brings additional information useful to verify the interpretation made with the gravimetric monitoring.

A vehicle health monitoring system for the Space Shuttle Reaction Control System during reentry. M.S. Thesis - Massachusetts Inst. of Technology

NASA Technical Reports Server (NTRS)

Rosello, Anthony David

1995-01-01

A general two tier framework for vehicle health monitoring of Guidance Navigation and Control (GN&C) system actuators, effectors, and propulsion devices is presented. In this context, a top level monitor that estimates jet thrust is designed for the Space Shuttle Reaction Control System (RCS) during the reentry phase of flight. Issues of importance for the use of estimation technologies in vehicle health monitoring are investigated and quantified for the Shuttle RCS demonstration application. These issues include rate of convergence, robustness to unmodeled dynamics, sensor quality, sensor data rates, and information recording objectives. Closed loop simulations indicate that a Kalman filter design is sensitive to modeling error and robust estimators may reduce this sensitivity. Jet plume interaction with the aerodynamic flowfield is shown to be a significant effect adversely impacting the ability to accurately estimate thrust.

Is comprehension necessary for error detection? A conflict-based account of monitoring in speech production

PubMed Central

Nozari, Nazbanou; Dell, Gary S.; Schwartz, Myrna F.

2011-01-01

Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the double dissociation between comprehension and error-detection ability observed in the aphasic patients. We propose a new theory of speech-error detection which is instead based on the production process itself. The theory borrows from studies of forced-choice-response tasks the notion that error detection is accomplished by monitoring response conflict via a frontal brain structure, such as the anterior cingulate cortex. We adapt this idea to the two-step model of word production, and test the model-derived predictions on a sample of aphasic patients. Our results show a strong correlation between patients’ error-detection ability and the model’s characterization of their production skills, and no significant correlation between error detection and comprehension measures, thus supporting a production-based monitor, generally, and the implemented conflict-based monitor in particular. The successful application of the conflict-based theory to error-detection in linguistic, as well as non-linguistic domains points to a domain-general monitoring system. PMID:21652015

Ascertainment-adjusted parameter estimation approach to improve robustness against misspecification of health monitoring methods

NASA Astrophysics Data System (ADS)

Juesas, P.; Ramasso, E.

2016-12-01

Condition monitoring aims at ensuring system safety which is a fundamental requirement for industrial applications and that has become an inescapable social demand. This objective is attained by instrumenting the system and developing data analytics methods such as statistical models able to turn data into relevant knowledge. One difficulty is to be able to correctly estimate the parameters of those methods based on time-series data. This paper suggests the use of the Weighted Distribution Theory together with the Expectation-Maximization algorithm to improve parameter estimation in statistical models with latent variables with an application to health monotonic under uncertainty. The improvement of estimates is made possible by incorporating uncertain and possibly noisy prior knowledge on latent variables in a sound manner. The latent variables are exploited to build a degradation model of dynamical system represented as a sequence of discrete states. Examples on Gaussian Mixture Models, Hidden Markov Models (HMM) with discrete and continuous outputs are presented on both simulated data and benchmarks using the turbofan engine datasets. A focus on the application of a discrete HMM to health monitoring under uncertainty allows to emphasize the interest of the proposed approach in presence of different operating conditions and fault modes. It is shown that the proposed model depicts high robustness in presence of noisy and uncertain prior.

The Cloud2SM Project

NASA Astrophysics Data System (ADS)

Crinière, Antoine; Dumoulin, Jean; Mevel, Laurent; Andrade-Barosso, Guillermo; Simonin, Matthieu

2015-04-01

From the past decades the monitoring of civil engineering structure became a major field of research and development process in the domains of modelling and integrated instrumentation. This increasing of interest can be attributed in part to the need of controlling the aging of such structures and on the other hand to the need to optimize maintenance costs. From this standpoint the project Cloud2SM (Cloud architecture design for Structural Monitoring with in-line Sensors and Models tasking), has been launched to develop a robust information system able to assess the long term monitoring of civil engineering structures as well as interfacing various sensors and data. The specificity of such architecture is to be based on the notion of data processing through physical or statistical models. Thus the data processing, whether material or mathematical, can be seen here as a resource of the main architecture. The project can be divided in various items: -The sensors and their measurement process: Those items provide data to the main architecture and can embed storage or computational resources. Dependent of onboard capacity and the amount of data generated it can be distinguished heavy and light sensors. - The storage resources: Based on the cloud concept this resource can store at least two types of data, raw data and processed ones. - The computational resources: This item includes embedded "pseudo real time" resources as the dedicated computer cluster or computational resources. - The models: Used for the conversion of raw data to meaningful data. Those types of resources inform the system of their needs they can be seen as independents blocks of the system. - The user interface: This item can be divided in various HMI to assess maintaining operation on the sensors or pop-up some information to the user. - The demonstrators: The structures themselves. This project follows previous research works initiated in the European project ISTIMES [1]. It includes the infrared thermal monitoring of civil engineering structures [2-3] and/or the vibration monitoring of such structures [4-5]. The chosen architecture is based on the OGC standard in order to ensure the interoperability between the various measurement systems. This concept is extended to the notion of physical models. The last but not the least main objective of this project is to explore the feasibility and the reliability to deploy mathematical models and process a large amount of data using the GPGPU capacity of a dedicated computational cluster, while studying OGC standardization to those technical concepts. References [1] M. Proto et al., « Transport Infrastructure surveillance and Monitoring by Electromagnetic Sensing: the ISTIMES project », Journal Sensors, Sensors 2010, 10(12), 10620-10639; doi:10.3390/s101210620, December 2010. [2] J. Dumoulin, A. Crinière, R. Averty ," Detection and thermal characterization of the inner structure of the "Musmeci" bridge deck by infrared thermography monitoring ",Journal of Geophysics and Engineering, Volume 10, Number 2, 17 pages ,November 2013, IOP Science, doi:10.1088/1742-2132/10/6/064003. [3] J Dumoulin and V Boucher; "Infrared thermography system for transport infrastructures survey with inline local atmospheric parameter measurements and offline model for radiation attenuation evaluations," J. Appl. Remote Sens., 8(1), 084978 (2014). doi:10.1117/1.JRS.8.084978. [4] V. Le Cam, M. Doehler, M. Le Pen, L. Mevel. "Embedded modal analysis algorithms on the smart wireless sensor platform PEGASE", In Proc. 9th International Workshop on Structural Health Monitoring, Stanford, CA, USA, 2013. [5] M. Zghal, L. Mevel, P. Del Moral, "Modal parameter estimation using interacting Kalman filter", Mechanical Systems and Signal Processing, 2014.

Combining model based and data based techniques in a robust bridge health monitoring algorithm.

DOT National Transportation Integrated Search

2014-09-01

Structural Health Monitoring (SHM) aims to analyze civil, mechanical and aerospace systems in order to assess : incipient damage occurrence. In this project, we are concerned with the development of an algorithm within the : SHM paradigm for applicat...

Strategies for Teaching Internet Ethics.

ERIC Educational Resources Information Center

Rader, Martha H.

2002-01-01

Ten strategies for teaching Internet ethics are as follows: establish acceptable use policy; communicate ethical codes; model behaviors and values; encourage discussion of ethical issues; reinforce ethical conduct; monitor student behavior; secure systems and software; discourage surfing without supervision; monitor e-mail and websites; and…

Improving catchment scale water quality modelling with continuous high resolution monitoring of metals in runoff

NASA Astrophysics Data System (ADS)

Saari, Markus; Rossi, Pekka; Blomberg von der Geest, Kalle; Mäkinen, Ari; Postila, Heini; Marttila, Hannu

2017-04-01

High metal concentrations in natural waters is one of the key environmental and health problems globally. Continuous in-situ analysis of metals from runoff water is technically challenging but essential for the better understanding of processes which lead to pollutant transport. Currently, typical analytical methods for monitoring elements in liquids are off-line laboratory methods such as ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) and ICP-MS (ICP combined with a mass spectrometer). Disadvantage of the both techniques is time consuming sample collection, preparation, and off-line analysis at laboratory conditions. Thus use of these techniques lack possibility for real-time monitoring of element transport. We combined a novel high resolution on-line metal concentration monitoring with catchment scale physical hydrological modelling in Mustijoki river in Southern Finland in order to study dynamics of processes and form a predictive warning system for leaching of metals. A novel on-line measurement technique based on micro plasma emission spectroscopy (MPES) is tested for on-line detection of selected elements (e.g. Na, Mg, Al, K, Ca, Fe, Ni, Cu, Cd and Pb) in runoff waters. The preliminary results indicate that MPES can sufficiently detect and monitor metal concentrations from river water. Water and Soil Assessment Tool (SWAT) catchment scale model was further calibrated with high resolution metal concentration data. We show that by combining high resolution monitoring and catchment scale physical based modelling, further process studies and creation of early warning systems, for example to optimization of drinking water uptake from rivers, can be achieved.

FT-IR/ATR univariate and multivariate calibration models for in situ monitoring of sugars in complex microalgal culture media.

PubMed

Girard, Jean-Michel; Deschênes, Jean-Sébastien; Tremblay, Réjean; Gagnon, Jonathan

2013-09-01

The objective of this work is to develop a quick and simple method for the in situ monitoring of sugars in biological cultures. A new technology based on Attenuated Total Reflectance-Fourier Transform Infrared (FT-IR/ATR) spectroscopy in combination with an external light guiding fiber probe was tested, first to build predictive models from solutions of pure sugars, and secondly to use those models to monitor the sugars in the complex culture medium of mixotrophic microalgae. Quantification results from the univariate model were correlated with the total dissolved solids content (R(2)=0.74). A vector normalized multivariate model was used to proportionally quantify the different sugars present in the complex culture medium and showed a predictive accuracy of >90% for sugars representing >20% of the total. This method offers an alternative to conventional sugar monitoring assays and could be used at-line or on-line in commercial scale production systems. Copyright © 2013 Elsevier Ltd. All rights reserved.

Real-time monitoring of capacity loss for vanadium redox flow battery

NASA Astrophysics Data System (ADS)

Wei, Zhongbao; Bhattarai, Arjun; Zou, Changfu; Meng, Shujuan; Lim, Tuti Mariana; Skyllas-Kazacos, Maria

2018-06-01

The long-term operation of the vanadium redox flow battery is accompanied by ion diffusion across the separator and side reactions, which can lead to electrolyte imbalance and capacity loss. The accurate online monitoring of capacity loss is therefore valuable for the reliable and efficient operation of vanadium redox flow battery system. In this paper, a model-based online monitoring method is proposed to detect capacity loss in the vanadium redox flow battery in real time. A first-order equivalent circuit model is built to capture the dynamics of the vanadium redox flow battery. The model parameters are online identified from the onboard measureable signals with the recursive least squares, in seeking to keep a high modeling accuracy and robustness under a wide range of working scenarios. Based on the online adapted model, an observer is designed with the extended Kalman Filter to keep tracking both the capacity and state of charge of the battery in real time. Experiments are conducted on a lab-scale battery system. Results suggest that the online adapted model is able to simulate the battery behavior with high accuracy. The capacity loss as well as the state of charge can be estimated accurately in a real-time manner.

A risk-based coverage model for video surveillance camera control optimization

NASA Astrophysics Data System (ADS)

Zhang, Hongzhou; Du, Zhiguo; Zhao, Xingtao; Li, Peiyue; Li, Dehua

2015-12-01

Visual surveillance system for law enforcement or police case investigation is different from traditional application, for it is designed to monitor pedestrians, vehicles or potential accidents. Visual surveillance risk is defined as uncertainty of visual information of targets and events monitored in present work and risk entropy is introduced to modeling the requirement of police surveillance task on quality and quantity of vide information. the prosed coverage model is applied to calculate the preset FoV position of PTZ camera.

Monitoring of injury induced brain regeneration of the adult zebrafish by using optical coherence tomography

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Zhang, Jian

2018-02-01

The adult zebrafish has pronounced regenerative capacity of the brain, which makes it an ideal model organism of vertebrate biology for the investigation of recovery of central nervous system injuries. The aim of this study was to employ spectral-domain optical coherence tomography (SD-OCT) system for long-term in vivo monitoring of tissue regeneration using an adult zebrafish model of brain injury. Based on a 1325 nm light source and two high-speed galvo mirrors, the SD-OCT system can offer a large field of view of the three-dimensional (3D) brain structures with high imaging resolution (12 μm axial and 13 μm lateral) at video rate. In vivo experiments based on this system were conducted to monitor the regeneration process of zebrafish brain after injury during a period of 43 days. To monitor and detect the process of tissue regeneration, we performed 3D in vivo imaging in a zebrafish model of adult brain injury during a period of 43 days. The coronal and sagittal views of the injured zebrafish brain at each time point (0 days, 10 days, 20 days and 43 days postlesion) were presented to show the changes of the brain lesion in detail. In addition, the 3D SD-OCT images for an injured zebrafish brain were also reconstructed at days 0 and days 43 post-lesion. We found that SD-OCT is able to effectively and noninvasively monitor the regeneration of the adult zebrafish brain after injury in real time with high 3D spatial resolution and good penetration depth. Our findings also suggested that the adult zebrafish has the extraordinary capability of brain regeneration and is able to repair itself after brain injury.

Application of a microcomputer-based system to control and monitor bacterial growth.

PubMed

Titus, J A; Luli, G W; Dekleva, M L; Strohl, W R

1984-02-01

A modular microcomputer-based system was developed to control and monitor various modes of bacterial growth. The control system was composed of an Apple II Plus microcomputer with 64-kilobyte random-access memory; a Cyborg ISAAC model 91A multichannel analog-to-digital and digital-to-analog converter; paired MRR-1 pH, pO(2), and foam control units; and in-house-designed relay, servo control, and turbidimetry systems. To demonstrate the flexibility of the system, we grew bacteria under various computer-controlled and monitored modes of growth, including batch, turbidostat, and chemostat systems. The Apple-ISAAC system was programmed in Labsoft BASIC (extended Applesoft) with an average control program using ca. 6 to 8 kilobytes of memory and up to 30 kilobytes for datum arrays. This modular microcomputer-based control system was easily coupled to laboratory scale fermentors for a variety of fermentations.

Application of a Microcomputer-Based System to Control and Monitor Bacterial Growth

PubMed Central

Titus, Jeffrey A.; Luli, Gregory W.; Dekleva, Michael L.; Strohl, William R.

1984-01-01

A modular microcomputer-based system was developed to control and monitor various modes of bacterial growth. The control system was composed of an Apple II Plus microcomputer with 64-kilobyte random-access memory; a Cyborg ISAAC model 91A multichannel analog-to-digital and digital-to-analog converter; paired MRR-1 pH, pO2, and foam control units; and in-house-designed relay, servo control, and turbidimetry systems. To demonstrate the flexibility of the system, we grew bacteria under various computer-controlled and monitored modes of growth, including batch, turbidostat, and chemostat systems. The Apple-ISAAC system was programmed in Labsoft BASIC (extended Applesoft) with an average control program using ca. 6 to 8 kilobytes of memory and up to 30 kilobytes for datum arrays. This modular microcomputer-based control system was easily coupled to laboratory scale fermentors for a variety of fermentations. PMID:16346462

Development of an Intelligent Monitoring and Control System for a Heterogeneous Numerical Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Afjeh, Abdollah A.; Lewandowski, Henry; Homer, Patrick T.; Schlichting, Richard D.

1996-01-01

The NASA Numerical Propulsion System Simulation (NPSS) project is exploring the use of computer simulation to facilitate the design of new jet engines. Several key issues raised in this research are being examined in an NPSS-related research project: zooming, monitoring and control, and support for heterogeneity. The design of a simulation executive that addresses each of these issues is described. In this work, the strategy of zooming, which allows codes that model at different levels of fidelity to be integrated within a single simulation, is applied to the fan component of a turbofan propulsion system. A prototype monitoring and control system has been designed for this simulation to support experimentation with expert system techniques for active control of the simulation. An interconnection system provides a transparent means of connecting the heterogeneous systems that comprise the prototype.

A COMPARISON OF INTERCELL METRICS ON DISCRETE GLOBAL GRID SYSTEMS

EPA Science Inventory

A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate a...

Combining inventories of land cover and forest resources with prediction models and remotely sensed data

Treesearch

Raymond L. Czaplewski

1989-01-01

It is difficult to design systems for national and global resource inventory and analysis that efficiently satisfy changing, and increasingly complex objectives. It is proposed that individual inventory, monitoring, modeling, and remote sensing systems be specialized to achieve portions of the objectives. These separate systems can be statistically linked to accomplish...

Unobtrusive Monitoring of Spaceflight Team Functioning

NASA Technical Reports Server (NTRS)

Maidel, Veronica; Stanton, Jeffrey M.

2010-01-01

This document contains a literature review suggesting that research on industrial performance monitoring has limited value in assessing, understanding, and predicting team functioning in the context of space flight missions. The review indicates that a more relevant area of research explores the effectiveness of teams and how team effectiveness may be predicted through the elicitation of individual and team mental models. Note that the mental models referred to in this literature typically reflect a shared operational understanding of a mission setting such as the cockpit controls and navigational indicators on a flight deck. In principle, however, mental models also exist pertaining to the status of interpersonal relations on a team, collective beliefs about leadership, success in coordination, and other aspects of team behavior and cognition. Pursuing this idea, the second part of this document provides an overview of available off-the-shelf products that might assist in extraction of mental models and elicitation of emotions based on an analysis of communicative texts among mission personnel. The search for text analysis software or tools revealed no available tools to enable extraction of mental models automatically, relying only on collected communication text. Nonetheless, using existing software to analyze how a team is functioning may be relevant for selection or training, when human experts are immediately available to analyze and act on the findings. Alternatively, if output can be sent to the ground periodically and analyzed by experts on the ground, then these software packages might be employed during missions as well. A demonstration of two text analysis software applications is presented. Another possibility explored in this document is the option of collecting biometric and proxemic measures such as keystroke dynamics and interpersonal distance in order to expose various individual or dyadic states that may be indicators or predictors of certain elements of team functioning. This document summarizes interviews conducted with personnel currently involved in observing or monitoring astronauts or who are in charge of technology that allows communication and monitoring. The objective of these interviews was to elicit their perspectives on monitoring team performance during long-duration missions and the feasibility of potential automatic non-obtrusive monitoring systems. Finally, in the last section, the report describes several priority areas for research that can help transform team mental models, biometrics, and/or proxemics into workable systems for unobtrusive monitoring of space flight team effectiveness. Conclusions from this work suggest that unobtrusive monitoring of space flight personnel is likely to be a valuable future tool for assessing team functioning, but that several research gaps must be filled before prototype systems can be developed for this purpose.

Functionality of empirical model-based predictive analytics for the early detection of hemodynamic instabilty.

PubMed

Summers, Richard L; Pipke, Matt; Wegerich, Stephan; Conkright, Gary; Isom, Kristen C

2014-01-01

Background. Monitoring cardiovascular hemodynamics in the modern clinical setting is a major challenge. Increasing amounts of physiologic data must be analyzed and interpreted in the context of the individual patient’s pathology and inherent biologic variability. Certain data-driven analytical methods are currently being explored for smart monitoring of data streams from patients as a first tier automated detection system for clinical deterioration. As a prelude to human clinical trials, an empirical multivariate machine learning method called Similarity-Based Modeling (“SBM”), was tested in an In Silico experiment using data generated with the aid of a detailed computer simulator of human physiology (Quantitative Circulatory Physiology or “QCP”) which contains complex control systems with realistic integrated feedback loops. Methods. SBM is a kernel-based, multivariate machine learning method that that uses monitored clinical information to generate an empirical model of a patient’s physiologic state. This platform allows for the use of predictive analytic techniques to identify early changes in a patient’s condition that are indicative of a state of deterioration or instability. The integrity of the technique was tested through an In Silico experiment using QCP in which the output of computer simulations of a slowly evolving cardiac tamponade resulted in progressive state of cardiovascular decompensation. Simulator outputs for the variables under consideration were generated at a 2-min data rate (0.083Hz) with the tamponade introduced at a point 420 minutes into the simulation sequence. The functionality of the SBM predictive analytics methodology to identify clinical deterioration was compared to the thresholds used by conventional monitoring methods. Results. The SBM modeling method was found to closely track the normal physiologic variation as simulated by QCP. With the slow development of the tamponade, the SBM model are seen to disagree while the simulated biosignals in the early stages of physiologic deterioration and while the variables are still within normal ranges. Thus, the SBM system was found to identify pathophysiologic conditions in a timeframe that would not have been detected in a usual clinical monitoring scenario. Conclusion. In this study the functionality of a multivariate machine learning predictive methodology that that incorporates commonly monitored clinical information was tested using a computer model of human physiology. SBM and predictive analytics were able to differentiate a state of decompensation while the monitored variables were still within normal clinical ranges. This finding suggests that the SBM could provide for early identification of a clinical deterioration using predictive analytic techniques. predictive analytics, hemodynamic, monitoring.

The GEOGLAM Rangelands and Pasture Productivity Activity: Recent Progress and Future Directions

NASA Astrophysics Data System (ADS)

Guerschman, J. P.; Held, A. A.; Donohue, R. J.; Renzullo, L. J.; Sims, N.; Kerblat, F.; Grundy, M.

2015-12-01

Rangelands and pastures cover about a third of the world's land area and support livestock production which represents ~40% of global agricultural gross domestic product. The global consumption of animal protein shows a clear increasing trend, driven by both total population and per capita income increases, putting a growing pressure on the sustainability of grazing lands worldwide. Despite their relevance, rangelands have received less attention than croplands regarding global monitoring of the resource productivity and condition. The Rangelands and Pasture Productivity (RaPP) activity is a component within the Global Agricultural Monitoring initiative established under the Group on Earth Observations (GEOGLAM) in 2013. GEOGLAM RaPP is aimed at providing the global community with the means to monitor the world's rangelands and pastures on a routine basis, and the capacity to produce animal protein in real-time, at global, regional and national levels. Since its launch two years ago GEOGLAM RAPP has made progress in the four implementation elements. These include: 1- the establishment of community of practice; 2- the development of a global monitoring system for rangeland condition; 3- the establishment of pilot sites in main rangeland systems for satellite data products validation and model testing; and 4- integration with livestock production models. Three international workshops have been held building the community of practice. A prototype monitoring system that provides global visualisations and querying capability of vegetation cover data and anomalies has been established. Pilot sites, mostly in areas with long records of field measurements of rangeland condition and productivity have been proposed for nine countries. The link to global livestock models, including physical and economic components, have been established. Future challenges for GEOGLAM RaPP have also been identified and include: better representation of the areas occupied by rangelands, pastures and mixed systems globally; intercomparison and validation of satellite data products and models depicting rangeland condition and forage availability; and better understanding of the environmental and social impacts of the potential use of pastures for biofuel production.

TPS In-Flight Health Monitoring Project Progress Report

NASA Technical Reports Server (NTRS)

Kostyk, Chris; Richards, Lance; Hudston, Larry; Prosser, William

2007-01-01

Progress in the development of new thermal protection systems (TPS) is reported. New approaches use embedded lightweight, sensitive, fiber optic strain and temperature sensors within the TPS. Goals of the program are to develop and demonstrate a prototype TPS health monitoring system, develop a thermal-based damage detection algorithm, characterize limits of sensor/system performance, and develop ea methodology transferable to new designs of TPS health monitoring systems. Tasks completed during the project helped establish confidence in understanding of both test setup and the model and validated system/sensor performance in a simple TPS structure. Other progress included complete initial system testing, commencement of the algorithm development effort, generation of a damaged thermal response characteristics database, initial development of a test plan for integration testing of proven FBG sensors in simple TPS structure, and development of partnerships to apply the technology.

Endovascular blood flow measurement system

NASA Astrophysics Data System (ADS)

Khe, A. K.; Cherevko, A. A.; Chupakhin, A. P.; Krivoshapkin, A. L.; Orlov, K. Yu

2016-06-01

In this paper an endovascular measurement system used for intraoperative cerebral blood flow monitoring is described. The system is based on a Volcano ComboMap Pressure and Flow System extended with analogue-to-digital converter and PC laptop. A series of measurements performed in patients with cerebrovascular pathologies allows us to introduce “velocity-pressure” and “flow rate-energy flow rate” diagrams as important characteristics of the blood flow. The measurement system presented here can be used as an additional instrument in neurosurgery for assessment and monitoring of the operation procedure. Clinical data obtained with the system are used for construction of mathematical models and patient-specific simulations. The monitoring of the blood flow parameters during endovascular interventions was approved by the Ethics Committee at the Meshalkin Novosibirsk Research Institute of Circulation Pathology and included in certain surgical protocols for pre-, intra- and postoperative examinations.

Watershed modeling and monitoring for assessing nutrient ...

EPA Pesticide Factsheets

Presentation for the American Water Works Association Water Sustainability Conference. The presentation highlights latest results from water quality trading research conducted by ORD using the East Fork Watershed in Southwestern Ohio as a case study. The watershed has a nutrient enrichment problem that is creating harmful algal blooms in a reservoir used for drinking water and recreation. Innovative modeling and monitoring is combined to understand how to best manage this water quality problem and costs associated with this endeavor. The presentation will provide an overview of the water quality trading feasibility research. The research includes the development and evaluation of innovative modeling and monitoring approaches to manage watersheds for nutrient pollution using a whole systems approach.

The use of baseline measurements and geophysical models for the estimation of crustal deformations and the terrestrial reference system. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Bock, Y.

1982-01-01

Four possible estimators are investigated for the monitoring of crustal deformations from a combination of repeated baseline length measurements and adopted geophysical models, particularly an absolute motion plate model. The first estimator is an extension of the familiar free adjustment. The next two are Bayesian type estimators, one weak and one strong. Finally, a weighted constraint estimator is presented. The properties of these four estimators are outlined and their physical interpretations discussed. A series of simulations are performed to test the four estimators and to determine whether or not to incorporate a plate model for the monitoring of deformations. The application of these estimations to the maintenance of a new conventional terrestrial reference system is discussed.

Automated biowaste sampling system feces monitoring system

NASA Technical Reports Server (NTRS)

Hunt, S. R.; Glanfield, E. J.

1979-01-01

The Feces Monitoring System (FMS) Program designed, fabricated, assembled and tested an engineering model waste collector system (WCS) to be used in support of life science and medical experiments related to Shuttle missions. The FMS design was patterned closely after the Shuttle WCS, including: interface provisions; mounting; configuration; and operating procedures. These similarities make it possible to eventually substitute an FMS for the Shuttle WCS of Orbiter. In addition, several advanced waste collection features, including the capability of real-time inertial fecal separation and fecal mass measurement and sampling were incorporated into the FMS design.

Multileaf collimator performance monitoring and improvement using semiautomated quality control testing and statistical process control.

PubMed

Létourneau, Daniel; Wang, An; Amin, Md Nurul; Pearce, Jim; McNiven, Andrea; Keller, Harald; Norrlinger, Bernhard; Jaffray, David A

2014-12-01

High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3-4 times/week over a period of 10-11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ± 0.5 and ± 1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. The precision of the MLC performance monitoring QC test and the MLC itself was within ± 0.22 mm for most MLC leaves and the majority of the apparent leaf motion was attributed to beam spot displacements between irradiations. The MLC QC test was performed 193 and 162 times over the monitoring period for the studied units and recalibration had to be repeated up to three times on one of these units. For both units, rate of MLC interlocks was moderately associated with MLC servicing events. The strongest association with the MLC performance was observed between the MLC servicing events and the total number of out-of-control leaves. The average elapsed time for which the number of out-of-specification or out-of-control leaves was within a given performance threshold was computed and used to assess adequacy of MLC test frequency. A MLC performance monitoring system has been developed and implemented to acquire high-quality QC data at high frequency. This is enabled by the relatively short acquisition time for the images and automatic image analysis. The monitoring system was also used to record and track the rate of MLC-related interlocks and servicing events. MLC performances for two commercially available MLC models have been assessed and the results support monthly test frequency for widely accepted ± 1 mm specifications. Higher QC test frequency is however required to maintain tighter specification and in-control behavior.

Systems, methods and computer-readable media to model kinetic performance of rechargeable electrochemical devices

DOEpatents

Gering, Kevin L.

2013-01-01

A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics. The computing system also analyzes the cell information of the electrochemical cell with a Butler-Volmer (BV) expression modified to determine exchange current density of the electrochemical cell by including kinetic performance information related to pulse-time dependence, electrode surface availability, or a combination thereof. A set of sigmoid-based expressions may be included with the modified-BV expression to determine kinetic performance as a function of pulse time. The determined exchange current density may be used with the modified-BV expression, with or without the sigmoid expressions, to analyze other characteristics of the electrochemical cell. Model parameters can be defined in terms of cell aging, making the overall kinetics model amenable to predictive estimates of cell kinetic performance along the aging timeline.

Slurry wall containment performance: monitoring and modeling of unsaturated and saturated flow.

PubMed

Pedretti, Daniele; Masetti, Marco; Marangoni, Tomaso; Beretta, Giovanni Pietro

2012-01-01

A specific 2-year program to monitor and test both the vadose zone and the saturated zone, coupled with a numerical analysis, was performed to evaluate the overall performance of slurry wall systems for containment of contaminated areas. Despite local physical confinement (slurry walls keyed into an average 2-m-thick aquitard), for at least two decades, high concentrations of chlorinated solvents (up to 110 mg l(-1)) have been observed in aquifers that supply drinking water close to the city of Milan (Italy). Results of monitoring and in situ tests have been used to perform an unsaturated-saturated numerical model. These results yielded the necessary quantitative information to be used both for the determination of the hydraulic properties of the different media in the area and for the calibration and validation of the numerical model. Backfill material in the shallower part of the investigated aquifer dramatically affects the natural recharge of the encapsulated area. A transient simulation from wet to drought periods highlights a change in the ratio between leakages from lateral barriers that support a specific scenario of water loss through the containment system. The combination of monitoring and modelling allows a reliable estimate of the overall performance of the physical confinement to be made without using any invasive techniques on slurry wall.

The Global Integrated Drought Monitoring and Prediction System (GIDMaPS): Overview and Capabilities

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Hao, Z.; Farahmand, A.; Nakhjiri, N.

2013-12-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The results indicate that GIDMaPS advances our drought monitoring and prediction capabilities through integration of multiple data and indicators.

Modular biowaste monitoring system

NASA Technical Reports Server (NTRS)

Fogal, G. L.

1975-01-01

The objective of the Modular Biowaste Monitoring System Program was to generate and evaluate hardware for supporting shuttle life science experimental and diagnostic programs. An initial conceptual design effort established requirements and defined an overall modular system for the collection, measurement, sampling and storage of urine and feces biowastes. This conceptual design effort was followed by the design, fabrication and performance evaluation of a flight prototype model urine collection, volume measurement and sampling capability. No operational or performance deficiencies were uncovered as a result of the performance evaluation tests.

Fuzzy intelligent quality monitoring model for X-ray image processing.

PubMed

Khalatbari, Azadeh; Jenab, Kouroush

2009-01-01

Today's imaging diagnosis needs to adapt modern techniques of quality engineering to maintain and improve its accuracy and reliability in health care system. One of the main factors that influences diagnostic accuracy of plain film X-ray on detecting pathology is the level of film exposure. If the level of film exposure is not adequate, a normal body structure may be interpretated as pathology and vice versa. This not only influences the patient management but also has an impact on health care cost and patient's quality of life. Therefore, providing an accurate and high quality image is the first step toward an excellent patient management in any health care system. In this paper, we study these techniques and also present a fuzzy intelligent quality monitoring model, which can be used to keep variables from degrading the image quality. The variables derived from chemical activity, cleaning procedures, maintenance, and monitoring may not be sensed, measured, or calculated precisely due to uncertain situations. Therefore, the gamma-level fuzzy Bayesian model for quality monitoring of an image processing is proposed. In order to apply the Bayesian concept, the fuzzy quality characteristics are assumed as fuzzy random variables. Using the fuzzy quality characteristics, the newly developed model calculates the degradation risk for image processing. A numerical example is also presented to demonstrate the application of the model.

Induction of Inflammation In Vivo by Electrocardiogram Sensor Operation Using Wireless Power Transmission.

PubMed

Heo, Jin-Chul; Kim, Beomjoon; Kim, Yoon-Nyun; Kim, Dae-Kwang; Lee, Jong-Ha

2017-12-14

Prolonged monitoring by cardiac electrocardiogram (ECG) sensors is useful for patients with emergency heart conditions. However, implant monitoring systems are limited by lack of tissue biocompatibility. Here, we developed an implantable ECG sensor for real-time monitoring of ventricular fibrillation and evaluated its biocompatibility using an animal model. The implantable sensor comprised transplant sensors with two electrodes, a wireless power transmission system, and a monitoring system. The sensor was inserted into the subcutaneous tissue of the abdominal area and operated for 1 h/day for 5 days using a wireless power system. Importantly, the sensor was encapsulated by subcutaneous tissue and induced angiogenesis, inflammation, and phagocytosis. In addition, we observed that the levels of inflammation-related markers increased with wireless-powered transmission via the ECG sensor; in particular, levels of the Th-1 cytokine interleukin-12 were significantly increased. The results showed that induced tissue damage was associated with the use of wireless-powered sensors. We also investigated research strategies for the prevention of adverse effects caused by lack of tissue biocompatibility of a wireless-powered ECG monitoring system and provided information on the clinical applications of inflammatory reactions in implant treatment using the wireless-powered transmission system.

A Low-Cost Sensor Buoy System for Monitoring Shallow Marine Environments

PubMed Central

Albaladejo, Cristina; Soto, Fulgencio; Torres, Roque; Sánchez, Pedro; López, Juan A.

2012-01-01

Monitoring of marine ecosystems is essential to identify the parameters that determine their condition. The data derived from the sensors used to monitor them are a fundamental source for the development of mathematical models with which to predict the behaviour of conditions of the water, the sea bed and the living creatures inhabiting it. This paper is intended to explain and illustrate a design and implementation for a new multisensor monitoring buoy system. The system design is based on a number of fundamental requirements that set it apart from other recent proposals: low cost of implementation, the possibility of application in coastal shallow-water marine environments, suitable dimensions for deployment and stability of the sensor system in a shifting environment like the sea bed, and total autonomy of power supply and data recording. The buoy system has successfully performed remote monitoring of temperature and marine pressure (SBE 39 sensor), temperature (MCP9700 sensor) and atmospheric pressure (YOUNG 61302L sensor). The above requirements have been satisfactorily validated by operational trials in a marine environment. The proposed buoy sensor system thus seems to offer a broad range of applications. PMID:23012562

Induction of Inflammation In Vivo by Electrocardiogram Sensor Operation Using Wireless Power Transmission

PubMed Central

Heo, Jin-Chul; Kim, Beomjoon; Kim, Yoon-Nyun; Kim, Dae-Kwang; Lee, Jong-Ha

2017-01-01

Prolonged monitoring by cardiac electrocardiogram (ECG) sensors is useful for patients with emergency heart conditions. However, implant monitoring systems are limited by lack of tissue biocompatibility. Here, we developed an implantable ECG sensor for real-time monitoring of ventricular fibrillation and evaluated its biocompatibility using an animal model. The implantable sensor comprised transplant sensors with two electrodes, a wireless power transmission system, and a monitoring system. The sensor was inserted into the subcutaneous tissue of the abdominal area and operated for 1 h/day for 5 days using a wireless power system. Importantly, the sensor was encapsulated by subcutaneous tissue and induced angiogenesis, inflammation, and phagocytosis. In addition, we observed that the levels of inflammation-related markers increased with wireless-powered transmission via the ECG sensor; in particular, levels of the Th-1 cytokine interleukin-12 were significantly increased. The results showed that induced tissue damage was associated with the use of wireless-powered sensors. We also investigated research strategies for the prevention of adverse effects caused by lack of tissue biocompatibility of a wireless-powered ECG monitoring system and provided information on the clinical applications of inflammatory reactions in implant treatment using the wireless-powered transmission system. PMID:29240666

PLANNING STUDY TO MODEL AND MONITOR COAL PILE RUNOFF. PHASE I

EPA Science Inventory

The report describes a planning study for predicting and monitoring the hydrologic and chemical characteristics of effluent streams resulting from precipitation impacting on open storage of coal. It includes: a survey of utilities on storage habits and treatment systems for coal ...

Numerical Simulation of Borehole Flow in Deep Monitor Wells, Pearl Harbor Aquifer, Oahu, Hawaii

NASA Astrophysics Data System (ADS)

Rotzoll, K.; Oki, D. S.; El-Kadi, A. I.

2010-12-01

Salinity profiles collected from uncased deep monitor wells are commonly used to monitor freshwater-lens thickness in coastal aquifers. However, vertical flow in these wells can cause the measured salinity to differ from salinity in the adjacent aquifer. Substantial borehole flow has been observed in uncased wells in the Pearl Harbor aquifer, Oahu, Hawaii. A numerical modeling approach, incorporating aquifer hydraulic characteristics and recharge rates representative of the Pearl Harbor aquifer, was used to evaluate the effects of borehole flow on measured salinity profiles from deep monitor wells. Borehole flow caused by vertical hydraulic gradients associated with the natural regional groundwater-flow system and local groundwater withdrawals was simulated. Model results were used to estimate differences between vertical salinity profiles in deep monitor wells and the adjacent aquifer in areas of downward, horizontal, and upward flow within the regional flow system—for cases with and without nearby pumped wells. Aquifer heterogeneity, represented in the model as layers of contrasting permeability, was incorporated in model scenarios. Results from this study provide insight into the magnitude of the differences between vertical salinity profiles from deep monitor wells and the salinity distributions in the aquifers. These insights are relevant and are critically needed for management and predictive modeling purposes.

Towards a machine learning framework for acquiring and exploiting monitoring and diagnostic knowledge

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug; Kulkarni, Deepak

1993-01-01

In this paper we address the problem of detecting and diagnosing faults in physical systems, for which neither prior expertise for the task nor suitable system models are available. We propose an architecture that integrates the on-line acquisition and exploitation of monitoring and diagnostic knowledge. The focus of the paper is on the component of the architecture that discovers classes of behaviors with similar characteristics by observing a system in operation. We investigate a characterization of behaviors based on best fitting approximation models. An experimental prototype has been implemented to test it. We present preliminary results in diagnosing faults of the Reaction Control System of the Space Shuttle. The merits and limitations of the approach are identified and directions for future work are set.

Real-Time Communication Support for Underwater Acoustic Sensor Networks †.

PubMed

Santos, Rodrigo; Orozco, Javier; Micheletto, Matias; Ochoa, Sergio F; Meseguer, Roc; Millan, Pere; Molina, And Carlos

2017-07-14

Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios.

Real-Time Communication Support for Underwater Acoustic Sensor Networks †

PubMed Central

Santos, Rodrigo; Orozco, Javier; Micheletto, Matias

2017-01-01

Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios. PMID:28708093

Effects of a mobility monitoring system on the cost of care in relation to reimbursement at Swiss nursing homes: learnings from a randomized controlled trial.

PubMed

Stark, Mario; Tietz, Rigo; Gattinger, Heidrun; Hantikainen, Virpi; Ott, Stefan

2017-12-01

Nursing homes in Switzerland are under pressure to efficiently coordinate staff activities to cover their personnel costs under the care financing system. In this study, the use of a mobility monitoring system accompanied with case conferences was investigated in order to improve sleep quality and estimate the cost benefit of this intervention. In an open two-phase randomized controlled trial at three nursing homes, residents with cognitive impairment were randomly assigned to an intervention group and a control group. In the intervention group, a 10-week period of intensive use of the monitoring system and case conferences led by an advanced nurse practitioner (Phase I) was followed by 3 months of reduced use of the monitoring system and case conferences led by an internal registered nurse (Phase II). In the control group, the monitoring system was only used for data acquisition. Nurses reported the activities with a specifically developed tool. Based on the recorded activities, the cost of care was calculated. The correlating reimbursement per patient was calculated from the care levels in the Swiss reimbursement system. Data from 44 residents was included in the analysis with a linear mixed model. Although analysis revealed no statistically significant effects, results indicate that the use of a monitoring system can guide nurses in organizing their tasks to increase effectiveness. Information systems such as the mobility monitor can help to identify single outliers that do not correspond with the overall situation. In the health care system, problematic individual cases can account for a disproportionally high cost levels. It was shown that information systems can have a significant economic impact in the long run. The study is registered at the German Clinical Trials Register under the Nr. DRKS00006829 .

Assessment of the use of space technology in the monitoring of oil spills and ocean pollution: Executive summary

NASA Technical Reports Server (NTRS)

Alvarado, U. R. (Editor)

1980-01-01

The adequacy of current technology in terms of stage of maturity, of sensing, support systems, and information extraction was assessed relative to oil spills, waste pollution, and inputs to pollution trajectory models. Needs for advanced techniques are defined and the characteristics of a future satellite system are determined based on the requirements of U.S. agencies involved in pollution monitoring.

Community-Based ECG Monitoring System for Patients with Cardiovascular Diseases.

PubMed

Lin, Bor-Shyh; Wong, Alice M; Tseng, Kevin C

2016-04-01

This study aims to develop a community-based electrocardiogram (ECG) monitoring system for cardiac outpatients to wirelessly detect heart rate, provide personalized healthcare, and enhance interactive social contact because of the prevalence of deaths from cardiovascular disease and the growing problem of aging in the world. The system not only strengthens the performance of the ECG monitoring system but also emphasizes the ergonomic design of wearable devices and user interfaces. In addition, it enables medical professionals to diagnose cardiac symptoms remotely and electronically manage medical reports and suggestions. The experimental result shows high performance of the dry electrode, even in dynamic conditions. The comparison result with different ECG healthcare systems shows the essential factors that the system should possess and the capability of the proposed system. Finally, a user survey was conducted based on the unified theory of acceptance and users of technology (UTAUT) model.

The Development of a Remote Patient Monitoring System using Java-enabled Mobile Phones.

PubMed

Kogure, Y; Matsuoka, H; Kinouchi, Y; Akutagawa, M

2005-01-01

A remote patient monitoring system is described. This system is to monitor information of multiple patients in ICU/CCU via 3G mobile phones. Conventionally, various patient information, such as vital signs, is collected and stored on patient information systems. In proposed system, the patient information is recollected by remote information server, and transported to mobile phones. The server is worked as a gateway between hospital intranet and public networks. Provided information from the server consists of graphs and text data. Doctors can browse patient's information on their mobile phones via the server. A custom Java application software is used to browse these data. In this study, the information server and Java application are developed, and communication between the server and mobile phone in model environment is confirmed. To apply this system to practical products of patient information systems is future work.

Model My Watershed: A high-performance cloud application for public engagement, watershed modeling and conservation decision support

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Tarboton, D. G.; Horsburgh, J. S.; Mayorga, E.; McFarland, M.; Robbins, A.; Haag, S.; Shokoufandeh, A.; Evans, B. M.; Arscott, D. B.

2017-12-01

The Model My Watershed Web app (https://app.wikiwatershed.org/) and the BiG-CZ Data Portal (http://portal.bigcz.org/) and are web applications that share a common codebase and a common goal to deliver high-performance discovery, visualization and analysis of geospatial data in an intuitive user interface in web browser. Model My Watershed (MMW) was designed as a decision support system for watershed conservation implementation. BiG CZ Data Portal was designed to provide context and background data for research sites. Users begin by creating an Area of Interest, via an automated watershed delineation tool, a free draw tool, selection of a predefined area such as a county or USGS Hydrological Unit (HUC), or uploading a custom polygon. Both Web apps visualize and provide summary statistics of land use, soil groups, streams, climate and other geospatial information. MMW then allows users to run a watershed model to simulate different scenarios of human impacts on stormwater runoff and water-quality. BiG CZ Data Portal allows users to search for scientific and monitoring data within the Area of Interest, which also serves as a prototype for the upcoming Monitor My Watershed web app. Both systems integrate with CUAHSI cyberinfrastructure, including visualizing observational data from CUAHSI Water Data Center and storing user data via CUAHSI HydroShare. Both systems also integrate with the new EnviroDIY Water Quality Data Portal (http://data.envirodiy.org/), a system for crowd-sourcing environmental monitoring data using open-source sensor stations (http://envirodiy.org/mayfly/) and based on the Observations Data Model v2.

Utilizing Time Domain Reflectometry on monitoring bedload in a mountain stream

NASA Astrophysics Data System (ADS)

Miyata, S.; Fujita, M.

2015-12-01

Understanding bedload transport processes in steep mountain streams is essential for disaster mitigation as well as predicting reservoir capacity and restoration of river ecosystem. Despite various monitoring methods proposed previously, precise bedload monitoring in steep streams still remains difficulty. This study aimed to develop a bedload monitoring system by continuous measurement of thickness and porosity of sediment under water that can be applicable to retention basins and pools in steep streams. When a probe of TDR (Time Domain Reflectometry) measurement system is inserted as to penetrate two adjacent layers with different dielectric constants, analysis of TDR waveform enables us to determine position of the layer boundary and ratio of materials in the layer. Methodology of analyzing observed TDR waveforms were established based on results of a series of column experiment, in which a single TDR probe with length of 40 cm was installed in a column filled with water and, then, sand was supplied gradually. Flume experiment was performed to apply the TDR system on monitoring sediment volume under flowing water conditions. Eight probes with lengths of 27 cm were distributed equally in a model retention basin (i.e., container), into which water and bedload were flowed from a connected flume. The model retention basin was weighed by a load cell and the sediment volume was calculated. A semi-automatic waveform analysis was developed to calculate continuously thicknesses and porosities of the sediment at the eight probes. Relative errors of sediment volume and bedload (=time differential of the volume) were 13 % at maximum, suggesting that the TDR system proposed in this study with multiple probes is applicable to bedload monitoring in retention basins of steep streams. Combination of this system and other indirect bedload monitoring method (e.g., geophone) potentially make a breakthrough for understanding sediment transport processes in steep mountain streams.

A Hybrid Numerical Analysis Method for Structural Health Monitoring

NASA Technical Reports Server (NTRS)

Forth, Scott C.; Staroselsky, Alexander

2001-01-01

A new hybrid surface-integral-finite-element numerical scheme has been developed to model a three-dimensional crack propagating through a thin, multi-layered coating. The finite element method was used to model the physical state of the coating (far field), and the surface integral method was used to model the fatigue crack growth. The two formulations are coupled through the need to satisfy boundary conditions on the crack surface and the external boundary. The coupling is sufficiently weak that the surface integral mesh of the crack surface and the finite element mesh of the uncracked volume can be set up independently. Thus when modeling crack growth, the finite element mesh can remain fixed for the duration of the simulation as the crack mesh is advanced. This method was implemented to evaluate the feasibility of fabricating a structural health monitoring system for real-time detection of surface cracks propagating in engine components. In this work, the authors formulate the hybrid surface-integral-finite-element method and discuss the mechanical issues of implementing a structural health monitoring system in an aircraft engine environment.

Cider fermentation process monitoring by Vis-NIR sensor system and chemometrics.

PubMed

Villar, Alberto; Vadillo, Julen; Santos, Jose I; Gorritxategi, Eneko; Mabe, Jon; Arnaiz, Aitor; Fernández, Luis A

2017-04-15

Optimization of a multivariate calibration process has been undertaken for a Visible-Near Infrared (400-1100nm) sensor system, applied in the monitoring of the fermentation process of the cider produced in the Basque Country (Spain). The main parameters that were monitored included alcoholic proof, l-lactic acid content, glucose+fructose and acetic acid content. The multivariate calibration was carried out using a combination of different variable selection techniques and the most suitable pre-processing strategies were selected based on the spectra characteristics obtained by the sensor system. The variable selection techniques studied in this work include Martens Uncertainty test, interval Partial Least Square Regression (iPLS) and Genetic Algorithm (GA). This procedure arises from the need to improve the calibration models prediction ability for cider monitoring. Copyright © 2016 Elsevier Ltd. All rights reserved.

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

2014-01-01

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

NASA Technical Reports Server (NTRS)

Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

1992-01-01

In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

Syndromic surveillance for health information system failures: a feasibility study.

PubMed

Ong, Mei-Sing; Magrabi, Farah; Coiera, Enrico

2013-05-01

To explore the applicability of a syndromic surveillance method to the early detection of health information technology (HIT) system failures. A syndromic surveillance system was developed to monitor a laboratory information system at a tertiary hospital. Four indices were monitored: (1) total laboratory records being created; (2) total records with missing results; (3) average serum potassium results; and (4) total duplicated tests on a patient. The goal was to detect HIT system failures causing: data loss at the record level; data loss at the field level; erroneous data; and unintended duplication of data. Time-series models of the indices were constructed, and statistical process control charts were used to detect unexpected behaviors. The ability of the models to detect HIT system failures was evaluated using simulated failures, each lasting for 24 h, with error rates ranging from 1% to 35%. In detecting data loss at the record level, the model achieved a sensitivity of 0.26 when the simulated error rate was 1%, while maintaining a specificity of 0.98. Detection performance improved with increasing error rates, achieving a perfect sensitivity when the error rate was 35%. In the detection of missing results, erroneous serum potassium results and unintended repetition of tests, perfect sensitivity was attained when the error rate was as small as 5%. Decreasing the error rate to 1% resulted in a drop in sensitivity to 0.65-0.85. Syndromic surveillance methods can potentially be applied to monitor HIT systems, to facilitate the early detection of failures.

Use of Synchronized Phasor Measurements for Model Validation in ERCOT

NASA Astrophysics Data System (ADS)

Nuthalapati, Sarma; Chen, Jian; Shrestha, Prakash; Huang, Shun-Hsien; Adams, John; Obadina, Diran; Mortensen, Tim; Blevins, Bill

2013-05-01

This paper discusses experiences in the use of synchronized phasor measurement technology in Electric Reliability Council of Texas (ERCOT) interconnection, USA. Implementation of synchronized phasor measurement technology in the region is a collaborative effort involving ERCOT, ONCOR, AEP, SHARYLAND, EPG, CCET, and UT-Arlington. As several phasor measurement units (PMU) have been installed in ERCOT grid in recent years, phasor data with the resolution of 30 samples per second is being used to monitor power system status and record system events. Post-event analyses using recorded phasor data have successfully verified ERCOT dynamic stability simulation studies. Real time monitoring software "RTDMS"® enables ERCOT to analyze small signal stability conditions by monitoring the phase angles and oscillations. The recorded phasor data enables ERCOT to validate the existing dynamic models of conventional and/or wind generator.

Research-Based Monitoring, Prediction, and Analysis Tools of the Spacecraft Charging Environment for Spacecraft Users

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Kuznetsova, Maria M.; Pulkkinen, Antti A.; Maddox, Marlo M.; Mays, Mona Leila

2015-01-01

The Space Weather Research Center (http://swrc. gsfc.nasa.gov) at NASA Goddard, part of the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov), is committed to providing research-based forecasts and notifications to address NASA's space weather needs, in addition to its critical role in space weather education. It provides a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, and weekly summaries and reports. In this paper, we focus on how (near) real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the integrated Space Weather Analysis system (http://iswa.gsfc.nasa.gov), enable monitoring, analyzing, and predicting the spacecraft charging environment for spacecraft users. Relevant tools and resources are discussed.

An overview of crop growing condition monitoring in China agriculture remote sensing monitoring system

NASA Astrophysics Data System (ADS)

Huang, Qing; Zhou, Qing-bo; Zhang, Li

2009-07-01

China is a large agricultural country. To understand the agricultural production condition timely and accurately is related to government decision-making, agricultural production management and the general public concern. China Agriculture Remote Sensing Monitoring System (CHARMS) can monitor crop acreage changes, crop growing condition, agriculture disaster (drought, floods, frost damage, pest etc.) and predict crop yield etc. quickly and timely. The basic principles, methods and regular operation of crop growing condition monitoring in CHARMS are introduced in detail in the paper. CHARMS can monitor crop growing condition of wheat, corn, cotton, soybean and paddy rice with MODIS data. An improved NDVI difference model was used in crop growing condition monitoring in CHARMS. Firstly, MODIS data of every day were received and processed, and the max NDVI values of every fifteen days of main crop were generated, then, in order to assessment a certain crop growing condition in certain period (every fifteen days, mostly), the system compare the remote sensing index data (NDVI) of a certain period with the data of the period in the history (last five year, mostly), the difference between NDVI can indicate the spatial difference of crop growing condition at a certain period. Moreover, Meteorological data of temperature, precipitation and sunshine etc. as well as the field investigation data of 200 network counties were used to modify the models parameters. Last, crop growing condition was assessment at four different scales of counties, provinces, main producing areas and nation and spatial distribution maps of crop growing condition were also created.

Research Area 3: Mathematics (3.1 Modeling of Complex Systems)

DTIC Science & Technology

2017-10-31

RESEARCH AREA 3: MATHEMATICS (3.1 Modeling of Complex Systems). Proposal should be directed to Dr. John Lavery The views, opinions and/or findings...so designated by other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research ...Title: RESEARCH AREA 3: MATHEMATICS (3.1 Modeling of Complex Systems). Proposal should be directed to Dr. John Lavery Report Term: 0-Other Email

The Croton-Yorktown Model of Individualized Earth Science.

ERIC Educational Resources Information Center

Matthias, George F.; Snyder, Edward B.

1980-01-01

The individualized learning model, discussed in this article, uses an efficient feedback mechanism which incorporates an innovative student evaluation program and a unique system of classroom management. The design provides a model for monitoring student progress. (Author/SA)

Africa-wide monitoring of small surface water bodies using multisource satellite data: a monitoring system for FEWS NET: chapter 5

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.; Rowland, James; Verdin, James P.; Alemu, Henok; Melesse, Assefa M.; Abtew, Wossenu; Setegn, Shimelis G.

2014-01-01

Continental Africa has the highest volume of water stored in wetlands, large lakes, reservoirs, and rivers, yet it suffers from problems such as water availability and access. With climate change intensifying the hydrologic cycle and altering the distribution and frequency of rainfall, the problem of water availability and access will increase further. Famine Early Warning Systems Network (FEWS NET) funded by the United States Agency for International Development (USAID) has initiated a large-scale project to monitor small to medium surface water points in Africa. Under this project, multisource satellite data and hydrologic modeling techniques are integrated to monitor several hundreds of small to medium surface water points in Africa. This approach has been already tested to operationally monitor 41 water points in East Africa. The validation of modeled scaled depths with field-installed gauge data demonstrated the ability of the model to capture both the spatial patterns and seasonal variations. Modeled scaled estimates captured up to 60 % of the observed gauge variability with a mean root-mean-square error (RMSE) of 22 %. The data on relative water level, precipitation, and evapotranspiration (ETo) for water points in East and West Africa were modeled since 1998 and current information is being made available in near-real time. This chapter presents the approach, results from the East African study, and the first phase of expansion activities in the West Africa region. The water point monitoring network will be further expanded to cover much of sub-Saharan Africa. The goal of this study is to provide timely information on the water availability that would support already established FEWS NET activities in Africa. This chapter also presents the potential improvements in modeling approach to be implemented during future expansion in Africa.

Investigation of a mathematical model of the system of electro-optical sensors for monitoring nonlinear surfaces

NASA Astrophysics Data System (ADS)

Petrochenko, Andrew V.; Konyakhin, Igor A.

2015-06-01

Actually during construction of the high building actively are used objects of various nonlinear surface, for example, sinuous (parabolic or hyperbolic) roofs of the sport complexes that require automatic deformation control [1,2,3,4]. This type of deformation has character of deflection that is impossible to monitor objectively with just one optoelectronic sensor (which is fixed on this surface). In this article is described structure of remote optoelectronic sensor, which is part of the optoelectronic monitoring system of nonlinear surface, and mathematical transformation of exterior orientation sensor elements in the coordinates of control points.

Modeling of flow systems for implementation under KATE

NASA Technical Reports Server (NTRS)

Whitlow, Jonathan E.

1990-01-01

The modeling of flow systems is a task currently being investigated at Kennedy Space Center in parallel with the development of the KATE artificial intelligence system used for monitoring diagnosis and control. Various aspects of the modeling issues are focussed on with particular emphasis on a water system scheduled for demonstration within the KATE environment in September of this year. LISP procedures were written to solve the continuity equations for three internal pressure nodes using Newton's method for simultaneous nonlinear equations.

Modeling of Revitalization of Atmospheric Water

NASA Technical Reports Server (NTRS)

Coker, Robert; Knox, Jim

2014-01-01

The Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project was initiated in September of 2011 as part of the Advanced Exploration Systems (AES) program. Under the ARREM project, testing of sub-scale and full-scale systems has been combined with multiphysics computer simulations for evaluation and optimization of subsystem approaches. In particular, this paper describes the testing and modeling of the water desiccant subsystem of the carbon dioxide removal assembly (CDRA). The goal is a full system predictive model of CDRA to guide system optimization and development.

Software for occupational health and safety risk analysis based on a fuzzy model.

PubMed

Stefanovic, Miladin; Tadic, Danijela; Djapan, Marko; Macuzic, Ivan

2012-01-01

Risk and safety management are very important issues in healthcare systems. Those are complex systems with many entities, hazards and uncertainties. In such an environment, it is very hard to introduce a system for evaluating and simulating significant hazards. In this paper, we analyzed different types of hazards in healthcare systems and we introduced a new fuzzy model for evaluating and ranking hazards. Finally, we presented a developed software solution, based on the suggested fuzzy model for evaluating and monitoring risk.

Specification and simulation of behavior of the Continuous Infusion Insulin Pump system.

PubMed

Babamir, Seyed Morteza; Dehkordi, Mehdi Borhani

2014-01-01

Continuous Infusion Insulin Pump (CIIP) system is responsible for monitoring diabetic blood sugar. In this paper, we aim to specify and simulate the CIIP software behavior. To this end, we first: (1) presented a model consisting of the CIIP system behavior in response to its environment (diabetic) behavior and (2) we formally defined the safety requirements of the system environment (diabetic) in the Z formal modeling language. Such requirements should be satisfied by the CIIP software. Finally, we programmed the model and requirements.

Active damage interrogation system for structural health monitoring

NASA Astrophysics Data System (ADS)

Lichtenwalner, Peter F.; Dunne, James P.; Becker, Ronald S.; Baumann, Erwin W.

1997-05-01

An integrated and automated smart structures approach for in situ damage assessment has been implemented and evaluated in a laboratory environment for health monitoring of a realistic aerospace structural component. This approach, called Active Damage Interrogation (ADI), utilizes an array of piezoelectric transducers attached to or embedded within the structure for both actuation and sensing. The ADI system, which is model independent, actively interrogates the structure through broadband excitation of multiple actuators across the desired frequency range. Statistical analysis of the changes in transfer functions between actuator/sensor pairs is used to detect, localize, and assess the severity of damage in the structure. This paper presents the overall concept of the ADI system and provides experimental results of damage assessment studies conducted for a composite structural component of the MD-900 Explorer helicopter rotor system. The potential advantages of this approach include simplicity (no need for a model), sensitivity, and low cost implementation. The results obtained thus far indicate considerably promise for integrated structural health monitoring of aerospace vehicles, leading to the practice of condition-based maintenance and consequent reduction in life cycle costs.

Remote coding scheme based on waveguide Bragg grating in PLC splitter chip for PON monitoring.

PubMed

Zhang, Xuan; Lu, Fengjun; Chen, Si; Zhao, Xingqun; Zhu, Min; Sun, Xiaohan

2016-03-07

A distributing arranged waveguide Bragg gratings (WBGs) in PLC splitter chip based remote coding scheme is proposed and analyzed for passive optical network (PON) monitoring, by which the management system can identify each drop fiber link through the same reflector in the terminal of each optical network unit, even though there exist several equidistant users. The corresponding coding and capacity models are respectively established and investigated so that we can obtain a minimum number of the WBGs needed under the condition of the distributed structure. Signal-to-noise ratio (SNR) model related to the number of equidistant users is also developed to extend the analyses for the overall performance of the system. Simulation results show the proposed scheme is feasible and allow the monitoring of a 64 users PON with SNR range of 7.5~10.6dB. The scheme can solve some of difficulties of construction site at the lower user cost for PON system.

Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan S.; Celaya, Jose Ramon; Biswas, Gautam; Goebel, Kai

2012-01-01

This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.

Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics

PubMed Central

Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna

2011-01-01

A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157

Data Acquisition for Land Subsidence Control

NASA Astrophysics Data System (ADS)

Zhu, Y.; Balke, K.

2009-12-01

For controlling land subsidence caused by groundwater over-exploitation, loading of engineered structures, mining and other anthropogenic activities in this fast changing world, a large variety of different data of various scales of concerning areas are needed for scientific study and administrative operational purposes. The economical, social and environmental impacts of anthropogenic land subsidence have long been recognized by many scientific institutions and management authorities based on results of monitoring and analysis at an interdisciplinary level. The land subsidence information systems composed of the surface and subsurface monitoring nets (monitoring and development wells, GPS stations and other facilities) and local data processing centers as a system management tool in Shanghai City was started with the use of GPS technology to monitor land subsidence in 1998. After years of experiences with a set of initiatives by adopting adequate countermeasures, the particular attention given to new improved methodologies to monitor and model the process of land subsidence in a simple and timely way, this is going to be promoted in the whole Yangtze River Delta region in China, where land subsidence expands in the entire region of urban cluster. The Delta land subsidence monitoring network construction aims to establish an efficient and coordinated water resource management system. The land subsidence monitoring network records "living history" of land subsidence, produces detailed scheduled reports and environmental impact statements. For the different areas with local factors and site characteristics, parallel packages need to be designed for predicting changes, land sensitivity and uncertainty analysis, especially for the risk analysis in the rapid growth of megacities and urban areas. In such cases, the new models with new types of local data and the new ways of data acquisition provide the best information for the decision makers for their mitigating decisions. The problems with outputs to professional and non-professional users, planning vs exploitation conflicts, 3D modeling and visualization are not yet solved due to the complex issues.

42 CFR § 414.1460 - Monitoring and program integrity.

Code of Federal Regulations, 2010 CFR

2017-10-01

... SERVICES (CONTINUED) MEDICARE PROGRAM (CONTINUED) PAYMENT FOR PART B MEDICAL AND OTHER HEALTH SERVICES Merit-Based Incentive Payment System and Alternative Payment Model Incentive § 414.1460 Monitoring and program integrity. (a) Vetting eligible clinicians prior to payment of the APM Incentive Payment. Prior to...

76 FR 59425 - Notice of Lodging of Consent Decree Under The Clean Air Act

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-26

... and collection systems, to correctly establish and monitor operating parameters, and to comply with... using model test protocols, adopt new monitoring practices, correct deficiencies in recordkeeping and... Environmental Protection Agency, Ariel Rios Building, 1200 Pennsylvania Avenue, NW., Washington, DC 20460...

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

Exploiting Analytics Techniques in CMS Computing Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bonacorsi, D.; Kuznetsov, V.; Magini, N.

The CMS experiment has collected an enormous volume of metadata about its computing operations in its monitoring systems, describing its experience in operating all of the CMS workflows on all of the Worldwide LHC Computing Grid Tiers. Data mining efforts into all these information have rarely been done, but are of crucial importance for a better understanding of how CMS did successful operations, and to reach an adequate and adaptive modelling of the CMS operations, in order to allow detailed optimizations and eventually a prediction of system behaviours. These data are now streamed into the CERN Hadoop data cluster formore » further analysis. Specific sets of information (e.g. data on how many replicas of datasets CMS wrote on disks at WLCG Tiers, data on which datasets were primarily requested for analysis, etc) were collected on Hadoop and processed with MapReduce applications profiting of the parallelization on the Hadoop cluster. We present the implementation of new monitoring applications on Hadoop, and discuss the new possibilities in CMS computing monitoring introduced with the ability to quickly process big data sets from mulltiple sources, looking forward to a predictive modeling of the system.« less

Case Studies Comparing System Advisor Model (SAM) Results to Real Performance Data: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blair, N.; Dobos, A.; Sather, N.

2012-06-01

NREL has completed a series of detailed case studies comparing the simulations of the System Advisor Model (SAM) and measured performance data or published performance expectations. These case studies compare PV measured performance data with simulated performance data using appropriate weather data. The measured data sets were primarily taken from NREL onsite PV systems and weather monitoring stations.

Impact of extended monitoring-guided intensive care on outcome after severe traumatic brain injury: A prospective multicentre cohort study (PariS-TBI study).

PubMed

Mateo, Joaquim; Payen, Didier; Ghout, Idir; Vallée, Fabrice; Lescot, Thomas; Welschbillig, Stephane; Tazarourte, Karim; Azouvi, Philippe; Weiss, Jean-Jacques; Aegerter, Philippe; Vigué, Bernard

2017-01-01

We evaluated whether an integrated monitoring with systemic and specific monitoring affect mortality and disability in adults with severe traumatic brain injury (sTBI). Adults with severeTBI (Glasgow Coma Scale [GCS] ≤ 8) admitted alive in intensive care units (ICUs) were prospectively included. Primary endpoints were in-hospital 30-day mortality and extended Glasgow outcome score (GOSE) at 3 years. Association with the intensity of monitoring and outcome was studied by comparing a high level of monitoring (HLM) (systemic and ≥3 specific monitoring) and low level of monitoring (LLM) (systemic and 0-2 specific monitoring) and using inverse probability weighting procedure. 476 patients were included and IPW was used to improve the balance between the two groups of treatments (HLM/LMM). Overall hospital mortality (at 30 days) was 43%, being significantly lower in HLM than LLM group (27% vs. 53%: RR, 1.63: 95% CI: 1.23-2.15). The 14-day hospital mortality was also lower in the HLM group than expected, based upon the CRASH prediction model (35%). At 3 years, disability was not significantly different between the monitoring groups. After adjustment, HLM group improved short-term mortality but did not show any improvement in the 3-year outcome compared with LLM.

IEEE 802.15.4 Frame Aggregation Enhancement to Provide High Performance in Life-Critical Patient Monitoring Systems

PubMed Central

Akbar, Muhammad Sajjad; Yu, Hongnian; Cang, Shuang

2017-01-01

In wireless body area sensor networks (WBASNs), Quality of Service (QoS) provision for patient monitoring systems in terms of time-critical deadlines, high throughput and energy efficiency is a challenging task. The periodic data from these systems generates a large number of small packets in a short time period which needs an efficient channel access mechanism. The IEEE 802.15.4 standard is recommended for low power devices and widely used for many wireless sensor networks applications. It provides a hybrid channel access mechanism at the Media Access Control (MAC) layer which plays a key role in overall successful transmission in WBASNs. There are many WBASN’s MAC protocols that use this hybrid channel access mechanism in variety of sensor applications. However, these protocols are less efficient for patient monitoring systems where life critical data requires limited delay, high throughput and energy efficient communication simultaneously. To address these issues, this paper proposes a frame aggregation scheme by using the aggregated-MAC protocol data unit (A-MPDU) which works with the IEEE 802.15.4 MAC layer. To implement the scheme accurately, we develop a traffic patterns analysis mechanism to understand the requirements of the sensor nodes in patient monitoring systems, then model the channel access to find the performance gap on the basis of obtained requirements, finally propose the design based on the needs of patient monitoring systems. The mechanism is initially verified using numerical modelling and then simulation is conducted using NS2.29, Castalia 3.2 and OMNeT++. The proposed scheme provides the optimal performance considering the required QoS. PMID:28134853

IEEE 802.15.4 Frame Aggregation Enhancement to Provide High Performance in Life-Critical Patient Monitoring Systems.

PubMed

Akbar, Muhammad Sajjad; Yu, Hongnian; Cang, Shuang

2017-01-28

In wireless body area sensor networks (WBASNs), Quality of Service (QoS) provision for patient monitoring systems in terms of time-critical deadlines, high throughput and energy efficiency is a challenging task. The periodic data from these systems generates a large number of small packets in a short time period which needs an efficient channel access mechanism. The IEEE 802.15.4 standard is recommended for low power devices and widely used for many wireless sensor networks applications. It provides a hybrid channel access mechanism at the Media Access Control (MAC) layer which plays a key role in overall successful transmission in WBASNs. There are many WBASN's MAC protocols that use this hybrid channel access mechanism in variety of sensor applications. However, these protocols are less efficient for patient monitoring systems where life critical data requires limited delay, high throughput and energy efficient communication simultaneously. To address these issues, this paper proposes a frame aggregation scheme by using the aggregated-MAC protocol data unit (A-MPDU) which works with the IEEE 802.15.4 MAC layer. To implement the scheme accurately, we develop a traffic patterns analysis mechanism to understand the requirements of the sensor nodes in patient monitoring systems, then model the channel access to find the performance gap on the basis of obtained requirements, finally propose the design based on the needs of patient monitoring systems. The mechanism is initially verified using numerical modelling and then simulation is conducted using NS2.29, Castalia 3.2 and OMNeT++. The proposed scheme provides the optimal performance considering the required QoS.

Monitoring osseointegration and developing intelligent systems (Conference Presentation)

NASA Astrophysics Data System (ADS)

Salvino, Liming W.

2017-05-01

Effective monitoring of structural and biological systems is an extremely important research area that enables technology development for future intelligent devices, platforms, and systems. This presentation provides an overview of research efforts funded by the Office of Naval Research (ONR) to establish structural health monitoring (SHM) methodologies in the human domain. Basic science efforts are needed to utilize SHM sensing, data analysis, modeling, and algorithms to obtain the relevant physiological and biological information for human-specific health and performance conditions. This overview of current research efforts is based on the Monitoring Osseointegrated Prosthesis (MOIP) program. MOIP develops implantable and intelligent prosthetics that are directly anchored to the bone of residual limbs. Through real-time monitoring, sensing, and responding to osseointegration of bones and implants as well as interface conditions and environment, our research program aims to obtain individualized actionable information for implant failure identification, load estimation, infection mitigation and treatment, as well as healing assessment. Looking ahead to achieve ultimate goals of SHM, we seek to expand our research areas to cover monitoring human, biological and engineered systems, as well as human-machine interfaces. Examples of such include 1) brainwave monitoring and neurological control, 2) detecting and evaluating brain injuries, 3) monitoring and maximizing human-technological object teaming, and 4) closed-loop setups in which actions can be triggered automatically based on sensors, actuators, and data signatures. Finally, some ongoing and future collaborations across different disciplines for the development of knowledge automation and intelligent systems will be discussed.

Automated Identification of Volcanic Plumes using the Ozone Monitoring Instrument (OMI)

NASA Astrophysics Data System (ADS)

Flower, V. J. B.; Oommen, T.; Carn, S. A.

2015-12-01

Volcanic eruptions are a global phenomenon which are increasingly impacting human populations due to factors such as the extension of population centres into areas of higher risk, expansion of agricultural sectors to accommodate increased production or the increasing impact of volcanic plumes on air travel. In areas where extensive monitoring is present these impacts can be moderated by ground based monitoring and alert systems, however many volcanoes have little or no monitoring capabilities. In many of these regions volcanic alerts are generated by local communities with limited resources or formal communication systems, however additional eruption alerts can result from chance encounters with passing aircraft. In contrast satellite based remote sensing instruments possess the capability to provide near global daily monitoring, facilitating automated volcanic eruption detection. One such system generates eruption alerts through the detection of thermal anomalies, known as MODVOLC, and is currently operational utilising moderate resolution MODIS satellite data. Within this work we outline a method to distinguish SO2 eruptions from background levels recorded by the Ozone Monitoring Instrument (OMI) through the identification and classification of volcanic activity over a 5 year period. The incorporation of this data into a logistic regression model facilitated the classification of volcanic events with an overall accuracy of 80% whilst consistently identifying plumes with a mass of 400 tons or higher. The implementation of the developed model could facilitate the near real time identification of new and ongoing volcanic activity on a global scale.

A seamless global hydrological monitoring and forecasting system for water resources assessment and hydrological hazard early warning

NASA Astrophysics Data System (ADS)

Sheffield, Justin; He, Xiaogang; Wood, Eric; Pan, Ming; Wanders, Niko; Zhan, Wang; Peng, Liqing

2017-04-01

Sustainable management of water resources and mitigation of the impacts of hydrological hazards are becoming ever more important at large scales because of inter-basin, inter-country and inter-continental connections in water dependent sectors. These include water resources management, food production, and energy production, whose needs must be weighed against the water needs of ecosystems and preservation of water resources for future generations. The strains on these connections are likely to increase with climate change and increasing demand from burgeoning populations and rapid development, with potential for conflict over water. At the same time, network connections may provide opportunities to alleviate pressures on water availability through more efficient use of resources such as trade in water dependent goods. A key constraint on understanding, monitoring and identifying solutions to increasing competition for water resources and hazard risk is the availability of hydrological data for monitoring and forecasting water resources and hazards. We present a global online system that provides continuous and consistent water products across time scales, from the historic instrumental period, to real-time monitoring, short-term and seasonal forecasts, and climate change projections. The system is intended to provide data and tools for analysis of historic hydrological variability and trends, water resources assessment, monitoring of evolving hazards and forecasts for early warning, and climate change scale projections of changes in water availability and extreme events. The system is particular useful for scientists and stakeholders interested in regions with less available in-situ data, and where forecasts have the potential to help decision making. The system is built on a database of high-resolution climate data from 1950 to present that merges available observational records with bias-corrected reanalysis and satellite data, which then drives a coupled land surface model-flood inundation model to produce hydrological variables and indices at daily, 0.25-degree resolution, globally. The system is updated in near real-time (< 2 days) using satellite precipitation and weather model data, and produces forecasts at short-term (out to 7 days) based on the Global Forecast System (GFS) and seasonal (up to 6 months) based on U.S. National Multi-Model Ensemble (NMME) seasonal forecasts. Climate change projections are based on bias-corrected and downscaled CMIP5 climate data that is used to force the hydrological model. Example products from the system include real-time and forecast drought indices for precipitation, soil moisture, and streamflow, and flood magnitude and extent indices. The model outputs are complemented by satellite based products and indices based on satellite data for vegetation health (MODIS NDVI) and soil moisture (SMAP). We show examples of the validation of the system at regional scales, including how local information can significantly improve predictions, and examples of how the system can be used to understand large-scale water resource issues, and in real-world contexts for early warning, decision making and planning.

Monitoring temperatures in coal conversion and combustion processes via ultrasound

NASA Astrophysics Data System (ADS)

Gopalsami, N.; Raptis, A. C.; Mulcahey, T. P.

1980-02-01

The state of the art of instrumentation for monitoring temperatures in coal conversion and combustion systems is examined. The instrumentation types studied include thermocouples, radiation pyrometers, and acoustical thermometers. The capabilities and limitations of each type are reviewed. A feasibility study of the ultrasonic thermometry is described. A mathematical model of a pulse-echo ultrasonic temperature measurement system is developed using linear system theory. The mathematical model lends itself to the adaptation of generalized correlation techniques for the estimation of propagation delays. Computer simulations are made to test the efficacy of the signal processing techniques for noise-free as well as noisy signals. Based on the theoretical study, acoustic techniques to measure temperature in reactors and combustors are feasible.

The internal model: A study of the relative contribution of proprioception and visual information to failure detection in dynamic systems. [sensitivity of operators versus monitors to failures

NASA Technical Reports Server (NTRS)

Kessel, C.; Wickens, C. D.

1978-01-01

The development of the internal model as it pertains to the detection of step changes in the order of control dynamics is investigated for two modes of participation: whether the subjects are actively controlling those dynamics or are monitoring an autopilot controlling them. A transfer of training design was used to evaluate the relative contribution of proprioception and visual information to the overall accuracy of the internal model. Sixteen subjects either tracked or monitored the system dynamics as a 2-dimensional pursuit display under single task conditions and concurrently with a sub-critical tracking task at two difficulty levels. Detection performance was faster and more accurate in the manual as opposed to the autopilot mode. The concurrent tracking task produced a decrement in detection performance for all conditions though this was more marked for the manual mode. The development of an internal model in the manual mode transferred positively to the automatic mode producing enhanced detection performance. There was no transfer from the internal model developed in the automatic mode to the manual mode.

INTELLIGENT MONITORING SYSTEM WITH HIGH TEMPERATURE DISTRIBUTED FIBEROPTIC SENSOR FOR POWER PLANT COMBUSTION PROCESSES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kwang Y. Lee; Stuart S. Yin; Andre Boheman

2004-12-26

The objective of the proposed work is to develop an intelligent distributed fiber optical sensor system for real-time monitoring of high temperature in a boiler furnace in power plants. Of particular interest is the estimation of spatial and temporal distributions of high temperatures within a boiler furnace, which will be essential in assessing and controlling the mechanisms that form and remove pollutants at the source, such as NOx. The basic approach in developing the proposed sensor system is three fold: (1) development of high temperature distributed fiber optical sensor capable of measuring temperatures greater than 2000 C degree with spatialmore » resolution of less than 1 cm; (2) development of distributed parameter system (DPS) models to map the three-dimensional (3D) temperature distribution for the furnace; and (3) development of an intelligent monitoring system for real-time monitoring of the 3D boiler temperature distribution. Under Task 1, improvement was made on the performance of in-fiber grating fabricated in single crystal sapphire fibers, test was performed on the grating performance of single crystal sapphire fiber with new fabrication methods, and the fabricated grating was applied to high temperature sensor. Under Task 2, models obtained from 3-D modeling of the Demonstration Boiler were used to study relationships between temperature and NOx, as the multi-dimensionality of such systems are most comparable with real-life boiler systems. Studies show that in boiler systems with no swirl, the distributed temperature sensor may provide information sufficient to predict trends of NOx at the boiler exit. Under Task 3, we investigate a mathematical approach to extrapolation of the temperature distribution within a power plant boiler facility, using a combination of a modified neural network architecture and semigroup theory. The 3D temperature data is furnished by the Penn State Energy Institute using FLUENT. Given a set of empirical data with no analytic expression, we first develop an analytic description and then extend that model along a single axis.« less

Monitoring Global Food Security with New Remote Sensing Products and Tools

NASA Astrophysics Data System (ADS)

Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Husak, G. J.; Magadzire, T.; Verdin, J. P.

2012-12-01

Global agriculture monitoring is a crucial aspect of monitoring food security in the developing world. The Famine Early Warning Systems Network (FEWS NET) has a long history of using remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and climate change. In recent years, it has become apparent that FEWS NET requires the ability to apply monitoring and modeling frameworks at a global scale to assess potential impacts of foreign production and markets on food security at regional, national, and local levels. Scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the University of California Santa Barbara (UCSB) Climate Hazards Group have provided new and improved data products as well as visualization and analysis tools in support of the increased mandate for remote monitoring. We present our monitoring products for measuring actual evapotranspiration (ETa), normalized difference vegetation index (NDVI) in a near-real-time mode, and satellite-based rainfall estimates and derivatives. USGS FEWS NET has implemented a Simplified Surface Energy Balance (SSEB) model to produce operational ETa anomalies for Africa and Central Asia. During the growing season, ETa anomalies express surplus or deficit crop water use, which is directly related to crop condition and biomass. We present current operational products and provide supporting validation of the SSEB model. The expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) production system provides FEWS NET with an improved NDVI dataset for crop and rangeland monitoring. eMODIS NDVI provides a reliable data stream with a relatively high spatial resolution (250-m) and short latency period (less than 12 hours) which allows for better operational vegetation monitoring. We provide an overview of these data and cite specific applications for crop monitoring. FEWS NET uses satellite rainfall estimates as inputs for monitoring agricultural food production and driving crop water balance models. We present a series of derived rainfall products and provide an update on efforts to improve satellite-based estimates. We also present advancements in monitoring tools, namely, the Early Warning eXplorer (EWX) and interactive rainfall and NDVI time series viewers. The EWX is a data analysis and visualization tool that allows users to rapidly visualize multiple remote sensing datasets and compare standardized anomaly maps and time series. The interactive time series viewers allow users to analyze rainfall and NDVI time series over multiple spatial domains. New and improved data products and more targeted analysis tools are a necessity as food security monitoring requirements expand and resources become limited.

Working Group Reports: Working Group 1 - Software Systems Design and Implementation for Environmental Modeling

EPA Science Inventory

The purpose of the Interagency Steering Committee on Multimedia Environmental Modeling (ISCMEM) is to foster the exchange of information about environmental modeling tools, modeling frameworks, and environmental monitoring databases that are all in the public domain. It is compos...

Wilderness monitoring and data management

USGS Publications Warehouse

Riebau, A. R.

1994-01-01

In the last decade, increased public interest in natural areas has resulted in increased monitoring activity by federal wilderness managers to assess the status of wilderness values. Wilderness values are those large-scale entities of wilderness which comprise, in sum, wilderness character. Data collected through wilderness monitoring must support the maintenance of wilderness values. Wilderness monitoring must include the development of clear data management strategies and provisions for hypothesis testing. Unfortunately, some monitoring programs do not support the status assessment of wilderness values. Often wilderness monitoring programs have neglected even the most rudimentary principles of data management. This paper presents a model for wilderness monitoring, guidelines for data management, and an overview of a PC-compatible wilderness monitoring data base, the Monitoring Information Data Analysis System (MIDAS).

An Uncertainty Quantification Framework for Prognostics and Condition-Based Monitoring

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Goebel, Kai

2014-01-01

This paper presents a computational framework for uncertainty quantification in prognostics in the context of condition-based monitoring of aerospace systems. The different sources of uncertainty and the various uncertainty quantification activities in condition-based prognostics are outlined in detail, and it is demonstrated that the Bayesian subjective approach is suitable for interpreting uncertainty in online monitoring. A state-space model-based framework for prognostics, that can rigorously account for the various sources of uncertainty, is presented. Prognostics consists of two important steps. First, the state of the system is estimated using Bayesian tracking, and then, the future states of the system are predicted until failure, thereby computing the remaining useful life of the system. The proposed framework is illustrated using the power system of a planetary rover test-bed, which is being developed and studied at NASA Ames Research Center.

System level modeling and component level control of fuel cells

NASA Astrophysics Data System (ADS)

Xue, Xingjian

This dissertation investigates the fuel cell systems and the related technologies in three aspects: (1) system-level dynamic modeling of both PEM fuel cell (PEMFC) and solid oxide fuel cell (SOFC); (2) condition monitoring scheme development of PEM fuel cell system using model-based statistical method; and (3) strategy and algorithm development of precision control with potential application in energy systems. The dissertation first presents a system level dynamic modeling strategy for PEM fuel cells. It is well known that water plays a critical role in PEM fuel cell operations. It makes the membrane function appropriately and improves the durability. The low temperature operating conditions, however, impose modeling difficulties in characterizing the liquid-vapor two phase change phenomenon, which becomes even more complex under dynamic operating conditions. This dissertation proposes an innovative method to characterize this phenomenon, and builds a comprehensive model for PEM fuel cell at the system level. The model features the complete characterization of multi-physics dynamic coupling effects with the inclusion of dynamic phase change. The model is validated using Ballard stack experimental result from open literature. The system behavior and the internal coupling effects are also investigated using this model under various operating conditions. Anode-supported tubular SOFC is also investigated in the dissertation. While the Nernst potential plays a central role in characterizing the electrochemical performance, the traditional Nernst equation may lead to incorrect analysis results under dynamic operating conditions due to the current reverse flow phenomenon. This dissertation presents a systematic study in this regard to incorporate a modified Nernst potential expression and the heat/mass transfer into the analysis. The model is used to investigate the limitations and optimal results of various operating conditions; it can also be utilized to perform the optimal design of tubular SOFC. With the system-level dynamic model as a basis, a framework for the robust, online monitoring of PEM fuel cell is developed in the dissertation. The monitoring scheme employs the Hotelling T2 based statistical scheme to handle the measurement noise and system uncertainties and identifies the fault conditions through a series of self-checking and conformal testing. A statistical sampling strategy is also utilized to improve the computation efficiency. Fuel/gas flow control is the fundamental operation for fuel cell energy systems. In the final part of the dissertation, a high-precision and robust tracking control scheme using piezoelectric actuator circuit with direct hysteresis compensation is developed. The key characteristic of the developed control algorithm includes the nonlinear continuous control action with the adaptive boundary layer strategy.

Dietary Exposure Potential Model

EPA Science Inventory

Existing food consumption and contaminant residue databases, typically products of nutrition and regulatory monitoring, contain useful information to characterize dietary intake of environmental chemicals. A PC-based model with resident database system, termed the Die...

Application of NARR-based NLDAS Ensemble Simulations to Continental-Scale Drought Monitoring

NASA Astrophysics Data System (ADS)

Alonge, C. J.; Cosgrove, B. A.

2008-05-01

Government estimates indicate that droughts cause billions of dollars of damage to agricultural interests each year. More effective identification of droughts would directly benefit decision makers, and would allow for the more efficient allocation of resources that might mitigate the event. Land data assimilation systems, with their high quality representations of soil moisture, present an ideal platform for drought monitoring, and offer many advantages over traditional modeling systems. The recently released North American Regional Reanalysis (NARR) covers the NLDAS domain and provides all fields necessary to force the NLDAS for 27 years. This presents an ideal opportunity to combine NARR and NLDAS resources into an effective real-time drought monitor. Toward this end, our project seeks to validate and explore the NARR's suitability as a base for drought monitoring applications - both in terms of data set length and accuracy. Along the same lines, the project will examine the impact of the use of different (longer) LDAS model climatologies on drought monitoring, and will explore the advantages of ensemble simulations versus single model simulations in drought monitoring activities. We also plan to produce a NARR- and observation-based high quality 27 year, 1/8th degree, 3-hourly, land surface and meteorological forcing data sets. An investigation of the best way to force an LDAS-type system will also be made, with traditional NLDAS and NLDASE forcing options explored. This presentation will focus on an overview of the drought monitoring project, and will include a summary of recent progress. Developments include the generation of forcing data sets, ensemble LSM output, and production of model-based drought indices over the entire NLDAS domain. Project forcing files use 32km NARR model output as a data backbone, and include observed precipitation (blended CPC gauge, PRISM gauge, Stage II, HPD, and CMORPH) and a GOES-based bias correction of downward solar radiation. Multiple LSM simulations have been conducted using the Noah, Mosaic, CLM3, HYSSiB, and Catchment LSMs. These simulations, along with the NARR-based forcing data form the basis for several drought indices. These include standard measures such as the Palmer-type indices, LDAS-type percentile and anomaly values, and CLM3-based vegetation condition index values.

Role of Large Clinical Datasets From Physiologic Monitors in Improving the Safety of Clinical Alarm Systems and Methodological Considerations: A Case From Philips Monitors.

PubMed

Sowan, Azizeh Khaled; Reed, Charles Calhoun; Staggers, Nancy

2016-09-30

Large datasets of the audit log of modern physiologic monitoring devices have rarely been used for predictive modeling, capturing unsafe practices, or guiding initiatives on alarm systems safety. This paper (1) describes a large clinical dataset using the audit log of the physiologic monitors, (2) discusses benefits and challenges of using the audit log in identifying the most important alarm signals and improving the safety of clinical alarm systems, and (3) provides suggestions for presenting alarm data and improving the audit log of the physiologic monitors. At a 20-bed transplant cardiac intensive care unit, alarm data recorded via the audit log of bedside monitors were retrieved from the server of the central station monitor. Benefits of the audit log are many. They include easily retrievable data at no cost, complete alarm records, easy capture of inconsistent and unsafe practices, and easy identification of bedside monitors missed from a unit change of alarm settings adjustments. Challenges in analyzing the audit log are related to the time-consuming processes of data cleaning and analysis, and limited storage and retrieval capabilities of the monitors. The audit log is a function of current capabilities of the physiologic monitoring systems, monitor's configuration, and alarm management practices by clinicians. Despite current challenges in data retrieval and analysis, large digitalized clinical datasets hold great promise in performance, safety, and quality improvement. Vendors, clinicians, researchers, and professional organizations should work closely to identify the most useful format and type of clinical data to expand medical devices' log capacity.

A Multidisciplinary Approach to Health Monitoring and Materials Damage Prognosis for Metallic Aerospace Systems

DTIC Science & Technology

2013-03-01

framework of orientation distribution functions and crack-induced texture o Quantify effects of temperature on damage behavior and damage monitoring...measurement model was obtained from hidden Markov modeling (HMM) of joint time-frequency (TF) features extracted from the PZT sensor signals using the...considered PZT sensor signals recorded from a bolted aluminum plate. About only 20% of the samples of a signal were first randomly selected as

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring.

PubMed

Alcalá, José M; Ureña, Jesús; Hernández, Álvaro; Gualda, David

2017-02-11

The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN) are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs), which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN) prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM), is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people' demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented.

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring

PubMed Central

Alcalá, José M.; Ureña, Jesús; Hernández, Álvaro; Gualda, David

2017-01-01

The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN) are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs), which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN) prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM), is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people’ demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented. PMID:28208672

Structural damage detection for in-service highway bridge under operational and environmental variability

NASA Astrophysics Data System (ADS)

Jin, Chenhao; Li, Jingcheng; Jang, Shinae; Sun, Xiaorong; Christenson, Richard

2015-03-01

Structural health monitoring has drawn significant attention in the past decades with numerous methodologies and applications for civil structural systems. Although many researchers have developed analytical and experimental damage detection algorithms through vibration-based methods, these methods are not widely accepted for practical structural systems because of their sensitivity to uncertain environmental and operational conditions. The primary environmental factor that influences the structural modal properties is temperature. The goal of this article is to analyze the natural frequency-temperature relationships and detect structural damage in the presence of operational and environmental variations using modal-based method. For this purpose, correlations between natural frequency and temperature are analyzed to select proper independent variables and inputs for the multiple linear regression model and neural network model. In order to capture the changes of natural frequency, confidence intervals to detect the damages for both models are generated. A long-term structural health monitoring system was installed on an in-service highway bridge located in Meriden, Connecticut to obtain vibration and environmental data. Experimental testing results show that the variability of measured natural frequencies due to temperature is captured, and the temperature-induced changes in natural frequencies have been considered prior to the establishment of the threshold in the damage warning system. This novel approach is applicable for structural health monitoring system and helpful to assess the performance of the structure for bridge management and maintenance.

An Integrated Gulf Coast Monitoring System Using Field, Remote Sensing and Model Results (Invited)

NASA Astrophysics Data System (ADS)

D'Sa, E. J.; Ko, D. S.; Stone, G.; Walker, N. D.

2010-12-01

The northern Gulf of Mexico is strongly influenced by the discharge of water, nutrients, dissolved and suspended particulate matter from the Mississippi-Atchafalaya River system, the largest in North America. It is also frequently impacted by energetic meteorological events that cause storm surge, high waves and affects water quality along its coastal waters. We describe the components of an integrated web-based Gulf Coast Information System (GCIS) (http://gulf-coast.lsu.edu) developed to serve remotely sensed products from a number of NASA satellite sensors such as the SeaWiFS and MODIS ocean color and the QuikSCAT wind sensors. GCIS also serves high-resolution nowcast and 48-hour forecast outputs (sea level variations, temperature, salinity and currents) from a 3-dimensional NCOM coastal circulation model for the coastal states of Mississippi, Louisiana and Texas. The GCIS is coupled to the near real-time outputs of a field monitoring and satellite receiving system, the Wave-Current Information System (WAVCIS) (http://www.wavcis.lsu.edu) and Earth Scan Laboratory (ESL) (www.esl.lsu.edu), respectively that provide critical decision support during hurricanes to the Gulf Coast. We present results on the use of the combined field, satellite and model outputs to monitor the effects of fronts, hurricanes, oil spill and the potential to study longer term climate impacts along the Gulf coast.

Software Health Management with Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole; Schumann, JOhann

2011-01-01

Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.

Automatic Welding System of Aluminum Pipe by Monitoring Backside Image of Molten Pool Using Vision Sensor

NASA Astrophysics Data System (ADS)

Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

An automatic welding system using Tungsten Inert Gas (TIG) welding with vision sensor for welding of aluminum pipe was constructed. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position and moving welding torch with the AC welding machine. The monitoring system consists of a vision sensor using a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Neural network model for welding speed control were constructed to perform the process automatically. From the experimental results it shows the effectiveness of the control system confirmed by good detection of molten pool and sound weld of experimental result.

Monte Carlo Uncertainty Quantification for an Unattended Enrichment Monitor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarman, Kenneth D.; Smith, Leon E.; Wittman, Richard S.

As a case study for uncertainty analysis, we consider a model flow monitor for measuring enrichment in gas centrifuge enrichment plants (GCEPs) that could provide continuous monitoring of all declared gas flow and provide high-accuracy gas enrichment estimates as a function of time. The monitor system could include NaI(Tl) gamma-ray spectrometers, a pressure signal-sharing device to be installed on an operator\\rq{}s pressure gauge or a dedicated inspector pressure sensor, and temperature sensors attached to the outside of the header pipe, to provide pressure, temperature, and gamma-ray spectra measurements of UFmore » $$_6$$ gas flow through unit header pipes. Our study builds on previous modeling and analysis methods development for enrichment monitor concepts and a software tool that was developed at Oak Ridge National Laboratory to generate and analyze synthetic data.« less

Data Optical Networking Architecture Using Wavelength-Division Multiplexing Method for Optical Sensors

NASA Technical Reports Server (NTRS)

Nguyen, Hung D.

2008-01-01

Recently there has been a growth in the number of fiber optical sensors used for health monitoring in the hostile environment of commercial aircraft. Health monitoring to detect the onset of failure in structural systems from such causes as corrosion, stress corrosion cracking, and fatigue is a critical factor in safety as well in aircraft maintenance costs. This report presents an assessment of an analysis model of optical data networking architectures used for monitoring data signals among these optical sensors. Our model is focused on the design concept of the wavelength-division multiplexing (WDM) method since most of the optical sensors deployed in the aircraft for health monitoring typically operate in a wide spectrum of optical wavelengths from 710 to 1550 nm.

Application of laser scanning technique in earthquake protection of Istanbul's historical heritage buildings

NASA Astrophysics Data System (ADS)

Çaktı, Eser; Ercan, Tülay; Dar, Emrullah

2017-04-01

Istanbul's vast historical and cultural heritage is under constant threat of earthquakes. Historical records report repeated damages to the city's landmark buildings. Our efforts towards earthquake protection of several buildings in Istanbul involve earthquake monitoring via structural health monitoring systems, linear and non-linear structural modelling and analysis in search of past and future earthquake performance, shake-table testing of scaled models and non-destructive testing. More recently we have been using laser technology in monitoring structural deformations and damage in five monumental buildings which are Hagia Sophia Museum and Fatih, Sultanahmet, Süleymaniye and Mihrimah Sultan Mosques. This presentation is about these efforts with special emphasis on the use of laser scanning in monitoring of edifices.

Estimating the susceptibility of surface water in Texas to nonpoint-source contamination by use of logistic regression modeling

USGS Publications Warehouse

Battaglin, William A.; Ulery, Randy L.; Winterstein, Thomas; Welborn, Toby

2003-01-01

In the State of Texas, surface water (streams, canals, and reservoirs) and ground water are used as sources of public water supply. Surface-water sources of public water supply are susceptible to contamination from point and nonpoint sources. To help protect sources of drinking water and to aid water managers in designing protective yet cost-effective and risk-mitigated monitoring strategies, the Texas Commission on Environmental Quality and the U.S. Geological Survey developed procedures to assess the susceptibility of public water-supply source waters in Texas to the occurrence of 227 contaminants. One component of the assessments is the determination of susceptibility of surface-water sources to nonpoint-source contamination. To accomplish this, water-quality data at 323 monitoring sites were matched with geographic information system-derived watershed- characteristic data for the watersheds upstream from the sites. Logistic regression models then were developed to estimate the probability that a particular contaminant will exceed a threshold concentration specified by the Texas Commission on Environmental Quality. Logistic regression models were developed for 63 of the 227 contaminants. Of the remaining contaminants, 106 were not modeled because monitoring data were available at less than 10 percent of the monitoring sites; 29 were not modeled because there were less than 15 percent detections of the contaminant in the monitoring data; 27 were not modeled because of the lack of any monitoring data; and 2 were not modeled because threshold values were not specified.

Smart monitoring system based on adaptive current control for superconducting cable test.

PubMed

Arpaia, Pasquale; Ballarino, Amalia; Daponte, Vincenzo; Montenero, Giuseppe; Svelto, Cesare

2014-12-01

A smart monitoring system for superconducting cable test is proposed with an adaptive current control of a superconducting transformer secondary. The design, based on Fuzzy Gain Scheduling, allows the controller parameters to adapt continuously, and finely, to the working variations arising from transformer nonlinear dynamics. The control system is integrated in a fully digital control loop, with all the related benefits, i.e., high noise rejection, ease of implementation/modification, and so on. In particular, an accurate model of the system, controlled by a Fuzzy Gain Scheduler of the superconducting transformer, was achieved by an experimental campaign through the working domain at several current ramp rates. The model performance was characterized by simulation, under all the main operating conditions, in order to guide the controller design. Finally, the proposed monitoring system was experimentally validated at European Organization for Nuclear Research (CERN) in comparison to the state-of-the-art control system [P. Arpaia, L. Bottura, G. Montenero, and S. Le Naour, "Performance improvement of a measurement station for superconducting cable test," Rev. Sci. Instrum. 83, 095111 (2012)] of the Facility for the Research on Superconducting Cables, achieving a significant performance improvement: a reduction in the system overshoot by 50%, with a related attenuation of the corresponding dynamic residual error (both absolute and RMS) up to 52%.

Hidden Markov models and neural networks for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.

Predictive monitoring research: Summary of the PREMON system

NASA Technical Reports Server (NTRS)

Doyle, Richard J.; Sellers, Suzanne M.; Atkinson, David J.

1987-01-01

Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device.

Development of a real time activity monitoring Android application utilizing SmartStep.

PubMed

Hegde, Nagaraj; Melanson, Edward; Sazonov, Edward

2016-08-01

Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback. The development of activity classification methods was based on the the data from a human study involving 4 participants. Participants were asked to perform activities of sitting, standing, walking, and cycling while they wore SmartStep insole system. Multinomial Logistic Discrimination (MLD) was utilized in the development of machine learning model for activity prediction. The resulting classification model was implemented in an Android Smartphone. The Android application was benchmarked for power consumption and CPU loading. Leave one out cross validation resulted in average accuracy of 96.9% during model training phase. The Android application for real time activity classification was tested on a human subject wearing SmartStep resulting in testing accuracy of 95.4%.

Research on intelligent monitoring technology of machining process

NASA Astrophysics Data System (ADS)

Wang, Taiyong; Meng, Changhong; Zhao, Guoli

1995-08-01

Based upon research on sound and vibration characteristics of tool condition, we explore the multigrade monitoring system which takes single-chip microcomputers as the core hardware. By using the specially designed pickup true signal devices, we can more effectively do the intelligent multigrade monitoring and forecasting, and furthermore, we can build the tool condition models adaptively. This is the key problem in FMS, CIMS, and even the IMS.

A Model of Managerial Effectiveness in Information Security: From Grounded Theory to Empirical Test

DTIC Science & Technology

2005-09-13

to observe employee performance (George, 1996) and encourage policy adherence ( Ariss , 2002) have been studied. While the published academic...for excessive monitoring ( Ariss , 2002). Managers have a key role to play in designing monitoring and enforcement systems that are effective yet not... Ariss , S. S. (2002). Computer Monitoring: Benefits and Pitfalls Facing Management. Information & Management, 39(7), 553-558. Armstrong, C. P

Mitochondrial function and tissue vitality: bench-to-bedside real-time optical monitoring system

NASA Astrophysics Data System (ADS)

Mayevsky, Avraham; Walden, Raphael; Pewzner, Eliyahu; Deutsch, Assaf; Heldenberg, Eitan; Lavee, Jacob; Tager, Salis; Kachel, Erez; Raanani, Ehud; Preisman, Sergey; Glauber, Violete; Segal, Eran

2011-06-01

Background: The involvement of mitochondria in pathological states, such as neurodegenerative diseases, sepsis, stroke, and cancer, are well documented. Monitoring of nicotinamide adenine dinucleotide (NADH) fluorescence in vivo as an intracellular oxygen indicator was established in 1950 to 1970 by Britton Chance and collaborators. We use a multiparametric monitoring system enabling assessment of tissue vitality. In order to use this technology in clinical practice, the commercial developed device, the CritiView (CRV), is tested in animal models as well as in patients. Methods and Results: The new CRV enables the optical monitoring of four different parameters, representing the energy balance of various tissues in vivo. Mitochondrial NADH is measured by surface fluorometry/reflectometry. In addition, tissue microcirculatory blood flow, tissue reflectance and oxygenation are measured as well. The device is tested both in vitro and in vivo in a small animal model and in preliminary clinical trials in patients undergoing vascular or open heart surgery. In patients, the monitoring is started immediately after the insertion of a three-way Foley catheter (urine collection) to the patient and is stopped when the patient is discharged from the operating room. The results show that monitoring the urethral wall vitality provides information in correlation to the surgical procedure performed.

Serial Network Flow Monitor

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Tate-Brown, Judy M.

2009-01-01

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

Integrated Hydro-geomorphological Monitoring System of the Upper Bussento river basin (Cilento and Vallo Diano Geopark, S-Italy)

NASA Astrophysics Data System (ADS)

Guida, D.; Cuomo, A.; Longobardi, A.; Villani, P.; Guida, M.; Guadagnuolo, D.; Cestari, A.; Siervo, V.; Benevento, G.; Sorvino, S.; Doto, R.; Verrone, M.; De Vita, A.; Aloia, A.; Positano, P.

2012-04-01

The Mediterranean river ecosystem functionings are supported by river-aquifer interactions. The assessment of their ecological services requires interdisciplinary scientific approaches, integrate monitoring systems and inter-institutional planning and management. This poster illustrates the Hydro-geomorphological Monitoring System build-up in the Upper Bussento river basin by the University of Salerno, in agreement with the local Basin Autorities and in extension to the other river basins located in the Cilento and Vallo Diano National Park (southern Italy), recently accepted in the European Geopark Network. The Monitoring System is based on a hierarchical Hydro-geomorphological Model (HGM), improved in a multiscale, nested and object-oriented Hydro-geomorphological Informative System (HGIS, Figure 1). Hydro-objects are topologically linked and functionally bounded by Hydro-elements at various levels of homogeneity (Table 1). Spatial Hydro-geomorpho-system, HG-complex and HG-unit support respectively areal Hydro-objects, as basin, sector and catchment and linear Hydro-objects, as river, segment, reach and section. Runoff initiation points, springs, disappearing points, junctions, gaining and water losing points complete the Hydro-systems. An automatic procedure use the Pfafstetter coding to hierarchically divide a terrain into arbitrarily small hydro-geomorphological units (basin, interfluve, headwater and no-contribution areas, each with a unique label with hierarchical topological properties. To obtain a hierarchy of hydro-geomorphological units, the method is then applied recursively on each basin and interbasin, and labels of the subdivided regions are appended to the existing label of the original region. The monitoring stations are ranked consequently in main, secondary, temporary and random and located progressively at the points or sections representative for the hydro-geomorphological responses by validation control and modeling calibration. The datasets are organized into a relational geodatabase supporting tracer testings, space-time analysis and hydrological modeling. At the moment, three main station for hourly streamflow measurements are located at the terminal sections of the main basin and the two main sub-basin; secondary stations for weekly discharge measurements are located along the Upper Bussento river segment, upstream and downstream of each river reach or tributary catchments or karst spring inflow. Temporary stations are located in the representative sections of the catchments to detect stream flow losses into alluvial beds or experimental parcels in the bare karst and forested sandstone headwaters. Streamflow measurements are combined with geochemical survey and water sampling for Radon activity concentration measurements. Results of measurement campains in Radon space-time distribution within the basin are given in other contribution of same EGU session. Monitoring results confirm the hourly, daily, weekly and monthly hydrological data and validate outcomes of semi-distributed hydrological models based on previously time series, allowing both academic consultants and institutional subject to extend the Integrated Hydro-geomorphological Monitoring System to the surrounding drainage areas of the Cilento and Vallo di Diano Geopark. Keywords: River-aquifer interaction, Upper Bussento river basin, monitoring system, hydro-geomorphology, semi-distributed hydrological model. Table 1: Comparative, hierarchical Hydro-morpho-climate entities Hierarchy levelArea (Km2) Scale Orography Entity Climate Entity Morfological Entity Areal Drainage Entity Linear Drainage Entity VIII 106 1:15E6 Orogen Macroscale α Morphological Region Hydrological Region VII 105 1:10E6 Chain Sistem Macroscale β Morphological Province Hydrological Province VI 104 1:5E5 Chain Mesoscale α Morphological Sistem Basin River V 103 1:2,5E5Chain Segment Mesoscale β Morphological Sub-systemSub-Basin Torrent IV 100 1:1,0E5Orographic Group Mesoscale γ Morphological Complex Basin Sector Mid Order Channel/ Segment III 10 1: 5E4 Orographic System Microscale αMorphological Unit Watershed Low Order Channel/ Reach II 1 1:2,5E3Orographic ComplexMicroscale βMorphological ComponentCatchment Transient Channel/ Pool I 10-2 1:5E3 Orographic Unit Microscale γMorphological Element Hollow Zero Order Channel PIC

Display/control requirements for VTOL aircraft

NASA Technical Reports Server (NTRS)

Hoffman, W. C.; Curry, R. E.; Kleinman, D. L.; Hollister, W. M.; Young, L. R.

1975-01-01

Quantative metrics were determined for system control performance, workload for control, monitoring performance, and workload for monitoring. Pilot tasks were allocated for navigation and guidance of automated commercial V/STOL aircraft in all weather conditions using an optimal control model of the human operator to determine display elements and design.

Sampling frequency for water quality variables in streams: Systems analysis to quantify minimum monitoring rates.

PubMed

Chappell, Nick A; Jones, Timothy D; Tych, Wlodek

2017-10-15

Insufficient temporal monitoring of water quality in streams or engineered drains alters the apparent shape of storm chemographs, resulting in shifted model parameterisations and changed interpretations of solute sources that have produced episodes of poor water quality. This so-called 'aliasing' phenomenon is poorly recognised in water research. Using advances in in-situ sensor technology it is now possible to monitor sufficiently frequently to avoid the onset of aliasing. A systems modelling procedure is presented allowing objective identification of sampling rates needed to avoid aliasing within strongly rainfall-driven chemical dynamics. In this study aliasing of storm chemograph shapes was quantified by changes in the time constant parameter (TC) of transfer functions. As a proportion of the original TC, the onset of aliasing varied between watersheds, ranging from 3.9-7.7 to 54-79 %TC (or 110-160 to 300-600 min). However, a minimum monitoring rate could be identified for all datasets if the modelling results were presented in the form of a new statistic, ΔTC. For the eight H + , DOC and NO 3 -N datasets examined from a range of watershed settings, an empirically-derived threshold of 1.3(ΔTC) could be used to quantify minimum monitoring rates within sampling protocols to avoid artefacts in subsequent data analysis. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Fourier Transform Infrared Spectroscopy and Multivariate Analysis for Online Monitoring of Dibutyl Phosphate Degradation Product in Tributyl Phosphate/n-Dodecane/Nitric Acid Solvent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tatiana G. Levitskaia; James M. Peterson; Emily L. Campbell

2013-12-01

In liquid–liquid extraction separation processes, accumulation of organic solvent degradation products is detrimental to the process robustness, and frequent solvent analysis is warranted. Our research explores the feasibility of online monitoring of the organic solvents relevant to used nuclear fuel reprocessing. This paper describes the first phase of developing a system for monitoring the tributyl phosphate (TBP)/n-dodecane solvent commonly used to separate used nuclear fuel. In this investigation, the effect of extraction of nitric acid from aqueous solutions of variable concentrations on the quantification of TBP and its major degradation product dibutylphosphoric acid (HDBP) was assessed. Fourier transform infrared (FTIR)more » spectroscopy was used to discriminate between HDBP and TBP in the nitric acid-containing TBP/n-dodecane solvent. Multivariate analysis of the spectral data facilitated the development of regression models for HDBP and TBP quantification in real time, enabling online implementation of the monitoring system. The predictive regression models were validated using TBP/n-dodecane solvent samples subjected to high-dose external ?-irradiation. The predictive models were translated to flow conditions using a hollow fiber FTIR probe installed in a centrifugal contactor extraction apparatus, demonstrating the applicability of the FTIR technique coupled with multivariate analysis for the online monitoring of the organic solvent degradation products.« less

Fourier Transform Infrared Spectroscopy and Multivariate Analysis for Online Monitoring of Dibutyl Phosphate Degradation Product in Tributyl Phosphate /n-Dodecane/Nitric Acid Solvent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levitskaia, Tatiana G.; Peterson, James M.; Campbell, Emily L.

2013-11-05

In liquid-liquid extraction separation processes, accumulation of organic solvent degradation products is detrimental to the process robustness and frequent solvent analysis is warranted. Our research explores feasibility of online monitoring of the organic solvents relevant to used nuclear fuel reprocessing. This paper describes the first phase of developing a system for monitoring the tributyl phosphate (TBP)/n-dodecane solvent commonly used to separate used nuclear fuel. In this investigation, the effect of extraction of nitric acid from aqueous solutions of variable concentrations on the quantification of TBP and its major degradation product dibutyl phosphoric acid (HDBP) was assessed. Fourier Transform Infrared Spectroscopymore » (FTIR) spectroscopy was used to discriminate between HDBP and TBP in the nitric acid-containing TBP/n-dodecane solvent. Multivariate analysis of the spectral data facilitated the development of regression models for HDBP and TBP quantification in real time, enabling online implementation of the monitoring system. The predictive regression models were validated using TBP/n-dodecane solvent samples subjected to the high dose external gamma irradiation. The predictive models were translated to flow conditions using a hollow fiber FTIR probe installed in a centrifugal contactor extraction apparatus demonstrating the applicability of the FTIR technique coupled with multivariate analysis for the online monitoring of the organic solvent degradation products.« less

Real time remote monitoring and pre-warning system for Highway landslide in mountain area.

PubMed

Zhang, Yonghui; Li, Hongxu; Sheng, Qian; Wu, Kai; Chen, Guoliang

2011-06-01

The wire-pulling trigger displacement meter with precision of 1 mm and the grid pluviometer with precision of 0.1 mm are used to monitor the surface displacement and rainfall for Highway slope, and the measured data are transferred to the remote computer in real time by general packet radio service (GPRS) net of China telecom. The wire-pulling trigger displacement meter, grid pluviometer, data acquisition and transmission unit, and solar power supply device are integrated to form a comprehensive monitoring hardware system for Highway landslide in mountain area, which proven to be economical, energy-saving, automatic and high efficient. Meantime, based on the map and geographic information system (MAPGIS) platform, the software system is also developed for three dimensional (3D) geology modeling and visualization, data inquiring and drawing, stability calculation, displacement forecasting, and real time pre-warning. Moreover, the pre-warning methods based on monitoring displacement and rainfall are discussed. The monitoring and forecasting system for Highway landslide has been successfully applied in engineering practice to provide security for Highway transportation and construction and reduce environment disruption. Copyright © 2011 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

An Overview of the NASA Aviation Safety Program Propulsion Health Monitoring Element

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2000-01-01

The NASA Aviation Safety Program (AvSP) has been initiated with aggressive goals to reduce the civil aviation accident rate, To meet these goals, several technology investment areas have been identified including a sub-element in propulsion health monitoring (PHM). Specific AvSP PHM objectives are to develop and validate propulsion system health monitoring technologies designed to prevent engine malfunctions from occurring in flight, and to mitigate detrimental effects in the event an in-flight malfunction does occur. A review of available propulsion system safety information was conducted to help prioritize PHM areas to focus on under the AvSP. It is noted that when a propulsion malfunction is involved in an aviation accident or incident, it is often a contributing factor rather than the sole cause for the event. Challenging aspects of the development and implementation of PHM technology such as cost, weight, robustness, and reliability are discussed. Specific technology plans are overviewed including vibration diagnostics, model-based controls and diagnostics, advanced instrumentation, and general aviation propulsion system health monitoring technology. Propulsion system health monitoring, in addition to engine design, inspection, maintenance, and pilot training and awareness, is intrinsic to enhancing aviation propulsion system safety.

Monitoring groundwater and river interaction along the Hanford reach of the Columbia River

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, M.D.

1994-04-01

As an adjunct to efficient Hanford Site characterization and remediation of groundwater contamination, an automatic monitor network has been used to measure Columbia River and adjacent groundwater levels in several areas of the Hanford Site since 1991. Water levels, temperatures, and electrical conductivity measured by the automatic monitor network provided an initial database with which to calibrate models and from which to infer ground and river water interactions for site characterization and remediation activities. Measurements of the dynamic river/aquifer system have been simultaneous at 1-hr intervals, with a quality suitable for hydrologic modeling and for computer model calibration and testing.more » This report describes the equipment, procedures, and results from measurements done in 1993.« less

Comparing methods suitable for monitoring marine mammals in low visibility conditions during seismic surveys.

PubMed

Verfuss, Ursula K; Gillespie, Douglas; Gordon, Jonathan; Marques, Tiago A; Miller, Brianne; Plunkett, Rachael; Theriault, James A; Tollit, Dominic J; Zitterbart, Daniel P; Hubert, Philippe; Thomas, Len

2018-01-01

Loud sound emitted during offshore industrial activities can impact marine mammals. Regulations typically prescribe marine mammal monitoring before and/or during these activities to implement mitigation measures that minimise potential acoustic impacts. Using seismic surveys under low visibility conditions as a case study, we review which monitoring methods are suitable and compare their relative strengths and weaknesses. Passive acoustic monitoring has been implemented as either a complementary or alternative method to visual monitoring in low visibility conditions. Other methods such as RADAR, active sonar and thermal infrared have also been tested, but are rarely recommended by regulatory bodies. The efficiency of the monitoring method(s) will depend on the animal behaviour and environmental conditions, however, using a combination of complementary systems generally improves the overall detection performance. We recommend that the performance of monitoring systems, over a range of conditions, is explored in a modelling framework for a variety of species. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Intelligent fault management for the Space Station active thermal control system

NASA Technical Reports Server (NTRS)

Hill, Tim; Faltisco, Robert M.

1992-01-01

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Drought Monitoring and Forecasting: Experiences from the US and Africa

NASA Astrophysics Data System (ADS)

Sheffield, Justin; Chaney, Nate; Yuan, Xing; Wood, Eric

2013-04-01

Drought has important but very different consequences regionally due to differences in vulnerability. These differences derive from variations in exposure related to climate variability and change, sensitivity of local populations, and coping capacity at all levels. Managing the risk of drought impacts relies on a variety of measures to reduce vulnerability that includes forewarning of drought development through early-warning systems. Existing systems rely on a variety of observing systems from satellites to local observers, modeling tools, and data dissemination methods. They range from sophisticated state-of-the-art systems to simple ground reports. In some regions, systems are virtually non-existent due to limited national capacity. This talk describes our experiences in developing and implementing drought monitoring and seasonal forecast systems in the US and sub-Saharan Africa as contrasting examples of the scientific challenges and user needs in developing early warning systems. In particular, early warning can help improve livelihoods based on subsistence farming in sub-Saharan Africa; whist reduction of economic impacts is generally foremost in the US. For the US, our national drought monitoring and seasonal forecast system has been operational for over 8 years and provides near real-time updates on hydrological states at ~12km resolution and hydrological forecasts out to 9 months. Output from the system contributes to national assessments such as from the NOAA Climate Prediction Center (CPC) and the US National Drought Monitor (USDM). For sub-Saharan Africa, our experimental drought monitoring system was developed as a translation of the US system but presents generally greater challenges due to, for example, lack of ground data and unique user needs. The system provides near real-time updates based on hydrological modeling and satellite based precipitation estimates, and has recently been augmented by a seasonal forecast component. We discuss the differences in experiences in development and implementation between the two systems in terms of the scientific challenges and the utility of the systems to stakeholders, for whom the information must be relevant to local conditions and needs.

System monitoring and diagnosis with qualitative models

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1991-01-01

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations'; 'Model-based monitoring of dynamic systems'; 'Numerical behavior envelopes for qualitative models'; 'Higher-order derivative constraints in qualitative simulation'; and 'Non-intersection of trajectories in qualitative phase space: a global constraint for qualitative simulation.'

Remote Health Monitoring for Older Adults and Those with Heart Failure: Adherence and System Usability.

PubMed

Evans, Jarrett; Papadopoulos, Amy; Silvers, Christine Tsien; Charness, Neil; Boot, Walter R; Schlachta-Fairchild, Loretta; Crump, Cindy; Martinez, Michele; Ent, Carrie Beth

2016-06-01

Remote health monitoring technology has been suggested as part of an early intervention and prevention care model. Older adults with a chronic health condition have been shown to benefit from remote monitoring but often have challenges with complex technology. The current study reports on the usability of and adherence with an integrated, real-time monitoring system over an extended period of time by older adults with and without a chronic health condition. Older adults 55 years of age and over with and without heart failure participated in a study in which a telehealth system was used for 6 months each. The system consisted of a wireless wristwatch-based monitoring device that continuously collected temperature and motion data. Other health information was collected daily using a weight scale, blood pressure cuff, and tablet that participants used for health surveys. Data were automatically analyzed and summarized by the system and presented to study nurses. Forty-one older adults participated. Seventy-one percent of surveys, 75% of blood pressure readings, and 81% of daily weight measurements were taken. Participants wore the watch monitor 77% of the overall 24/7 time requested. The weight scale had the highest usability rating in both groups. The groups did not otherwise differ on device usage. The findings indicate that a health monitoring system designed for older adults can and will be used for an extended period of time and may help older adults with chronic conditions reside longer in their own homes in partnership with the healthcare system.

Integrating environmental monitoring with cumulative effects management and decision making.

PubMed

Cronmiller, Joshua G; Noble, Bram F

2018-05-01

Cumulative effects (CE) monitoring is foundational to emerging regional and watershed CE management frameworks, yet monitoring is often poorly integrated with CE management and decision-making processes. The challenges are largely institutional and organizational, more so than scientific or technical. Calls for improved integration of monitoring with CE management and decision making are not new, but there has been limited research on how best to integrate environmental monitoring programs to ensure credible CE science and to deliver results that respond to the more immediate questions and needs of regulatory decision makers. This paper examines options for the integration of environmental monitoring with CE frameworks. Based on semistructured interviews with practitioners, regulators, and other experts in the Lower Athabasca, Alberta, Canada, 3 approaches to monitoring system design are presented. First, a distributed monitoring system, reflecting the current approach in the Lower Athabasca, where monitoring is delegated to different external programs and organizations; second, a 1-window system in which monitoring is undertaken by a single, in-house agency for the purpose of informing management and regulatory decision making; third, an independent system driven primarily by CE science and understanding causal relationships, with knowledge adopted for decision support where relevant to specific management questions. The strengths and limitations of each approach are presented. A hybrid approach may be optimal-an independent, nongovernment, 1-window model for CE science, monitoring, and information delivery-capitalizing on the strengths of distributed, 1-window, and independent monitoring systems while mitigating their weaknesses. If governments are committed to solving CE problems, they must invest in the long-term science needed to do so; at the same time, if science-based monitoring programs are to be sustainable over the long term, they must be responsive to the more immediate, often shorter term needs and CE information requirements of decision makers. Integr Environ Assess Manag 2018;14:407-417. © 2018 SETAC. © 2018 SETAC.

Engineering research, development and technology FY99

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langland, R T

The growth of computer power and connectivity, together with advances in wireless sensing and communication technologies, is transforming the field of complex distributed systems. The ability to deploy large numbers of sensors with a rapid, broadband communication system will enable high-fidelity, near real-time monitoring of complex systems. These technological developments will provide unprecedented insight into the actual performance of engineered and natural environment systems, enable the evolution of many new types of engineered systems for monitoring and detection, and enhance our ability to perform improved and validated large-scale simulations of complex systems. One of the challenges facing engineering is tomore » develop methodologies to exploit the emerging information technologies. Particularly important will be the ability to assimilate measured data into the simulation process in a way which is much more sophisticated than current, primarily ad hoc procedures. The reports contained in this section on the Center for Complex Distributed Systems describe activities related to the integrated engineering of large complex systems. The first three papers describe recent developments for each link of the integrated engineering process for large structural systems. These include (1) the development of model-based signal processing algorithms which will formalize the process of coupling measurements and simulation and provide a rigorous methodology for validation and update of computational models; (2) collaborative efforts with faculty at the University of California at Berkeley on the development of massive simulation models for the earth and large bridge structures; and (3) the development of wireless data acquisition systems which provide a practical means of monitoring large systems like the National Ignition Facility (NIF) optical support structures. These successful developments are coming to a confluence in the next year with applications to NIF structural characterizations and analysis of large bridge structures for the State of California. Initial feasibility investigations into the development of monitoring and detection systems are described in the papers on imaging of underground structures with ground-penetrating radar, and the use of live insects as sensor platforms. These efforts are establishing the basic performance characteristics essential to the decision process for future development of sensor arrays for information gathering related to national security.« less

Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan.

PubMed

Ahmad, Zulfiqar; Ashraf, Arshad; Fryar, Alan; Akhter, Gulraiz

2011-02-01

The integration of the Geographic Information System (GIS) with groundwater modeling and satellite remote sensing capabilities has provided an efficient way of analyzing and monitoring groundwater behavior and its associated land conditions. A 3-dimensional finite element model (Feflow) has been used for regional groundwater flow modeling of Upper Chaj Doab in Indus Basin, Pakistan. The approach of using GIS techniques that partially fulfill the data requirements and define the parameters of existing hydrologic models was adopted. The numerical groundwater flow model is developed to configure the groundwater equipotential surface, hydraulic head gradient, and estimation of the groundwater budget of the aquifer. GIS is used for spatial database development, integration with a remote sensing, and numerical groundwater flow modeling capabilities. The thematic layers of soils, land use, hydrology, infrastructure, and climate were developed using GIS. The Arcview GIS software is used as additive tool to develop supportive data for numerical groundwater flow modeling and integration and presentation of image processing and modeling results. The groundwater flow model was calibrated to simulate future changes in piezometric heads from the period 2006 to 2020. Different scenarios were developed to study the impact of extreme climatic conditions (drought/flood) and variable groundwater abstraction on the regional groundwater system. The model results indicated a significant response in watertable due to external influential factors. The developed model provides an effective tool for evaluating better management options for monitoring future groundwater development in the study area.

Remote sensing of multimodal transportation systems : research brief.

DOT National Transportation Integrated Search

2016-09-01

Remote Sensing of Multimodal Transportation Systems : Rapid condition monitoring and performance evaluations of the vast and vulnerable transportation infrastructure has been elusive. The framework and models developed in this research will enable th...

Pilots' monitoring strategies and performance on automated flight decks: an empirical study combining behavioral and eye-tracking data.

PubMed

Sarter, Nadine B; Mumaw, Randall J; Wickens, Christopher D

2007-06-01

The objective of the study was to examine pilots' automation monitoring strategies and performance on highly automated commercial flight decks. A considerable body of research and operational experience has documented breakdowns in pilot-automation coordination on modern flight decks. These breakdowns are often considered symptoms of monitoring failures even though, to date, only limited and mostly anecdotal data exist concerning pilots' monitoring strategies and performance. Twenty experienced B-747-400 airline pilots flew a 1-hr scenario involving challenging automation-related events on a full-mission simulator. Behavioral, mental model, and eye-tracking data were collected. The findings from this study confirm that pilots monitor basic flight parameters to a much greater extent than visual indications of the automation configuration. More specifically, they frequently fail to verify manual mode selections or notice automatic mode changes. In other cases, they do not process mode annunciations in sufficient depth to understand their implications for aircraft behavior. Low system observability and gaps in pilots' understanding of complex automation modes were shown to contribute to these problems. Our findings describe and explain shortcomings in pilot's automation monitoring strategies and performance based on converging behavioral, eye-tracking, and mental model data. They confirm that monitoring failures are one major contributor to breakdowns in pilot-automation interaction. The findings from this research can inform the design of improved training programs and automation interfaces that support more effective system monitoring.

Regional health workforce monitoring as governance innovation: a German model to coordinate sectoral demand, skill mix and mobility.

PubMed

Kuhlmann, E; Lauxen, O; Larsen, C

2016-11-28

As health workforce policy is gaining momentum, data sources and monitoring systems have significantly improved in the European Union and internationally. Yet data remain poorly connected to policy-making and implementation and often do not adequately support integrated approaches. This brings the importance of governance and the need for innovation into play. The present case study introduces a regional health workforce monitor in the German Federal State of Rhineland-Palatinate and seeks to explore the capacity of monitoring to innovate health workforce governance. The monitor applies an approach from the European Network on Regional Labour Market Monitoring to the health workforce. The novel aspect of this model is an integrated, procedural approach that promotes a 'learning system' of governance based on three interconnected pillars: mixed methods and bottom-up data collection, strong stakeholder involvement with complex communication tools and shared decision- and policy-making. Selected empirical examples illustrate the approach and the tools focusing on two aspects: the connection between sectoral, occupational and mobility data to analyse skill/qualification mixes and the supply-demand matches and the connection between monitoring and stakeholder-driven policy. Regional health workforce monitoring can promote effective governance in high-income countries like Germany with overall high density of health workers but maldistribution of staff and skills. The regional stakeholder networks are cost-effective and easily accessible and might therefore be appealing also to low- and middle-income countries.

Evaluation for Bearing Wear States Based on Online Oil Multi-Parameters Monitoring

PubMed Central

Hu, Hai-Feng

2018-01-01

As bearings are critical components of a mechanical system, it is important to characterize their wear states and evaluate health conditions. In this paper, a novel approach for analyzing the relationship between online oil multi-parameter monitoring samples and bearing wear states has been proposed based on an improved gray k-means clustering model (G-KCM). First, an online monitoring system with multiple sensors for bearings is established, obtaining oil multi-parameter data and vibration signals for bearings through the whole lifetime. Secondly, a gray correlation degree distance matrix is generated using a gray correlation model (GCM) to express the relationship of oil monitoring samples at different times and then a KCM is applied to cluster the matrix. Analysis and experimental results show that there is an obvious correspondence that state changing coincides basically in time between the lubricants’ multi-parameters and the bearings’ wear states. It also has shown that online oil samples with multi-parameters have early wear failure prediction ability for bearings superior to vibration signals. It is expected to realize online oil monitoring and evaluation for bearing health condition and to provide a novel approach for early identification of bearing-related failure modes. PMID:29621175

Evaluation for Bearing Wear States Based on Online Oil Multi-Parameters Monitoring.

PubMed

Wang, Si-Yuan; Yang, Ding-Xin; Hu, Hai-Feng

2018-04-05

As bearings are critical components of a mechanical system, it is important to characterize their wear states and evaluate health conditions. In this paper, a novel approach for analyzing the relationship between online oil multi-parameter monitoring samples and bearing wear states has been proposed based on an improved gray k-means clustering model (G-KCM). First, an online monitoring system with multiple sensors for bearings is established, obtaining oil multi-parameter data and vibration signals for bearings through the whole lifetime. Secondly, a gray correlation degree distance matrix is generated using a gray correlation model (GCM) to express the relationship of oil monitoring samples at different times and then a KCM is applied to cluster the matrix. Analysis and experimental results show that there is an obvious correspondence that state changing coincides basically in time between the lubricants' multi-parameters and the bearings' wear states. It also has shown that online oil samples with multi-parameters have early wear failure prediction ability for bearings superior to vibration signals. It is expected to realize online oil monitoring and evaluation for bearing health condition and to provide a novel approach for early identification of bearing-related failure modes.

Real-Time Hydrology of LID Systems, Rainfall-Runoff Hydrographs, and Modeling

EPA Science Inventory

Continuous monitoring of moisture content within bioretention and permeable pavement systems (porous asphalt and permeable pavers) demonstrate that these systems rarely achieve saturation. This is understandable for the permeable pavement because the watershed area to filter are...

HappyFace as a generic monitoring tool for HEP experiments

NASA Astrophysics Data System (ADS)

Kawamura, Gen; Magradze, Erekle; Musheghyan, Haykuhi; Quadt, Arnulf; Rzehorz, Gerhard

2015-12-01

The importance of monitoring on HEP grid computing systems is growing due to a significant increase in their complexity. Computer scientists and administrators have been studying and building effective ways to gather information on and clarify a status of each local grid infrastructure. The HappyFace project aims at making the above-mentioned workflow possible. It aggregates, processes and stores the information and the status of different HEP monitoring resources into the common database of HappyFace. The system displays the information and the status through a single interface. However, this model of HappyFace relied on the monitoring resources which are always under development in the HEP experiments. Consequently, HappyFace needed to have direct access methods to the grid application and grid service layers in the different HEP grid systems. To cope with this issue, we use a reliable HEP software repository, the CernVM File System. We propose a new implementation and an architecture of HappyFace, the so-called grid-enabled HappyFace. It allows its basic framework to connect directly to the grid user applications and the grid collective services, without involving the monitoring resources in the HEP grid systems. This approach gives HappyFace several advantages: Portability, to provide an independent and generic monitoring system among the HEP grid systems. Eunctionality, to allow users to perform various diagnostic tools in the individual HEP grid systems and grid sites. Elexibility, to make HappyFace beneficial and open for the various distributed grid computing environments. Different grid-enabled modules, to connect to the Ganga job monitoring system and to check the performance of grid transfers among the grid sites, have been implemented. The new HappyFace system has been successfully integrated and now it displays the information and the status of both the monitoring resources and the direct access to the grid user applications and the grid collective services.

Solute Transport Dynamics in a Large Hyporheic Corridor System

NASA Astrophysics Data System (ADS)

Zachara, J. M.; Chen, X.; Murray, C. J.; Shuai, P.; Rizzo, C.; Song, X.; Dai, H.

2016-12-01

A hyporheic corridor is an extended zone of groundwater surface water-interaction that occurs within permeable aquifer sediments in hydrologic continuity with a river. These systems are dynamic and tightly coupled to river stage variations that may occur over variable time scales. Here we describe the behavior of a persistent uranium (U) contaminant plume that exists within the hyporheic corridor of a large, managed river system - the Columbia River. Temporally dense monitoring data were collected for a two year period from wells located within the plume at varying distances up to 400 m from the river shore. Groundwater U originates from desorption of residual U in the lower vadose zone during periods of high river stage and associated elevated water table. U is weakly adsorbed to aquifer sediments because of coarse texture, and along with specific conductance, serves as a tracer of vadose zone source terms, solute transport pathways, and groundwater-surface water mixing. Complex U concentration and specific conductance trends were observed for all wells that varied with distance from the river shoreline and the river hydrograph, although trends for each well were generally repeatable for each year during the monitoring period. Statistical clustering analysis was used to identify four groups of wells that exhibited common trends in dissolved U and specific conductance. A flow and reactive transport code, PFLOTRAN, was implemented within a hydrogeologic model of the groundwater-surface water interaction zone to provide insights on hydrologic processes controlling monitoring trends and cluster behavior. The hydrogeologic model was informed by extensive subsurface characterization, with the spatially variable topography of a basal aquitard being one of several key parameters. Numerical tracer experiments using PFLOTRAN revealed the presence of temporally complex flow trajectories, spatially variable domains of groundwater - river water mixing, and locations of enhanced groundwater - river exchange that helped to explain monitoring trends. Observations and modeling results are integrated into a conceptual model of this highly complex and dynamic system with applicability to hyporheic corridor systems elsewhere.

Transient upset models in computer systems

NASA Technical Reports Server (NTRS)

Mason, G. M.

1983-01-01

Essential factors for the design of transient upset monitors for computers are discussed. The upset is a system level event that is software dependent. It can occur in the program flow, the opcode set, the opcode address domain, the read address domain, and the write address domain. Most upsets are in the program flow. It is shown that simple, external monitors functioning transparently relative to the system operations can be built if a detailed accounting is made of the characteristics of the faults that can happen. Sample applications are provided for different states of the Z-80 and 8085 based system.

Detecting GNSS spoofing attacks using INS coupling

NASA Astrophysics Data System (ADS)

Tanil, Cagatay

Vulnerability of Global Navigation Satellite Systems (GNSS) users to signal spoofing is a critical threat to positioning integrity, especially in aviation applications, where the consequences are potentially catastrophic. In response, this research describes and evaluates a new approach to directly detect spoofing using integrated Inertial Navigation Systems (INS) and fault detection concepts based on integrity monitoring. The monitors developed here can be implemented into positioning systems using INS/GNSS integration via 1) tightly-coupled, 2) loosely-coupled, and 3) uncoupled schemes. New evaluation methods enable the statistical computation of integrity risk resulting from a worst-case spoofing attack - without needing to simulate an unmanageably large number of individual aircraft approaches. Integrity risk is an absolute measure of safety and a well-established metric in aircraft navigation. A novel closed-form solution to the worst-case time sequence of GNSS signals is derived to maximize the integrity risk for each monitor and used in the covariance analyses. This methodology tests the performance of the monitors against the most sophisticated spoofers, capable of tracking the aircraft position - for example, by means of remote tracking or onboard sensing. Another contribution is a comprehensive closed-loop model that encapsulates the vehicle and compensator (estimator and controller) dynamics. A sensitivity analysis uses this model to quantify the leveraging impact of the vehicle's dynamic responses (e.g., to wind gusts, or to autopilot's acceleration commands) on the monitor's detection capability. The performance of the monitors is evaluated for two safety-critical terminal area navigation applications: 1) autonomous shipboard landing and 2) Boeing 747 (B747) landing assisted with Ground Based Augmentation Systems (GBAS). It is demonstrated that for both systems, the monitors are capable of meeting the most stringent precision approach and landing integrity requirements of the International Civil Aviation Organization (ICAO). The statistical evaluation methods developed here can be used as a baseline procedure in the Federal Aviation Administration's (FAA) certification of spoof-free navigation systems. The final contribution is an investigation of INS sensor quality on detection performance. This determines the minimum sensor requirements to perform standalone GNSS positioning in general en route applications with guaranteed spoofing detection integrity.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate.

PubMed

Lee, Henry; Reusser, Deborah A; Olden, Julian D; Smith, Scott S; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S; Piorkowski, Robert J; McPhedran, John

2008-06-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate

USGS Publications Warehouse

Lee, Henry; Reusser, Deborah A.; Olden, Julian D.; Smith, Scott S.; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S.; Piorkowski, Robert J.; Mcphedran, John

2008-01-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change

Forest management under uncertainty for multiple bird population objectives

USGS Publications Warehouse

Moore, C.T.; Plummer, W.T.; Conroy, M.J.; Ralph, C. John; Rich, Terrell D.

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in a set of alternative models. The models generate testable predictions about the response of populations to management, and monitoring data provide the basis for assessing these predictions and informing future management decisions. To illustrate these principles, we examine forest management at the Piedmont National Wildlife Refuge, where management attention is focused on the recovery of the Red-cockaded Woodpecker (Picoides borealis) population. However, managers are also sensitive to the habitat needs of many non-target organisms, including Wood Thrushes (Hylocichla mustelina) and other forest interior Neotropical migratory birds. By simulating several management policies on a set of-alternative forest and bird models, we found a decision policy that maximized a composite response by woodpeckers and Wood Thrushes despite our complete uncertainty regarding system behavior. Furthermore, we used monitoring data to update our measure of belief in each alternative model following one cycle of forest management. This reduction of uncertainty translates into a reallocation of model influence on the choice of optimal decision action at the next decision opportunity.

Energy Performance Monitoring and Optimization System for DoD Campuses

DTIC Science & Technology

2014-02-01

estimated that, on average, the EPMO system exceeded the energy consumption reduction target of 20% and improved occupant thermal comfort by reducing the...dynamic models, operational and thermal comfort constraints, and plant efficiency in the same framework (Borrelli and Keviczky, 2008; Borrelli, Pekar...optimization modeling language uses the models described above in conjunction with information such as: thermal comfort constraints, equipment constraints, and

Federating Cyber and Physical Models for Event-Driven Situational Awareness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stephan, Eric G.; Pawlowski, Ronald A.; Sridhar, Siddharth

The purpose of this paper is to describe a novel method to improve electric power system monitoring and control software application interoperability. This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interface to link all of domain models.

Cost-effective water quality assessment through the integration of monitoring data and modeling results

NASA Astrophysics Data System (ADS)

Lobuglio, Joseph N.; Characklis, Gregory W.; Serre, Marc L.

2007-03-01

Sparse monitoring data and error inherent in water quality models make the identification of waters not meeting regulatory standards uncertain. Additional monitoring can be implemented to reduce this uncertainty, but it is often expensive. These costs are currently a major concern, since developing total maximum daily loads, as mandated by the Clean Water Act, will require assessing tens of thousands of water bodies across the United States. This work uses the Bayesian maximum entropy (BME) method of modern geostatistics to integrate water quality monitoring data together with model predictions to provide improved estimates of water quality in a cost-effective manner. This information includes estimates of uncertainty and can be used to aid probabilistic-based decisions concerning the status of a water (i.e., impaired or not impaired) and the level of monitoring needed to characterize the water for regulatory purposes. This approach is applied to the Catawba River reservoir system in western North Carolina as a means of estimating seasonal chlorophyll a concentration. Mean concentration and confidence intervals for chlorophyll a are estimated for 66 reservoir segments over an 11-year period (726 values) based on 219 measured seasonal averages and 54 model predictions. Although the model predictions had a high degree of uncertainty, integration of modeling results via BME methods reduced the uncertainty associated with chlorophyll estimates compared with estimates made solely with information from monitoring efforts. Probabilistic predictions of future chlorophyll levels on one reservoir are used to illustrate the cost savings that can be achieved by less extensive and rigorous monitoring methods within the BME framework. While BME methods have been applied in several environmental contexts, employing these methods as a means of integrating monitoring and modeling results, as well as application of this approach to the assessment of surface water monitoring networks, represent unexplored areas of research.

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

Remote and terrestrial ground monitoring techniques integration for hazard assessment in mountain areas

NASA Astrophysics Data System (ADS)

Chinellato, Giulia; Kenner, Robert; Iasio, Christian; Mair, Volkmar; Mosna, David; Mulas, Marco; Phillips, Marcia; Strada, Claudia; Zischg, Andreas

2014-05-01

In high mountain regions the choice of appropriate sites for infrastructure such as roads, railways, cable cars or hydropower dams is often very limited. In parallel, the increasing demand for supply infrastructure in the Alps induces a continuous transformation of the territory. The new role played by the precautionary monitoring in the risk governance becomes fundamental and may overcome the modeling of future events, which represented so far the predominant approach to these sort of issues. Furthermore the consequence of considering methodologies alternative to those more exclusive allow to reduce costs and increasing the frequency of measurements, updating continuously the cognitive framework of existing hazard condition in most susceptible territories. The scale factor of the observed area and the multiple purpose of such regional ordinary surveys make it convenient to adopt Radar Satellite-based systems, but they need to be integrated with terrestrial systems for validation and eventual early warning purposes. Significant progress over the past decade in Remote Sensing (RS), Proximal Sensing and integration-based sensor networks systems now provide technologies, that allow to implement monitoring systems for ordinary surveys of extensive areas or regions, which are affected by active natural processes and slope instability. The Interreg project SloMove aims to provide solutions for such challenges and focuses on using remote sensing monitoring techniques for the monitoring of mass movements in two test sites, in South Tyrol (Italy) and in Grisons Canton (Switzerland). The topics faced in this project concern mass movements and slope deformation monitoring techniques, focusing mainly on the integration of multi-temporal interferometry, new generation of terrestrial technologies for differential digital terrain model elaboration provided by laser scanner (TLS), and GNSS-based topographic surveys, which are used not only for validation purpose, but also for adding value and information to the whole monitoring survey. The test sites are currently observed by an original integrated methodology specifically developed within the aim of the project. The integrated monitoring design includes reference targets for the different monitoring systems placed together on the same point or rigid foundation, to facilitate the comparison of the data and, in the operational use, to be able to switch consistently from one to the other system. The principal goal of the project is to define a shared procedure to select scalable technologies, best practices and institutional action plans more adequate to deal with different sort of hazard related to ground displacement, in densely populated mountain areas containing recreational and critical infrastructures. Keywords: integrated monitoring, multi-temporal interferometry, artificial reflectors; mass movement, SloMove.eu

Design, Development, Test, and Evaluation of Atmosphere Revitalization and Environmental Monitoring Systems for Long Duration Missions

NASA Technical Reports Server (NTRS)

Roman, Monsi C.; Perry, Jay L.; Jan, Darrell L.

2012-01-01

The Advanced Exploration Systems Program's Atmosphere Resource Recovery and Environmental Monitoring (ARREM) project is working to mature optimum atmosphere revitalization and environmental monitoring system architectures. It is the project's objective to enable exploration beyond Lower Earth Orbit (LEO) and improve affordability by focusing on three primary goals: 1) achieving high reliability, 2) reducing dependence on a ground-based logistics resupply model, and 3) maximizing commonality between atmosphere revitalization subsystem components and those needed to support other exploration elements. The ARREM project's strengths include using existing developmental hardware and testing facilities, when possible, and and a well-coordinated effort among the NASA field centers that contributed to past ARS and EMS technology development projects.

Multileaf collimator performance monitoring and improvement using semiautomated quality control testing and statistical process control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Létourneau, Daniel, E-mail: daniel.letourneau@rmp.uh.on.ca; McNiven, Andrea; Keller, Harald

2014-12-15

Purpose: High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. Methods:more » The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3–4 times/week over a period of 10–11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ±0.5 and ±1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. Results: The precision of the MLC performance monitoring QC test and the MLC itself was within ±0.22 mm for most MLC leaves and the majority of the apparent leaf motion was attributed to beam spot displacements between irradiations. The MLC QC test was performed 193 and 162 times over the monitoring period for the studied units and recalibration had to be repeated up to three times on one of these units. For both units, rate of MLC interlocks was moderately associated with MLC servicing events. The strongest association with the MLC performance was observed between the MLC servicing events and the total number of out-of-control leaves. The average elapsed time for which the number of out-of-specification or out-of-control leaves was within a given performance threshold was computed and used to assess adequacy of MLC test frequency. Conclusions: A MLC performance monitoring system has been developed and implemented to acquire high-quality QC data at high frequency. This is enabled by the relatively short acquisition time for the images and automatic image analysis. The monitoring system was also used to record and track the rate of MLC-related interlocks and servicing events. MLC performances for two commercially available MLC models have been assessed and the results support monthly test frequency for widely accepted ±1 mm specifications. Higher QC test frequency is however required to maintain tighter specification and in-control behavior.« less

Automated monitoring of medical protocols: a secure and distributed architecture.

PubMed

Alsinet, T; Ansótegui, C; Béjar, R; Fernández, C; Manyà, F

2003-03-01

The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

Hydrological information system based on on-line monitoring--from strategy to implementation in the Brantas River Basin, East Java, Indonesia.

PubMed

Marini, G W; Wellguni, H

2003-01-01

The worsening environmental situation of the Brantas River, East Java, is addressed by a comprehensive basin management strategy which relies on accurate water quantity and quality data retrieved from a newly installed online monitoring network. Integrated into a Hydrological Information System, the continuously measured indicative parameters allow early warning, control and polluter identification. Additionally, long-term analyses have been initiated for improving modelling applications like flood forecasting, water resource management and pollutant propagation. Preliminary results illustrate the efficiency of the installed system.

Self-calibrating models for dynamic monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1994-01-01

The present goal in qualitative reasoning is to develop methods for automatically building qualitative and semiquantitative models of dynamic systems and to use them for monitoring and fault diagnosis. The qualitative approach to modeling provides a guarantee of coverage while our semiquantitative methods support convergence toward a numerical model as observations are accumulated. We have developed and applied methods for automatic creation of qualitative models, developed two methods for obtaining tractable results on problems that were previously intractable for qualitative simulation, and developed more powerful methods for learning semiquantitative models from observations and deriving semiquantitative predictions from them. With these advances, qualitative reasoning comes significantly closer to realizing its aims as a practical engineering method.

Development of real-time voltage stability monitoring tool for power system transmission network using Synchrophasor data

NASA Astrophysics Data System (ADS)

Pulok, Md Kamrul Hasan

Intelligent and effective monitoring of power system stability in control centers is one of the key issues in smart grid technology to prevent unwanted power system blackouts. Voltage stability analysis is one of the most important requirements for control center operation in smart grid era. With the advent of Phasor Measurement Unit (PMU) or Synchrophasor technology, real time monitoring of voltage stability of power system is now a reality. This work utilizes real-time PMU data to derive a voltage stability index to monitor the voltage stability related contingency situation in power systems. The developed tool uses PMU data to calculate voltage stability index that indicates relative closeness of the instability by producing numerical indices. The IEEE 39 bus, New England power system was modeled and run on a Real-time Digital Simulator that stream PMU data over the Internet using IEEE C37.118 protocol. A Phasor data concentrator (PDC) is setup that receives streaming PMU data and stores them in Microsoft SQL database server. Then the developed voltage stability monitoring (VSM) tool retrieves phasor measurement data from SQL server, performs real-time state estimation of the whole network, calculate voltage stability index, perform real-time ranking of most vulnerable transmission lines, and finally shows all the results in a graphical user interface. All these actions are done in near real-time. Control centers can easily monitor the systems condition by using this tool and can take precautionary actions if needed.

General Purpose Data-Driven Monitoring for Space Operations

NASA Technical Reports Server (NTRS)

Iverson, David L.; Martin, Rodney A.; Schwabacher, Mark A.; Spirkovska, Liljana; Taylor, William McCaa; Castle, Joseph P.; Mackey, Ryan M.

2009-01-01

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Observation and integrated Earth-system science: A roadmap for 2016-2025

NASA Astrophysics Data System (ADS)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, Venkatachalam; Trenberth, Kevin; Asrar, Ghassem; Balmaseda, Magdalena; Burrows, John P.; Ciais, Philippe; Drinkwater, Mark; Friedlingstein, Pierre; Gobron, Nadine; Guilyardi, Eric; Halpern, David; Heimann, Martin; Johannessen, Johnny; Levelt, Pieternel F.; Lopez-Baeza, Ernesto; Penner, Joyce; Scholes, Robert; Shepherd, Ted

2016-05-01

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types of observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016-2025 and some of the issues to be faced. Observations that are organised on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation.

Observation and integrated Earth-system science: A roadmap for 2016–2025

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, V.

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types ofmore » observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016–2025 and some of the issues to be faced. Observations that are organized on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation.« less

Specification and Verification of Medical Monitoring System Using Petri-nets.

PubMed

Majma, Negar; Babamir, Seyed Morteza

2014-07-01

To monitor the patient behavior, data are collected from patient's body by a medical monitoring device so as to calculate the output using embedded software. Incorrect calculations may endanger the patient's life if the software fails to meet the patient's requirements. Accordingly, the veracity of the software behavior is a matter of concern in the medicine; moreover, the data collected from the patient's body are fuzzy. Some methods have already dealt with monitoring the medical monitoring devices; however, model based monitoring fuzzy computations of such devices have been addressed less. The present paper aims to present synthesizing a fuzzy Petri-net (FPN) model to verify behavior of a sample medical monitoring device called continuous infusion insulin (INS) because Petri-net (PN) is one of the formal and visual methods to verify the software's behavior. The device is worn by the diabetic patients and then the software calculates the INS dose and makes a decision for injection. The input and output of the infusion INS software are not crisp in the real world; therefore, we present them in fuzzy variables. Afterwards, we use FPN instead of clear PN to model the fuzzy variables. The paper follows three steps to synthesize an FPN to deal with verification of the infusion INS device: (1) Definition of fuzzy variables, (2) definition of fuzzy rules and (3) design of the FPN model to verify the software behavior.

Progress and lessons learned from water-quality monitoring networks

USGS Publications Warehouse

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

A Leak Monitor for Industry

NASA Technical Reports Server (NTRS)

1996-01-01

GenCorp Aerojet Industrial Products, Lewis Research Center, Marshall Space Flight Center, and Case Western Reserve University developed a gas leak detection system, originally for use with the Space Shuttle propulsion system and reusable launch vehicles. The Model HG200 Automated Gas Leak Detection System has miniaturized sensors that can identify extremely low concentrations of hydrogen without requiring oxygen. A microprocessor-based hardware/software system monitors the sensors and displays the source and magnitude of hydrogen leaks in real time. The system detects trace hydrogen around pipes, connectors, flanges and pressure tanks, and has been used by Ford Motor Company in the production of a natural gas-powered car.

NASA Integrated Network Monitor and Control Software Architecture

NASA Technical Reports Server (NTRS)

Shames, Peter; Anderson, Michael; Kowal, Steve; Levesque, Michael; Sindiy, Oleg; Donahue, Kenneth; Barnes, Patrick

2012-01-01

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation office (SCaN) has commissioned a series of trade studies to define a new architecture intended to integrate the three existing networks that it operates, the Deep Space Network (DSN), Space Network (SN), and Near Earth Network (NEN), into one integrated network that offers users a set of common, standardized, services and interfaces. The integrated monitor and control architecture utilizes common software and common operator interfaces that can be deployed at all three network elements. This software uses state-of-the-art concepts such as a pool of re-programmable equipment that acts like a configurable software radio, distributed hierarchical control, and centralized management of the whole SCaN integrated network. For this trade space study a model-based approach using SysML was adopted to describe and analyze several possible options for the integrated network monitor and control architecture. This model was used to refine the design and to drive the costing of the four different software options. This trade study modeled the three existing self standing network elements at point of departure, and then described how to integrate them using variations of new and existing monitor and control system components for the different proposed deployments under consideration. This paper will describe the trade space explored, the selected system architecture, the modeling and trade study methods, and some observations on useful approaches to implementing such model based trade space representation and analysis.

Vaccine safety monitoring systems in developing countries: an example of the Vietnam model.

PubMed

Ali, Mohammad; Rath, Barbara; Thiem, Vu Dinh

2015-01-01

Only few health intervention programs have been as successful as vaccination programs with respect to preventing morbidity and mortality in developing countries. However, the success of a vaccination program is threatened by rumors and misunderstanding about the risks of vaccines. It is short-sighted to plan the introduction of vaccines into developing countries unless effective vaccine safety monitoring systems are in place. Such systems that track adverse events following immunization (AEFI) is currently lacking in most developing countries. Therefore, any rumor may affect the entire vaccination program. Public health authorities should implement the safety monitoring system of vaccines, and disseminate safety issues in a proactive mode. Effective safety surveillance systems should allow for the conduct of both traditional and alternative epidemiologic studies through the use of prospective data sets. The vaccine safety data link implemented in Vietnam in mid-2002 indicates that it is feasible to establish a vaccine safety monitoring system for the communication of vaccine safety in developing countries. The data link provided the investigators an opportunity to evaluate AEFI related to measles vaccine. Implementing such vaccine safety monitoring system is useful in all developing countries. The system should be able to make objective and clear communication regarding safety issues of vaccines, and the data should be reported to the public on a regular basis for maintaining their confidence in vaccination programs.