Evaluation of the response of tritium-in-air instrumentation to HT in dry and humid conditions and to HTO vapor

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

Phillips, H.; Dean, J.; Privas, E.

2015-03-15

Nuclear plant operators (power generation, decommissioning and reprocessing operations) are required to monitor releases of tritium species for regulatory compliance and radiation protection purposes. Tritium monitoring is performed using tritium-in-air gas monitoring instrumentation based either on flow-through ion chambers or proportional counting systems. Tritium-in-air monitors are typically calibrated in dry conditions but in service may operate at elevated levels of relative humidity. The NPL (National Physical Laboratory) radioactive gas-in-air calibration system has been used to study the effect of humidity on the response to tritium of two tritium-in-air ion chamber based monitors and one proportional counting system which uses amore » P10/air gas mixture. The response of these instruments to HTO vapour has also been evaluated. In each case, instrument responses were obtained for HT in dry conditions (relative humidity (RH) about 2%), HT in 45% RH, and finally HTO at 45% RH. Instrumentation response to HT in humid conditions has been found to slightly exceed that in dry conditions. (authors)« less

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

Health Monitoring System for Car Seat

NASA Technical Reports Server (NTRS)

Elrod, Susan Vinz (Inventor); Dabney, Richard W. (Inventor)

2004-01-01

A health monitoring system for use with a child car seat has sensors mounted in the seat to monitor one or more health conditions of the seat's occupant. A processor monitors the sensor's signals and generates status signals related to the monitored conditions. A transmitter wireless transmits the status signals to a remotely located receiver. A signaling device coupled to the receiver produces at least one sensory (e.g., visual, audible, tactile) output based on the status signals.

On-line Monitoring for Cutting Tool Wear Condition Based on the Parameters

NASA Astrophysics Data System (ADS)

Han, Fenghua; Xie, Feng

2017-07-01

In the process of cutting tools, it is very important to monitor the working state of the tools. On the basis of acceleration signal acquisition under the constant speed, time domain and frequency domain analysis of relevant indicators monitor the online of tool wear condition. The analysis results show that the method can effectively judge the tool wear condition in the process of machining. It has certain application value.

Utilization of wireless structural health monitoring as decision making tools for a condition and reliability-based assessment of railroad bridges

NASA Astrophysics Data System (ADS)

Flanigan, Katherine A.; Johnson, Nephi R.; Hou, Rui; Ettouney, Mohammed; Lynch, Jerome P.

2017-04-01

The ability to quantitatively assess the condition of railroad bridges facilitates objective evaluation of their robustness in the face of hazard events. Of particular importance is the need to assess the condition of railroad bridges in networks that are exposed to multiple hazards. Data collected from structural health monitoring (SHM) can be used to better maintain a structure by prompting preventative (rather than reactive) maintenance strategies and supplying quantitative information to aid in recovery. To that end, a wireless monitoring system is validated and installed on the Harahan Bridge which is a hundred-year-old long-span railroad truss bridge that crosses the Mississippi River near Memphis, TN. This bridge is exposed to multiple hazards including scour, vehicle/barge impact, seismic activity, and aging. The instrumented sensing system targets non-redundant structural components and areas of the truss and floor system that bridge managers are most concerned about based on previous inspections and structural analysis. This paper details the monitoring system and the analytical method for the assessment of bridge condition based on automated data-driven analyses. Two primary objectives of monitoring the system performance are discussed: 1) monitoring fatigue accumulation in critical tensile truss elements; and 2) monitoring the reliability index values associated with sub-system limit states of these members. Moreover, since the reliability index is a scalar indicator of the safety of components, quantifiable condition assessment can be used as an objective metric so that bridge owners can make informed damage mitigation strategies and optimize resource management on single bridge or network levels.

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.

PROBABILITY SURVEYS , CONDITIONAL PROBABILITIES AND ECOLOGICAL RISK ASSESSMENT

EPA Science Inventory

We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...

PROBABILITY SURVEYS, CONDITIONAL PROBABILITIES, AND ECOLOGICAL RISK ASSESSMENT

EPA Science Inventory

We show that probability-based environmental resource monitoring programs, such as U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Asscssment Program EMAP) can be analyzed with a conditional probability analysis (CPA) to conduct quantitative probabi...

Health Monitoring and Management for Manufacturing Workers in Adverse Working Conditions.

PubMed

Xu, Xiaoya; Zhong, Miao; Wan, Jiafu; Yi, Minglun; Gao, Tiancheng

2016-10-01

In adverse working conditions, environmental parameters such as metallic dust, noise, and environmental temperature, directly affect the health condition of manufacturing workers. It is therefore important to implement health monitoring and management based on important physiological parameters (e.g., heart rate, blood pressure, and body temperature). In recent years, new technologies, such as body area networks, cloud computing, and smart clothing, have allowed the improvement of the quality of services. In this article, we first give five-layer architecture for health monitoring and management of manufacturing workers. Then, we analyze the system implementation process, including environmental data processing, physical condition monitoring and system services and management, and present the corresponding algorithms. Finally, we carry out an evaluation and analysis from the perspective of insurance and compensation for manufacturing workers in adverse working conditions. The proposed scheme will contribute to the improvement of workplace conditions, realize health monitoring and management, and protect the interests of manufacturing workers.

Knowledge based ranking algorithm for comparative assessment of post-closure care needs of closed landfills.

PubMed

Sizirici, Banu; Tansel, Berrin; Kumar, Vivek

2011-06-01

Post-closure care (PCC) activities at landfills include cap maintenance; water quality monitoring; maintenance and monitoring of the gas collection/control system, leachate collection system, groundwater monitoring wells, and surface water management system; and general site maintenance. The objective of this study was to develop an integrated data and knowledge based decision making tool for preliminary estimation of PCC needs at closed landfills. To develop the decision making tool, 11 categories of parameters were identified as critical areas which could affect future PCC needs. Each category was further analyzed by detailed questions which could be answered with limited data and knowledge about the site, its history, location, and site specific characteristics. Depending on the existing knowledge base, a score was assigned to each question (on a scale 1-10, as 1 being the best and 10 being the worst). Each category was also assigned a weight based on its relative importance on the site conditions and PCC needs. The overall landfill score was obtained from the total weighted sum attained. Based on the overall score, landfill conditions could be categorized as critical, acceptable, or good. Critical condition indicates that the landfill may be a threat to the human health and the environment and necessary steps should be taken. Acceptable condition indicates that the landfill is currently stable and the monitoring should be continued. Good condition indicates that the landfill is stable and the monitoring activities can be reduced in the future. The knowledge base algorithm was applied to two case study landfills for preliminary assessment of PCC performance. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quaternion Based Thermal Condition Monitoring System

NASA Astrophysics Data System (ADS)

Wong, Wai Kit; Loo, Chu Kiong; Lim, Way Soong; Tan, Poi Ngee

In this paper, we will propose a new and effective machine condition monitoring system using log-polar mapper, quaternion based thermal image correlator and max-product fuzzy neural network classifier. Two classification characteristics namely: peak to sidelobe ratio (PSR) and real to complex ratio of the discrete quaternion correlation output (p-value) are applied in the proposed machine condition monitoring system. Large PSR and p-value observe in a good match among correlation of the input thermal image with a particular reference image, while small PSR and p-value observe in a bad/not match among correlation of the input thermal image with a particular reference image. In simulation, we also discover that log-polar mapping actually help solving rotation and scaling invariant problems in quaternion based thermal image correlation. Beside that, log-polar mapping can have a two fold of data compression capability. Log-polar mapping can help smoother up the output correlation plane too, hence makes a better measurement way for PSR and p-values. Simulation results also show that the proposed system is an efficient machine condition monitoring system with accuracy more than 98%.

A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

PubMed Central

Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

2017-01-01

The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components. PMID:28524088

Probability Surveys, Conditional Probability, and Ecological Risk Assessment

EPA Science Inventory

We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency’s (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...

Monitoring growth condition of spring maize in Northeast China using a process-based model

NASA Astrophysics Data System (ADS)

Wang, Peijuan; Zhou, Yuyu; Huo, Zhiguo; Han, Lijuan; Qiu, Jianxiu; Tan, Yanjng; Liu, Dan

2018-04-01

Early and accurate assessment of the growth condition of spring maize, a major crop in China, is important for the national food security. This study used a process-based Remote-Sensing-Photosynthesis-Yield Estimation for Crops (RS-P-YEC) model, driven by satellite-derived leaf area index and ground-based meteorological observations, to simulate net primary productivity (NPP) of spring maize in Northeast China from the first ten-day (FTD) of May to the second ten-day (STD) of August during 2001-2014. The growth condition of spring maize in 2014 in Northeast China was monitored and evaluated spatially and temporally by comparison with 5- and 13-year averages, as well as 2009 and 2013. Results showed that NPP simulated by the RS-P-YEC model, with consideration of multi-scattered radiation inside the crop canopy, could reveal the growth condition of spring maize more reasonably than the Boreal Ecosystem Productivity Simulator. Moreover, NPP outperformed other commonly used vegetation indices (e.g., Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) for monitoring and evaluating the growth condition of spring maize. Compared with the 5- and 13-year averages, the growth condition of spring maize in 2014 was worse before the STD of June and after the FTD of August, and it was better from the third ten-day (TTD) of June to the TTD of July across Northeast China. Spatially, regions with slightly worse and worse growth conditions in the STD of August 2014 were concentrated mainly in central Northeast China, and they accounted for about half of the production area of spring maize in Northeast China. This study confirms that NPP is a good indicator for monitoring and evaluating growth condition because of its capacity to reflect the physiological characteristics of crops. Meanwhile, the RS-P-YEC model, driven by remote sensing and ground-based meteorological data, is effective for monitoring crop growth condition over large areas in a near real time.

A NATIONAL COASTAL ASSESSMENT OF COASTAL SEDIMENT CONDITION

EPA Science Inventory

One element of the Environmental Monitoring and Assessment Program's National Coastal Assessment is to estimate the current status, extent, changes and trends in the condition of the Nation's coastal sediments on a national basis. Based on NCA monitoring activities from 1999-2001...

Crack propagation monitoring in a full-scale aircraft fatigue test based on guided wave-Gaussian mixture model

NASA Astrophysics Data System (ADS)

Qiu, Lei; Yuan, Shenfang; Bao, Qiao; Mei, Hanfei; Ren, Yuanqiang

2016-05-01

For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a full-scale aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback-Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the full-scale aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.

The Monitoring Case of Ground-Based Synthetic Aperture Radar with Frequency Modulated Continuous Wave System

NASA Astrophysics Data System (ADS)

Zhang, H. Y.; Zhai, Q. P.; Chen, L.; Liu, Y. J.; Zhou, K. Q.; Wang, Y. S.; Dou, Y. D.

2017-09-01

The features of the landslide geological disaster are wide distribution, variety, high frequency, high intensity, destructive and so on. It has become a natural disaster with harmful and wide range of influence. The technology of ground-based synthetic aperture radar is a novel deformation monitoring technology developed in recent years. The features of the technology are large monitoring area, high accuracy, long distance without contact and so on. In this paper, fast ground-based synthetic aperture radar (Fast-GBSAR) based on frequency modulated continuous wave (FMCW) system is used to collect the data of Ma Liuzui landslide in Chongqing. The device can reduce the atmospheric errors caused by rapidly changing environment. The landslide deformation can be monitored in severe weather conditions (for example, fog) by Fast-GBSAR with acquisition speed up to 5 seconds per time. The data of Ma Liuzui landslide in Chongqing are analyzed in this paper. The result verifies that the device can monitor landslide deformation under severe weather conditions.

Self-Monitoring and Reactivity in the Modification of Cigarette Smoking.

ERIC Educational Resources Information Center

Abrams, David B.; Wilson, G. Terence

1979-01-01

Subjects were assigned to conditions based on smoking rates: self-monitoring nicotine plus health hazard information; self-monitoring cigarettes plus health information; and self-monitoring cigarettes with no health information. Nicotine self-monitoring groups showed greater reactivity. Exposure to health hazard information had no effect. (Author)

Monitoring network-design influence on assessment of ecological condition in wadeable streams

EPA Science Inventory

We investigated outcomes of three monitoring networks for assessing ecological character and condition of wadeable streams in the Waikato region, New Zealand. Sites were selected 1) based on a professional judgment network, 2) within categories of stream and watershed characteris...

A Wavelet-Based Methodology for Grinding Wheel Condition Monitoring

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

Liao, T. W.; Ting, C.F.; Qu, Jun

2007-01-01

Grinding wheel surface condition changes as more material is removed. This paper presents a wavelet-based methodology for grinding wheel condition monitoring based on acoustic emission (AE) signals. Grinding experiments in creep feed mode were conducted to grind alumina specimens with a resinoid-bonded diamond wheel using two different conditions. During the experiments, AE signals were collected when the wheel was 'sharp' and when the wheel was 'dull'. Discriminant features were then extracted from each raw AE signal segment using the discrete wavelet decomposition procedure. An adaptive genetic clustering algorithm was finally applied to the extracted features in order to distinguish differentmore » states of grinding wheel condition. The test results indicate that the proposed methodology can achieve 97% clustering accuracy for the high material removal rate condition, 86.7% for the low material removal rate condition, and 76.7% for the combined grinding conditions if the base wavelet, the decomposition level, and the GA parameters are properly selected.« less

Use of email and telephone prompts to increase self-monitoring in a Web-based intervention: randomized controlled trial.

PubMed

Greaney, Mary L; Sprunck-Harrild, Kim; Bennett, Gary G; Puleo, Elaine; Haines, Jess; Viswanath, K Vish; Emmons, Karen M

2012-07-27

Self-monitoring is a key behavior change mechanism associated with sustained health behavior change. Although Web-based interventions can offer user-friendly approaches for self-monitoring, engagement with these tools is suboptimal. Increased use could encourage, promote, and sustain behavior change. To determine whether email prompts or email plus telephone prompts increase self-monitoring of behaviors on a website created for a multiple cancer risk reduction program. We recruited and enrolled participants (N = 100) in a Web-based intervention during a primary care well visit at an urban primary care health center. The frequency of daily self-monitoring was tracked on the study website. Participants who tracked at least one behavior 3 or more times during week 1 were classified as meeting the tracking threshold and were assigned to the observation-only group (OO, n = 14). This group was followed but did not receive prompts. Participants who did not meet the threshold during week 1 were randomly assigned to one of 2 prompting conditions: automated assistance (AA, n = 36) or automated assistance + calls (AAC, n = 50). During prompting periods (weeks 2-3), participants in the AA and AAC conditions received daily automated emails that encouraged tracking and two tailored self-monitoring reports (end of week 2, end of week 3) that provided feedback on tracking frequency. Individuals in the AAC condition also received two technical assistance calls from trained study staff. Frequency of self-monitoring was tracked from week 2 through week 17. Self-monitoring rates increased in both intervention conditions during prompting and declined when prompting ceased. Over the 16 weeks of observation, there was a significant between-group difference in the percentage who met the self-monitoring threshold each week, with better maintenance in the AAC than in the AA condition (P < .001). Self-monitoring rates were greater in the OO group than in either the AA or AAC condition (P < .001). Prompting can increase self-monitoring rates. The decrease in self-monitoring after the promoting period suggests that additional reminder prompts would be useful. The use of technical assistance calls appeared to have a greater effect in promoting self-monitoring at a therapeutic threshold than email reminders and the tailored self-monitoring reports alone. ClinicalTrials.gov NCT01415492; http://clinicaltrials.gov/ct2/show/NCT01415492 (Archived by WebCite at http://www.webcitation.org/68LOXOMe2).

Instrument for analysis of electric motors based on slip-poles component

DOEpatents

Haynes, Howard D.; Ayers, Curtis W.; Casada, Donald A.

1996-01-01

A new instrument for monitoring the condition and speed of an operating electric motor from a remote location. The slip-poles component is derived from a motor current signal. The magnitude of the slip-poles component provides the basis for a motor condition monitor, while the frequency of the slip-poles component provides the basis for a motor speed monitor. The result is a simple-to-understand motor health monitor in an easy-to-use package. Straightforward indications of motor speed, motor running current, motor condition (e.g., rotor bar condition) and synthesized motor sound (audible indication of motor condition) are provided. With the device, a relatively untrained worker can diagnose electric motors in the field without requiring the presence of a trained engineer or technician.

Instrument for analysis of electric motors based on slip-poles component

DOEpatents

Haynes, H.D.; Ayers, C.W.; Casada, D.A.

1996-11-26

A new instrument is described for monitoring the condition and speed of an operating electric motor from a remote location. The slip-poles component is derived from a motor current signal. The magnitude of the slip-poles component provides the basis for a motor condition monitor, while the frequency of the slip-poles component provides the basis for a motor speed monitor. The result is a simple-to-understand motor health monitor in an easy-to-use package. Straightforward indications of motor speed, motor running current, motor condition (e.g., rotor bar condition) and synthesized motor sound (audible indication of motor condition) are provided. With the device, a relatively untrained worker can diagnose electric motors in the field without requiring the presence of a trained engineer or technician. 4 figs.

Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops.

PubMed

Zhang, Cunji; Yao, Xifan; Zhang, Jianming

2015-12-03

Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi(®) Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops.

Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops

PubMed Central

Zhang, Cunji; Yao, Xifan; Zhang, Jianming

2015-01-01

Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi® Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops. PMID:26633418

Self-Monitoring Using Continuous Glucose Monitors with Real-Time Feedback Improves Exercise Adherence in Individuals with Impaired Blood Glucose: A Pilot Study.

PubMed

Bailey, Kaitlyn J; Little, Jonathan P; Jung, Mary E

2016-03-01

Exercise helps individuals with prediabetes or type 2 diabetes (T2D) manage their blood glucose (BG); however, exercise adherence in this population is dismal. In this pilot study we tested the efficacy of a self-monitoring group-based intervention using continuous glucose monitors (CGMs) at increasing exercise adherence in individuals with impaired BG. Thirteen participants with prediabetes or T2D were randomized to an 8-week standard care exercise program (CON condition) (n = 7) or self-monitoring exercise intervention (SM condition) (n = 6). Participants in the SM condition were taught how to self-monitor their exercise and BG, to goal set, and to use CGM to observe how exercise influences BG. We hypothesized that compared with the CON condition, using a real-time CGM would facilitate self-monitoring behavior, resulting in increased exercise adherence. Repeated-measures analysis of variance revealed significant Condition × Time interactions for self-monitoring (P < 0.01), goal setting (P = 0.01), and self-efficacy to self-monitor (P = 0.01), such that the SM condition showed greater increases in these outcomes immediately after the program and at the 1-month follow-up compared with the CON condition. The SM condition had higher program attendance rates (P = 0.03), and a greater proportion of participants reregistered for additional exercise programs (P = 0.048) compared with the CON condition. Participants in both conditions experienced improvements in health-related quality of life, waist circumference, and fitness (P values <0.05). These findings provide promising initial support for the use of a real-time CGM to foster self-monitoring and exercise behavior in individuals living with prediabetes or T2D.

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

Ramuhalli, Pradeep; Hirt, Evelyn H.; Dib, Gerges

This project involved the development of enhanced risk monitors (ERMs) for active components in Advanced Reactor (AdvRx) designs by integrating real-time information about equipment condition with risk monitors. Health monitoring techniques in combination with predictive estimates of component failure based on condition and risk monitors can serve to indicate the risk posed by continued operation in the presence of detected degradation. This combination of predictive health monitoring based on equipment condition assessment and risk monitors can also enable optimization of maintenance scheduling with respect to the economics of plant operation. This report summarizes PNNL’s multi-year project on the development andmore » evaluation of an ERM concept for active components while highlighting FY2016 accomplishments. Specifically, this report provides a status summary of the integration and demonstration of the prototypic ERM framework with the plant supervisory control algorithms being developed at Oak Ridge National Laboratory (ORNL), and describes additional case studies conducted to assess sensitivity of the technology to different quantities. Supporting documentation on the software package to be provided to ONRL is incorporated in this report.« less

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.

Online Condition Monitoring of a Rail Fastening System on High-Speed Railways Based on Wavelet Packet Analysis

PubMed Central

Wei, Jiahong; Liu, Chong; Ren, Tongqun; Liu, Haixia; Zhou, Wenjing

2017-01-01

The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management. PMID:28208732

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.

An Improved Gaussian Mixture Model for Damage Propagation Monitoring of an Aircraft Wing Spar under Changing Structural Boundary Conditions.

PubMed

Qiu, Lei; Yuan, Shenfang; Mei, Hanfei; Fang, Fang

2016-02-26

Structural Health Monitoring (SHM) technology is considered to be a key technology to reduce the maintenance cost and meanwhile ensure the operational safety of aircraft structures. It has gradually developed from theoretic and fundamental research to real-world engineering applications in recent decades. The problem of reliable damage monitoring under time-varying conditions is a main issue for the aerospace engineering applications of SHM technology. Among the existing SHM methods, Guided Wave (GW) and piezoelectric sensor-based SHM technique is a promising method due to its high damage sensitivity and long monitoring range. Nevertheless the reliability problem should be addressed. Several methods including environmental parameter compensation, baseline signal dependency reduction and data normalization, have been well studied but limitations remain. This paper proposes a damage propagation monitoring method based on an improved Gaussian Mixture Model (GMM). It can be used on-line without any structural mechanical model and a priori knowledge of damage and time-varying conditions. With this method, a baseline GMM is constructed first based on the GW features obtained under time-varying conditions when the structure under monitoring is in the healthy state. When a new GW feature is obtained during the on-line damage monitoring process, the GMM can be updated by an adaptive migration mechanism including dynamic learning and Gaussian components split-merge. The mixture probability distribution structure of the GMM and the number of Gaussian components can be optimized adaptively. Then an on-line GMM can be obtained. Finally, a best match based Kullback-Leibler (KL) divergence is studied to measure the migration degree between the baseline GMM and the on-line GMM to reveal the weak cumulative changes of the damage propagation mixed in the time-varying influence. A wing spar of an aircraft is used to validate the proposed method. The results indicate that the crack propagation under changing structural boundary conditions can be monitored reliably. The method is not limited by the properties of the structure, and thus it is feasible to be applied to composite structure.

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.

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.

The Structure Design of Piezoelectric Poly(vinylidene Fluoride) (PVDF) Polymer-Based Sensor Patch for the Respiration Monitoring under Dynamic Walking Conditions.

PubMed

Lei, Kin-Fong; Hsieh, Yi-Zheng; Chiu, Yi-Yuan; Wu, Min-Hsien

2015-07-31

This study reports a piezoelectric poly(vinylidene fluoride) (PVDF) polymer-based sensor patch for respiration detections in dynamic walking condition. The working mechanism of respiration signal generation is based on the periodical deformations on a human chest wall during the respiratory movements, which in turn mechanically stretch the piezoelectric PVDF film to generate the corresponding electrical signals. In this study, the PVDF sensing film was completely encapsulated within the sensor patch forming a mass-spring-damper mechanical system to prevent the noises generated in a dynamic condition. To verify the design of sensor patch to prevent dynamic noises, experimental investigations were carried out. Results demonstrated the respiration signals generated and the respiratory rates measured by the proposed sensor patch were in line with the same measurements based on a commercial respiratory effort transducer both in a static (e.g., sitting) or dynamic (e.g., walking) condition. As a whole, this study has developed a PVDF-based sensor patch which is capable of monitoring respirations in a dynamic walking condition with high fidelity. Other distinctive features include its small size, light weight, ease of use, low cost, and portability. All these make it a promising sensing device to monitor respirations particularly in home care units.

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.

Are we missing the boat? Current uses of long-term biological monitoring data in the evaluation and management of marine protected areas.

PubMed

Addison, P F E; Flander, L B; Cook, C N

2015-02-01

Protected area management agencies are increasingly using management effectiveness evaluation (MEE) to better understand, learn from and improve conservation efforts around the globe. Outcome assessment is the final stage of MEE, where conservation outcomes are measured to determine whether management objectives are being achieved. When quantitative monitoring data are available, best-practice examples of outcome assessments demonstrate that data should be assessed against quantitative condition categories. Such assessments enable more transparent and repeatable integration of monitoring data into MEE, which can promote evidence-based management and improve public accountability and reporting. We interviewed key informants from marine protected area (MPA) management agencies to investigate how scientific data sources, especially long-term biological monitoring data, are currently informing conservation management. Our study revealed that even when long-term monitoring results are available, management agencies are not using them for quantitative condition assessment in MEE. Instead, many agencies conduct qualitative condition assessments, where monitoring results are interpreted using expert judgment only. Whilst we found substantial evidence for the use of long-term monitoring data in the evidence-based management of MPAs, MEE is rarely the sole mechanism that facilitates the knowledge transfer of scientific evidence to management action. This suggests that the first goal of MEE (to enable environmental accountability and reporting) is being achieved, but the second and arguably more important goal of facilitating evidence-based management is not. Given that many MEE approaches are in their infancy, recommendations are made to assist management agencies realize the full potential of long-term quantitative monitoring data for protected area evaluation and evidence-based management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Non-invasive, photonics-based diagnostic, imaging, monitoring, and light delivery techniques for the recognition, quantification and treatment of malignant and chronic inflammatory conditions

NASA Astrophysics Data System (ADS)

Davies, N.; Davies-Shaw, D.; Shaw, J. D.

2007-02-01

We report firsthand on innovative developments in non-invasive, biophotonic techniques for a wide range of diagnostic, imaging and treatment options, including the recognition and quantification of cancerous, pre-cancerous cells and chronic inflammatory conditions. These techniques have benefited from the ability to target the affected site by both monochromatic light and broad multiple wavelength spectra. The employment of such wavelength or color-specific properties embraces the fluorescence stimulation of various photosensitizing drugs, and the instigation and detection of identified fluorescence signatures attendant upon laser induced fluorescence (LIF) phenomena as transmitted and propagated by precancerous, cancerous and normal tissue. In terms of tumor imaging and therapeutic and treatment options, we have exploited the abilities of various wavelengths to penetrate to different depths, through different types of tissues, and have explored quantifiable absorption and reflection characteristics upon which diagnostic assumptions can be reliably based and formulated. These biophotonic-based diagnostic, sensing and imaging techniques have also benefited from, and have been further enhanced by, the integrated ability to provide various power levels to be employed at various stages in the procedure. Applications are myriad, including non-invasive, non destructive diagnosis of in vivo cell characteristics and functions; light-based tissue analysis; real-time monitoring and mapping of brain function and of tumor growth; real time monitoring of the surgical completeness of tumor removal during laser-imaged/guided brain resection; diagnostic procedures based on fluorescence life-time monitoring, the monitoring of chronic inflammatory conditions (including rheumatoid arthritis), and continuous blood glucose monitoring in the control of diabetes.

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

Wireless sensing system for bridge condition assessment and health monitoring

NASA Astrophysics Data System (ADS)

Gangone, Michael V.; Whelan, Matthew J.; Janoyan, Kerop D.

2009-03-01

Discussed in this paper is the deployment of a universal and low-cost dense wireless sensor system for structural monitoring, load rating and condition assessment of bridges. The wireless sensor system developed is designed specifically for diagnostic bridge monitoring, providing independent conditioning for both accelerometers and strain transducers in addition to high-rate wireless data transmission. The system was field deployed on a three span simply supported bridge superstructure, where strain and acceleration measurements were obtained simultaneously and in realtime at critical locations under several loading conditions, providing reliable quantitative information as to the actual performance level of the bridge. Monitoring was also conducted as the bridge was subjected to various controlled damage scenarios on the final day of testing. Select cases of detected damage using strain and modal based analysis are presented.

Community-based Monitoring of Water Resources in Remote Mountain Regions

NASA Astrophysics Data System (ADS)

Buytaert, W.; Hannah, D. M.; Dewulf, A.; Clark, J.; Zulkafli, Z. D.; Karpouzoglou, T.; Mao, F.; Ochoa-Tocachi, B. F.

2016-12-01

Remote mountain regions are often represented by pockets of poverty combined with accelerated environmental change. The combination of harsh climatic and topographical conditions with limited infrastructure puts severe pressures on local livelihoods, many of which rely strongly on local ecosystem services (ESS) such as agricultural production and water supply. It is therefore paramount to optimise the management of ESS for the benefit of local people. This is hindered by a scarcity of quantitative data about physical processes such as precipitation and river flow as well as qualitative data concerning the management of water and land. National and conventional scientific monitoring networks tend to be insufficient to cover adequately the spatial and temporal gradients. Additionally, the data that are being collected often fail to be converted into locally relevant and actionable knowledge for ESS management. In such conditions, community-based monitoring of natural resources may be an effective way to reduce this knowledge gap. The participatory nature of such monitoring also enhances knowledge co-production and integration in locally-based decision-making processes. Here, we present the results of a 4-year consortium project on the use of citizen science technologies for ecosystem services management (Mountain-EVO). The project analyzed ecosystem service dynamics and decision-making processes and implemented a comparative analysis of experiments with community-based monitoring of water resources in 4 remote mountain regions, i.e. Peru, Nepal, Kyrgyzstan, and Ethiopia. We find that community-based monitoring can have a transformative impact on local ESS management, because of its potential to be more inclusive, polycentric, and context-driven as compared to conventional monitoring. However, the results and effectiveness of community-based approaches depend strongly on the natural and socio-economic boundary conditions. As such, this requires a tailored and bottom-up approach to implementation, which ideally isrooted in locally-based set of actors that can act as catalysts for knowledge co-production between the scientific community and local ESS users.

The impact of cognitive control on children's goal monitoring in a time-based prospective memory task.

PubMed

Mahy, Caitlin E V; Voigt, Babett; Ballhausen, Nicola; Schnitzspahn, Katharina; Ellis, Judi; Kliegel, Matthias

2015-01-01

The present study investigated whether developmental changes in cognitive control may underlie improvements of time-based prospective memory. Five-, 7-, 9-, and 11-year-olds (N = 166) completed a driving simulation task (ongoing task) in which they had to refuel their vehicle at specific points in time (PM task). The availability of cognitive control resources was experimentally manipulated by imposing a secondary task that required divided attention. Children completed the driving simulation task both in a full-attention condition and a divided-attention condition where they had to carry out a secondary task. Results revealed that older children performed better than younger children on the ongoing task and PM task. Children performed worse on the ongoing and PM tasks in the divided-attention condition compared to the full-attention condition. With respect to time monitoring in the final interval prior to the PM target, divided attention interacted with age such that older children's time monitoring was more negatively affected by the secondary task compared to younger children. Results are discussed in terms of developmental shifts from reactive to proactive monitoring strategies.

Hybrid monitoring scheme for end-to-end performance enhancement of multicast-based real-time media

NASA Astrophysics Data System (ADS)

Park, Ju-Won; Kim, JongWon

2004-10-01

As real-time media applications based on IP multicast networks spread widely, end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) a next-generation group collaboration tool based on multi-party media services, the applicability of hybrid monitoring scheme that combines active and passive monitoring is investigated. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks both application-layer metrics (i.e., user traffic condition by analyzing RTCP packets) and system metrics. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.

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.

Bridge condition assessment based on long-term strain monitoring

NASA Astrophysics Data System (ADS)

Sun, LiMin; Sun, Shouwang

2011-04-01

In consideration of the important role that bridges play as transportation infrastructures, their safety, durability and serviceability have always been deeply concerned. Structural Health Monitoring Systems (SHMS) have been installed to many long-span bridges to provide bridge engineers with the information needed in making rational decisions for maintenance. However, SHMS also confronted bridge engineers with the challenge of efficient use of monitoring data. Thus, methodologies which are robust to random disturbance and sensitive to damage become a subject on which many researches in structural condition assessment concentrate. In this study, an innovative probabilistic approach for condition assessment of bridge structures was proposed on the basis of long-term strain monitoring on steel girder of a cable-stayed bridge. First, the methodology of damage detection in the vicinity of monitoring point using strain-based indices was investigated. Then, the composition of strain response of bridge under operational loads was analyzed. Thirdly, the influence of temperature and wind on strains was eliminated and thus strain fluctuation under vehicle loads is obtained. Finally, damage evolution assessment was carried out based on the statistical characteristics of rain-flow cycles derived from the strain fluctuation under vehicle loads. The research conducted indicates that the methodology proposed is qualified for structural condition assessment so far as the following respects are concerned: (a) capability of revealing structural deterioration; (b) immunity to the influence of environmental variation; (c) adaptability to the random characteristic exhibited by long-term monitoring data. Further examination of the applicability of the proposed methodology in aging bridge may provide a more convincing validation.

A remote condition monitoring system for wind-turbine based DG systems

NASA Astrophysics Data System (ADS)

Ma, X.; Wang, G.; Cross, P.; Zhang, X.

2012-05-01

In this paper, a remote condition monitoring system is proposed, which fundamentally consists of real-time monitoring modules on the plant side, a remote support centre and the communications between them. The paper addresses some of the key issues related on the monitoring system, including i) the implementation and configuration of a VPN connection, ii) an effective database system to be able to handle huge amount of monitoring data, and iii) efficient data mining techniques to convert raw data into useful information for plant assessment. The preliminary results have demonstrated that the proposed system is practically feasible and can be deployed to monitor the emerging new energy generation systems.

Mathematical Frameworks for Diagnostics, Prognostics and Condition Based Maintenance Problems

DTIC Science & Technology

2008-08-15

REPORT Mathematical Frameworks for Diagnostics, Prognostics and Condition Based Maintenance Problems (W911NF-05-1-0426) 14. ABSTRACT 16. SECURITY ...other documentation. 12. DISTRIBUTION AVAILIBILITY STATEMENT Approved for Public Release; Distribution Unlimited 9. SPONSORING/MONITORING AGENCY NAME...parallel and distributed computing environment were researched. In support of the Condition Based Maintenance (CBM) philosophy, a theoretical framework

Home monitoring of patients with Parkinson's disease via wearable technology and a web-based application.

PubMed

Patel, Shyamal; Chen, Bor-Rong; Buckley, Thomas; Rednic, Ramona; McClure, Doug; Tarsy, Daniel; Shih, Ludy; Dy, Jennifer; Welsh, Matt; Bonato, Paolo

2010-01-01

Objective long-term health monitoring can improve the clinical management of several medical conditions ranging from cardiopulmonary diseases to motor disorders. In this paper, we present our work toward the development of a home-monitoring system. The system is currently used to monitor patients with Parkinson's disease who experience severe motor fluctuations. Monitoring is achieved using wireless wearable sensors whose data are relayed to a remote clinical site via a web-based application. The work herein presented shows that wearable sensors combined with a web-based application provide reliable quantitative information that can be used for clinical decision making.

Multi-sensor sheets based on large-area electronics for advanced structural health monitoring of civil infrastructure.

DOT National Transportation Integrated Search

2014-09-01

Structural Health Monitoring has a great potential to provide valuable information about the actual structural : condition and can help optimize the management activities. However, few eective and robust monitoring technology exist which hinders a...

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.

EMIR: a configurable hierarchical system for event monitoring and incident response

NASA Astrophysics Data System (ADS)

Deich, William T. S.

2014-07-01

The Event Monitor and Incident Response system (emir) is a flexible, general-purpose system for monitoring and responding to all aspects of instrument, telescope, and general facility operations, and has been in use at the Automated Planet Finder telescope for two years. Responses to problems can include both passive actions (e.g. generating alerts) and active actions (e.g. modifying system settings). Emir includes a monitor-and-response daemon, plus graphical user interfaces and text-based clients that automatically configure themselves from data supplied at runtime by the daemon. The daemon is driven by a configuration file that describes each condition to be monitored, the actions to take when the condition is triggered, and how the conditions are aggregated into hierarchical groups of conditions. Emir has been implemented for the Keck Task Library (KTL) keyword-based systems used at Keck and Lick Observatories, but can be readily adapted to many event-driven architectures. This paper discusses the design and implementation of Emir , and the challenges in balancing the competing demands for simplicity, flexibility, power, and extensibility. Emir 's design lends itself well to multiple purposes, and in addition to its core monitor and response functions, it provides an effective framework for computing running statistics, aggregate values, and summary state values from the primitive state data generated by other subsystems, and even for creating quick-and-dirty control loops for simple systems.

Development of system decision support tools for behavioral trends monitoring of machinery maintenance in a competitive environment

NASA Astrophysics Data System (ADS)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani

2017-06-01

The article is centred on software system development for manufacturing company that produces polyethylene bags using mostly conventional machines in a competitive world where each business enterprise desires to stand tall. This is meant to assist in gaining market shares, taking maintenance and production decisions by the dynamism and flexibilities embedded in the package as customers' demand varies under the duress of meeting the set goals. The production and machine condition monitoring software (PMCMS) is programmed in C# and designed in such a way to support hardware integration, real-time machine conditions monitoring, which is based on condition maintenance approach, maintenance decision suggestions and suitable production strategies as the demand for products keeps changing in a highly competitive environment. PMCMS works with an embedded device which feeds it with data from the various machines being monitored at the workstation, and the data are read at the base station through transmission via a wireless transceiver and stored in a database. A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.

Fiber optic monitoring methods for composite steel-concrete structures based on determination of neutral axis and deformed shape.

DOT National Transportation Integrated Search

2014-01-01

Structural Health Monitoring has great potential to provide valuable information about the actual structural condition and can help optimize the management activities. However, few effective and robust monitoring methods exist which hinders a nationw...

Noninvasive pulmonary artery pressure monitoring by EIT: a model-based feasibility study.

PubMed

Proença, Martin; Braun, Fabian; Solà, Josep; Thiran, Jean-Philippe; Lemay, Mathieu

2017-06-01

Current monitoring modalities for patients with pulmonary hypertension (PH) are limited to invasive solutions. A novel approach for the noninvasive and unsupervised monitoring of pulmonary artery pressure (PAP) in patients with PH was proposed and investigated. The approach was based on the use of electrical impedance tomography (EIT), a noninvasive and safe monitoring technique, and was tested through simulations on a realistic 4D bio-impedance model of the human thorax. Changes in PAP were induced in the model by simulating multiple types of hypertensive conditions. A timing parameter physiologically linked to the PAP via the so-called pulse wave velocity principle was automatically estimated from the EIT data. It was found that changes in PAP could indeed be reliably monitored by EIT, irrespective of the pathophysiological condition that caused them. If confirmed clinically, these findings could open the way for a new generation of noninvasive PAP monitoring solutions for the follow-up of patients with PH.

An adaptive management process for forest soil conservation.

Treesearch

Michael P. Curran; Douglas G. Maynard; Ronald L. Heninger; Thomas A. Terry; Steven W. Howes; Douglas M. Stone; Thomas Niemann; Richard E. Miller; Robert F. Powers

2005-01-01

Soil disturbance guidelines should be based on comparable disturbance categories adapted to specific local soil conditions, validated by monitoring and research. Guidelines, standards, and practices should be continually improved based on an adaptive management process, which is presented in this paper. Core components of this process include: reliable monitoring...

Combine harvester monitor system based on wireless sensor network

USDA-ARS?s Scientific Manuscript database

A measurement method based on Wireless Sensor Network (WSN) was developed to monitor the working condition of combine harvester for remote application. Three JN5139 modules were chosen for sensor data acquisition and another two as a router and a coordinator, which could create a tree topology netwo...

Computer-Assisted Monitoring Of A Complex System

NASA Technical Reports Server (NTRS)

Beil, Bob J.; Mickelson, Eric M.; Sterritt, John M.; Costantino, Rob W.; Houvener, Bob C.; Super, Mike A.

1995-01-01

Propulsion System Advisor (PSA) computer-based system assists engineers and technicians in analyzing masses of sensory data indicative of operating conditions of space shuttle propulsion system during pre-launch and launch activities. Designed solely for monitoring; does not perform any control functions. Although PSA developed for highly specialized application, serves as prototype of noncontrolling, computer-based subsystems for monitoring other complex systems like electric-power-distribution networks and factories.

Remote sensing of vegetation pattern and condition to monitor changes in Everglades biogeochemistry

USGS Publications Warehouse

Jones, John W.

2011-01-01

Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management.

A real time study on condition monitoring of distribution transformer using thermal imager

NASA Astrophysics Data System (ADS)

Mariprasath, T.; Kirubakaran, V.

2018-05-01

The transformer is one of the critical apparatus in the power system. At any cost, a few minutes of outages harshly influence the power system. Hence, prevention-based maintenance technique is very essential. The continuous conditioning and monitoring technology significantly increases the life span of the transformer, as well as reduces the maintenance cost. Hence, conditioning and monitoring of transformer's temperature are very essential. In this paper, a critical review has been made on various conditioning and monitoring techniques. Furthermore, a new method, hot spot indication technique, is discussed. Also, transformer's operating condition is monitored by using thermal imager. From the thermal analysis, it is inferred that major hotspot locations are appearing at connection lead out; also, the bushing of the transformer is the very hottest spot in transformer, so monitoring the level of oil is essential. Alongside, real time power quality analysis has been carried out using the power analyzer. It shows that industrial drives are injecting current harmonics to the distribution network, which causes the power quality problem on the grid. Moreover, the current harmonic limit has exceeded the IEEE standard limit. Hence, the adequate harmonics suppression technique is need an hour.

Risk Identification in a Smart Monitoring System Used to Preserve Artefacts Based on Textile Materials

NASA Astrophysics Data System (ADS)

Diaconescu, V. D.; Scripcariu, L.; Mătăsaru, P. D.; Diaconescu, M. R.; Ignat, C. A.

2018-06-01

Exhibited textile-materials-based artefacts can be affected by the environmental conditions. A smart monitoring system that commands an adaptive automatic environment control system is proposed for indoor exhibition spaces containing various textile artefacts. All exhibited objects are monitored by many multi-sensor nodes containing temperature, relative humidity and light sensors. Data collected periodically from the entire sensor network is stored in a database and statistically processed in order to identify and classify the environment risk. Risk consequences are analyzed depending on the risk class and the smart system commands different control measures in order to stabilize the indoor environment conditions to the recommended values and prevent material degradation.

Concentrations and Loads of Nutrients and Suspended Sediments in Englesby Brook and Little Otter Creek, Lake Champlain Basin, Vermont, 2000-2005

USGS Publications Warehouse

Medalie, Laura

2007-01-01

The effectiveness of best-management practices (BMPs) in improving water quality in Lake Champlain tributaries was evaluated from 2000 through 2005 on the basis of analysis of data collected on concentrations of total phosphorus and suspended sediment in Englesby Brook, an urban stream in Burlington, and Little Otter Creek, an agricultural stream in Ferrisburg. Data also were collected on concentrations of total nitrogen in the Englesby Brook watershed. In the winter of 2001-2002, one of three planned structural BMPs was installed in the urban watershed. At approximately the same time, a set of barnyard BMPs was installed in the agricultural watershed; however, the other planned BMPs, which included streambank fencing and nutrient management, were not implemented within the study period. At Englesby Brook, concentrations of phosphorus ranged from 0.024 to 0.3 milligrams per liter (mg/L) during base-flow and from 0.032 to 11.8 mg/L during high-flow conditions. Concentrations of suspended sediment ranged from 3 to 189 mg/L during base-flow and from 5 to 6,880 mg/L during high-flow conditions. An assessment of the effectiveness of an urban BMP was made by comparing concentrations and loads of phosphorus and suspended sediment before and after a golf-course irrigation pond in the Englesby Brook watershed was retrofitted with the objective of reducing sediment transport. Results from a modified paired watershed study design showed that the BMP reduced concentrations of phosphorus and suspended sediment during high-flow events - when average streamflow was greater than 3 cubic feet per second. While construction of the BMP did not reduce storm loads of phosphorus or suspended sediment, an evaluation of changes in slope of double-mass curves showing cumulative monthly streamflow plotted against cumulative monthly loads indicated a possible reduction in cumulative loads of phosphorus and suspended sediment after BMP construction. Results from the Little Otter Creek assessment of agricultural BMPs showed that concentrations of phosphorus ranged from 0.016 to 0.141 mg/L during base-flow and from 0.019 to 0.565 mg/L during high-flow conditions at the upstream monitoring station. Concentrations of suspended sediment ranged from 2 to 13 mg/L during base-flow and from 1 to 473 mg/L during high-flow conditions at the upstream monitoring station. Concentrations of phosphorus ranged from 0.018 to 0.233 mg/L during base-flow and from 0.019 to 1.95 mg/L during high-flow conditions at the downstream monitoring station. Concentrations of suspended sediment ranged from 10 to 132 mg/L during base-flow and from 8 to 1,190 mg/L during high-flow conditions at the downstream monitoring station. Annual loads of phosphorus at the downstream monitoring station were significantly larger than loads at the upstream monitoring station, and annual loads of suspended sediment at the downstream monitoring station were larger than loads at the upstream monitoring station for 4 out of 6 years. On a monthly basis, loads of phosphorus and suspended sediment at the downstream monitoring station were significantly larger than loads at the upstream monitoring station. Pairs of concentrations of phosphorus and monthly loads of phosphorus and suspended sediment from the upstream and downstream monitoring stations were evaluated using the paired watershed study design. The only significant reduction between the calibration and treatment periods was for monthly loads of phosphorus; all other evaluations showed no change between periods.

Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

PubMed Central

Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

2014-01-01

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability. PMID:25405514

Force sensor based tool condition monitoring using a heterogeneous ensemble learning model.

PubMed

Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

2014-11-14

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

PubMed

Liu, Ya-Juan; André, Silvère; Saint Cristau, Lydia; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Devos, Olivier; Duponchel, Ludovic

2017-02-01

Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T 2 and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry. Copyright © 2016 Elsevier B.V. All rights reserved.

A Five-Year Analysis of MODIS NDVI and NDWI for Rangeland Drought Assessment: Preliminary Results

NASA Astrophysics Data System (ADS)

Gu, Y.; Brown, J. F.; Verdin, J. P.; Wardlow, B.

2006-12-01

Drought is one of the most costly natural disasters in the United States. Traditionally, drought monitoring has been based on weather station observations, which lack the continuous spatial coverage needed to adequately characterize and monitor detailed spatial patterns of drought conditions. Satellite remote sensing observations can provide a synoptic view of the land and provide a spatial context for measuring drought. A common satellite-based index, the normalized difference vegetation index (NDVI) has a 30-year history of use for vegetation condition monitoring. NDVI is calculated from the visible red and near infrared channels and measures the changes in chlorophyll absorption and reflection in the spongy mesophyll of the vegetation canopy that are reflected in these respective bands. The normalized difference water index (NDWI) is another index, derived from the near-infrared and short wave infrared channels, and reflects changes in both the water content and spongy mesophyll in the vegetation canopy. As a result, the NDWI is influenced by both desiccation and wilting in the vegetation canopy and may be a more sensitive indicator than the NDVI for large- area drought monitoring. The objective of this study was to process and evaluate a 5-year history of 500-meter NDVI and NDWI data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument and to investigate methods for measuring and monitoring drought in rangeland over the southern plains of the United States. This initial study included: (1) the development of a climatological database for MODIS NDVI and NDWI, (2) a study of the relationship between the NDVI, NDWI, and drought condition over rangeland, (3) the development of a method to provide threshold NDVI/NDWI values under drought conditions based on the 5-year NDVI/NDWI/drought condition analysis, and (4) the investigation of additional vegetation drought information provided by the NDWI versus the NDVI in a 5-year comparison of the two indices. The MODIS data were obtained from the Land Processes Distributed Active Archive System. Results show strong relationships among NDVI, NDWI, and drought analyzed over grasslands in the Flint Hills region of Kansas and Oklahoma. During the summer months, the average NDVI and NDWI values were consistently lower (NDVI<0.5 and NDWI<0.3) for the tallgrass prairie under drought conditions than under normal climate conditions (NDVI>0.6 and NDWI>0.4). The distinctions between drought conditions and normal climate conditions are based on the historic U.S. Drought Monitor maps and the historic Palmer index data. To take advantage of information contained in both indices, we calculated the difference between NDVI and NDWI (NDVI-NDWI). The difference between NDVI and NDWI slightly increases during the summer drought condition. Based on these analyses, the NDWI appears to be more sensitive than NDVI to drought conditions. The results of statistical analysis of the relationships among these indices will be presented in the poster.

Liquefied Petroleum Gas Monitoring System Based on Polystyrene Coated Long Period Grating

PubMed Central

Zotti, Aldobenedetto; Palumbo, Giovanna; Zuppolini, Simona; Consales, Marco; Cutolo, Antonello; Borriello, Anna; Zarrelli, Mauro; Iadicicco, Agostino

2018-01-01

In this work, we report the in-field demonstration of a liquefied petroleum gas monitoring system based on optical fiber technology. Long-period grating coated with a thin layer of atactic polystyrene (aPS) was employed as a gas sensor, and an array comprising two different fiber Bragg gratings was set for the monitoring of environmental conditions such as temperature and humidity. A custom package was developed for the sensors, ensuring their suitable installation and operation in harsh conditions. The developed system was installed in a real railway location scenario (i.e., a southern Italian operative railway tunnel), and tests were performed to validate the system performances in operational mode. Daytime normal working operations of the railway line and controlled gas expositions, at very low concentrations, were the searched realistic conditions for an out-of-lab validation of the developed system. Encouraging results were obtained with a precise indication of the gas concentration and external conditioning of the sensor. PMID:29734731

Monitoring Engine Vibrations And Spectrum Of Exhaust

NASA Technical Reports Server (NTRS)

Martinez, Carol L.; Randall, Michael R.; Reinert, John W.

1991-01-01

Real-time computation of intensities of peaks in visible-light emission spectrum of exhaust combined with real-time spectrum analysis of vibrations into developmental monitoring technique providing up-to-the-second information on conditions of critical bearings in engine. Conceived to monitor conditions of bearings in turbopump suppling oxygen to Space Shuttle main engine, based on observations that both vibrations in bearings and intensities of visible light emitted at specific wavelengths by exhaust plume of engine indicate wear and incipient failure of bearings. Applicable to monitoring "health" of other machinery via spectra of vibrations and electromagnetic emissions from exhausts. Concept related to one described in "Monitoring Bearing Vibrations For Signs Of Damage", (MFS-29734).

Patients’ Heart Monitoring System Based on Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Sollu, T. S.; Alamsyah; Bachtiar, M.; Sooai, A. G.

2018-04-01

Wireless sensor network (WSN) has been utilized to support the health field such as monitoring the patient’s heartbeat. Heart health monitoring is essential in maintaining health, especially in the elderly. Such an arrangement is needed to understand the patient’s heart characteristics. The increasing number of patients certainly will enhance the burdens of doctors or nurses in dealing with the condition of the patients. Therefore, required a solution that could help doctors or nurses in monitoring the progress of patients’ health at a real time. This research proposes a design and application of a patient heart monitoring system based on WSN. This system with using electrocardiograph (ECG) mounted on the patients’ body and sent to the server through the ZigBee. The results indicated that the retrieval of data for 15 seconds in male patients, with the age of 25 years was 17 times rate or equal to 68 bpm. For 884 data packets sent for 15 minutes using ZigBee produce a data as much as 4488 bytes, throughput of 2.39 Kbps, and 0.24486 seconds of average delay. The measurement of the communication coverage based on the open space conditions within 15 seconds through ZigBee resulting throughput value of 4.19 Kbps, packet loss of 0 %, and 6.667 seconds of average delay. While, the measurement of communication range based on closed space condition through ZigBee resulting throughput of 4.27 Kbps, packet loss of 0 %, and 6.55 seconds of average delay.

Smart sensor technology for advanced launch vehicles

NASA Astrophysics Data System (ADS)

Schoess, Jeff

1989-07-01

Next-generation advanced launch vehicles will require improved use of sensor data and the management of multisensor resources to achieve automated preflight checkout, prelaunch readiness assessment and vehicle inflight condition monitoring. Smart sensor technology is a key component in meeting these needs. This paper describes the development of a smart sensor-based condition monitoring system concept referred to as the Distributed Sensor Architecture. A significant event and anomaly detection scheme that provides real-time condition assessment and fault diagnosis of advanced launch system rocket engines is described. The design and flight test of a smart autonomous sensor for Space Shuttle structural integrity health monitoring is presented.

Methods, apparatus, and systems for monitoring transmission systems

DOEpatents

Polk, Robert E; Svoboda, John M; West, Phillip B; Heath, Gail L; Scott, Clark L

2015-01-27

A sensing platform for monitoring a transmission system, and method therefor, may include a sensor that senses one or more conditions relating to a condition of the transmission system and/or the condition of an environment around the transmission system. A control system operatively associated with the sensor produces output data based on an output signal produced by the sensor. A transmitter operatively associated with the control system transmits the output data from the control system.

Methods, apparatus, and systems for monitoring transmission systems

DOEpatents

Polk, Robert E [Idaho Falls, ID; Svoboda, John M [Idaho Falls, ID; West, Phillip B [Idaho Falls, ID; Heath, Gail L [Iona, ID; Scott, Clark L [Idaho Falls, ID

2010-08-31

A sensing platform for monitoring a transmission system, and method therefor, may include a sensor that senses one or more conditions relating to a condition of the transmission system and/or the condition of an environment around the transmission system. A control system operatively associated with the sensor produces output data based on an output signal produced by the sensor. A transmitter operatively associated with the control system transmits the output data from the control system.

Methods, apparatus, and systems for monitoring transmission systems

DOEpatents

Polk, Robert E; Svoboda, John M.; West, Phillip B.; Heath, Gail L.; Scott, Clark L.

2016-07-19

A sensing platform for monitoring a transmission system, and method therefor, may include a sensor that senses one or more conditions relating to a condition of the transmission system and/or the condition of an environment around the transmission system. A control system operatively associated with the sensor produces output data based on an output signal produced by the sensor. A transmitter operatively associated with the control system transmits the output data from the control system.

Emerging ecological datasets with application for modeling North American dust emissions

USDA-ARS?s Scientific Manuscript database

In 2011 the US Bureau of Land Management (BLM) established the Assessment, Inventory and Monitoring (AIM) program to monitor the condition of BLM land and to provide data to support evidence-based management of multi-use public lands. The monitoring program shares core data collection methods with t...

Video-based respiration monitoring with automatic region of interest detection.

PubMed

Janssen, Rik; Wang, Wenjin; Moço, Andreia; de Haan, Gerard

2016-01-01

Vital signs monitoring is ubiquitous in clinical environments and emerging in home-based healthcare applications. Still, since current monitoring methods require uncomfortable sensors, respiration rate remains the least measured vital sign. In this paper, we propose a video-based respiration monitoring method that automatically detects a respiratory region of interest (RoI) and signal using a camera. Based on the observation that respiration induced chest/abdomen motion is an independent motion system in a video, our basic idea is to exploit the intrinsic properties of respiration to find the respiratory RoI and extract the respiratory signal via motion factorization. We created a benchmark dataset containing 148 video sequences obtained on adults under challenging conditions and also neonates in the neonatal intensive care unit (NICU). The measurements obtained by the proposed video respiration monitoring (VRM) method are not significantly different from the reference methods (guided breathing or contact-based ECG; p-value  =  0.6), and explain more than 99% of the variance of the reference values with low limits of agreement (-2.67 to 2.81 bpm). VRM seems to provide a valid solution to ECG in confined motion scenarios, though precision may be reduced for neonates. More studies are needed to validate VRM under challenging recording conditions, including upper-body motion types.

Improved maintainability of space-based reusable rocket engines

NASA Technical Reports Server (NTRS)

Barkhoudarian, S.; Szemenyei, B.; Nelson, R. S.; Pauckert, R.; Harmon, T.

1988-01-01

Advanced, noninferential, noncontacting, in situ measurement technologies, combined with automated testing and expert systems, can provide continuous, automated health monitoring of critical space-based rocket engine components, requiring minimal disassembly and no manual data analysis, thus enhancing their maintainability. This paper concentrates on recent progress of noncontacting combustion chamber wall thickness condition-monitoring technologies.

Monitoring Urban Quality of Life: The Porto Experience

ERIC Educational Resources Information Center

Santos, Luis Delfim; Martins, Isabel

2007-01-01

This paper describes the monitoring system of the urban quality of life developed by the Porto City Council, a new tool being used to support urban planning and management. The two components of this system--a quantitative approach based on statistical indicators and a qualitative analysis based on the citizens' perceptions of the conditions of…

A Review of Indicators of Estuarine Tidal Wetland Condition

EPA Science Inventory

This review critically evaluates indicators of tidal wetland condition based on 36 indicator development studies and indicators developed as part of U.S. state tidal wetland monitoring programs. Individual metrics were evaluated based on relative scores on two sets of evaluation ...

Assessing interactions among multiple physiological systems during walking outside a laboratory: An Android based gait monitor

PubMed Central

Sejdić, E.; Millecamps, A.; Teoli, J.; Rothfuss, M. A.; Franconi, N. G.; Perera, S.; Jones, A. K.; Brach, J. S.; Mickle, M. H.

2015-01-01

Gait function is traditionally assessed using well-lit, unobstructed walkways with minimal distractions. In patients with subclinical physiological abnormalities, these conditions may not provide enough stress on their ability to adapt to walking. The introduction of challenging walking conditions in gait can induce responses in physiological systems in addition to the locomotor system. There is a need for a device that is capable of monitoring multiple physiological systems in various walking conditions. To address this need, an Android-based gait-monitoring device was developed that enabled the recording of a patient's physiological systems during walking. The gait-monitoring device was tested during self-regulated overground walking sessions of fifteen healthy subjects that included 6 females and 9 males aged 18 to 35 years. The gait-monitoring device measures the patient's stride interval, acceleration, electrocardiogram, skin conductance and respiratory rate. The data is stored on an Android phone and is analyzed offline through the extraction of features in the time, frequency and time-frequency domains. The analysis of the data depicted multisystem physiological interactions during overground walking in healthy subjects. These interactions included locomotion-electrodermal, locomotion-respiratory and cardiolocomotion couplings. The current results depicting strong interactions between the locomotion system and the other considered systems (i.e., electrodermal, respiratory and cardivascular systems) warrant further investigation into multisystem interactions during walking, particularly in challenging walking conditions with older adults. PMID:26390946

Remote sensing of vegetation pattern and condition to monitor changes in everglades biogeochemistry

USGS Publications Warehouse

Jones, J.W.

2011-01-01

Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management. Copyright ?? 2011 Taylor & Francis Group, LLC.

A suite of optical fibre sensors for structural condition monitoring

NASA Astrophysics Data System (ADS)

Sun, T.; Grattan, K. T. V.; Carlton, J.

2015-05-01

This paper is to review the research activities at City University London in the development of a range of fibre Bragg grating (FBG)-based sensors, including strain, temperature, relative humidity, vibration and acoustic sensors, with an aim to meet the increasing demands from industry for structural condition monitoring. As a result, arrays of optical fibre sensors have been instrumented into various types of structures, including concrete, limestone, marine propellers, pantograph and electrical motors, allowing for both static and dynamic monitoring and thus enhanced structural reliability and integrity.

Development of an Index of Ecological Condition based on Great River Fish Assemblages

EPA Science Inventory

As part of the Environmental Monitoring and Assessment Program for Great River Ecosystems we developed a fish-assemblage based multimetric index (Great River Fish Index,GRFIn) as an indicator of ecological conditions in the Lower Missouri, impounded Upper Mississippi,.unimpoun...

Novel spectrometers for environmental dose rate monitoring.

PubMed

Kessler, P; Behnke, B; Dabrowski, R; Dombrowski, H; Röttger, A; Neumaier, S

2018-07-01

A new generation of dosemeters, based on the scintillators LaBr 3 , CeBr 3 and SrI 2 , read out with conventional photomultipliers, to be used in the field of environmental gamma-radiation monitoring, was investigated. The main features of these new instruments and especially their outdoor performance, studied by long-term investigations under real weather conditions, are presented. The systems were tested at the reference sites for environmental radiation of the Physikalisch-Technische Bundesanstalt. The measurements are compared with that of well characterized classical dose rate reference instruments to demonstrate the suitability of new spectrometers for environmental dose rate monitoring even in adverse weather conditions. Their potential to replace the (mainly Geiger Müller based) dose rate meters operated in about 5000 European early waning network stations as well as in environmental radiation monitoring in general is shown. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Architecture for Improving Terrestrial Logistics Based on the Web of Things

PubMed Central

Castro, Miguel; Jara, Antonio J.; Skarmeta, Antonio

2012-01-01

Technological advances for improving supply chain efficiency present three key challenges for managing goods: tracking, tracing and monitoring (TTM), in order to satisfy the requirements for products such as perishable goods where the European Legislations requires them to ship within a prescribed temperature range to ensure freshness and suitability for consumption. The proposed system integrates RFID for tracking and tracing through a distributed architecture developed for heavy goods vehicles, and the sensors embedded in the SunSPOT platform for monitoring the goods transported based on the concept of the Internet of Things. This paper presents how the Internet of Things is integrated for improving terrestrial logistics offering a comprehensive and flexible architecture, with high scalability, according to the specific needs for reaching an item-level continuous monitoring solution. The major contribution from this work is the optimization of the Embedded Web Services based on RESTful (Web of Things) for the access to TTM services at any time during the transportation of goods. Specifically, it has been extended the monitoring patterns such as observe and blockwise transfer for the requirements from the continuous conditional monitoring, and for the transfer of full inventories and partial ones based on conditional queries. In definitive, this work presents an evolution of the previous TTM solutions, which were limited to trailer identification and environment monitoring, to a solution which is able to provide an exhaustive item-level monitoring, required for several use cases. This exhaustive monitoring has required new communication capabilities through the Web of Things, which has been optimized with the use and improvement of a set of communications patterns. PMID:22778657

Architecture for improving terrestrial logistics based on the Web of Things.

PubMed

Castro, Miguel; Jara, Antonio J; Skarmeta, Antonio

2012-01-01

Technological advances for improving supply chain efficiency present three key challenges for managing goods: tracking, tracing and monitoring (TTM), in order to satisfy the requirements for products such as perishable goods where the European Legislations requires them to ship within a prescribed temperature range to ensure freshness and suitability for consumption. The proposed system integrates RFID for tracking and tracing through a distributed architecture developed for heavy goods vehicles, and the sensors embedded in the SunSPOT platform for monitoring the goods transported based on the concept of the Internet of Things. This paper presents how the Internet of Things is integrated for improving terrestrial logistics offering a comprehensive and flexible architecture, with high scalability, according to the specific needs for reaching an item-level continuous monitoring solution. The major contribution from this work is the optimization of the Embedded Web Services based on RESTful (Web of Things) for the access to TTM services at any time during the transportation of goods. Specifically, it has been extended the monitoring patterns such as observe and blockwise transfer for the requirements from the continuous conditional monitoring, and for the transfer of full inventories and partial ones based on conditional queries. In definitive, this work presents an evolution of the previous TTM solutions, which were limited to trailer identification and environment monitoring, to a solution which is able to provide an exhaustive item-level monitoring, required for several use cases. This exhaustive monitoring has required new communication capabilities through the Web of Things, which has been optimized with the use and improvement of a set of communications patterns.

Intelligent Performance Analysis with a Natural Language Interface

NASA Astrophysics Data System (ADS)

Juuso, Esko K.

2017-09-01

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

The Effects of Mindfulness-Based Intervention on Children's Attention Regulation.

PubMed

Felver, Joshua C; Tipsord, Jessica M; Morris, Maxwell J; Racer, Kristina Hiatt; Dishion, Thomas J

2017-08-01

This article describes results from a randomized clinical trial of a mindfulness-based intervention for parents and children, Mindful Family Stress Reduction, on a behavioral measure of attention in youths, the Attention Network Task (ANT). Forty-one parent-child dyads were randomly assigned to either the mindfulness-based intervention condition or a wait-list control. School-age youths completed the ANT before and after the intervention. Results demonstrate significant, medium-size ( f 2 = -.16) intervention effects to the conflict monitoring subsystem of the ANT such that those in the intervention condition decreased in conflict monitoring more than those in the wait-list control. Youths in the intervention condition also showed improvements in their orienting subsystem scores, compared with controls. Mindfulness-based interventions for youths have potential utility to improve attentional self-regulation, and future research should consider incorporating measures of attention into interventions that use mindfulness training.

Development of an Index of Ecological Condition Based on Great River Fish Assemblages, Presentation

EPA Science Inventory

As part of the Environmental Monitoring and Assessment Program for Great River Ecosystems we developed a fish-assemblage based multimetric index (Great River Fish Index,GRFIn) as an indicator of ecological conditions in the Lower Missouri, impounded Upper Mississippi,.unimpounded...

Monitoring Agents for Assisting NASA Engineers with Shuttle Ground Processing

NASA Technical Reports Server (NTRS)

Semmel, Glenn S.; Davis, Steven R.; Leucht, Kurt W.; Rowe, Danil A.; Smith, Kevin E.; Boeloeni, Ladislau

2005-01-01

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has designed, developed, and deployed a rule-based agent to monitor the Space Shuttle's ground processing telemetry stream. The NASA Engineering Shuttle Telemetry Agent increases situational awareness for system and hardware engineers during ground processing of the Shuttle's subsystems. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when user defined conditions are satisfied. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the agent's rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules within this domain. The declarative paradigm of the rule-based agent yields a highly modular and scalable design spanning multiple subsystems of the Shuttle. Several hundred monitoring rules have been written thus far with corresponding notifications sent to Shuttle engineers. This chapter discusses the rule-based telemetry agent used for Space Shuttle ground processing. We present the problem domain along with design and development considerations such as information modeling, knowledge capture, and the deployment of the product. We also present ongoing work with other condition monitoring agents.

Framework of sensor-based monitoring for pervasive patient care.

PubMed

Triantafyllidis, Andreas K; Koutkias, Vassilis G; Chouvarda, Ioanna; Adami, Ilia; Kouroubali, Angelina; Maglaveras, Nicos

2016-09-01

Sensor-based health systems can often become difficult to use, extend and sustain. The authors propose a framework for designing sensor-based health monitoring systems aiming to provide extensible and usable monitoring services in the scope of pervasive patient care. The authors' approach relies on a distributed system for monitoring the patient health status anytime-anywhere and detecting potential health complications, for which healthcare professionals and patients are notified accordingly. Portable or wearable sensing devices measure the patient's physiological parameters, a smart mobile device collects and analyses the sensor data, a Medical Center system receives notifications on the detected health condition, and a Health Professional Platform is used by formal caregivers in order to review the patient condition and configure monitoring schemas. A Service-oriented architecture is utilised to provide extensible functional components and interoperable interactions among the diversified system components. The framework was applied within the REMOTE ambient-assisted living project in which a prototype system was developed, utilising Bluetooth to communicate with the sensors and Web services for data exchange. A scenario of using the REMOTE system and preliminary usability results show the applicability, usefulness and virtue of our approach.

Framework of sensor-based monitoring for pervasive patient care

PubMed Central

Koutkias, Vassilis G.; Chouvarda, Ioanna; Adami, Ilia; Kouroubali, Angelina; Maglaveras, Nicos

2016-01-01

Sensor-based health systems can often become difficult to use, extend and sustain. The authors propose a framework for designing sensor-based health monitoring systems aiming to provide extensible and usable monitoring services in the scope of pervasive patient care. The authors’ approach relies on a distributed system for monitoring the patient health status anytime-anywhere and detecting potential health complications, for which healthcare professionals and patients are notified accordingly. Portable or wearable sensing devices measure the patient's physiological parameters, a smart mobile device collects and analyses the sensor data, a Medical Center system receives notifications on the detected health condition, and a Health Professional Platform is used by formal caregivers in order to review the patient condition and configure monitoring schemas. A Service-oriented architecture is utilised to provide extensible functional components and interoperable interactions among the diversified system components. The framework was applied within the REMOTE ambient-assisted living project in which a prototype system was developed, utilising Bluetooth to communicate with the sensors and Web services for data exchange. A scenario of using the REMOTE system and preliminary usability results show the applicability, usefulness and virtue of our approach. PMID:27733920

Integrated Systems Health Management as an Enabler for Condition Based Maintenance and Autonomic Logistics

DTIC Science & Technology

2015-09-17

turbines , SHM tools, maintenance scheduling, and performance of the SHM system determine the added value of the system of systems (A. Van Horenbeek...J. R., & Pintelon, L. (2013). Quantifying the added value of an imperfectly performing condition monitoring system— Application to a wind turbine ...INTEGRATED SYSTEMS HEALTH MANAGEMENT AS AN ENABLER FOR CONDITION BASED MAINTENANCE AND AUTONOMIC

Noise Monitoring Titan III D Launch Vandenberg AFB, Calif

DTIC Science & Technology

1975-01-01

ent weather conditions. d. Estimated Environmental Impact : (1) The impact of any single noise event is difficult to determine when one is concerned...from average atmospheric conditions should be considered when extrapolating these data. 2. No significant environmental impact is expected to result...AD-A012 748 NOISE MONITORING TITAN III D LAUNCH VANDENBERG AIR FORCE BASE, CALIFORNIA Ronald D. Burnett Environmental Health Laboratory McClellan Air

Electrical condition monitoring method for polymers

DOEpatents

Watkins, Jr., Kenneth S.; Morris, Shelby J [Hampton, VA; Masakowski, Daniel D [Worcester, MA; Wong, Ching Ping [Duluth, GA; Luo, Shijian [Boise, ID

2008-08-19

An electrical condition monitoring method utilizes measurement of electrical resistivity of an age sensor made of a conductive matrix or composite disposed in a polymeric structure such as an electrical cable. The conductive matrix comprises a base polymer and conductive filler. The method includes communicating the resistivity to a measuring instrument and correlating resistivity of the conductive matrix of the polymeric structure with resistivity of an accelerated-aged conductive composite.

Compressed-Sensing Reconstruction Based on Block Sparse Bayesian Learning in Bearing-Condition Monitoring

PubMed Central

Sun, Jiedi; Yu, Yang; Wen, Jiangtao

2017-01-01

Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression only, cannot overcome these limitations. Aiming at these problems, this paper proposed a compressed data acquisition and reconstruction scheme based on Compressed Sensing (CS) which is a novel signal-processing technique and applied it for bearing conditions monitoring via WSN. The compressed data acquisition is realized by projection transformation and can greatly reduce the data volume, which needs the nodes to process and transmit. The reconstruction of original signals is achieved in the host computer by complicated algorithms. The bearing vibration signals not only exhibit the sparsity property, but also have specific structures. This paper introduced the block sparse Bayesian learning (BSBL) algorithm which works by utilizing the block property and inherent structures of signals to reconstruct CS sparsity coefficients of transform domains and further recover the original signals. By using the BSBL, CS reconstruction can be improved remarkably. Experiments and analyses showed that BSBL method has good performance and is suitable for practical bearing-condition monitoring. PMID:28635623

Ten-year monitoring of high-rise building columns using long-gauge fiber optic sensors

NASA Astrophysics Data System (ADS)

Glisic, B.; Inaudi, D.; Lau, J. M.; Fong, C. C.

2013-05-01

A large-scale lifetime building monitoring program was implemented in Singapore in 2001. The monitoring aims of this unique program were to increase safety, verify performance, control quality, increase knowledge, optimize maintenance costs, and evaluate the condition of the structures after a hazardous event. The first instrumented building, which has now been monitored for more than ten years, is presented in this paper. The long-gauge fiber optic strain sensors were embedded in fresh concrete of ground-level columns, thus the monitoring started at the birth of both the construction material and the structure. Measurement sessions were performed during construction, upon completion of each new story and the roof, and after the construction, i.e., in-service. Based on results it was possible to follow and evaluate long-term behavior of the building through every stage of its life. The results of monitoring were analyzed at a local (column) and global (building) level. Over-dimensioning of one column was identified. Differential settlement of foundations was detected, localized, and its magnitude estimated. Post-tremor analysis was performed. Real long-term behavior of concrete columns was assessed. Finally, the long-term performance of the monitoring system was evaluated. The researched monitoring method, monitoring system, rich results gathered over approximately ten years, data analysis algorithms, and the conclusions on the structural behavior and health condition of the building based on monitoring are presented in this paper.

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.

Hand-held radiometer red and photographic infrared spectral measurements of agricultural crops

NASA Technical Reports Server (NTRS)

Tucker, C. J.; Fan, C. J.; Elgin, J. H., Jr.; Mcmurtrey, J. E., III

1978-01-01

Red and photographic infrared radiance data, collected under a variety of conditions at weekly intervals throughout the growing season using a hand-held radiometer, were used to monitor crop growth and development. The vegetation index transformation was used to effectively compensate for the different irradiational conditions encountered during the study period. These data, plotted against time, compared the different crops measured by comparing their green leaf biomass dynamics. This approach, based entirely upon spectral inputs, closely monitors crop growth and development and indicates the promise of ground-based hand-held radiometer measurements of crops.

Watching grass grow: Successes and limitations of image-based methods for monitoring grassland phenology

USDA-ARS?s Scientific Manuscript database

Seasonal changes in aboveground primary production (i.e. phenology) are influenced by environmental conditions with implications for land-atmosphere interactions, carbon cycling, and agricultural production. Monitoring phenology and quantifying seasonal patterns across spatially extensive grasslands...

Eco-Environment Status Evaluation and Change Analysis of Qinghai Based on National Geographic Conditions Census Data

NASA Astrophysics Data System (ADS)

Zheng, M.; Zhu, M.; Wang, Y.; Xu, C.; Yang, H.

2018-04-01

As the headstream of the Yellow River, the Yangtze River and the Lantsang River, located in the hinterland of Qinghai-Tibet Plateau, Qinghai province is hugely significant for ecosystem as well as for ecological security and sustainable development in China. With the accomplishment of the first national geographic condition census, the frequent monitoring has begun. The classification indicators of the census and monitoring data are highly correlated with Technical Criterion for Ecosystem Status Evaluation released by Ministry of Environmental Protection in 2015. Based on three years' geographic conditions data (2014-2016), Landsat-8 images and thematic data (water resource, pollution emissions, meteorological data, soil erosion, etc.), a multi-years and high-precision eco-environment status evaluation and spatiotemporal change analysis of Qinghai province has been researched on the basis of Technical Criterion for Ecosystem Status Evaluation in this paper. Unlike the evaluation implemented by environmental protection department, the evaluation unit in this paper is town rather than county. The evaluation result shows that the eco-environment status in Qinghai is generally in a fine condition, and has significant regional differences. The eco-environment status evaluation based on national geographic conditions census and monitoring data can improve both the time and space precision. The eco-environment status with high space precise and multi-indices is a key basis for environment protection decision-making.

Lithium-ion battery diagnostic and prognostic techniques

DOEpatents

Singh, Harmohan N.

2009-11-03

Embodiments provide a method and a system for determining cell imbalance condition of a multi-cell battery including a plurality of cell strings. To determine a cell imbalance condition, a charge current is applied to the battery and is monitored during charging. The charging time for each cell string is determined based on the monitor of the charge current. A charge time difference of any two cell strings in the battery is used to determine the cell imbalance condition by comparing with a predetermined acceptable charge time difference for the cell strings.

Robust Strategy for Rocket Engine Health Monitoring

NASA Technical Reports Server (NTRS)

Santi, L. Michael

2001-01-01

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

Metrological analysis of a virtual flowmeter-based transducer for cryogenic helium

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

Arpaia, P., E-mail: pasquale.arpaia@unina.it; Technology Department, European Organization for Nuclear Research; Girone, M., E-mail: mario.girone@cern.ch

2015-12-15

The metrological performance of a virtual flowmeter-based transducer for monitoring helium under cryogenic conditions is assessed. At this aim, an uncertainty model of the transducer, mainly based on a valve model, exploiting finite-element approach, and a virtual flowmeter model, based on the Sereg-Schlumberger method, are presented. The models are validated experimentally on a case study for helium monitoring in cryogenic systems at the European Organization for Nuclear Research (CERN). The impact of uncertainty sources on the transducer metrological performance is assessed by a sensitivity analysis, based on statistical experiment design and analysis of variance. In this way, the uncertainty sourcesmore » most influencing metrological performance of the transducer are singled out over the input range as a whole, at varying operating and setting conditions. This analysis turns out to be important for CERN cryogenics operation because the metrological design of the transducer is validated, and its components and working conditions with critical specifications for future improvements are identified.« less

The nursing perspective on monitoring hemodynamics and oxygen transport.

PubMed

Tucker, Dawn; Hazinski, Mary Fran

2011-07-01

Maintenance of adequate systemic oxygen delivery requires careful clinical assessment integrated with hemodynamic measurements and calculations to detect and treat conditions that may compromise oxygen delivery and lead to life-threatening shock, respiratory failure, or cardiac arrest. The bedside nurse constantly performs such assessments and measurements to detect subtle changes and trends in patient condition. The purpose of this editorial is to highlight nursing perspectives about the hemodynamic and oxygen transport monitoring systems summarized in the Pediatric Cardiac Intensive Care Society Evidence- Based Review and Consensus Statement on Monitoring of Hemodynamics and Oxygen Transport Balance. There is no substitute for the observations of a knowledgeable and experienced clinician who understands the patient's condition and potential causes of deterioration and is able to evaluate response to therapy.

Development of the USGS national land-cover database over two decades

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.; Yang, Limin; Weng, Qihao

2011-01-01

Land-cover composition and change have profound impacts on terrestrial ecosystems. Land-cover and land-use (LCLU) conditions and their changes can affect social and physical environments by altering ecosystem conditions and services. Information about LCLU change is often used to produce landscape-based metrics and evaluate landscape conditions to monitor LCLU status and trends over a specific time interval (Loveland et al. 2002; Coppin et al. 2004; Lunetta et al. 2006). Continuous, accurate, and up-to-date land-cover data are important for natural resource and ecosystem management and are needed to support consistent monitoring of landscape attributes over time. Large-area land-cover information at regional, national, and global scales is critical for monitoring landscape variations over large areas.

Wind Turbine Gearbox Oil Filtration and Condition Monitoring

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

Sheng, Shuangwen

This is an invited presentation for a pre-conference workshop, titled advances and opportunities in lubrication: wind turbine, at the 2015 Society of Tribologists and Lubrication Engineers (STLE) Tribology Frontiers Conference held in Denver, CO. It gives a brief overview of wind turbine gearbox oil filtration and condition monitoring by highlighting typical industry practices and challenges. The presentation starts with an introduction by covering recent growth of global wind industry, reliability challenges, benefits of oil filtration and condition monitoring, and financial incentives to conduct wind operation and maintenance research, which includes gearbox oil filtration and condition monitoring work presented herein. Then,more » the presentation moves on to oil filtration by stressing the benefits of filtration, discussing typical main- and offline-loop practices, highlighting important factors considered when specifying a filtration system, and illustrating real-world application challenges through a cold-start example. In the next section on oil condition monitoring, a discussion on oil sample analysis, oil debris monitoring, oil cleanliness measurements and filter analysis is given based on testing results mostly obtained by and at NREL, and by pointing out a few challenges with oil sample analysis. The presentation concludes with a brief touch on future research and development (R and D) opportunities. It is hoping that the information presented can inform the STLE community to start or redirect their R and D work to help the wind industry advance.« less

Real-Time Remote Monitoring with Data Acquisition System

NASA Astrophysics Data System (ADS)

Faizal Zainal Abidin, Ahmad; Huzaimy Jusoh, Mohammad; James, Elster; Junid, Syed Abdul Mutalib Al; Mohd Yassin, Ahmad Ihsan

2015-11-01

The purpose of this system is to provide monitoring system for an electrical device and enable remote monitoring via web based application. This monitoring system allow the user to monitor the device condition from anywhere as the information will be synchronised to the website. The current and voltage reading of the monitored equipment, ambient temperature and humidity level are monitored and recorded. These parameters will be updated on the web page. All these sensor are connected to the microcontroller and the data will saved in micro secure digital (SD) card and send all the gathered information to a web page using the GPRS service connection synchronously. The collected data will be displayed on the website and the user enable to download the data directly from the website. The system will help user to monitor the devices condition and ambient changes with ease. The system is successfully developed, tested and has been installed at residential area in Taman Cahaya Alam, Section U12, Shah Alam, Selangor, Malaysia.

Real-time indoor monitoring system based on wireless sensor networks

NASA Astrophysics Data System (ADS)

Wu, Zhengzhong; Liu, Zilin; Huang, Xiaowei; Liu, Jun

2008-10-01

Wireless sensor networks (WSN) greatly extend our ability to monitor and control the physical world. It can collaborate and aggregate a huge amount of sensed data to provide continuous and spatially dense observation of environment. The control and monitoring of indoor atmosphere conditions represents an important task with the aim of ensuring suitable working and living spaces to people. However, the comprehensive air quality, which includes monitoring of humidity, temperature, gas concentrations, etc., is not so easy to be monitored and controlled. In this paper an indoor WSN monitoring system was developed. In the system several sensors such as temperature sensor, humidity sensor, gases sensor, were built in a RF transceiver board for monitoring indoor environment conditions. The indoor environmental monitoring parameters can be transmitted by wireless to database server and then viewed throw PC or PDA accessed to the local area networks by administrators. The system, which was also field-tested and showed a reliable and robust characteristic, is significant and valuable to people.

Why are we prolonging QT interval monitoring?

PubMed

Barrett, Trina

2015-01-01

At present, monitoring of the QT interval (QTI) is not a standard practice in the medical intensive care unit setting, where many drugs that prolong the QTI are administered. This literature review looked at the current research for evidence-based standards to support QTI monitoring of patients with risk factors for QTI prolongation, which can result in life-threatening arrhythmias such as torsade de pointes. The objective of this article is to establish the existence of evidence-based standards for monitoring of the QTI and to raise awareness in the nursing profession of the need for such monitoring among patients who are at high risk for prolonged QTI. To determine whether published standards for QTI monitoring exist, a search was conducted of the bibliographic databases CINAHL, EBSCOhost, Medline, PubMed, Google Scholar, and the Cochrane Library for the years 2013 and 2014. Also, a survey was conducted to determine whether practice standards for QTI monitoring are being implemented at 4 major hospitals in the Memphis area, including a level 1 trauma center. The database search established the existence of published guidelines that support the need for QTI monitoring. Results of the hospital survey indicated that direct care nurses were not aware of the need to identify high-risk patients, drugs with the potential to prolong QTI that were being administered to their patients, or evidence-based standards for QTI monitoring. Review of the research literature underscored the need for QTI monitoring among high-risk patients, that is, those with genetic conditions that predispose them to QTI prolongation, those with existing cardiac conditions being treated with antiarrhythmic medications, or those who are prescribed any new medication classified as high risk on the basis of clinical research. This need is especially crucial in intensive care unit settings, where many antiarrhythmic medications are administered.

Task-dependent response conflict monitoring and cognitive control in anterior cingulate and dorsolateral prefrontal cortices.

PubMed

Kim, Chobok; Chung, Chongwook; Kim, Jeounghoon

2013-11-06

Previous experience affects our behavior in terms of adjustments. It has been suggested that the conflict monitor-controller system implemented in the prefrontal cortex plays a critical role in such adjustments. Previous studies suggested that there exists multiple conflict monitor-controller systems associated with the level of information (i.e., stimulus and response levels). In this study, we sought to test whether different types of conflicts occur at the same information processing level (i.e., response level) are independently processed. For this purpose, we designed a task paradigm to measure two different types of response conflicts using color-based and location-based conflict stimuli and measured the conflict adaptation effects associated with the two types of conflicts either independently (i.e., single conflict conditions) or simultaneously (i.e., a double-conflict condition). The behavioral results demonstrated that performance on current incongruent trials was faster only when the preceding trial was the same type of response conflict regardless of whether they included a single- or double-conflict. Imaging data also showed that anterior cingulate and dorsolateral prefrontal cortices operate in a task-specific manner. These findings suggest that there may be multiple monitor-controller loops for color-based and location-based conflicts even at the same response level. Importantly, our results suggest that double-conflict processing is qualitatively different from single-conflict processing although double-conflict shares the same sources of conflict with two single-conflict conditions. © 2013 Published by Elsevier B.V.

Non-Intrusive Load Monitoring of HVAC Components using Signal Unmixing

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

Rahimpour, Alireza; Qi, Hairong; Fugate, David L

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving higher energy efficiency. In this paper, a novel non-intrusive load monitoring method based on group constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only measuring the whole building aggregated power signal. At the first level of this hierarchical approach, power consumptionmore » of the building is decomposed to energy consumption of the HVAC unit and all the other electrical devices operating in the building such as lighting and plug loads. Then, the estimated power signal of the HVAC is used for estimating the power consumption profile of the HVAC major electrical loads such as compressors, condenser fans and indoor blower. Experiments conducted on real data collected from a building testbed maintained at the Oak Ridge National Laboratory (ORNL) demonstrate high accuracy on the disaggregation task.« less

Vibration energy harvesting based monitoring of an operational bridge undergoing forced vibration and train passage

NASA Astrophysics Data System (ADS)

Cahill, Paul; Hazra, Budhaditya; Karoumi, Raid; Mathewson, Alan; Pakrashi, Vikram

2018-06-01

The application of energy harvesting technology for monitoring civil infrastructure is a bourgeoning topic of interest. The ability of kinetic energy harvesters to scavenge ambient vibration energy can be useful for large civil infrastructure under operational conditions, particularly for bridge structures. The experimental integration of such harvesters with full scale structures and the subsequent use of the harvested energy directly for the purposes of structural health monitoring shows promise. This paper presents the first experimental deployment of piezoelectric vibration energy harvesting devices for monitoring a full-scale bridge undergoing forced dynamic vibrations under operational conditions using energy harvesting signatures against time. The calibration of the harvesters is presented, along with details of the host bridge structure and the dynamic assessment procedures. The measured responses of the harvesters from the tests are presented and the use the harvesters for the purposes of structural health monitoring (SHM) is investigated using empirical mode decomposition analysis, following a bespoke data cleaning approach. Finally, the use of sequential Karhunen Loeve transforms to detect train passages during the dynamic assessment is presented. This study is expected to further develop interest in energy-harvesting based monitoring of large infrastructure for both research and commercial purposes.

Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines

PubMed Central

He, Kun; Yang, Zhijun; Bai, Yun; Long, Jianyu; Li, Chuan

2018-01-01

Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM). An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field intensity. The attitude data of the working printer were collected under different conditions involving 12 fault types and a normal condition. The collected data were analyzed for diagnosing the health condition. To this end, the combination of binary classification, one-against-one with least-square SVM, was adopted for fault diagnosis modelling by using all channels of attitude monitoring data in the experiment. For comparison, each one channel of the attitude monitoring data was employed for model training and testing. On the other hand, a back propagation neural network (BPNN) was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44%) was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers. PMID:29690641

Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines.

PubMed

He, Kun; Yang, Zhijun; Bai, Yun; Long, Jianyu; Li, Chuan

2018-04-23

Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM). An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field intensity. The attitude data of the working printer were collected under different conditions involving 12 fault types and a normal condition. The collected data were analyzed for diagnosing the health condition. To this end, the combination of binary classification, one-against-one with least-square SVM, was adopted for fault diagnosis modelling by using all channels of attitude monitoring data in the experiment. For comparison, each one channel of the attitude monitoring data was employed for model training and testing. On the other hand, a back propagation neural network (BPNN) was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44%) was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers.

Towards a sampling strategy for the assessment of forest condition at European level: combining country estimates.

PubMed

Travaglini, Davide; Fattorini, Lorenzo; Barbati, Anna; Bottalico, Francesca; Corona, Piermaria; Ferretti, Marco; Chirici, Gherardo

2013-04-01

A correct characterization of the status and trend of forest condition is essential to support reporting processes at national and international level. An international forest condition monitoring has been implemented in Europe since 1987 under the auspices of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The monitoring is based on harmonized methodologies, with individual countries being responsible for its implementation. Due to inconsistencies and problems in sampling design, however, the ICP Forests network is not able to produce reliable quantitative estimates of forest condition at European and sometimes at country level. This paper proposes (1) a set of requirements for status and change assessment and (2) a harmonized sampling strategy able to provide unbiased and consistent estimators of forest condition parameters and of their changes at both country and European level. Under the assumption that a common definition of forest holds among European countries, monitoring objectives, parameters of concern and accuracy indexes are stated. On the basis of fixed-area plot sampling performed independently in each country, an unbiased and consistent estimator of forest defoliation indexes is obtained at both country and European level, together with conservative estimators of their sampling variance and power in the detection of changes. The strategy adopts a probabilistic sampling scheme based on fixed-area plots selected by means of systematic or stratified schemes. Operative guidelines for its application are provided.

Development and implementation of a GEOGLAM Crop Monitor web interface

NASA Astrophysics Data System (ADS)

Oliva, P.; Sanchez, A.; Humber, M. L.; Becker-Reshef, I.; Justice, C. J.; McGaughey, K.; Barker, B.

2016-12-01

Beginning in September 2013, the GEOGLAM Crop Monitor activity has provided earth observation (EO) data to a network of partners and collected crop assessments on a subnational basis through a web interface known as the Crop Assessment Tool. Based on the collection of monthly crop assessments, a monthly crop condition bulletin is published in the Agricultural Market Information System (AMIS) Market Monitor report. This workflow has been successfully applied to food security applications through the Early Warning Crop Monitor activity. However, a lack of timely and accurate information on crop conditions and prospects at the national scale is a critical issue in the majority of southern and eastern African countries and some South American countries. Such information is necessary for informed and prompt decision making in the face of emergencies, food insecurity and planning requirements for agricultural markets. This project addresses these needs through the development of relevant, user-friendly remote sensing monitor systems, collaborative internet technology, and collaboration with national and regional agricultural monitoring networks. By building on current projects and relationships established through the various GEOGLAM Crop Monitor activities, this project aims to ultimately provide EO-informed crop condition maps and charts designed for economics and policy oriented audiences, thereby providing quick and easy to understand products on crop conditions as the season progresses. Integrating these data and assessments vertically throughout the system provides a basis for regional sharing and collaboration in food security applications.

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

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

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less

Supervised versus unsupervised technology-based levodopa monitoring in Parkinson's disease: an intrasubject comparison.

PubMed

Lopane, Giovanna; Mellone, Sabato; Corzani, Mattia; Chiari, Lorenzo; Cortelli, Pietro; Calandra-Buonaura, Giovanna; Contin, Manuela

2018-06-01

We aimed to assess the intrasubject reproducibility of a technology-based levodopa (LD) therapeutic monitoring protocol administered in supervised versus unsupervised conditions in patients with Parkinson's disease (PD). The study design was pilot, intrasubject, single center, open and prospective. Twenty patients were recruited. Patients performed a standardized monitoring protocol instrumented by an ad hoc embedded platform after their usual first morning LD dose in two different randomized ambulatory sessions: one under a physician's supervision, the other self-administered. The protocol is made up of serial motor and non-motor tests, including alternate finger tapping, Timed Up and Go test, and measurement of blood pressure. Primary motor outcomes included comparisons of intrasubject LD subacute motor response patterns over the 3-h test in the two experimental conditions. Secondary outcomes were the number of intrasession serial test repetitions due to technical or handling errors and patients' satisfaction with the unsupervised LD monitoring protocol. Intrasubject LD motor response patterns were concordant between the two study sessions in all patients but one. Platform handling problems averaged 4% of total planned serial tests for both sessions. Ninety-five percent of patients were satisfied with the self-administered LD monitoring protocol. To our knowledge, this study is the first to explore the potential of unsupervised technology-based objective motor and non-motor tasks to monitor subacute LD dosing effects in PD patients. The results are promising for future telemedicine applications.

Damage Detection Sensitivity of a Vehicle-based Bridge Health Monitoring System

NASA Astrophysics Data System (ADS)

Miyamoto, Ayaho; Yabe, Akito; Lúcio, Válter J. G.

2017-05-01

As one solution to the problem for condition assessment of existing short and medium span (10-30m) reinforced/prestressed concrete bridges, a new monitoring method using a public bus as part of a public transit system (called “Bus monitoring system”) was proposed, along with safety indices, namely, “characteristic deflection”, which is relatively free from the influence of dynamic disturbances due to such factors as the roughness of the road surface, and a structural anomaly parameter. In this study, to evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. In here, although there are some useful monitoring methods for short and medium span bridges based on the qualitative or quantitative information, the sensitivity of damage detection was newly discussed for safety assessment based on long term health monitoring data. The verification results thus obtained are also described in this paper, and also evaluates the sensitivity of the “characteristic deflection”, which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of “characteristic deflection” is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. Furthermore, the sensitivity of “characteristic deflection” is verified by 3D FEM analysis.

Tetramethylbenzidine method for monitoring the free available chlorine and microbicidal activity of chlorite-based sanitizers under organic-matter-rich environments.

PubMed

Yamaoka, H; Nakayama-Imaohji, H; Horiuchi, I; Yamasaki, H; Nagao, T; Fujita, Y; Maeda, H; Goda, H; Kuwahara, T

2016-01-01

Chlorine is a principal disinfectant for food and environmental sanitation. Monitoring of free available chlorine (FAC) is essential for ensuring the efficacy of food disinfection processes that rely on chlorine. N,N-diethyl-p-phenylenediamine (DPD) is commonly used for FAC monitoring. However, here, we show that upon contact with bovine serum albumin (BSA) or broiler carcasses, chlorite (HClO2 )-based sanitizers acquire a pink colour, which can interfere with measurement of oxidized DPD absorbance at 513-550 nm. Alternatively, the pink colour did not interfere with 3,3',5,5'-tetramethylbenzidine (TMB)-based FAC monitoring. The FAC levels of NaClO and weakly acidified chlorous acid water (WACAW) were first adjusted by the TMB method and the killing activity of these sanitizers towards methicillin-resistant Staphylococcus aureus (MRSA) and feline calicivirus (FCV) was compared in the presence or absence of 0·5% BSA. At 200 ppm FAC, NaClO lost its bactericidal activity against MRSA after 10-min incubation with 0·5% BSA. Meanwhile, under the same conditions WACAW reduced the number of bacteria to below the detection limit. Similar results were obtained with FCV, indicating that the chlorite-based WACAW sanitizer is relatively stable under organic-matter-rich conditions. Moreover, TMB is suitable for in situ FAC monitoring of chlorite-based sanitizers in food and environmental disinfection processes. For practical applications of chlorine in food processing, monitoring of FAC is critical to validate disinfection efficacy. In this study we found that chlorite-based sanitizers acquired a pink colour upon contact with BSA or broiler carcasses. This pink colour interfered with FAC monitoring by methods that measure oxidized N,N-diethyl-p-phenylenediamine absorbance between 513-550 nm. Alternatively, FAC levels of chlorite-based sanitizers could be monitored using the absorbance of 3,3',5,5'-tetramethylbenzidine at 650 nm, which does not overlap with the acquired pink colour. These data provide valuable information for safety management of disinfection processes that use chlorite-based sanitizers. © 2015 The Society for Applied Microbiology.

Sound at the zoo: Using animal monitoring, sound measurement, and noise reduction in zoo animal management.

PubMed

Orban, David A; Soltis, Joseph; Perkins, Lori; Mellen, Jill D

2017-05-01

A clear need for evidence-based animal management in zoos and aquariums has been expressed by industry leaders. Here, we show how individual animal welfare monitoring can be combined with measurement of environmental conditions to inform science-based animal management decisions. Over the last several years, Disney's Animal Kingdom® has been undergoing significant construction and exhibit renovation, warranting institution-wide animal welfare monitoring. Animal care and science staff developed a model that tracked animal keepers' daily assessments of an animal's physical health, behavior, and responses to husbandry activity; these data were matched to different external stimuli and environmental conditions, including sound levels. A case study of a female giant anteater and her environment is presented to illustrate how this process worked. Associated with this case, several sound-reducing barriers were tested for efficacy in mitigating sound. Integrating daily animal welfare assessment with environmental monitoring can lead to a better understanding of animals and their sensory environment and positively impact animal welfare. © 2017 Wiley Periodicals, Inc.

Resilient monitoring systems: architecture, design, and application to boiler/turbine plant.

PubMed

Garcia, Humberto E; Lin, Wen-Chiao; Meerkov, Semyon M; Ravichandran, Maruthi T

2014-11-01

Resilient monitoring systems, considered in this paper, are sensor networks that degrade gracefully under malicious attacks on their sensors, causing them to project misleading information. The goal of this paper is to design, analyze, and evaluate the performance of a resilient monitoring system intended to monitor plant conditions (normal or anomalous). The architecture developed consists of four layers: data quality assessment, process variable assessment, plant condition assessment, and sensor network adaptation. Each of these layers is analyzed by either analytical or numerical tools. The performance of the overall system is evaluated using a simplified boiler/turbine plant. The measure of resiliency is quantified based on the Kullback-Leibler divergence and shown to be sufficiently high in all scenarios considered.

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.

Motor current signature analysis for gearbox condition monitoring under transient speeds using wavelet analysis and dual-level time synchronous averaging

NASA Astrophysics Data System (ADS)

Bravo-Imaz, Inaki; Davari Ardakani, Hossein; Liu, Zongchang; García-Arribas, Alfredo; Arnaiz, Aitor; Lee, Jay

2017-09-01

This paper focuses on analyzing motor current signature for fault diagnosis of gearboxes operating under transient speed regimes. Two different strategies are evaluated, extensively tested and compared to analyze the motor current signature in order to implement a condition monitoring system for gearboxes in industrial machinery. A specially designed test bench is used, thoroughly monitored to fully characterize the experiments, in which gears in different health status are tested. The measured signals are analyzed using discrete wavelet decomposition, in different decomposition levels using a range of mother wavelets. Moreover, a dual-level time synchronous averaging analysis is performed on the same signal to compare the performance of the two methods. From both analyses, the relevant features of the signals are extracted and cataloged using a self-organizing map, which allows for an easy detection and classification of the diverse health states of the gears. The results demonstrate the effectiveness of both methods for diagnosing gearbox faults. A slightly better performance was observed for dual-level time synchronous averaging method. Based on the obtained results, the proposed methods can used as effective and reliable condition monitoring procedures for gearbox condition monitoring using only motor current signature.

Online Condition Monitoring of Gripper Cylinder in TBM Based on EMD Method

NASA Astrophysics Data System (ADS)

Li, Lin; Tao, Jian-Feng; Yu, Hai-Dong; Huang, Yi-Xiang; Liu, Cheng-Liang

2017-11-01

The gripper cylinder that provides braced force for Tunnel Boring Machine (TBM) might fail due to severe vibration when the TBM excavates in the tunnel. Early fault diagnosis of the gripper cylinder is important for the safety and efficiency of the whole tunneling project. In this paper, an online condition monitoring system based on the Empirical Mode Decomposition (EMD) method is established for fault diagnosis of the gripper cylinder while TBM is working. Firstly, the lumped mass parameter model of the gripper cylinder is established considering the influence of the variable stiffness at the rock interface, the equivalent stiffness of the oil, the seals, and the copper guide sleeve. The dynamic performance of the gripper cylinder is investigated to provide basis for its health condition evaluation. Then, the EMD method is applied to identify the characteristic frequencies of the gripper cylinder for fault diagnosis and a field test is used to verify the accuracy of the EMD method for detection of the characteristic frequencies. Furthermore, the contact stiffness at the interface between the barrel and the rod is calculated with Hertz theory and the relationship between the natural frequency and the stiffness varying with the health condition of the cylinder is simulated based on the dynamic model. The simulation shows that the characteristic frequencies decrease with the increasing clearance between the barrel and the rod, thus the defects could be indicated by monitoring the natural frequency. Finally, a health condition management system of the gripper cylinder based on the vibration signal and the EMD method is established, which could ensure the safety of TBM.

Design and implementation of a Bluetooth-based infant monitoring/saver (BIMS) system

NASA Astrophysics Data System (ADS)

Sonmez, Ahmet E.; Nalcaci, Murat T.; Pazarbasi, Mehmet A.; Toker, Onur; Fidanboylu, Kemal

2007-04-01

In this work, we discuss the design and implementation of a Bluetooth technology based infant monitoring system, which will enable the mother to monitor her baby's health condition remotely in real-time. The system will measure the heart rate, and temperature of the infant, and stream this data to the mother's Bluetooth based mobile unit, e.g. cell phone, PDA, etc. Existing infant monitors either require so many cables, or transmit only voice and/or video information, which is not enough for monitoring the health condition of an infant. With the proposed system, the mother will be warned against any abnormalities, which may be an indication of a disease, which in turn may result a sudden infant death. High temperature is a common symptom for several diseases, and heart rate is an essential sign of life, low or high heart rates are also essentials symptoms. Because of these reasons, the proposed system continously measures these two critical values. A 12 bits digital temperature sensor is used to measure infant's body temperature, and a piezo film sensor is used measure infant's heartbeat rate. These sensors, some simple analog circuitry, and a ToothPick unit are the main components of our embedded system. ToothPick unit is basically a Microchip 18LF6720 microcontroller, plus an RF circuitry with Bluetooth stack.

Priority target conditions for algorithms for monitoring children's growth: Interdisciplinary consensus.

PubMed

Scherdel, Pauline; Reynaud, Rachel; Pietrement, Christine; Salaün, Jean-François; Bellaïche, Marc; Arnould, Michel; Chevallier, Bertrand; Piloquet, Hugues; Jobez, Emmanuel; Cheymol, Jacques; Bichara, Emmanuelle; Heude, Barbara; Chalumeau, Martin

2017-01-01

Growth monitoring of apparently healthy children aims at early detection of serious conditions through the use of both clinical expertise and algorithms that define abnormal growth. Optimization of growth monitoring requires standardization of the definition of abnormal growth, and the selection of the priority target conditions is a prerequisite of such standardization. To obtain a consensus about the priority target conditions for algorithms monitoring children's growth. We applied a formal consensus method with a modified version of the RAND/UCLA method, based on three phases (preparatory, literature review, and rating), with the participation of expert advisory groups from the relevant professional medical societies (ranging from primary care providers to hospital subspecialists) as well as parent associations. We asked experts in the pilot (n = 11), reading (n = 8) and rating (n = 60) groups to complete the list of diagnostic classification of the European Society for Paediatric Endocrinology and then to select the conditions meeting the four predefined criteria of an ideal type of priority target condition. Strong agreement was obtained for the 8 conditions selected by the experts among the 133 possible: celiac disease, Crohn disease, craniopharyngioma, juvenile nephronophthisis, Turner syndrome, growth hormone deficiency with pituitary stalk interruption syndrome, infantile cystinosis, and hypothalamic-optochiasmatic astrocytoma (in decreasing order of agreement). This national consensus can be used to evaluate the algorithms currently suggested for growth monitoring. The method used for this national consensus could be re-used to obtain an international consensus.

Comparison of different incubation conditions for microbiological environmental monitoring.

PubMed

Gordon, Oliver; Berchtold, Manfred; Staerk, Alexandra; Roesti, David

2014-01-01

Environmental monitoring represents an integral part of the microbiological quality control system of a pharmaceutical manufacturing operation. However, guidance documents differ regarding recommendation of a procedure, particularly regarding incubation time, incubation temperature, or nutrient media. Because of these discrepancies, many manufacturers decide for a particular environmental monitoring sample incubation strategy and support this decision with validation data. Such validations are typically laboratory-based in vitro studies, meaning that these are based on comparing incubation conditions and nutrient media through use of cultured microorganisms. An informal survey of the results of these in vitro studies performed at Novartis or European manufacturing sites of different pharmaceutical companies highlighted that no consensus regarding the optimal incubation conditions for microbial recovery existed. To address this question differently, we collected a significant amount of samples directly from air, inanimate surfaces, and personnel in pharmaceutical production and packaging rooms during manufacturing operation (in situ study). Samples were incubated under different conditions suggested in regulatory guidelines, and recovery of total aerobic microorganisms as well as moulds was assessed. We found the highest recovery of total aerobic count from areas with personnel flow using a general microbiological growth medium incubated at 30-35 °C. The highest recovery of moulds was obtained with mycological medium incubated at 20-25 °C. Single-plate strategies (two-temperature incubation or an intermediate incubation temperature of 25-30 °C) also yielded reasonable recovery of total aerobic count and moulds. However, recovery of moulds was found to be highly inefficient at 30-35 °C compared to lower incubation temperatures. This deficiency could not be rectified by subsequent incubation at 20-25 °C. A laboratory-based in vitro study performed in parallel was inconclusive. We consider our results potentially conferrable to other pharmaceutical manufacturing sites in moderate climate zones and believe that these should represent a valuable reference for definition of the incubation strategy of microbiological environmental monitoring samples. Microbiological environmental monitoring confirms that pharmaceutical cleanrooms are in an appropriate hygienic condition for manufacturing of drug products. Guidance documents from different health authorities or expert groups differ regarding recommendation of the applied incubation time, incubation temperature, or nutrient media. Therefore, many pharmaceutical manufacturers perform studies that aim to identify the optimal incubation setup for environmental monitoring samples. An informal survey of the results of such studies, which had been performed at Novartis or European manufacturing sites of different pharmaceutical companies, highlighted no consensus regarding the optimal incubation conditions for microbial recovery. All these studies had been conducted in the laboratory using selections of cultured microbial strains. We tried to solve this disagreement by collecting a significant amount of real environmental monitoring samples directly from the environment in pharmaceutical production and packaging rooms during manufacturing operation. These samples were then incubated under different conditions suggested in the regulatory guidelines. We believe that the results of our study are more meaningful than laboratory-based experiments because we used environmental samples with microorganisms directly isolated from the manufacturing area. Therefore, we believe that our results should represent a valuable reference for definition of the incubation strategy of microbiological environmental monitoring samples. © PDA, Inc. 2014.

Low-cost measurement and monitoring system for cryogenic applications

NASA Astrophysics Data System (ADS)

Tubío Araújo, Óscar; Hernández Suárez, Elvio; Gracia Temich, Félix

2016-07-01

Cryostats are closed chambers that hinder the monitoring of materials, structures or systems installed therein. This paper presents a webcam-based measurement and monitoring system, which can operate under vacuum and cryogenic conditions to be mainly used in astrophysical applications. The system can be configured in two different assemblies: wide field that can be used for mechanism monitoring and narrow field, especially useful in cryogenic precision measurements with a resolution up to 4 microns/pixel.

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

Integration of multispectral and SAR data for monitoring forest ecosystems recovery after fire

NASA Astrophysics Data System (ADS)

Stankova, Nataliya; Nedkov, Roumen; Ivanova, Iva; Avetisyan, Daniela

2017-09-01

The aim of this study is assessing the impacts and monitoring the condition and recovery processes of forest ecosystems after fire based on remote aerospace methods and data. To achieve this goal, satellite imagery in microwave and optical range of the spectrum were used. A hybrid model for assessing the instantaneous condition of forest ecosystems after fire that uses parallel data from optical and Synthetic Aperture Radar (SAR) was developed. Based on the three Tasseled Cap components (Brightness-BR, Greenness-GR and Wetness-W), a vector describing the current condition of the forest ecosystems was obtained and used as input data from the optical range. Results obtained by implementation of the proposed approach show that the integrated composite images of VIC and SAR represent the degree of recovery.

Investigation of piezoelectric impedance-based health monitoring of structure interface debonding

NASA Astrophysics Data System (ADS)

Xiao, Li; Chen, Guofeng; Chen, Xiaoming; Qu, Wenzhong

2016-04-01

Various damages might occur during the solid rocket motor (SRM) manufacturing/operational phase, and the debonding of propellant/insulator/composite case interfaces is one of damage types which determine the life of a motor. The detection of such interface debonding damage will be beneficial for developing techniques for reliable nondestructive evaluation (NDE) and structural health monitoring (SHM). Piezoelectric sensors are widely used for structural health monitoring technique. In particular, electromechanical impedance (EMI) techniques give simple and low-cost solutions for detecting damage in various structures. In this work, piezoelectric EMI structural health monitoring technique is applied to identify the debonding condition of propellant/insulator interface structure using finite element method and experimental investigation. A three-dimensional coupled field finite element model is developed using the software ANSYS and the harmonic analysis is conducted for high-frequency impedance analysis procedure. In the experimental study, the impedance signals were measured from PZT and MFC sensors outside attached to composite case monitoring the different debonding conditions between the propellant and insulator. Root mean square deviation (RMSD) based damage index is conducted to quantify the changes i n impedance for different de bonding conditions and frequency range. Simulation and experimental results confirmed that the EMI technique can be used effectively for detecting the debonding damage in SRM and is expected to be useful for future application of real SRM's SHM.

Vehicle Counting and Moving Direction Identification Based on Small-Aperture Microphone Array.

PubMed

Zu, Xingshui; Zhang, Shaojie; Guo, Feng; Zhao, Qin; Zhang, Xin; You, Xing; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

2017-05-10

The varying trend of a moving vehicle's angles provides much important intelligence for an unattended ground sensor (UGS) monitoring system. The present study investigates the capabilities of a small-aperture microphone array (SAMA) based system to identify the number and moving direction of vehicles travelling on a previously established route. In this paper, a SAMA-based acoustic monitoring system, including the system hardware architecture and algorithm mechanism, is designed as a single node sensor for the application of UGS. The algorithm is built on the varying trend of a vehicle's bearing angles around the closest point of approach (CPA). We demonstrate the effectiveness of our proposed method with our designed SAMA-based monitoring system in various experimental sites. The experimental results in harsh conditions validate the usefulness of our proposed UGS monitoring system.

ELECTRONIC PUBLICATION OF DATA AND METHODS FOR COASTAL MONITORING AND ASSESSMENT

EPA Science Inventory

We are designing an electronic report on coastal conditions in the Northeast (from Delaware to Maine) for release in 2005. The report will be similar in appearance to a chapter on Northeast Coastal Conditions (EPA, National Coastal Condition Report 2), but based on twice as many...

Haul truck tire dynamics due to tire condition

NASA Astrophysics Data System (ADS)

Vaghar Anzabi, R.; Nobes, D. S.; Lipsett, M. G.

2012-05-01

Pneumatic tires are costly components on large off-road haul trucks used in surface mining operations. Tires are prone to damage during operation, and these events can lead to injuries to personnel, loss of equipment, and reduced productivity. Damage rates have significant variability, due to operating conditions and a range of tire fault modes. Currently, monitoring of tire condition is done by physical inspection; and the mean time between inspections is often longer than the mean time between incipient failure and functional failure of the tire. Options for new condition monitoring methods include off-board thermal imaging and camera-based optical methods for detecting abnormal deformation and surface features, as well as on-board sensors to detect tire faults during vehicle operation. Physics-based modeling of tire dynamics can provide a good understanding of the tire behavior, and give insight into observability requirements for improved monitoring systems. This paper describes a model to simulate the dynamics of haul truck tires when a fault is present to determine the effects of physical parameter changes that relate to faults. To simulate the dynamics, a lumped mass 'quarter-vehicle' model has been used to determine the response of the system to a road profile when a failure changes the original properties of the tire. The result is a model of tire vertical displacement that can be used to detect a fault, which will be tested under field conditions in time-varying conditions.

Marine environmental impact assessment of abalone, Haliotis discus hannai, cage farm in Wan-do, Republic of Korea

NASA Astrophysics Data System (ADS)

Oh, Hyun-Taik; Jung, Rae-Hong; Cho, Yoon-Sik; Hwang, Dong-Woon; Yi, Yong-Min

2015-12-01

To assess the marine environmental impacts of abalone, Haliotis discus hannai, cage farms in Wan-do, we monitored the benthic environment on top of the sediment underneath cage farm stations and reference stations. We applied two methods for this assessment. One was the A- and B-investigation of the MOM system (Modeling-On fish farm-Monitoring) developed in Norway. The other was a general environmental monitoring method which is widely used. In this study, we found benthic animals in all samples that belonged to condition 1 which were based on group 1(presence of macrofauna) of the B-investigation method. The values of redox potential (group 2-pH, redox potential) in all samples were above +65 mV belonging to condition 1. Based on sensory results (group 3-gas, color, odor, thickness of deposits), five out of seven experiment samples showed condition 1 while stations 2 and 7 showed condition 2, which have been cultured for 10 years in semi-closed waters. As group 2 takes precedence over group 3, the level of the conditions for B-investigation results consequently showed condition 1 in all stations. We found that pollutants and trace metals in the sediment underneath cage farms were lower than the pollution standard. This led us to conclude that the environmental impacts of the cage farms in this study were not significant.

BioMon: A Google Earth Based Continuous Biomass Monitoring System (Demo Paper)

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

Vatsavai, Raju

2009-01-01

We demonstrate a Google Earth based novel visualization system for continuous monitoring of biomass at regional and global scales. This system is integrated with a back-end spatiotemporal data mining system that continuously detects changes using high temporal resolution MODIS images. In addition to the visualization, we demonstrate novel query features of the system that provides insights into the current conditions of the landscape.

Intracranial pressure and cerebral perfusion pressure monitoring in non-TBI patients: special considerations.

PubMed

Helbok, Raimund; Olson, DaiWai M; Le Roux, Peter D; Vespa, Paul

2014-12-01

The effect of intracranial pressure (ICP) and the role of ICP monitoring are best studied in traumatic brain injury (TBI). However, a variety of acute neurologic illnesses e.g., subarachnoid hemorrhage, intracerebral hemorrhage, ischemic stroke, meningitis/encephalitis, and select metabolic disorders, e.g., liver failure and malignant, brain tumors can affect ICP. The purpose of this paper is to review the literature about ICP monitoring in conditions other than TBI and to provide recommendations how the technique may be used in patient management. A PubMed search between 1980 and September 2013 identified 989 articles; 225 of which were reviewed in detail. The technique used to monitor ICP in non-TBI conditions is similar to that used in TBI; however, indications for ICP monitoring often are intertwined with the presence of obstructive hydrocephalus and hence the use of ventricular catheters is more frequent. Increased ICP can adversely affect outcome, particularly when it fails to respond to treatment. However, patients with elevated ICP can still have favorable outcomes. Although the influence of ICP-based care on outcome in non-TBI conditions appears less robust than in TBI, monitoring ICP and cerebral perfusion pressure can play a role in guiding therapy in select patients.

Applicability of rapid and on-site measured enzyme activity for surface water quality monitoring in an agricultural catchment

NASA Astrophysics Data System (ADS)

Stadler, Philipp; Farnleitner, Andreas H.; Sommer, Regina; Kumpan, Monika; Zessner, Matthias

2014-05-01

For the near real time and on-site detection of microbiological fecal pollution of water, the measurement of beta-D- Glucuronidase (GLUC) enzymatic activity has been suggested as a surrogate parameter and has been already successfully operated for water quality monitoring of ground water resources (Ryzinska-Paier et al. 2014). Due to possible short measure intervals of three hours, this method has high potential as a water quality monitoring tool. While cultivation based standard determination takes more than one working day (Cabral 2010) the potential advantage of detecting the GLUC activity is the high temporal measuring resolution. Yet, there is still a big gap of knowledge on the fecal indication capacity of GLUC (specificity, sensitivity, persistence, etc.) in relation to potential pollution sources and catchment conditions (Cabral 2010, Ryzinska-Paier et al. 2014). Furthermore surface waters are a big challenge for automated detection devices in a technical point of view due to the high sediment load during event conditions. This presentation shows results gained form two years of monitoring in an experimental catchment (HOAL) dominated by agricultural land use. Two enzymatic measurement devices are operated parallel at the catchment outlet to test the reproducibility and precision of the method. Data from continuous GLUC monitoring under both base flow and event conditions is compared with reference samples analyzed by standardized laboratory methods for fecal pollution detection (e.g. ISO 16649-1, Colilert18). It is shown that rapid enzymatic on-site GLUC determination can successfully be operated from a technical point of view for surface water quality monitoring under the observed catchment conditions. The comparison of enzyme activity with microbiological standard analytics reveals distinct differences in the dynamic of the signals during event conditions. Cabral J. P. S. (2010) "Water Microbiology. Bacterial Pathogens and Water" International Journal of Environmental Research and Public Health 7 (10): 3657-3703. Ryzinska-Paier, G., T. Lendenfeld, K. Correa, P. Stadler, A.P. Blaschke, R. L. Mach, H. Stadler, AKT Kirschner und A.H. Farnleitner (2014) A sensitive and robust method for automated on-line monitoring of enzymatic activities in water and water resources. Water Sci. Technol. in press

The changes of cerebral hemodynamics during ketamine induced anesthesia in a rat model.

PubMed

Bae, Jayyoung; Shin, Teo J; Kim, Seonghyun; Choi, Dong-Hyuk; Cho, Dongrae; Ham, Jinsil; Manca, Marco; Jeong, Seongwook; Lee, Boreom; Kim, Jae G

2018-05-25

Current electroencephalogram (EEG) based-consciousness monitoring technique is vulnerable to specific clinical conditions (eg, epilepsy and dementia). However, hemodynamics is the most fundamental and well-preserved parameter to evaluate, even under severe clinical situations. In this study, we applied near-infrared spectroscopy (NIRS) system to monitor hemodynamic change during ketamine-induced anesthesia to find its correlation with the level of consciousness. Oxy-hemoglobin (OHb) and deoxy-hemoglobin concentration levels were continuously acquired throughout the experiment, and the reflectance ratio between 730 and 850 nm was calculated to quantify the hemodynamic changes. The results showed double peaks of OHb concentration change during ketamine anesthesia, which seems to be closely related to the consciousness state of the rat. This finding suggests the possibility of NIRS based-hemodynamic monitoring as a supplementary parameter for consciousness monitoring, compensating drawbacks of EEG signal based monitoring. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A new fiber sensor based on graphene coating technique for wearable equipment

NASA Astrophysics Data System (ADS)

Wu, Ensen; Zhang, Jinnan; Qiao, Min; Cao, Yanghua; Wang, Qi; Ren, Xiaomin; Zuo, Yong

2018-02-01

We propose and implement a graphene-based composite fiber sensor in this paper. The advantages of this composite fiber lie in simple and practicable fabrication, high sensitivity to tensile strain deformation, wide maximal sensing range. The experiment shows that the composite fiber can monitor small signals of the body and massive movements in conventionality condition such as human pulse and the movement of elbow. This suggests that this graphene-based composite fiber has a broad prospect in health monitoring and movement recognition.

Monitoring the Condition of Education.

ERIC Educational Resources Information Center

Buccino, Alphonse

Five categories of data collection are recommended for monitoring the quality of education: (1) outcomes, based on an input-output model, including data from student testing and credentials and degrees; (2) participation--who is served by education; (3) resources available to education; (4) long-term impact of education on work, income,…

A method for turbine blade temperature data segmentation

NASA Astrophysics Data System (ADS)

Feng, Chi; Wang, Li; Gao, Shan

2017-08-01

Turbine blade, as one of the key components of the engine, operates in the badly working conditions. In order to better monitor the temperature status of turbine blades, research on temperature distribution of working blades is significant. The paper applies discrete Fourier transform to develop mathematical models, and the changes of period and peaks are summarized. The changing trends of temperature are reflected in each blade. The trends can be treated as one of the bases of the blade condition monitoring and fault diagnosis.

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.

Home medical monitoring network based on embedded technology

NASA Astrophysics Data System (ADS)

Liu, Guozhong; Deng, Wenyi; Yan, Bixi; Lv, Naiguang

2006-11-01

Remote medical monitoring network for long-term monitoring of physiological variables would be helpful for recovery of patients as people are monitored at more comfortable conditions. Furthermore, long-term monitoring would be beneficial to investigate slowly developing deterioration in wellness status of a subject and provide medical treatment as soon as possible. The home monitor runs on an embedded microcomputer Rabbit3000 and interfaces with different medical monitoring module through serial ports. The network based on asymmetric digital subscriber line (ADSL) or local area network (LAN) is established and a client - server model, each embedded home medical monitor is client and the monitoring center is the server, is applied to the system design. The client is able to provide its information to the server when client's request of connection to the server is permitted. The monitoring center focuses on the management of the communications, the acquisition of medical data, and the visualization and analysis of the data, etc. Diagnosing model of sleep apnea syndrome is built basing on ECG, heart rate, respiration wave, blood pressure, oxygen saturation, air temperature of mouth cavity or nasal cavity, so sleep status can be analyzed by physiological data acquired as people in sleep. Remote medical monitoring network based on embedded micro Internetworking technology have advantages of lower price, convenience and feasibility, which have been tested by the prototype.

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System

PubMed Central

Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco

2017-01-01

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.

PubMed

Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco

2017-08-31

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.

Speckle-correlation monitoring of the internal micro-vascular flow

NASA Astrophysics Data System (ADS)

Zimnyakov, D. A.; Khmara, M. B.; Vilensky, M. A.; Kozlov, V. V.; Gorfinkel, I. V.; Zdrajevsky, R. A.

2009-10-01

The results of experimental study of possibility to monitor the micro-vascular blood flow in superficial tissues of various organs with the use of endoscope-based full-field speckle correlometer are presented. The blood microcirculation monitoring was carried out in the course of the laparotomy of abdominal cavity of laboratory animals (rats). Transfer of laser light to the area of interest and scattered radiation from the probed zone to the detector (CMOS camera) was carried out via fiber-optic bundles of endoscopic system. Microscopic hemodynamics was analyzed for small intestine, liver, spleen, kidney, and pancreas under different conditions (normal state, provocated peritonitis and ischemia, administration of vasodilative agents such as papaverine, lidocaine). The prospects and problems of internal monitoring of microvascular flow in laboratory and clinical conditions are discussed.

Multivariate EMD and full spectrum based condition monitoring for rotating machinery

NASA Astrophysics Data System (ADS)

Zhao, Xiaomin; Patel, Tejas H.; Zuo, Ming J.

2012-02-01

Early assessment of machinery health condition is of paramount importance today. A sensor network with sensors in multiple directions and locations is usually employed for monitoring the condition of rotating machinery. Extraction of health condition information from these sensors for effective fault detection and fault tracking is always challenging. Empirical mode decomposition (EMD) is an advanced signal processing technology that has been widely used for this purpose. Standard EMD has the limitation in that it works only for a single real-valued signal. When dealing with data from multiple sensors and multiple health conditions, standard EMD faces two problems. First, because of the local and self-adaptive nature of standard EMD, the decomposition of signals from different sources may not match in either number or frequency content. Second, it may not be possible to express the joint information between different sensors. The present study proposes a method of extracting fault information by employing multivariate EMD and full spectrum. Multivariate EMD can overcome the limitations of standard EMD when dealing with data from multiple sources. It is used to extract the intrinsic mode functions (IMFs) embedded in raw multivariate signals. A criterion based on mutual information is proposed for selecting a sensitive IMF. A full spectral feature is then extracted from the selected fault-sensitive IMF to capture the joint information between signals measured from two orthogonal directions. The proposed method is first explained using simple simulated data, and then is tested for the condition monitoring of rotating machinery applications. The effectiveness of the proposed method is demonstrated through monitoring damage on the vane trailing edge of an impeller and rotor-stator rub in an experimental rotor rig.

Observations of interference between portable particle counters and NOx monitors

NASA Astrophysics Data System (ADS)

Bereznicki, Sarah D.; Kamal, Ali

2013-08-01

Studies in environmental exposure science have developed a preference for smaller devices that can be easily co-located without need for gas standards, such as those instruments utilized in the Near-road Exposures and Effects from Urban Air Pollutants Study (NEXUS). One observation from NEXUS was the potential for instrument interference from alcohol-based particle counters on photometric-based nitrogen oxide (NOx) monitors. This article reports the findings from laboratory tests replicating enclosed-shelter monitoring configurations and operation cycles for a common photometric-based NOx monitor and a widely used alcohol-based particle counter. These tests monitored the NOx response while the particle counter sampling interval and ambient airflow rate were varied to (1) confirm that proximity between the instruments induced interferences, (2) identify any dependencies in NOx monitor recovery on ambient airflow, and (3) determine the time needed for the NOx monitor to recover to pre-interference levels under different atmospheric conditions. During particle counter operations, NOx concentrations responded instantaneously with a several-fold jump above the measurement baseline. When the particle counter was operated for more than 10 min, this interference period also showed a marked decline in the NOx baseline. The overall recovery time of the NOx monitor depended less on the time of particle counter operation, and more on the speed of ambient airflow. If photometric-based NOx monitors need to be operated alongside alcohol-based particle counters, mechanisms must be employed to exhaust alcohol-based vapors from enclosed monitoring environments. Given the strong evidence for interference, however, it is recommended these devices not be operated within close proximity to one another.

The Web Based Monitoring Project at the CMS Experiment

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

Lopez-Perez, Juan Antonio; Badgett, William; Behrens, Ulf

The Compact Muon Solenoid is a large a complex general purpose experiment at the CERN Large Hadron Collider (LHC), built and maintained by many collaborators from around the world. Efficient operation of the detector requires widespread and timely access to a broad range of monitoring and status information. To the end the Web Based Monitoring (WBM) system was developed to present data to users located anywhere from many underlying heterogeneous sources, from real time messaging systems to relational databases. This system provides the power to combine and correlate data in both graphical and tabular formats of interest to the experimenters,more » including data such as beam conditions, luminosity, trigger rates, detector conditions, and many others, allowing for flexibility on the user’s side. This paper describes the WBM system architecture and describes how the system has been used from the beginning of data taking until now (Run1 and Run 2).« less

The web based monitoring project at the CMS experiment

NASA Astrophysics Data System (ADS)

Lopez-Perez, Juan Antonio; Badgett, William; Behrens, Ulf; Chakaberia, Irakli; Jo, Youngkwon; Maeshima, Kaori; Maruyama, Sho; Patrick, James; Rapsevicius, Valdas; Soha, Aron; Stankevicius, Mantas; Sulmanas, Balys; Toda, Sachiko; Wan, Zongru

2017-10-01

The Compact Muon Solenoid is a large a complex general purpose experiment at the CERN Large Hadron Collider (LHC), built and maintained by many collaborators from around the world. Efficient operation of the detector requires widespread and timely access to a broad range of monitoring and status information. To that end the Web Based Monitoring (WBM) system was developed to present data to users located anywhere from many underlying heterogeneous sources, from real time messaging systems to relational databases. This system provides the power to combine and correlate data in both graphical and tabular formats of interest to the experimenters, including data such as beam conditions, luminosity, trigger rates, detector conditions, and many others, allowing for flexibility on the user’s side. This paper describes the WBM system architecture and describes how the system has been used from the beginning of data taking until now (Run1 and Run 2).

Web Based Monitoring in the CMS Experiment at CERN

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

Badgett, William; Borrello, Laura; Chakaberia, Irakli

2014-09-03

The Compact Muon Solenoid (CMS) is a large and complex general purpose experiment at the CERN Large Hadron Collider (LHC), built and maintained by many collaborators from around the world. Efficient operation of the detector requires widespread and timely access to a broad range of monitoring and status information. To this end the Web Based Monitoring (WBM) system was developed to present data to users located anywhere from many underlying heterogeneous sources, from real time messaging systems to relational databases. This system provides the power to combine and correlate data in both graphical and tabular formats of interest to themore » experimenters, including data such as beam conditions, luminosity, trigger rates, detector conditions, and many others, allowing for flexibility on the user side. This paper describes the WBM system architecture and describes how the system was used during the first major data taking run of the LHC.« less

Monitoring of the infrastructure and services used to handle and automatically produce Alignment and Calibration conditions at CMS

NASA Astrophysics Data System (ADS)

Sipos, Roland; Govi, Giacomo; Franzoni, Giovanni; Di Guida, Salvatore; Pfeiffer, Andreas

2017-10-01

The CMS experiment at CERN LHC has a dedicated infrastructure to handle the alignment and calibration data. This infrastructure is composed of several services, which take on various data management tasks required for the consumption of the non-event data (also called as condition data) in the experiment activities. The criticality of these tasks imposes tights requirements for the availability and the reliability of the services executing them. In this scope, a comprehensive monitoring and alarm generating system has been developed. The system has been implemented based on the Nagios open source industry standard for monitoring and alerting services, and monitors the database back-end, the hosting nodes and key heart-beat functionalities for all the services involved. This paper describes the design, implementation and operational experience with the monitoring system developed and deployed at CMS in 2016.

The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study.

PubMed

Ferguson, Ty; Rowlands, Alex V; Olds, Tim; Maher, Carol

2015-03-27

Technological advances have seen a burgeoning industry for accelerometer-based wearable activity monitors targeted at the consumer market. The purpose of this study was to determine the convergent validity of a selection of consumer-level accelerometer-based activity monitors. 21 healthy adults wore seven consumer-level activity monitors (Fitbit One, Fitbit Zip, Jawbone UP, Misfit Shine, Nike Fuelband, Striiv Smart Pedometer and Withings Pulse) and two research-grade accelerometers/multi-sensor devices (BodyMedia SenseWear, and ActiGraph GT3X+) for 48-hours. Participants went about their daily life in free-living conditions during data collection. The validity of the consumer-level activity monitors relative to the research devices for step count, moderate to vigorous physical activity (MVPA), sleep and total daily energy expenditure (TDEE) was quantified using Bland-Altman analysis, median absolute difference and Pearson's correlation. All consumer-level activity monitors correlated strongly (r > 0.8) with research-grade devices for step count and sleep time, but only moderately-to-strongly for TDEE (r = 0.74-0.81) and MVPA (r = 0.52-0.91). Median absolute differences were generally modest for sleep and steps (<10% of research device mean values for the majority of devices) moderate for TDEE (<30% of research device mean values), and large for MVPA (26-298%). Across the constructs examined, the Fitbit One, Fitbit Zip and Withings Pulse performed most strongly. In free-living conditions, the consumer-level activity monitors showed strong validity for the measurement of steps and sleep duration, and moderate valid for measurement of TDEE and MVPA. Validity for each construct ranged widely between devices, with the Fitbit One, Fitbit Zip and Withings Pulse being the strongest performers.

Knowledge-Acquisition Tool For Expert System

NASA Technical Reports Server (NTRS)

Disbrow, James D.; Duke, Eugene L.; Regenie, Victoria A.

1988-01-01

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

Geospace monitoring for space weather research and operation

NASA Astrophysics Data System (ADS)

Nagatsuma, Tsutomu

2017-10-01

Geospace, a space surrounding the Earth, is one of the key area for space weather. Because geospace environment dynamically varies depending on the solar wind conditions. Many kinds of space assets are operating in geospace for practical purposes. Anomalies of space assets are sometimes happened because of space weather disturbances in geospace. Therefore, monitoring and forecasting of geospace environment is very important tasks for NICT's space weather research and development. To monitor and to improve forecasting model, fluxgate magnetometers and HF radars are operated by our laboratory, and its data are used for our research work, too. We also operate real-time data acquisition system for satellite data, such as DSCOVR, STEREO, and routinely received high energy particle data from Himawari-8. Based on these data, we are monitoring current condition of geomagnetic disturbances, and that of radiation belt. Using these data, we have developed empirical models for relativistic electron flux at GEO and inner magnetosphere. To provide userfriendly information , we are trying to develop individual spacecraft anomaly risk estimation tool based on combining models of space weather and those of spacecraft charging, Current status of geospace monitoring, forecasting, and research activities are introduced.

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.

Integrating policy-based management and SLA performance monitoring

NASA Astrophysics Data System (ADS)

Liu, Tzong-Jye; Lin, Chin-Yi; Chang, Shu-Hsin; Yen, Meng-Tzu

2001-10-01

Policy-based management system provides the configuration capability for the system administrators to focus on the requirements of customers. The service level agreement performance monitoring mechanism helps system administrators to verify the correctness of policies. However, it is difficult for a device to process the policies directly because the policies are the management concept. This paper proposes a mechanism to decompose a policy into rules that can be efficiently processed by a device. Thus, the device may process the rule and collect the performance statistics information efficiently; and the policy-based management system may collect these performance statistics information and report the service-level agreement performance monitoring information to the system administrator. The proposed policy-based management system achieves both the policy configuration and service-level agreement performance monitoring requirements. A policy consists of a condition part and an action part. The condition part is a Boolean expression of a source host IP group, a destination host IP group, etc. The action part is the parameters of services. We say that an address group is compact if it only consists of a range of IP address that can be denoted by a pair of IP address and corresponding IP mask. If the condition part of a policy only consists of the compact address group, we say that the policy is a rule. Since a device can efficiently process a compact address and a system administrator prefers to define a range of IP address, the policy-based management system has to translate policy into rules and supplements the gaps between policy and rules. The proposed policy-based management system builds the relationships between VPN and policies, policy and rules. Since the system administrator wants to monitor the system performance information of VPNs and policies, the proposed policy-based management system downloads the relationships among VPNs, policies and rules to the SNMP agents. The SNMP agents build the management information base (MIB) of all VPNs, policies and rules according to the relationships obtained from the management server. Thus, the proposed policy-based management system may get all performance monitoring information of VPNs and policies from agents. The proposed policy-based manager achieves two goals: a) provide a management environment for the system administrator to configure their network only considering the policy requirement issues and b) let the device have only to process the packet and then collect the required performance information. These two things make the proposed management system satisfy both the user and device requirements.

Fiber-Optic Based Compact Gas Leak Detection System

NASA Technical Reports Server (NTRS)

deGroot, Wim A.

1995-01-01

A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

Non-invasive glucose monitoring in patients with diabetes: a novel system based on impedance spectroscopy.

PubMed

Caduff, A; Dewarrat, F; Talary, M; Stalder, G; Heinemann, L; Feldman, Yu

2006-12-15

The aim of this work was to evaluate the performance of a novel non-invasive continuous glucose-monitoring system based on impedance spectroscopy (IS) in patients with diabetes. Ten patients with type 1 diabetes (mean+/-S.D., age 28+/-8 years, BMI 24.2+/-3.2 kg/m(2) and HbA(1C) 7.3+/-1.6%) and five with type 2 diabetes (age 61+/-8 years, BMI 27.5+/-3.2 kg/m(2) and HbA(1C) 8.3+/-1.8%) took part in this study, which comprised a glucose clamp experiment followed by a 7-day outpatient evaluation. The measurements obtained by the NI-CGMD and the reference blood glucose-measuring techniques were evaluated using retrospective data evaluation procedures. Under less controlled outpatient conditions a correlation coefficient of r=0.640 and a standard error of prediction (SEP) of 45 mg dl(-1) with a total of 590 paired glucose measurements was found (versus r=0.926 and a SEP of 26 mg dl(-1) under controlled conditions). Clark error grid analyses (EGA) showed 56% of all values in zone A, 37% in B and 7% in C-E. In conclusion, these results indicate that IS in the used technical setting allows retrospective, continuous and truly non-invasive glucose monitoring under defined conditions for patients with diabetes. Technical advances and developments are needed to expand on this concept to bring the results from the outpatient study closer to those in the experimental section of the study. Further studies will not only help to evaluate the performance and limitations of using such a technique for non non-invasive glucose monitoring but also help to verify technical extensions towards a IS-based concept that offers improved performance under real life operating conditions.

Dynamic species classification of microorganisms across time, abiotic and biotic environments—A sliding window approach

PubMed Central

Griffiths, Jason I.; Fronhofer, Emanuel A.; Garnier, Aurélie; Seymour, Mathew; Altermatt, Florian; Petchey, Owen L.

2017-01-01

The development of video-based monitoring methods allows for rapid, dynamic and accurate monitoring of individuals or communities, compared to slower traditional methods, with far reaching ecological and evolutionary applications. Large amounts of data are generated using video-based methods, which can be effectively processed using machine learning (ML) algorithms into meaningful ecological information. ML uses user defined classes (e.g. species), derived from a subset (i.e. training data) of video-observed quantitative features (e.g. phenotypic variation), to infer classes in subsequent observations. However, phenotypic variation often changes due to environmental conditions, which may lead to poor classification, if environmentally induced variation in phenotypes is not accounted for. Here we describe a framework for classifying species under changing environmental conditions based on the random forest classification. A sliding window approach was developed that restricts temporal and environmentally conditions to improve the classification. We tested our approach by applying the classification framework to experimental data. The experiment used a set of six ciliate species to monitor changes in community structure and behavior over hundreds of generations, in dozens of species combinations and across a temperature gradient. Differences in biotic and abiotic conditions caused simplistic classification approaches to be unsuccessful. In contrast, the sliding window approach allowed classification to be highly successful, as phenotypic differences driven by environmental change, could be captured by the classifier. Importantly, classification using the random forest algorithm showed comparable success when validated against traditional, slower, manual identification. Our framework allows for reliable classification in dynamic environments, and may help to improve strategies for long-term monitoring of species in changing environments. Our classification pipeline can be applied in fields assessing species community dynamics, such as eco-toxicology, ecology and evolutionary ecology. PMID:28472193

Activity and heart rate-based measures for outpatient cardiac rehabilitation.

PubMed

Bidargaddi, N P; Sarela, A

2008-01-01

Derive activity and heart rate (HR) monitor-based clinically relevant measures for outpatient cardiac rehabilitation (CR). We are currently collecting activity/ECG data from patients undergoing cardiac rehabilitation over duration of six weeks. From these data sets, we a) derive various measures which can be used in assessing home-based CR patients remotely and b) investigate the usefulness of continuous ambulatory HR and heart rate variability (HRV) for various core components of CR. The information provided by these measures is interpreted according to the CR guidelines framework by American Association of Cardiovascular and Pulmonary Rehabilitation (AACVPR), thus showing how these tools can be used in assessing the progress of patients' condition. The usefulness and significance of these measures from a health care professional perspective is also presented by evaluating them against the existing hospital-based measures through examples. Hospital-based CR programs, despite their clinical benefits are severely under-utilized and resource-demanding. Ambulatory monitoring technologies, which provide a means for continuous physiological monitoring of patients at home compared to hospital-based tools, can enable home-based CR. The clinically relevant measures derived from these tools not only reflect patients' condition in a similar way as conventional tools but also show the continuous status of functional capacity (FC).

Atmospheric Visibility Monitoring for planetary optical communications

NASA Technical Reports Server (NTRS)

Cowles, Kelly

1991-01-01

The Atmospheric Visibility Monitoring project endeavors to improve current atmospheric models and generate visibility statistics relevant to prospective earth-satellite optical communications systems. Three autonomous observatories are being used to measure atmospheric conditions on the basis of observed starlight; these data will yield clear-sky and transmission statistics for three sites with high clear-sky probabilities. Ground-based data will be compared with satellite imagery to determine the correlation between satellite data and ground-based observations.

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China

PubMed Central

Chen, Kai; Ni, Minjie; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO4-P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas. PMID:27777951

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China.

PubMed

Chen, Kai; Ni, Minjie; Cai, Minggang; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO 4 -P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas.

The use of ambulatory blood pressure monitoring to confirm a diagnosis of high blood pressure by primary-care physicians in Oregon.

PubMed

Carter, Brittany U; Kaylor, Mary Beth

2016-04-01

Hypertension is the most commonly diagnosed medical condition in the USA. Unfortunately, patients are misdiagnosed in primary care because of inaccurate office-based blood pressure measurements. Several US healthcare organizations currently recommend confirming an office-based hypertension diagnosis with ambulatory blood pressure monitoring to avoid overtreatment; however, its use for the purpose of confirming an office-based hypertension diagnosis is relatively unknown. This descriptive study surveyed 143 primary-care physicians in Oregon with regard to their current use of ambulatory blood pressure monitoring. Nineteen percent of the physicians reported that they would use ambulatory blood pressure monitoring to confirm an office-based hypertension diagnosis, although over half had never ordered it. The most frequent indication for ordering ambulatory blood pressure monitoring was to investigate suspected white-coat hypertension (37.3%). In addition, many of the practices did not own an ambulatory blood pressure monitoring device (79.7%) and, therefore, had to refer patients to other clinics or departments for testing. Many primary-care physicians will need to change their current clinical practice to align with the shift toward a confirmation process for office-based hypertension diagnoses to improve population health.

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.

Condition Monitoring of Large-Scale Facilities

NASA Technical Reports Server (NTRS)

Hall, David L.

1999-01-01

This document provides a summary of the research conducted for the NASA Ames Research Center under grant NAG2-1182 (Condition-Based Monitoring of Large-Scale Facilities). The information includes copies of view graphs presented at NASA Ames in the final Workshop (held during December of 1998), as well as a copy of a technical report provided to the COTR (Dr. Anne Patterson-Hine) subsequent to the workshop. The material describes the experimental design, collection of data, and analysis results associated with monitoring the health of large-scale facilities. In addition to this material, a copy of the Pennsylvania State University Applied Research Laboratory data fusion visual programming tool kit was also provided to NASA Ames researchers.

Monitoring stress changes in a concrete bridge with coda wave interferometry.

PubMed

Stähler, Simon Christian; Sens-Schönfelder, Christoph; Niederleithinger, Ernst

2011-04-01

Coda wave interferometry is a recent analysis method now widely used in seismology. It uses the increased sensitivity of multiply scattered elastic waves with long travel-times for monitoring weak changes in a medium. While its application for structural monitoring has been shown to work under laboratory conditions, the usability on a real structure with known material changes had yet to be proven. This article presents experiments on a concrete bridge during construction. The results show that small velocity perturbations induced by a changing stress state in the structure can be determined even under adverse conditions. Theoretical estimations based on the stress calculations by the structural engineers are in good agreement with the measured velocity variations.

State-and-transition models for heterogeneous landscapes: A strategy for development and application

USDA-ARS?s Scientific Manuscript database

Interpretation of assessment and monitoring data requires information about reference conditions and ecological resilience. Reference conditions used as benchmarks can be specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially obser...

WATER QUALITY MONITORING FOR PUBLIC HEALTH AND ENVIRONMENTAL PROTECTION

EPA Science Inventory

The applicability of using microbial population measures as indicators of aquatic condition has a rich history based primarily to study factors that affect the sanitary and ecological condition of fresh water streams. These studies are generally conducted by collecting water site...

Method for assessing motor insulation on operating motors

DOEpatents

Kueck, John D.; Otaduy, Pedro J.

1997-01-01

A method for monitoring the condition of electrical-motor-driven devices. The method is achieved by monitoring electrical variables associated with the functioning of an operating motor, applying these electrical variables to a three phase equivalent circuit and determining non-symmetrical faults in the operating motor based upon symmetrical components analysis techniques.

Monitoring of diesel engine combustions based on the acoustic source characterisation of the exhaust system

NASA Astrophysics Data System (ADS)

Jiang, J.; Gu, F.; Gennish, R.; Moore, D. J.; Harris, G.; Ball, A. D.

2008-08-01

Acoustic methods are among the most useful techniques for monitoring the condition of machines. However, the influence of background noise is a major issue in implementing this method. This paper introduces an effective monitoring approach to diesel engine combustion based on acoustic one-port source theory and exhaust acoustic measurements. It has been found that the strength, in terms of pressure, of the engine acoustic source is able to provide a more accurate representation of the engine combustion because it is obtained by minimising the reflection effects in the exhaust system. A multi-load acoustic method was then developed to determine the pressure signal when a four-cylinder diesel engine was tested with faults in the fuel injector and exhaust valve. From the experimental results, it is shown that a two-load acoustic method is sufficient to permit the detection and diagnosis of abnormalities in the pressure signal, caused by the faults. This then provides a novel and yet reliable method to achieve condition monitoring of diesel engines even if they operate in high noise environments such as standby power stations and vessel chambers.

Padres Trabajando por la Paz: a randomized trial of a parent education intervention to prevent violence among middle school children.

PubMed

Murray, N G; Kelder, S H; Parcel, G S; Frankowski, R; Orpinas, P

1999-06-01

This paper reports the results of a randomized trial to test the effectiveness of a theoretically derived intervention designed to increase parental monitoring among Hispanic parents of middle school students. Role model story newsletters developed through the process of Intervention Mapping were mailed to half of a subsample of parents whose children participated in Students for Peace, a comprehensive violence prevention program. The results indicated that parents in the experimental condition (N = 38) who had lower social norms for monitoring at baseline reported higher norms after the intervention than the parents in the control condition (N = 39) (P = 0.009). Children of parents in the experimental group reported slightly higher levels of monitoring at follow-up across baseline values, whereas control children who reported moderate to high levels of monitoring at pre-test reported lower levels at follow-up (P = 0.04). These newsletters are a population-based strategy for intervention with parents that show some promise for comprehensive school-based interventions for youth.

A Delay Vector Variance based Marker for an Output-Only Assessment of Structural Changes in Tension Leg Platforms

NASA Astrophysics Data System (ADS)

Jaksic, V.; Wright, C.; Mandic, D. P.; Murphy, J.; Pakrashi, V.

2015-07-01

Although aspects of power generation of many offshore renewable devices are well understood, their dynamic responses under high wind and wave conditions are still to be investigated to a great detail. Output only statistical markers are important for these offshore devices, since access to the device is limited and information about the exposure conditions and the true behaviour of the devices are generally partial, limited, and vague or even absent. The markers can summarise and characterise the behaviour of these devices from their dynamic response available as time series data. The behaviour may be linear or nonlinear and consequently a marker that can track the changes in structural situations can be quite important. These markers can then be helpful in assessing the current condition of the structure and can indicate possible intervention, monitoring or assessment. This paper considers a Delay Vector Variance based marker for changes in a tension leg platform tested in an ocean wave basin for structural changes brought about by single column dampers. The approach is based on dynamic outputs of the device alone and is based on the estimation of the nonlinearity of the output signal. The advantages of the selected marker and its response with changing structural properties are discussed. The marker is observed to be important for monitoring the as- deployed structural condition and is sensitive to changes in such conditions. Influence of exposure conditions of wave loading is also discussed in this study based only on experimental data.

High-resolution near real-time drought monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat and cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature, which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05°. The bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub-basin levels.

Effects of Performance Versus Game-Based Mobile Applications on Response to Exercise.

PubMed

Gillman, Arielle S; Bryan, Angela D

2016-02-01

Given the popularity of mobile applications (apps) designed to increase exercise participation, it is important to understand their effects on psychological predictors of exercise behavior. This study tested a performance feedback-based app compared to a game-based app to examine their effects on aspects of immediate response to an exercise bout. Twenty-eight participants completed a 30-min treadmill run while using one of two randomly assigned mobile running apps: Nike + Running, a performance-monitoring app which theoretically induces an associative, goal-driven state, or Zombies Run!, an app which turns the experience of running into a virtual reality game, theoretically inducing dissociation from primary exercise goals. The two conditions did not differ on primary motivational state outcomes; however, participants reported more associative attentional focus in the performance-monitoring app condition compared to more dissociative focus in the game-based app condition. Game-based and performance-tracking running apps may not have differential effects on goal motivation during exercise. However, game-based apps may help recreational exercisers dissociate from exercise more readily. Increasing the enjoyment of an exercise bout through the development of new and innovative mobile technologies is an important avenue for future research.

The impact of evidence-based practice implementation and fidelity monitoring on staff turnover: evidence for a protective effect.

PubMed

Aarons, Gregory A; Sommerfeld, David H; Hecht, Debra B; Silovsky, Jane F; Chaffin, Mark J

2009-04-01

Staff retention is an ongoing challenge in mental health and community-based service organizations. Little is known about the impact of evidence-based practice implementation on the mental health and social service workforce. The present study examined the effect of evidence-based practice implementation and ongoing fidelity monitoring on staff retention in a children's services system. The study took place in the context of a statewide, regionally randomized effectiveness trial of an evidence-based intervention designed to reduce child neglect. In the study 21 teams consisting of 153 home-based service providers were followed over a 29-month period. Survival analyses revealed greater staff retention in the condition where the evidence-based practice was implemented along with ongoing fidelity monitoring presented to staff as supportive consultation. These results should help to allay concerns about staff retention when implementing evidence-based practices where there is good values-innovation fit and when fidelity monitoring is designed as an aid and support to service providers in providing a high standard of care for children and families.

The Impact of Evidence-Based Practice Implementation and Fidelity Monitoring on Staff Turnover: Evidence for a Protective Effect

PubMed Central

Aarons, Gregory A.; Sommerfeld, David H.; Hecht, Debra B.; Silovsky, Jane F.; Chaffin, Mark J.

2009-01-01

Staff retention is an ongoing challenge in mental health and community-based service organizations. Little is known about the impact of evidence-based practice implementation on the mental health and social service workforce. The present study examined the effect of evidence-based practice implementation and ongoing fidelity monitoring on staff retention in a children’s services system. The study took place in the context of a statewide regionally randomized effectiveness trial of an evidence-based intervention designed to reduce child neglect. Twenty-one teams consisting of 153 home-based service providers were followed over a 29 month period. Survival analyses revealed greater staff retention in the condition where the evidence-based practice was implemented along with ongoing fidelity monitoring presented to staff as supportive consultation. These results should help to allay concerns about staff retention when implementing evidence-based practices where there is good values-innovation fit and when fidelity monitoring is designed as an aid and support to service providers in providing a high standard of care for children and families. PMID:19309186

Characterizing meteorological and hydrologic conditions associated with shallow landslide initiation in the coastal bluffs of the Atlantic Highlands, New Jersey

USGS Publications Warehouse

Ashland, Francis; Fiore, Alex R.; Reilly, Pamela A.; De Graff, Jerome V.; Shakoor, Abdul

2017-01-01

Meteorological and hydrologic conditions associated with shallow landslide initiation in the coastal bluffs of the Atlantic Highlands, New Jersey remain undocumented despite a history of damaging slope movement extending back to at least 1903. This study applies an empirical approach to quantify the rainfall conditions leading to shallow landsliding based on analysis of overlapping historical precipitation data and records of landslide occurrence, and uses continuous monitoring to quantify antecedent soil moisture and hydrologic response to rainfall events at two failure-prone hillslopes. Analysis of historical rainfall data reveals that both extended duration and cumulative rainfall amounts are critical characteristics of many landslide-inducing storms, and is consistent with current monitoring results that show notable increases in shallow soil moisture and pore-water pressure in continuous rainfall periods. Monitoring results show that shallow groundwater levels and soil moisture increase from annual lows in late summer-early fall to annual highs in late winter-early spring, and historical data indicate that shallow landslides occur most commonly from tropical cyclones in late summer through fall and nor’easters in spring. Based on this seasonality, we derived two provisional rainfall thresholds using a limited dataset of documented landslides and rainfall conditions for each season and storm type. A lower threshold for landslide initiation in spring corresponds with high antecedent moisture conditions, and higher rainfall amounts are required to induce shallow landslides during the drier soil moisture conditions in late summer-early fall.

Challenges in sensor development for the electric utility industry

NASA Astrophysics Data System (ADS)

Ward, Barry H.

1999-01-01

The electric utility industry is reducing operating costs in order to prepare for deregulation. The reduction in operating cost has meant a reduction in manpower. The ability to utilize remaining maintenance staff more effectively and to stay competitive in a deregulated environment has therefore become critical. In recent years, the industry has moved away from routine or periodic maintenance to predictive or condition based maintenance. This requires the assessment of equipment condition by frequent testing and inspection; a requirement that is incompatible with cost reduction. To overcome this dilemma, industry trends are toward condition monitoring, whereby the health of apparatus is monitored continuously. This requires the installation of sensors hr transducers on power equipment and the data taken forwarded to an intelligent device for further processing. These devices then analyze the data and make evaluations based on parameter levels or trends, in an attempt to predict possible deterioration. This continuous monitoring allows the electric utility to schedule maintenance on an as needed basis. The industry has been faced with many challenges in sensor design. The measurement of physical, chemical and electrical parameters under extreme conditions of electric fields, magnetic fields, temperature, corrosion, etc. is extensive. This paper will give an overview of these challenges and the solutions adopted for apparatus such as power transformers, circuit breakers, boilers, cables, batteries, and rotating machinery.

A monitoring system for vegetable greenhouses based on a wireless sensor network.

PubMed

Li, Xiu-hong; Cheng, Xiao; Yan, Ke; Gong, Peng

2010-01-01

A wireless sensor network-based automatic monitoring system is designed for monitoring the life conditions of greenhouse vegetables. The complete system architecture includes a group of sensor nodes, a base station, and an internet data center. For the design of wireless sensor node, the JN5139 micro-processor is adopted as the core component and the Zigbee protocol is used for wireless communication between nodes. With an ARM7 microprocessor and embedded ZKOS operating system, a proprietary gateway node is developed to achieve data influx, screen display, system configuration and GPRS based remote data forwarding. Through a Client/Server mode the management software for remote data center achieves real-time data distribution and time-series analysis. Besides, a GSM-short-message-based interface is developed for sending real-time environmental measurements, and for alarming when a measurement is beyond some pre-defined threshold. The whole system has been tested for over one year and satisfactory results have been observed, which indicate that this system is very useful for greenhouse environment monitoring.

NATIONAL COASTAL ASSESSMENT: MONITORING AND MODELING IN SUPPORT OF TMDL CALCULATIONS

EPA Science Inventory

The National Coastal Assessment (NCA) has three major goals: 1) assess ecological condition of the nation's estuarine resources based on comparable data of know quality; 2) determine reference conditions, 3) help build infrastructure in states and EPA Regions. Much of the init...

[Demonstrating that monitoring and punishing increase non-cooperative behavior in a social dilemma game].

PubMed

Kitakaji, Yoko; Ohnuma, Susumu

2014-04-01

This research demonstrated the negative influence of monitoring and punishing during a social dilemma game, taking the illegal dumping of industrial waste as an example. The first study manipulated three conditions: a producing-industries monitoring condition (PIM), an administrative monitoring condition (ADM), and a control condition (no monitoring). The results showed that non-cooperative behavior was more frequent in the PIM condition than in the control condition. The second study had three conditions: a punishing condition (PC), a monitoring condition (MC), and a control condition (no monitoring, no punishing). The results indicated that non-cooperative behavior was observed the most in the PC, and the least in the control condition. Furthermore, information regarding other players' costs and benefits was shared the most in the control conditions in both studies. The results suggest that sanctions prevent people from sharing information, which decreases expectations of mutual cooperation.

Web-based monitoring tools for Resistive Plate Chambers in the CMS experiment at CERN

NASA Astrophysics Data System (ADS)

Kim, M. S.; Ban, Y.; Cai, J.; Li, Q.; Liu, S.; Qian, S.; Wang, D.; Xu, Z.; Zhang, F.; Choi, Y.; Kim, D.; Goh, J.; Choi, S.; Hong, B.; Kang, J. W.; Kang, M.; Kwon, J. H.; Lee, K. S.; Lee, S. K.; Park, S. K.; Pant, L. M.; Mohanty, A. K.; Chudasama, R.; Singh, J. B.; Bhatnagar, V.; Mehta, A.; Kumar, R.; Cauwenbergh, S.; Costantini, S.; Cimmino, A.; Crucy, S.; Fagot, A.; Garcia, G.; Ocampo, A.; Poyraz, D.; Salva, S.; Thyssen, F.; Tytgat, M.; Zaganidis, N.; Doninck, W. V.; Cabrera, A.; Chaparro, L.; Gomez, J. P.; Gomez, B.; Sanabria, J. C.; Avila, C.; Ahmad, A.; Muhammad, S.; Shoaib, M.; Hoorani, H.; Awan, I.; Ali, I.; Ahmed, W.; Asghar, M. I.; Shahzad, H.; Sayed, A.; Ibrahim, A.; Aly, S.; Assran, Y.; Radi, A.; Elkafrawy, T.; Sharma, A.; Colafranceschi, S.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Iaselli, G.; Loddo, F.; Maggi, M.; Nuzzo, S.; Pugliese, G.; Radogna, R.; Venditti, R.; Verwilligen, P.; Benussi, L.; Bianco, S.; Piccolo, D.; Paolucci, P.; Buontempo, S.; Cavallo, N.; Merola, M.; Fabozzi, F.; Iorio, O. M.; Braghieri, A.; Montagna, P.; Riccardi, C.; Salvini, P.; Vitulo, P.; Vai, I.; Magnani, A.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Aleksandrov, A.; Genchev, V.; Iaydjiev, P.; Rodozov, M.; Sultanov, G.; Vutova, M.; Stoykova, S.; Hadjiiska, R.; Ibargüen, H. S.; Morales, M. I. P.; Bernardino, S. C.; Bagaturia, I.; Tsamalaidze, Z.; Crotty, I.

2014-10-01

The Resistive Plate Chambers (RPC) are used in the CMS experiment at the trigger level and also in the standard offline muon reconstruction. In order to guarantee the quality of the data collected and to monitor online the detector performance, a set of tools has been developed in CMS which is heavily used in the RPC system. The Web-based monitoring (WBM) is a set of java servlets that allows users to check the performance of the hardware during data taking, providing distributions and history plots of all the parameters. The functionalities of the RPC WBM monitoring tools are presented along with studies of the detector performance as a function of growing luminosity and environmental conditions that are tracked over time.

Monitoring and seasonal forecasting of meteorological droughts

NASA Astrophysics Data System (ADS)

Dutra, Emanuel; Pozzi, Will; Wetterhall, Fredrik; Di Giuseppe, Francesca; Magnusson, Linus; Naumann, Gustavo; Barbosa, Paulo; Vogt, Jurgen; Pappenberger, Florian

2015-04-01

Near-real time drought monitoring can provide decision makers valuable information for use in several areas, such as water resources management, or international aid. Unfortunately, a major constraint in current drought outlooks is the lack of reliable monitoring capability for observed precipitation globally in near-real time. Furthermore, drought monitoring systems requires a long record of past observations to provide mean climatological conditions. We address these constraints by developing a novel drought monitoring approach in which monthly mean precipitation is derived from short-range using ECMWF probabilistic forecasts and then merged with the long term precipitation climatology of the Global Precipitation Climatology Centre (GPCC) dataset. Merging the two makes available a real-time global precipitation product out of which the Standardized Precipitation Index (SPI) can be estimated and used for global or regional drought monitoring work. This approach provides stability in that by-passes problems of latency (lags) in having local rain-gauge measurements available in real time or lags in satellite precipitation products. Seasonal drought forecasts can also be prepared using the common methodology and based upon two data sources used to provide initial conditions (GPCC and the ECMWF ERA-Interim reanalysis (ERAI) combined with either the current ECMWF seasonal forecast or a climatology based upon ensemble forecasts. Verification of the forecasts as a function of lead time revealed a reduced impact on skill for: (i) long lead times using different initial conditions, and (ii) short lead times using different precipitation forecasts. The memory effect of initial conditions was found to be 1 month lead time for the SPI-3, 3 to 4 months for the SPI-6 and 5 months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value, a skill similar to or better than climatological forecasts. In some cases, particularly for long SPI time scales, it is very difficult to improve on the use of climatological forecasts. However, results presented regionally and globally pinpoint several regions in the world where drought onset forecasting is feasible and skilful.

Process Evaluation of the Project SHINE Intervention for African American Families: An Integrated Positive Parenting and Peer Monitoring Approach to Health Promotion.

PubMed

St George, Sara M; Wilson, Dawn K; McDaniel, Tyler; Alia, Kassandra A

2016-07-01

This study describes the process evaluation of Project SHINE, a randomized family-based health promotion intervention that integrated parenting and peer monitoring for improving sedentary behavior, physical activity, and diet in African American families. Adolescent-parent dyads (n = 89) were randomized to a 6-week behavioral, positive parenting, and peer monitoring skills intervention or a general health education comparison condition. Process evaluation included observational ratings of fidelity, attendance records, psychosocial measures, and qualitative interviews. Results indicated that the intervention was delivered with high fidelity based on facilitator adherence (>98% of content delivered) and competent use of theoretically based behavior change and positive parenting skills (100% of ratings >3 on a 1-4 scale). Although only 43% of peers attended the "bring a friend" session, overall attendance was high (4.39 ± 1.51 sessions) as was the retention rate (88%). Parents in the intervention condition reported significant improvements in communication related to adolescents' engagement in health behaviors both on their own and with peers. These findings were supported by qualitative themes related to improvements in family communication and connectedness. This study provides an innovative example of how future family-based health promotion trials can expand their process evaluation approaches by assessing theoretically relevant positive parenting variables as part of ongoing monitoring. © 2016 Society for Public Health Education.

The impact of attentional and emotional demands on memory performance in obsessive-compulsive disorder.

PubMed

Fink, Jakob; Hendrikx, Friederike; Stierle, Christian; Stengler, Katarina; Jahn, Ina; Exner, Cornelia

2017-08-01

Lower performance on memory tests in obsessive-compulsive disorder (OCD) has been repeatedly observed. However, the origins of these performance deficits are not sufficiently explained. In this study we tested if OCD-related extensive focus of attention on thoughts (heightened self-consciousness) could be an explanatory mechanism for lower memory performance. Heightened situational self-consciousness was manipulated by instructing participants to either monitor neutral thoughts or to monitor OCD-related thoughts. We included a Behavioral Avoidance Task based on individual obsessions and compulsions to induce OCD-related thoughts. Participants were asked to perform these monitoring tasks in parallel to a taxing verbal memory task, resulting in learning under divided attention. The two conditions of learning under divided attention were compared to a single-task condition. Twenty-four participants with OCD and 24 healthy controls took part in these three learning conditions. The results indicate that in both groups memory performance deteriorated in the two conditions with divided attention compared to the single task condition. In the OCD-related thought monitoring condition (OTM) self-consciousness and Behavioral Avoidance Task-induced stress and fear were particularly increased and memory performance further deteriorated in the OCD group. This finding highlights an important and underestimated mechanism (personal involvement) which might serve to better understand lower memory performance in OCD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fault detection and diagnosis for gas turbines based on a kernelized information entropy model.

PubMed

Wang, Weiying; Xu, Zhiqiang; Tang, Rui; Li, Shuying; Wu, Wei

2014-01-01

Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.

Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model

PubMed Central

Wang, Weiying; Xu, Zhiqiang; Tang, Rui; Li, Shuying; Wu, Wei

2014-01-01

Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms. PMID:25258726

Methodology for Automated Detection of Degradation and Faults in Packaged Air Conditioners and Heat Pumps Using Only Two Sensors

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

2016-02-10

The software was created in the process of developing a system known as the Smart Monitoring and Diagnostic System (SMDS) for packaged air conditioners and heat pumps used on commercial buildings (known as RTUs). The SMDS provides automated remote monitoring and detection of performance degradation and faults in these RTUs and could increase the awareness by building owners and maintenance providers of the condition of the equipment, the cost of operating it in degraded condition, and the quality of maintenance and repair service when it is performed. The SMDS provides these capabilities and would enable conditioned-based maintenance rather than themore » reactive and schedule-based preventive maintenance commonly used today, when maintenance of RTUs is done at all. Improved maintenance would help ensure persistent peak operating efficiencies, reducing energy consumption by an estimated 10% to 30%.« less

Data Fusion Tool for Spiral Bevel Gear Condition Indicator Data

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Antolick, Lance J.; Branning, Jeremy S.; Thomas, Josiah

2014-01-01

Tests were performed on two spiral bevel gear sets in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig to simulate the fielded failures of spiral bevel gears installed in a helicopter. Gear sets were tested until damage initiated and progressed on two or more gear or pinion teeth. During testing, gear health monitoring data was collected with two different health monitoring systems. Operational parameters were measured with a third data acquisition system. Tooth damage progression was documented with photographs taken at inspection intervals throughout the test. A software tool was developed for fusing the operational data and the vibration based gear condition indicator (CI) data collected from the two health monitoring systems. Results of this study illustrate the benefits of combining the data from all three systems to indicate progression of damage for spiral bevel gears. The tool also enabled evaluation of the effectiveness of each CI with respect to operational conditions and fault mode.

Monitoring psychosocial stress at work: development of the Psychosocial Working Conditions Questionnaire.

PubMed

Widerszal-Bazyl, M; Cieślak, R

2000-01-01

Many studies on the impact of psychosocial working conditions on health prove that psychosocial stress at work is an important risk factor endangering workers' health. Thus it should be constantly monitored like other work hazards. The paper presents a newly developed instrument for stress monitoring called the Psychosocial Working Conditions Questionnaire (PWC). Its structure is based on Robert Karasek's model of job stress (Karasek, 1979; Karasek & Theorell, 1990). It consists of 3 main scales Job Demands, Job Control, Social Support and 2 additional scales adapted from the Occupational Stress Questionnaire (Elo, Leppanen, Lindstrom, & Ropponen, 1992), Well-Being and Desired Changes. The study of 8 occupational groups (bank and insurance specialists, middle medical personnel, construction workers, shop assistants, government and self-government administration officers, computer scientists, public transport drivers, teachers, N = 3,669) indicates that PWC has satisfactory psychometrics parameters. Norms for the 8 groups were developed.

Application for temperature and humidity monitoring of data center environment

NASA Astrophysics Data System (ADS)

Albert, Ş.; Truşcǎ, M. R. C.; Soran, M. L.

2015-12-01

The technology and computer science registered a large development in the last years. Most systems that use high technologies require special working conditions. The monitoring and the controlling are very important. The temperature and the humidity are important parameters in the operation of computer systems, industrial and research, maintaining it between certain values to ensure their proper functioning being important. Usually, the temperature is maintained in the established range using an air conditioning system, but the humidity is affected. In the present work we developed an application based on a board with own firmware called "AVR_NET_IO" using a microcontroller ATmega32 type for temperature and humidity monitoring in Data Center of INCDTIM. On this board, temperature sensors were connected to measure the temperature in different points of the Data Center and outside of this. Humidity monitoring is performed using data from integrated sensors of the air conditioning system, thus achieving a correlation between humidity and temperature variation. It was developed a software application (CM-1) together with the hardware, which allows temperature monitoring and register inside Data Center and trigger an alarm when variations are greater with 3°C than established limits of the temperature.

WATERSHED BASED SURVEY DESIGNS

EPA Science Inventory

The development of watershed-based design and assessment tools will help to serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional condition to meet Section 305(b), identification of impaired water bodies or wate...

WATERSHED-BASED SURVEY DESIGNS

EPA Science Inventory

Water-based sampling design and assessment tools help serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional conditions to meet Section 305(b), identification if impaired water bodies or watersheds to meet Sectio...

Construction safety monitoring based on the project's characteristic with fuzzy logic approach

NASA Astrophysics Data System (ADS)

Winanda, Lila Ayu Ratna; Adi, Trijoko Wahyu; Anwar, Nadjadji; Wahyuni, Febriana Santi

2017-11-01

Construction workers accident is the highest number compared with other industries and falls are the main cause of fatal and serious injuries in high rise projects. Generally, construction workers accidents are caused by unsafe act and unsafe condition that can occur separately or together, thus a safety monitoring system based on influencing factors is needed to achieve zero accident in construction industry. The dynamic characteristic in construction causes high mobility for workers while doing the task, so it requires a continuously monitoring system to detect unsafe condition and to protect workers from potential hazards. In accordance with the unique nature of project, fuzzy logic approach is one of the appropriate methods for workers safety monitoring on site. In this study, the focus of discussion is based on the characteristic of construction projects in analyzing "potential hazard" and the "protection planning" to be used in accident prevention. The data have been collected from literature review, expert opinion and institution of safety and health. This data used to determine hazard identification. Then, an application model is created using Delphi programming. The process in fuzzy is divided into fuzzification, inference and defuzzification, according to the data collection. Then, the input and final output data are given back to the expert for assessment as a validation of application model. The result of the study showed that the potential hazard of construction workers accident could be analysed based on characteristic of project and protection system on site and fuzzy logic approach can be used for construction workers accident analysis. Based on case study and the feedback assessment from expert, it showed that the application model can be used as one of the safety monitoring tools.

Selected algorithms for measurement data processing in impulse-radar-based system for monitoring of human movements

NASA Astrophysics Data System (ADS)

Miękina, Andrzej; Wagner, Jakub; Mazurek, Paweł; Morawski, Roman Z.

2016-11-01

The importance of research on new technologies that could be employed in care services for elderly and disabled persons is highlighted. Advantages of impulse-radar sensors, when applied for non-intrusive monitoring of such persons in their home environment, are indicated. Selected algorithms for the measurement data preprocessing - viz. the algorithms for clutter suppression and echo parameter estimation, as well as for estimation of the twodimensional position of a monitored person - are proposed. The capability of an impulse-radar- based system to provide some application-specific parameters, viz. the parameters characterising the patient's health condition, is also demonstrated.

The Department of Defense Critical Technologies Plan for the Committees on Armed Services United States Congress

DTIC Science & Technology

1991-05-01

health monitoring , and detection avoidance. Similar to the im!proved ca abi!ities of electr,-.ics with the introduction of the integrated circuit...Sensors not needing to emit signals to detect targets, monitor the environment, or determine 1he status or condition of equipment. 9 Signal & Image... monitoring , and detection avoidance. Photonics R &D will significantly affect the high-speed computing defense iadustrial base through the development of

ECOLOGICAL CONDITION OF THE U.S. MID-ATLANTIC ESTUARIES: THE MID-ATLANTIC INTEGRATED ASSESSMENT (MAIA)

EPA Science Inventory

The Mid-Atlantic Integrated Assessment (MAIA-Estuaries) evaluated ecological conditions in US Mid-Atlantic estuaries during the summers of 1997 and 1998. Over 800 probability-based stations were monitored in four main estuarine systems?Chesapeake Bay, the Delaware Estuary, Maryla...

Method for assessing motor insulation on operating motors

DOEpatents

Kueck, J.D.; Otaduy, P.J.

1997-03-18

A method for monitoring the condition of electrical-motor-driven devices is disclosed. The method is achieved by monitoring electrical variables associated with the functioning of an operating motor, applying these electrical variables to a three phase equivalent circuit and determining non-symmetrical faults in the operating motor based upon symmetrical components analysis techniques. 15 figs.

Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

NASA Astrophysics Data System (ADS)

Aghakouchak, Amir; Tourian, Mohammad J.

2015-04-01

Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014 California Drought will be presented. Further Reading: Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1.

Lateralization of spatial information processing in response monitoring

PubMed Central

Stock, Ann-Kathrin; Beste, Christian

2014-01-01

The current study aims at identifying how lateralized multisensory spatial information processing affects response monitoring and action control. In a previous study, we investigated multimodal sensory integration in response monitoring processes using a Simon task. Behavioral and neurophysiologic results suggested that different aspects of response monitoring are asymmetrically and independently allocated to the hemispheres: while efference-copy-based information on the motor execution of the task is further processed in the hemisphere that originally generated the motor command, proprioception-based spatial information is processed in the hemisphere contralateral to the effector. Hence, crossing hands (entering a “foreign” spatial hemifield) yielded an augmented bilateral activation during response monitoring since these two kinds of information were processed in opposing hemispheres. Because the traditional Simon task does not provide the possibility to investigate which aspect of the spatial configuration leads to the observed hemispheric allocation, we introduced a new “double crossed” condition that allows for the dissociation of internal/physiological and external/physical influences on response monitoring processes. Comparing behavioral and neurophysiologic measures of this new condition to those of the traditional Simon task setup, we could demonstrate that the egocentric representation of the physiological effector's spatial location accounts for the observed lateralization of spatial information in action control. The finding that the location of the physical effector had a very small influence on response monitoring measures suggests that this aspect is either less important and/or processed in different brain areas than egocentric physiological information. PMID:24550855

Mobile Phone-Based Field Monitoring for Satsuma Mandarin and Its Application to Watering Advice System

NASA Astrophysics Data System (ADS)

Kamiya, Toshiyuki; Numano, Nagisa; Yagyu, Hiroyuki; Shimazu, Hideo

This paper describes a mobile phone-based data logging system for monitoring the growing status of Satsuma mandarin, a type of citrus fruit, in the field. The system can provide various feedback to the farm producers with collected data, such as visualization of related data as a timeline chart or advice on the necessity of watering crops. It is important to collect information on environment conditions, plant status and product quality, to analyze it and to provide it as feedback to the farm producers to aid their operations. This paper proposes a novel framework of field monitoring and feedback for open-field farming. For field monitoring, it combines a low-cost plant status monitoring method using a simple apparatus and a Field Server for environment condition monitoring. Each field worker has a simple apparatus to measure fruit firmness and records data with a mobile phone. The logged data are stored in the database of the system on the server. The system analyzes stored data for each field and is able to show the necessity of watering to the user in five levels. The system is also able to show various stored data in timeline chart form. The user and coach can compare or analyze these data via a web interface. A test site was built at a Satsuma mandarin field at Kumano in Mie Prefecture, Japan using the framework, and farm workers monitor in the area used and evaluated the system.

More than just consumers: Integrating local observations into drought monitoring to better support decision making

NASA Astrophysics Data System (ADS)

Ferguson, D. B.; Masayesva, A.; Meadow, A. M.; Crimmins, M.

2016-12-01

Drought monitoring and drought planning are complex endeavors. Measures of precipitation or streamflow provide little context for understanding how social and environmental systems impacted by drought are responding. In arid and semi-arid regions of the world, this challenge is particularly acute since social-ecological systems are already well-adapted to dry conditions. Understanding what drought means in these regions is an important first step in developing a decision-relevant monitoring system. Traditional drought indices may be of some use, but local observations may ultimately be more relevant for informing difficult decisions in response to unusually dry conditions. This presentation will focus on insights gained from a collaborative project between the University of Arizona and the Hopi Tribe-a Native American community in the U.S. Southwest-to develop a drought information system that is responsive to local needs. The primary goal of the project was to develop a system that: is based on how drought is experienced by Hopi citizens and resource managers, can incorporate local observations of drought impacts as well as conventional indicators, and brings together local expertise with conventional science-based observations. This kind of drought monitoring system can harnesses as much available information as possible to inform resource managers, political leaders, and citizens about drought conditions, but such a system can also engage these local drought stakeholders in observing, thinking about, and helping guide planning for drought.

The investigation of using 5G millimeter-wave communications links for environmental monitoring

NASA Astrophysics Data System (ADS)

Han, Congzheng

2017-04-01

There has been significantly increasing recognition that millimeter waves from 30 GHz to 300 GHz as carriers for future 5G cellular networks. This is good for high speed, line-of-sight communication, potentially using very densely deployed infrastructure involving many small cells. High resolution, continuous and accurate monitoring of environmental conditions, such as rainfall and water vapor are of great important to meteorology, hydrology (e.g. flood warning), agriculture, environmental policy (e.g. pollution regulation) and weather forecasting. We have built a 28GHz measurement link at our research institute in central Beijing, China. This work will study the potential of using millimeter wave based wireless links to monitor environmental conditions including rainfall and water vapor.

Evaluation of Forest Health Conditions using Unmanned Aircraft Systems (UAS)

NASA Astrophysics Data System (ADS)

Hatfield, M. C.; Heutte, T. M.

2016-12-01

US Forest Service Alaska Region Forest Health Protection (FHP) and University of Alaska Fairbanks, Alaska Center for Unmanned Aircraft Systems Integration (ACUASI) are evaluating capability of Unmanned Aerial Systems (UAS) to monitor forest health conditions in Alaska's Interior Region. In July 2016, the team deployed UAS at locations in the Tanana Valley near Fairbanks in order to familiarize FHP staff with capabilities of UAS for evaluating insect and disease damage. While many potential uses of UAS to evaluate and monitor forest health can be envisioned, this project focused on use of a small UAS for rapid assessment of insect and disease damage. Traditional ground-based methods are limited by distance from ground to canopy and inaccessibility of forest stands due to terrain conditions. Observation from fixed-wing aircraft provide a broad overview of conditions but are limited by minimum safe flying altitude (500' AGL) and aircraft speed ( 100 mph). UAS may provide a crucial bridge to fill in gaps between ground and airborne methods, and offer significant cost savings and greater flexibility over helicopter-based observations. Previous uses of UAS for forest health monitoring are limited - this project focuses on optimizing choice of vehicle, sensors, resolution and area scanned from different altitudes, and use of visual spectrum vs NIR image collection. The vehicle selected was the ACUASI Ptarmigan, a small hexacopter (based on DJI S800 airframe and 3DR autopilot) capable of carrying a 1.5 kg payload for 15 min for close-range environmental monitoring missions. Sites were chosen for conditions favorable to UAS operation and presence of forest insect and disease agents including spruce broom rust, aspen leaf miner, birch leaf roller, and willow leafblotch miner. A total of 29 flights were conducted with 9000+ images collected. Mission variables included camera height, UAS speed, and medium- (Sony NEX-7) vs low-resolution (GoPro Hero) cameras. Invaluable knowledge was gained as to limitations and opportunities for field deployment of UAS relative to local conditions of terrain and forest type. Analysis will include image suitability for orthocorrection and production of stand level image mosaic, with further optimization of image collection parameters to detect known insect- and disease-caused disturbance.

Monitoring with Data Automata

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.

The Wireless Sensor Network (WSN) Based Coal Ash Impoundments Safety Monitoring System

NASA Astrophysics Data System (ADS)

Sun, E. J.; Nieto, A.; Zhang, X. K.

2017-01-01

Coal ash impoundments are inevitable production of the coal-fired power plants. All coal ash impoundments in North Carolina USA that tested for groundwater contamination are leaking toxic heavy metals and other pollutants. Coal ash impoundments are toxic sources of dangerous pollutants that pose a danger to human and environmental health if the toxins spread to adjacent surface waters and drinking water wells. Coal ash impoundments failures accidents resulted in serious water contamination along with toxic heavy metals. To improve the design and stability of coal ash impoundments, the Development of a Coal Ash Impoundment Safety Monitoring System (CAISM) was proposed based on the implementation of a wireless sensor network (WSN) with the ability to monitor the stability of coal ash impoundments, water level, and saturation levels on-demand and remotely. The monitoring system based on a robust Ad-hoc network could be adapted to different safety conditions.

Supporting metacognitive monitoring in mathematics learning for young people with autism spectrum disorder: A classroom-based study.

PubMed

Maras, Katie; Gamble, Tim; Brosnan, Mark

2017-10-01

Previous research suggests impaired metacognitive monitoring and mathematics under-achievement in autism spectrum disorder. Within educational settings, metacognitive monitoring is supported through the provision of feedback (e.g. with goal reminders and by explicitly correcting errors). Given the strength of the relationship between metacognition, learning and educational attainment, this research tested new computer-based metacognitive support (the 'Maths Challenge') for mathematics learners with autism spectrum disorder within the context of their classroom. The Maths Challenge required learners to engage in metacognitive monitoring before and after answering each question (e.g. intentions and judgements of accuracy) and negotiate with the system the level of difficulty. Forty secondary school children with autism spectrum disorder and 95 typically developing learners completed the Maths Challenge in either a Feedback condition, with metacognitive monitoring support regarding the accuracy of their answers, goal reminders and strategy support, or with No Feedback. Contrary to previous findings, learners with autism showed an undiminished ability to detect errors. They did, however, demonstrate reduced cohesion between their pre- and post-test intentions. Crucially, support from the Feedback condition significantly improved task performance for both groups. Findings highlight important implications for educational interventions regarding the provision of metacognitive support for learners with autism to ameliorate under-performance in mathematics within the classroom.

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Phantom-derived estimation of effective dose equivalent from X rays with and without a lead apron.

PubMed

Mateya, C F; Claycamp, H G

1997-06-01

Organ dose equivalents were measured in a humanoid phantom in order to estimate effective dose equivalent (H(E)) and effective dose (E) from low-energy x rays and in the presence or absence of a protective lead apron. Plane-parallel irradiation conditions were approximated using direct x-ray beams of 76 and 104 kVp and resulting dosimetry data was adjusted to model exposures conditions in fluoroscopy settings. Values of H(E) and E estimated under-shielded conditions were compared to the results of several recent studies that used combinations of measured and calculated dosimetry to model exposures to radiologists. While the estimates of H(E) and E without the lead apron were within 0.2 to 20% of expected values, estimates based on personal monitors worn at the (phantom) waist (underneath the apron) underestimated either H(E) or E while monitors placed at the neck (above the apron) significantly overestimated both quantities. Also, the experimentally determined H(E) and E were 1.4 to 3.3 times greater than might be estimated using recently reported "two-monitor" algorithms for the estimation of effective dose quantities. The results suggest that accurate estimation of either H(E) or E from personal monitors under conditions of partial body exposures remains problematic and is likely to require the use of multiple monitors.

In situ monitoring of the integrity of bonded repair patches on aircraft and civil infrastructures

NASA Astrophysics Data System (ADS)

Kumar, Amrita; Roach, Dennis; Beard, Shawn; Qing, Xinlin; Hannum, Robert

2006-03-01

Monitoring the continued health of aircraft subsystems and identifying problems before they affect airworthiness has been a long-term goal of the aviation industry. Because in-service conditions and failure modes experienced by structures are generally complex and unknown, conservative calendar-based or usage-based scheduled maintenance practices are overly time-consuming, labor-intensive and expensive. Metal structures such as helicopters and other transportation systems are likely to develop fatigue cracks under cyclic loads and corrosive service environments. Early detection of cracks is a key element to prevent catastrophic failure and prolong structural life. Furthermore, as structures age, maintenance service frequency and costs increase while performance and availability decrease. Current non-destructive inspection (NDI) techniques that can potentially be used for this purpose typically involve complex, time-intensive procedures, which are labor-intensive and expensive. Most techniques require access to the damaged area on at least one side, and sometimes on both sides. This can be very difficult for monitoring of certain inaccessible regions. In those cases, inspection may require removal of access panels or even structural disassembly. Once access has been obtained, automated inspection techniques likely will not be practical due to the bulk of the required equipment. Results obtained from these techniques may also be sensitive to the sweep speed, tool orientation, and downward pressure. This can be especially problematic for hand-held inspection tools where none of these parameters is mechanically controlled. As a result, data can vary drastically from one inspection to the next, from one technician to the next, and even from one sweep to the next. Structural health monitoring (SHM) offers the promise of a paradigm shift from schedule-driven maintenance to condition-based maintenance (CBM) of assets. Sensors embedded permanently in aircraft safety critical structures that can monitor damage can provide for improved reliability and streamlining of aircraft maintenance. Early detection of damage such as fatigue crack initiation can improve personnel safety and prolong service life. This paper presents the testing of an acousto-ultrasonic piezoelectric sensor based structural health monitoring system for real-time monitoring of fatigue cracks and disbonds in bonded repairs. The system utilizes a network of distributed miniature piezoelectric sensors/actuators embedded on a thin dielectric carrier film, to query, monitor and evaluate the condition of a structure. The sensor layers are extremely flexible and can be integrated with any type of metal or composite structure. Diagnostic signals obtained from a structure during structural monitoring are processed by a portable diagnostic unit. With appropriate diagnostic software, the signals can be analyzed to ascertain the integrity of the structure being monitored. Details on the system, its integration and examples of detection of fatigue crack and disbond growth and quantification for bonded repairs will be presented here.

Study and Test of a New Bundle-Structure Riser Stress Monitoring Sensor Based on FBG.

PubMed

Xu, Jian; Yang, Dexing; Qin, Chuan; Jiang, Yajun; Sheng, Leixiang; Jia, Xiangyun; Bai, Yang; Shen, Xiaohong; Wang, Haiyan; Deng, Xin; Xu, Liangbin; Jiang, Shiquan

2015-11-24

To meet the requirements of riser safety monitoring in offshore oil fields, a new Fiber Bragg Grating (FBG)-based bundle-structure riser stress monitoring sensor has been developed. In cooperation with many departments, a 49-day marine test in water depths of 1365 m and 1252 m was completed on the "HYSY-981" ocean oil drilling platform. No welding and pasting were used when the sensor was installed on risers. Therefore, the installation is convenient, reliable and harmless to risers. The continuous, reasonable, time-consistent data obtained indicates that the sensor worked normally under water. In all detailed working conditions, the test results show that the sensor can do well in reflecting stresses and bending moments both in and in magnitude. The measured maximum stress is 132.7 MPa, which is below the allowable stress. In drilling and testing conditions, the average riser stress was 86.6 MPa, which is within the range of the China National Offshore Oil Corporation (CNOOC) mechanical simulation results.

Study and Test of a New Bundle-Structure Riser Stress Monitoring Sensor Based on FBG

PubMed Central

Xu, Jian; Yang, Dexing; Qin, Chuan; Jiang, Yajun; Sheng, Leixiang; Jia, Xiangyun; Bai, Yang; Shen, Xiaohong; Wang, Haiyan; Deng, Xin; Xu, Liangbin; Jiang, Shiquan

2015-01-01

To meet the requirements of riser safety monitoring in offshore oil fields, a new Fiber Bragg Grating (FBG)-based bundle-structure riser stress monitoring sensor has been developed. In cooperation with many departments, a 49-day marine test in water depths of 1365 m and 1252 m was completed on the “HYSY-981” ocean oil drilling platform. No welding and pasting were used when the sensor was installed on risers. Therefore, the installation is convenient, reliable and harmless to risers. The continuous, reasonable, time-consistent data obtained indicates that the sensor worked normally under water. In all detailed working conditions, the test results show that the sensor can do well in reflecting stresses and bending moments both in and in magnitude. The measured maximum stress is 132.7 MPa, which is below the allowable stress. In drilling and testing conditions, the average riser stress was 86.6 MPa, which is within the range of the China National Offshore Oil Corporation (CNOOC) mechanical simulation results. PMID:26610517

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology.

PubMed

Singh, Om Prakash; Mekonnen, Dawit; Malarvili, M B

2015-01-01

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Labview where the digital filter techniques have been implemented to remove the noise from the acquired signal. After processing, the algorithm was developed to calculate the heart rate and to analyze the arrhythmia condition. Finally, SMTP technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the telediagnosis and monitoring of ECG signals. The technology also can be easily implemented over already existing Internet.

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology

PubMed Central

Singh, Om Prakash; Mekonnen, Dawit; Malarvili, M. B.

2015-01-01

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Labview where the digital filter techniques have been implemented to remove the noise from the acquired signal. After processing, the algorithm was developed to calculate the heart rate and to analyze the arrhythmia condition. Finally, SMTP technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the telediagnosis and monitoring of ECG signals. The technology also can be easily implemented over already existing Internet. PMID:27006940

Project SHINE: Effects of Parent–Adolescent Communication on Sedentary Behavior in African American Adolescents

PubMed Central

Wilson, Dawn K.; Schneider, Elizabeth M.; Alia, Kassandra A.

2013-01-01

Objective This study examined parenting variables (communication, monitoring) as moderators of a family-based intervention for reducing sedentary behavior (SB) in African American adolescents. As a secondary aim, a similar model was tested using adolescent weight status as the outcome. Methods African American adolescents (n = 73; 12.45 ± 1.45 years; 60% girls; 63% overweight/obese) and caregivers were randomized to a 6-week interactive, parent-based intervention or general health condition. Parent–adolescent communication and monitoring of health behaviors were self-reported by parents. Adolescent SB was self-reported by youth. Results There was a significant intervention by communication interaction, such that intervention families with more positive communication showed lower adolescent SB than those with less positive communication or those in the comparison condition. No effects were found for monitoring on SB or for the model with weight status as the outcome. Conclusions Parent–adolescent communication may be an effective component to integrate into health promotion programs for African American adolescents. PMID:23685450

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

PubMed

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

Intelligent Control and Health Monitoring. Chapter 3

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Kumar, Aditya; Mathews, H. Kirk; Rosenfeld, Taylor; Rybarik, Pavol; Viassolo, Daniel E.

2009-01-01

Advanced model-based control architecture overcomes the limitations state-of-the-art engine control and provides the potential of virtual sensors, for example for thrust and stall margin. "Tracking filters" are used to adapt the control parameters to actual conditions and to individual engines. For health monitoring standalone monitoring units will be used for on-board analysis to determine the general engine health and detect and isolate sudden faults. Adaptive models open up the possibility of adapting the control logic to maintain desired performance in the presence of engine degradation or to accommodate any faults. Improved and new sensors are required to allow sensing at stations within the engine gas path that are currently not instrumented due in part to the harsh conditions including high operating temperatures and to allow additional monitoring of vibration, mass flows and energy properties, exhaust gas composition, and gas path debris. The environmental and performance requirements for these sensors are summarized.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

PubMed Central

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977

Signal Processing for Determining Water Height in Steam Pipes with Dynamic Surface Conditions

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Lee, Hyeong Jae; Bar-Cohen, Yoseph

2015-01-01

An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

50 CFR 217.225 - Requirements for monitoring and reporting.

Code of Federal Regulations, 2014 CFR

2014-10-01

... usual (i.e., 12-16 hours). (C) The number of observers shall be increased and/or positions changed to...-based), observer name and location, climate and weather conditions, and tidal conditions; (B... measurements shall be taken to ensure that hydrophones do not drag on the bottom during tidal changes. (v...

PUBLIC HEALTH AND ECOLOGICAL INTERCONNECTIVITY: A CONDITIONAL PROBABILITY APPROACH ASSOCIATING DEGRADATION OF STREAMS AND INFANT MORTALITY

EPA Science Inventory

Effective public health policy should not be based solely on clinical, individualbased

information, but requires a broad characterization of human health conditions

across large geographic areas. For the most part, the necessary monitoring of human

health to ...

Entrepreneurship Development and Business Climate of Kazakhstan

ERIC Educational Resources Information Center

Kydyrova, Zhamilya Sh.; Satymbekova, Katira B.; Kerimbek, Galymzhan E.; Imanbayev?, Zauresh O.; Saparbayev?, Saule S.; Nurgalieva, Ainash A.; Ilyas, Akylbek A.; Zhalbinova, Saule K.; Jrauovai, Kuralay S.; Kanafina, Ainura T.

2016-01-01

The goal is to explore the state of development of entrepreneurship and business climate for the formation of a clear mechanism of state support for small and average business in conditions of economy modernization. A special science-based methodology was developed to monitor the condition of entrepreneurship development and business climate in…

Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion

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

Gribok, Andrei; Patnaik, Sobhan; Williams, Christian

This report describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants. The report also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that couldmore » be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real-time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long-range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.« less

Statewide water-quality network for Massachusetts

USGS Publications Warehouse

Desimone, Leslie A.; Steeves, Peter A.; Zimmerman, Marc James

2001-01-01

A water-quality monitoring program is proposed that would provide data to meet multiple information needs of Massachusetts agencies and other users concerned with the condition of the State's water resources. The program was designed by the U.S. Geological Survey and the Massachusetts Department of Environmental Protection, Division of Watershed Management, with input from many organizations involved in water-quality monitoring in the State, and focuses on inland surface waters (streams and lakes). The proposed monitoring program consists of several components, or tiers, which are defined in terms of specific monitoring objectives, and is intended to complement the Massachusetts Watershed Initiative (MWI) basin assessments. Several components were developed using the Neponset River Basin in eastern Massachusetts as a pilot area, or otherwise make use of data from and sampling approaches used in that basin as part of a MWI pilot assessment in 1994. To guide development of the monitoring program, reviews were conducted of general principles of network design, including monitoring objectives and approaches, and of ongoing monitoring activities of Massachusetts State agencies.Network tiers described in this report are primarily (1) a statewide, basin-based assessment of existing surface-water-quality conditions, and (2) a fixed-station network for determining contaminant loads carried by major rivers. Other components, including (3) targeted programs for hot-spot monitoring and other objectives, and (4) compliance monitoring, also are discussed. Monitoring programs for the development of Total Maximum Daily Loads for specific water bodies, which would constitute another tier of the network, are being developed separately and are not described in this report. The basin-based assessment of existing conditions is designed to provide information on the status of surface waters with respect to State water-quality standards and designated uses in accordance with the reporting requirements [Section 305(b)] of the Clean Water Act (CWA). Geographic Information System (GIS)-based procedures were developed to inventory streams and lakes in a basin for these purposes. Several monitoring approaches for this tier and their associated resource requirements were investigated. Analysis of the Neponset Basin for this purpose demonstrated that the large number of sites needed in order for all the small streams in a basin to be sampled (about half of stream miles in the basin were headwater or first-order streams) pose substantial resource-based problems for a comprehensive assessment of existing conditions. The many lakes pose similar problems. Thus, a design is presented in which probabilistic monitoring of small streams is combined with deterministic or targeted monitoring of large streams and lakes to meet CWA requirements and to provide data for other information needs of Massachusetts regulatory agencies and MWI teams.The fixed-station network is designed to permit the determination of contaminant loads carried by the State's major rivers to sensitive inland and coastal receiving waters and across State boundaries. Sampling at 19 proposed sites in 17 of the 27 major basins in Massachusetts would provide information on contaminant loads from 67 percent of the total land area of the State; unsampled areas are primarily coastal areas drained by many small streams that would be impossible to sample within realistic resource limitations. Strategies for hot-spot monitoring, a targeted monitoring program focused on identifying contaminant sources, are described with reference to an analysis of the bacteria sampling program of the 1994 Neponset Basin assessment. Finally, major discharge sites permitted under the National Pollutant Discharge Elimination System (NPDES) were evaluated as a basis for ambient water-quality monitoring. The discharge sites are well distributed geographically among basins, but are primarily on large rivers (two-thirds or more

High-Resolution Near Real-Time Drought Monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Implementation science for ambulatory care safety: a novel method to develop context-sensitive interventions to reduce quality gaps in monitoring high-risk patients.

PubMed

McDonald, Kathryn M; Su, George; Lisker, Sarah; Patterson, Emily S; Sarkar, Urmimala

2017-06-24

Missed evidence-based monitoring in high-risk conditions (e.g., cancer) leads to delayed diagnosis. Current technological solutions fail to close this safety gap. In response, we aim to demonstrate a novel method to identify common vulnerabilities across clinics and generate attributes for context-flexible population-level monitoring solutions for widespread implementation to improve quality. Based on interviews with staff in otolaryngology, pulmonary, urology, breast, and gastroenterology clinics at a large urban publicly funded health system, we applied journey mapping to co-develop a visual representation of how patients are monitored for high-risk conditions. Using a National Academies framework and context-sensitivity theory, we identified common systems vulnerabilities and developed preliminary concepts for improving the robustness for monitoring patients with high-risk conditions ("design seeds" for potential solutions). Finally, we conducted a face validity and prioritization assessment of the design seeds with the original interviewees. We identified five high-risk situations for potentially consequential diagnostic delays arising from suboptimal patient monitoring. All situations related to detection of cancer (head and neck, lung, prostate, breast, and colorectal). With clinic participants we created 5 journey maps, each representing specialty clinic workflow directed at evidence-based monitoring. System vulnerabilities common to the different clinics included challenges with: data systems, communications handoffs, population-level tracking, and patient activities. Clinic staff ranked 13 design seeds (e.g., keep patient list up to date, use triggered notifications) addressing these vulnerabilities. Each design seed has unique evaluation criteria for the usefulness of potential solutions developed from the seed. We identified and ranked 13 design seeds that characterize situations that clinicians described 'wake them up at night', and thus could reduce their anxiety, save time, and improve monitoring of high-risk patients. We anticipate that the design seed approach promotes robust and context-sensitive solutions to safety and quality problems because it provides a human-centered link between the experienced problem and various solutions that can be tested for viability. The study also demonstrates a novel integration of industrial and human factors methods (journey mapping, process tracing and design seeds) linked to implementation theory for use in designing interventions that anticipate and reduce implementation challenges.

Remote Monitoring of Post-eruption Volcano Environment Based-On Wireless Sensor Network (WSN): The Mount Sinabung Case

NASA Astrophysics Data System (ADS)

Soeharwinto; Sinulingga, Emerson; Siregar, Baihaqi

2017-01-01

An accurate information can be useful for authorities to make good policies for preventive and mitigation after volcano eruption disaster. Monitoring of environmental parameters of post-eruption volcano provides an important information for authorities. Such monitoring system can be develop using the Wireless Network Sensor technology. Many application has been developed using the Wireless Sensor Network technology, such as floods early warning system, sun radiation mapping, and watershed monitoring. This paper describes the implementation of a remote environment monitoring system of mount Sinabung post-eruption. The system monitor three environmental parameters: soil condition, water quality and air quality (outdoor). Motes equipped with proper sensors, as components of the monitoring system placed in sample locations. The measured value from the sensors periodically sends to data server using 3G/GPRS communication module. The data can be downloaded by the user for further analysis.The measurement and data analysis results generally indicate that the environmental parameters in the range of normal/standard condition. The sample locations are safe for living and suitable for cultivation, but awareness is strictly required due to the uncertainty of Sinabung status.

Crack width monitoring of concrete structures based on smart film

NASA Astrophysics Data System (ADS)

Zhang, Benniu; Wang, Shuliang; Li, Xingxing; Zhang, Xu; Yang, Guang; Qiu, Minfeng

2014-04-01

Due to its direct link to structural security, crack width is thought to be one of the most important parameters reflecting damage conditions of concrete structures. However, the width problem is difficult to solve with the existing structural health monitoring methods. In this paper, crack width monitoring by means of adhering enameled copper wires with different ultimate strains on the surface of structures is proposed, based on smart film crack monitoring put forward by the present authors. The basic idea of the proposed method is related to a proportional relationship between the crack width and ultimate strain of the broken wire. Namely, when a certain width of crack passes through the wire, some low ultimate strain wires will be broken and higher ultimate strain wires may stay non-broken until the crack extends to a larger scale. Detection of the copper wire condition as broken or non-broken may indicate the width of the structural crack. Thereafter, a multi-layered stress transfer model and specimen experiment are performed to quantify the relationship. A practical smart film is then redesigned with this idea and applied to Chongqing Jiangjin Yangtze River Bridge.

Ultrasonic guided wave monitoring of composite wing skin-to-spar bonded joints in aerospace structures

NASA Astrophysics Data System (ADS)

Matt, Howard; Bartoli, Ivan; Lanza di Scalea, Francesco

2005-10-01

The monitoring of adhesively bonded joints by ultrasonic guided waves is the general topic of this paper. Specifically, composite-to-composite joints representative of the wing skin-to-spar bonds of unmanned aerial vehicles (UAVs) are examined. This research is the first step towards the development of an on-board structural health monitoring system for UAV wings based on integrated ultrasonic sensors. The study investigates two different lay-ups for the wing skin and two different types of bond defects, namely poorly cured adhesive and disbonded interfaces. The assessment of bond state is based on monitoring the strength of transmission through the joints of selected guided modes. The wave propagation problem is studied numerically by a semi-analytical finite element method that accounts for viscoelastic damping, and experimentally by ultrasonic testing that uses small PZT disks preferably exciting and detecting the single-plate s0 mode. Both the models and the experiments confirm that the ultrasonic energy transmission through the joint is highly dependent on the bond conditions, with defected bonds resulting in increased transmission strength. Large sensitivity to the bond conditions is found at mode coupling points, as a result of the large interlayer energy transfer.

Respiration rate detection based on intensity modulation using plastic optical fiber

NASA Astrophysics Data System (ADS)

Anwar, Zawawi Mohd; Ziran Nurul Sufia, Nor; Hadi, Manap

2017-11-01

This paper presents the implementation of respiration rate measurement via a simple intensity-based optical fiber sensor using optical fiber technology. The breathing rate is measured based on the light intensity variation due to the longitudinal gap changes between two separated fibers. In order to monitor the breathing rate continuously, the output from the photodetector conditioning circuit is connected to a low-cost Arduino kit. At the sensing point, two optical fiber cables are positioned in series with a small gap and fitted inside a transparent plastic tube. To ensure smooth movement of the fiber during inhale and exhale processes as well as to maintain the gap of the fiber during idle condition, the fiber is attached firmly to a stretchable bandage. This study shows that this simple fiber arrangement can be applied to detect respiration activity which might be critical for patient monitoring.

Speckle-correlation analysis of the microcapillary blood circulation in nail bed

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

Vilenskii, M A; Agafonov, D N; Zimnyakov, D A

2011-04-30

We present the results of the experimental studies of the possibility of monitoring the blood microcirculation in human finger nail bed with application of speckle-correlation analysis, based on estimating the contrast of time-averaged dynamic speckles. The hemodynamics at normal blood circulation and under conditions of partially suppressed blood circulation is analysed. A microscopic analysis is performed to visualise the structural changes in capillaries that are caused by suppressing blood circulation. The problems and prospects of speckle-correlation monitoring of the nail bed microhemodynamics under laboratory and clinical conditions are discussed. (optical technologies in biophysics and medicine)

Non-Dispersive Infrared Sensor for Online Condition Monitoring of Gearbox Oil.

PubMed

Rauscher, Markus S; Tremmel, Anton J; Schardt, Michael; Koch, Alexander W

2017-02-18

The condition of lubricating oil used in automotive and industrial gearboxes must be controlled in order to guarantee optimum performance and prevent damage to machinery parts. In normal practice, this is done by regular oil change intervals and routine laboratory analysis, both of which involve considerable operating costs. In this paper, we present a compact and robust optical sensor that can be installed in the lubrication circuit to provide quasi-continuous information about the condition of the oil. The measuring principle is based on non-dispersive infrared spectroscopy. The implemented sensor setup consists of an optical measurement cell, two thin-film infrared emitters, and two four-channel pyroelectric detectors equipped with optical bandpass filters. We present a method based on multivariate partial least squares regression to select appropriate optical bandpass filters for monitoring the oxidation, water content, and acid number of the oil. We perform a ray tracing analysis to analyze and correct the influence of the light path in the optical setup on the optical parameters of the bandpass filters. The measurement values acquired with the sensor for three different gearbox oil types show high correlation with laboratory reference data for the oxidation, water content, and acid number. The presented sensor can thus be a useful supplementary tool for the online condition monitoring of lubricants when integrated into a gearbox oil circuit.

Non-Dispersive Infrared Sensor for Online Condition Monitoring of Gearbox Oil

PubMed Central

Rauscher, Markus S.; Tremmel, Anton J.; Schardt, Michael; Koch, Alexander W.

2017-01-01

The condition of lubricating oil used in automotive and industrial gearboxes must be controlled in order to guarantee optimum performance and prevent damage to machinery parts. In normal practice, this is done by regular oil change intervals and routine laboratory analysis, both of which involve considerable operating costs. In this paper, we present a compact and robust optical sensor that can be installed in the lubrication circuit to provide quasi-continuous information about the condition of the oil. The measuring principle is based on non-dispersive infrared spectroscopy. The implemented sensor setup consists of an optical measurement cell, two thin-film infrared emitters, and two four-channel pyroelectric detectors equipped with optical bandpass filters. We present a method based on multivariate partial least squares regression to select appropriate optical bandpass filters for monitoring the oxidation, water content, and acid number of the oil. We perform a ray tracing analysis to analyze and correct the influence of the light path in the optical setup on the optical parameters of the bandpass filters. The measurement values acquired with the sensor for three different gearbox oil types show high correlation with laboratory reference data for the oxidation, water content, and acid number. The presented sensor can thus be a useful supplementary tool for the online condition monitoring of lubricants when integrated into a gearbox oil circuit. PMID:28218701

Daylighting performance and thermal implications of skylights vs. south-facing roof monitors

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

Rosenbaum, M.; Coldham, B.

1997-12-31

This paper reports the results of a comparison of skylights vs. south-facing roof monitors for daylighting the north wall zone of a 10,000 ft{sup 2} office building near Manchester, NH. A physical model was constructed and tested. Simultaneously, the building`s annual thermal performance was modeled with Energy-10 hourly simulation software, and its peak heating and cooling load performance was modeled with the Carrier Corp. Hourly Analysis Program (HAP). Apertures were built into the roof of the model, and several skylight and south-facing roof monitor configurations were tested in both clear and overcast conditions. A design goal was to have themore » building be daylit on overcast as well as clear days. This goal was based more on enhancement of the working environment than it was on electrical energy savings. Monitors with overhangs performed poorly in the overcast conditions--it was determined that 2.4 times as much monitor aperture was needed to yield equivalent light levels in overcast conditions. The thermal models showed that the annual heating and cooling energy cost for the building was the same for either strategy, but that peak cooling loads and peak heating loads were lower with the skylit version. The authors concluded that skylights were preferred over monitors in this application, due to similar annual energy costs, lower peak loads, and lower construction cost.« less

Research and design of smart grid monitoring control via terminal based on iOS system

NASA Astrophysics Data System (ADS)

Fu, Wei; Gong, Li; Chen, Heli; Pan, Guangji

2017-06-01

Aiming at a series of problems existing in current smart grid monitoring Control Terminal, such as high costs, poor portability, simple monitoring system, poor software extensions, low system reliability when transmitting information, single man-machine interface, poor security, etc., smart grid remote monitoring system based on the iOS system has been designed. The system interacts with smart grid server so that it can acquire grid data through WiFi/3G/4G networks, and monitor each grid line running status, as well as power plant equipment operating conditions. When it occurs an exception in the power plant, incident information can be sent to the user iOS terminal equipment timely, which will provide troubleshooting information to help the grid staff to make the right decisions in a timely manner, to avoid further accidents. Field tests have shown the system realizes the integrated grid monitoring functions, low maintenance cost, friendly interface, high security and reliability, and it possesses certain applicable value.

Health Monitoring Survey of Bell 412EP Transmissions

NASA Technical Reports Server (NTRS)

Tucker, Brian E.; Dempsey, Paula J.

2016-01-01

Health and usage monitoring systems (HUMS) use vibration-based Condition Indicators (CI) to assess the health of helicopter powertrain components. A fault is detected when a CI exceeds its threshold value. The effectiveness of fault detection can be judged on the basis of assessing the condition of actual components from fleet aircraft. The Bell 412 HUMS-equipped helicopter is chosen for such an evaluation. A sample of 20 aircraft included 12 aircraft with confirmed transmission and gearbox faults (detected by CIs) and eight aircraft with no known faults. The associated CI data is classified into "healthy" and "faulted" populations based on actual condition and these populations are compared against their CI thresholds to quantify the probability of false alarm and the probability of missed detection. Receiver Operator Characteristic analysis is used to optimize thresholds. Based on the results of the analysis, shortcomings in the classification method are identified for slow-moving CI trends. Recommendations for improving classification using time-dependent receiver-operator characteristic methods are put forth. Finally, lessons learned regarding OEM-operator communication are presented.

Proposed modifications to the RCRA post-closure permit for the Chestnut Ridge Hydrogeologic Regime at the U.S. Department of Energy Y-12 Plant, Oak Ridge, Tennessee

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

NONE

1997-05-01

This report presents proposed modifications to several conditions of the Resource Conservation and Recovery Act (RCRA) Post-Closure Permit (PCP) for the Chestnut Ridge Hydrogeologic Regime (CRHR) (permit number TNHW-088, EPA ID No. TN3 89 009 0001). These permit conditions define the requirements for RCRA post-closure detection groundwater monitoring at the Chestnut Ridge Sediment Disposal Basin (CRSDB) and Kerr Hollow Quarry (KHQ), and RCRA post-closure corrective action groundwater monitoring at the Chestnut Ridge Security Pits (CRSPs). Modification of these PCP conditions is requested to: (1) clarify the planned integration of RCRA post-closure corrective action groundwater monitoring at the CRSPs with themore » monitoring program to be established in the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) record of decision (ROD), (2) revise several of the current technical requirements for groundwater monitoring based on implementation of the RCRA monitoring programs during 1996, (3) replace several of the technical procedures included in the PCP with updated versions recently issued by the Y-12 Plant Groundwater Protection Program (GWPP), and (4) correct inaccurate regulatory citations and references to permit conditions and permit attachments. With these modifications, the Y- 12 Plant will continue to meet the full intent of all regulatory obligations for post-closure care of these facilities. Section 2 provides the technical justification for each proposed permit modification. Section 3.0 contains proposed changes to Section II of the PCP. Modifications to site-specific permit conditions are presented in Section 4.0 (CRSDB), Section 5.0 (CRSPs), and Section 6.0 (KHQ). Sections 7.0 and 8.0 reference updated and revised procedures for groundwater sampling, and monitoring well plugging and abandonment, respectively. Appendix A includes all proposed revisions to the permit attachments.« less

Vibro-acoustic condition monitoring of Internal Combustion Engines: A critical review of existing techniques

NASA Astrophysics Data System (ADS)

Delvecchio, S.; Bonfiglio, P.; Pompoli, F.

2018-01-01

This paper deals with the state-of-the-art strategies and techniques based on vibro-acoustic signals that can monitor and diagnose malfunctions in Internal Combustion Engines (ICEs) under both test bench and vehicle operating conditions. Over recent years, several authors have summarized what is known in critical reviews mainly focused on reciprocating machines in general or on specific signal processing techniques: no attempts to deal with IC engine condition monitoring have been made. This paper first gives a brief summary of the generation of sound and vibration in ICEs in order to place further discussion on fault vibro-acoustic diagnosis in context. An overview of the monitoring and diagnostic techniques described in literature using both vibration and acoustic signals is also provided. Different faulty conditions are described which affect combustion, mechanics and the aerodynamics of ICEs. The importance of measuring acoustic signals, as opposed to vibration signals, is due since the former seem to be more suitable for implementation on on-board monitoring systems in view of their non-intrusive behaviour, capability in simultaneously capturing signatures from several mechanical components and because of the possibility of detecting faults affecting airborne transmission paths. In view of the recent needs of the industry to (-) optimize component structural durability adopting long-life cycles, (-) verify the engine final status at the end of the assembly line and (-) reduce the maintenance costs monitoring the ICE life during vehicle operations, monitoring and diagnosing system requests are continuously growing up. The present review can be considered a useful guideline for test engineers in understanding which types of fault can be diagnosed by using vibro-acoustic signals in sufficient time in both test bench and operating conditions and which transducer and signal processing technique (of which the essential background theory is here reported) could be considered the most reliable and informative to be implemented for the fault in question.

A Monitoring System for Vegetable Greenhouses based on a Wireless Sensor Network

PubMed Central

Li, Xiu-hong; Cheng, Xiao; Yan, Ke; Gong, Peng

2010-01-01

A wireless sensor network-based automatic monitoring system is designed for monitoring the life conditions of greenhouse vegetatables. The complete system architecture includes a group of sensor nodes, a base station, and an internet data center. For the design of wireless sensor node, the JN5139 micro-processor is adopted as the core component and the Zigbee protocol is used for wireless communication between nodes. With an ARM7 microprocessor and embedded ZKOS operating system, a proprietary gateway node is developed to achieve data influx, screen display, system configuration and GPRS based remote data forwarding. Through a Client/Server mode the management software for remote data center achieves real-time data distribution and time-series analysis. Besides, a GSM-short-message-based interface is developed for sending real-time environmental measurements, and for alarming when a measurement is beyond some pre-defined threshold. The whole system has been tested for over one year and satisfactory results have been observed, which indicate that this system is very useful for greenhouse environment monitoring. PMID:22163391

Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin

NASA Astrophysics Data System (ADS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo

2016-12-01

The authors have recently developed a soft-elastomeric capacitive (SEC)-based thin film sensor for monitoring strain on mesosurfaces. Arranged in a network configuration, the sensing system is analogous to a biological skin, where local strain can be monitored over a global area. Under plane stress conditions, the sensor output contains the additive measurement of the two principal strain components over the monitored surface. In applications where the evaluation of strain maps is useful, in structural health monitoring for instance, such signal must be decomposed into linear strain components along orthogonal directions. Previous work has led to an algorithm that enabled such decomposition by leveraging a dense sensor network configuration with the addition of assumed boundary conditions. Here, we significantly improve the algorithm’s accuracy by leveraging mature off-the-shelf solutions to create a hybrid dense sensor network (HDSN) to improve on the boundary condition assumptions. The system’s boundary conditions are enforced using unidirectional RSGs and assumed virtual sensors. Results from an extensive experimental investigation demonstrate the good performance of the proposed algorithm and its robustness with respect to sensors’ layout. Overall, the proposed algorithm is seen to effectively leverage the advantages of a hybrid dense network for application of the thin film sensor to reconstruct surface strain fields over large surfaces.

Wearable sensors for health monitoring

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

2015-02-01

In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

Passive seismic monitoring of the Bering Glacier during its last surge event

NASA Astrophysics Data System (ADS)

Zhan, Z.

2017-12-01

The physical causes behind glacier surges are still unclear. Numerous evidences suggest that they probably involve changes in glacier basal conditions, such as switch of basal water system from concentrated large tunnels to a distributed "layer" as "connected cavities". However, most remote sensing approaches can not penetrate to the base to monitor such changes continuously. Here we apply seismic interferometry using ambient noise to monitor glacier seismic structures, especially to detect possible signatures of the hypothesized high-pressure water "layer". As an example, we derive an 11-year long history of seismic structure of the Bering Glacier, Alaska, covering its latest surge event. We observe substantial drops of Rayleigh and Love wavespeeds across the glacier during the surge event, potentially caused by changes in crevasse density, glacier thickness, and basal conditions.

[Bioimpedance means of skin condition monitoring during therapeutic and cosmetic procedures].

PubMed

Alekseenko, V A; Kus'min, A A; Filist, S A

2008-01-01

Engineering and technological problems of bioimpedance skin surface mapping are considered. A typical design of a device based on a PIC 16F microcontroller is suggested. It includes a keyboard, LCD indicator, probing current generator with programmed frequency tuning, and units for probing current monitoring and bioimpedance measurement. The electrode matrix of the device is constructed using nanotechnology. A microcontroller-controlled multiplexor provides scanning of interelectrode impedance, which makes it possible to obtain the impedance image of the skin surface under the electrode matrix. The microcontroller controls the probing signal generator frequency and allows layer-by-layer images of skin under the electrode matrix to be obtained. This makes it possible to use reconstruction tomography methods for analysis and monitoring of the skin condition during therapeutic and cosmetic procedures.

Comparison of land use regression models for NO2 based on routine and campaign monitoring data from an urban area of Japan.

PubMed

Kashima, Saori; Yorifuji, Takashi; Sawada, Norie; Nakaya, Tomoki; Eboshida, Akira

2018-08-01

Typically, land use regression (LUR) models have been developed using campaign monitoring data rather than routine monitoring data. However, the latter have advantages such as low cost and long-term coverage. Based on the idea that LUR models representing regional differences in air pollution and regional road structures are optimal, the objective of this study was to evaluate the validity of LUR models for nitrogen dioxide (NO 2 ) based on routine and campaign monitoring data obtained from an urban area. We selected the city of Suita in Osaka (Japan). We built a model based on routine monitoring data obtained from all sites (routine-LUR-All), and a model based on campaign monitoring data (campaign-LUR) within the city. Models based on routine monitoring data obtained from background sites (routine-LUR-BS) and based on data obtained from roadside sites (routine-LUR-RS) were also built. The routine LUR models were based on monitoring networks across two prefectures (i.e., Osaka and Hyogo prefectures). We calculated the predictability of the each model. We then compared the predicted NO 2 concentrations from each model with measured annual average NO 2 concentrations from evaluation sites. The routine-LUR-All and routine-LUR-BS models both predicted NO 2 concentrations well: adjusted R 2 =0.68 and 0.76, respectively, and root mean square error=3.4 and 2.1ppb, respectively. The predictions from the routine-LUR-All model were highly correlated with the measured NO 2 concentrations at evaluation sites. Although the predicted NO 2 concentrations from each model were correlated, the LUR models based on routine networks, and particularly those based on all monitoring sites, provided better visual representations of the local road conditions in the city. The present study demonstrated that LUR models based on routine data could estimate local traffic-related air pollution in an urban area. The importance and usefulness of data from routine monitoring networks should be acknowledged. Copyright © 2018 Elsevier B.V. All rights reserved.

Trends in the nutrient enrichment of U.S. rivers during the late 20th century and their relation to changes in probable stream trophic conditions

USGS Publications Warehouse

Alexander, R.B.; Smith, R.A.

2006-01-01

We estimated trends in concentrations of total phosphorus (TP) and total nitrogen (TN) and the related change in the probabilities of trophic conditions from 1975 to 1994 at 250 nationally representative riverine monitoring locations in the U.S. with drainage areas larger than about 1,000 km2. Statistically significant (p < 0.05) declines were detected in TP and TN concentrations at 44% and 37% of the monitoring sites, and significant increases were detected at 3% and 9% of the sites, respectively. We used a statistical model to assess changes in the probable trophic-state classification of the sites after adjusting for climate-related variability in nutrient concentrations. The probabilistic assessment accounts for current knowledge of the trophic response of streams to nutrient enrichment, based on a recently proposed definition of "eutrophic," "mesotrophic," and "oligotrophic" conditions in relation to total nutrient concentrations. Based on these trophic definitions, we found that the trophic state improved at 25% of the monitoring sites and worsened at fewer than 5% of the sites; about 70% of the sites were unchanged. Improvements in trophic-state related to declines in TP were more common in predominantly forested and shrub-grassland watersheds, whereas the trophic state of predominantly agricultural sites was unchanged. Despite the declines in TP concentrations at many sites, about 50% of all monitoring sites, and more than 60% of the sites in predominantly agricultural and urban watersheds, were classified as eutrophic in 1994 based on TP concentrations. Contemporaneous reductions in major nutrient sources to streams, related to wastewater treatment upgrades, phosphate detergent bans, and declines in some agricultural sources, may have contributed to the declines in riverine nutrient concentrations and associated improvements in trophic conditions. ?? 2006, by the American Society of Limnology and Oceanography, Inc.

A Comprehensive Study on Technologies of Tyre Monitoring Systems and Possible Energy Solutions

PubMed Central

Kubba, Ali E.; Jiang, Kyle

2014-01-01

This article presents an overview on the state of the art of Tyre Pressure Monitoring System related technologies. This includes examining the latest pressure sensing methods and comparing different types of pressure transducers, particularly their power consumption and measuring range. Having the aim of this research to investigate possible means to obtain a tyre condition monitoring system (TCMS) powered by energy harvesting, various approaches of energy harvesting techniques were evaluated to determine which approach is the most applicable for generating energy within the pneumatic tyre domain and under rolling tyre dynamic conditions. This article starts with an historical review of pneumatic tyre development and demonstrates the reasons and explains the need for using a tyre condition monitoring system. Following this, different tyre pressure measurement approaches are compared in order to determine what type of pressure sensor is best to consider in the research proposal plan. Then possible energy harvesting means inside land vehicle pneumatic tyres are reviewed. Following this, state of the art battery-less tyre pressure monitoring systems developed by individual researchers or by world leading tyre manufacturers are presented. Finally conclusions are drawn based on the reviewed documents cited in this article and a research proposal plan is presented. PMID:24922457

A new portable sulfide monitor with a zinc-oxide semiconductor sensor for daily use and field study.

PubMed

Tanda, Naoko; Washio, Jumpei; Ikawa, Kyoko; Suzuki, Kengo; Koseki, Takeyoshi; Iwakura, Masaki

2007-07-01

For measuring oral malodor in daily clinical practice and in field study, we developed and evaluated a highly sensitive portable monitor system. We examined sensitivity and specificity of the sensor for volatile sulfur compounds (VSC) and obstructive gases, such as ethanol, acetone, and acetaldehyde. Each mouth air provided by 46 people was measured by this monitor, gas chromatography (GC), and olfactory panel and compared with each other. Based on the result, we used the monitor for mass health examination of a rural town with standardized measuring. The sensor detected hydrogen sulfide, methyl mercaptan, and dimethyl sulfide with 10-1000 times higher sensitivity than the other gases. The monitor's specificity was significantly improved by a VSC-selective filter. There were significant correlations between VSC concentration by the sulfide monitor and by GC, and by organoleptic score. Thirty-six percent of 969 examinees had oral malodor in a rural town. Seventy-eight percent of 969 examinees were motivated to take care of their oral condition by oral malodor measuring with the monitor. The portable sulfide monitor was useful to promote oral health care not only in clinics, but also in field study. The simple and quick operation system and the standardized measuring make it one of parameters of oral condition.

The Significance of Forest Monitoring Programmes: the Finnish Perspective

NASA Astrophysics Data System (ADS)

Merila, P.; Derome, J.; Lindgren, M.

2007-12-01

Finland has been participating in the ICP Forests programme (the International Co-operative Programme on the Assessment and Monitoring of Air Pollution Effects on Forests) based on international agreements on the long- range transportation of air pollutants (LRTAP) and other associated monitoring programmes (e.g. Forest Focus, ICP Integrated Monitoring, ICP Vegetation) since 1985. The knowledge gained during the years has greatly increased our understanding of the overall condition of our forests and the factors affecting forest condition, the processes underlying forest ecosystem functioning, and the potential threats to our forests posed by human activities, both at home and abroad. The success of the monitoring activities in Finland is largely based on the experience gained during the early 1980's with our own national acidification project and, during the late 1980's and early 1990"s, in a number of regional monitoring projects. Finland's membership of the European Union (entry in 1996) has enabled us to further develop the infrastructure and coverage of both our extensive and intensive level networks. This broadening of our ecological understanding and development of international collaboration are now providing us with an invaluable basis for addressing the new monitoring challenges (biodiversity, climate change). The results gained in our monitoring activities clearly demonstrate the value of long-term monitoring programmes. The main results have been regularly reported both at the European (e.g. http://www.icp- forests.org/Reports.htm) and national level (e.g. http://www.metla.fi/julkaisut/workingpapers/2007/mwp045- en.htm). However, the datasets have not been intensively explored and exploited, and few of the important methodological and ecological findings have been published in peer-reviewed scientific journals. This has, understandably, not been the first priority of the international monitoring programmes. A number of the intensive forest monitoring plots in Finland have recently been included in LTER platforms, thus potentially increasing scientific collaboration between researchers across different governmental institutes and education bodies.

Electrokinetic Enrichment and Detection of Neuropeptide for Performance Monitor

DTIC Science & Technology

2016-06-14

conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...nanoparticle immunoassays and aptamer -based approaches for enhancing detection specificity. Experiment: Towards addressing AFRL’s grand challenge of

Electrokinetic enrichment and detection of neuropeptide for performance monitoring

DTIC Science & Technology

2016-06-14

conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...nanoparticle immunoassays and aptamer -based approaches for enhancing detection specificity. Experiment: Towards addressing AFRL’s grand challenge of

Compositing MODIS Terra and Aqua 250m daily surface reflectance data sets for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

Remote sensing based vegetation Indices have been proven valuable in providing a spatially complete view of crop’s vegetation condition, which also manifests the impact of the disastrous events such as massive flood and drought. VegScape, a web GIS application for crop vegetation condition monitorin...

Non-invasive Monitoring of Intracranial Pressure Using Transcranial Doppler Ultrasonography: Is It Possible?

PubMed

Cardim, Danilo; Robba, C; Bohdanowicz, M; Donnelly, J; Cabella, B; Liu, X; Cabeleira, M; Smielewski, P; Schmidt, B; Czosnyka, M

2016-12-01

Although intracranial pressure (ICP) is essential to guide management of patients suffering from acute brain diseases, this signal is often neglected outside the neurocritical care environment. This is mainly attributed to the intrinsic risks of the available invasive techniques, which have prevented ICP monitoring in many conditions affecting the intracranial homeostasis, from mild traumatic brain injury to liver encephalopathy. In such scenario, methods for non-invasive monitoring of ICP (nICP) could improve clinical management of these conditions. A review of the literature was performed on PUBMED using the search keywords 'Transcranial Doppler non-invasive intracranial pressure.' Transcranial Doppler (TCD) is a technique primarily aimed at assessing the cerebrovascular dynamics through the cerebral blood flow velocity (FV). Its applicability for nICP assessment emerged from observation that some TCD-derived parameters change during increase of ICP, such as the shape of FV pulse waveform or pulsatility index. Methods were grouped as: based on TCD pulsatility index; aimed at non-invasive estimation of cerebral perfusion pressure and model-based methods. Published studies present with different accuracies, with prediction abilities (AUCs) for detection of ICP ≥20 mmHg ranging from 0.62 to 0.92. This discrepancy could result from inconsistent assessment measures and application in different conditions, from traumatic brain injury to hydrocephalus and stroke. Most of the reports stress a potential advantage of TCD as it provides the possibility to monitor changes of ICP in time. Overall accuracy for TCD-based methods ranges around ±12 mmHg, with a great potential of tracing dynamical changes of ICP in time, particularly those of vasogenic nature.

Chapel of cemetery church of all saints in Sedlec - Long-term analysis of hygrothermal conditions

NASA Astrophysics Data System (ADS)

Pavlík, Zbyšek; Balík, Lukáš; Kudrnáčová, Lucie; Maděra, Jiří; Černý, Robert

2017-07-01

In this paper, long-term monitoring of hygrothermal conditions of the chapel of the cemetery church of All Saints in Sedlec, Czech Republic is presented as a practical tool for evaluation of functional problems of the researched structure. Within the performed experimental tests, interior and exterior climatic conditions were monitored over one year period. Herewith, surface temperature of the chapel wall was measured. Exterior climatic data were collected using weather station Vantage Pro2 placed in church tower. In interior, precise combined relative humidity/temperature sensors were installed. Based on the accessed hygrothermal state of the inspected chapel and identified periods of possible surface condensation, service conditions of the chapel will be optimized in order to prevent extensive damage of historically valuable finishing and furnishing materials, paintings, plasters, and architectural ornaments.

On-line monitoring system of PV array based on internet of things technology

NASA Astrophysics Data System (ADS)

Li, Y. F.; Lin, P. J.; Zhou, H. F.; Chen, Z. C.; Wu, L. J.; Cheng, S. Y.; Su, F. P.

2017-11-01

The Internet of Things (IoT) Technology is used to inspect photovoltaic (PV) array which can greatly improve the monitoring, performance and maintenance of the PV array. In order to efficiently realize the remote monitoring of PV operating environment, an on-line monitoring system of PV array based on IoT is designed in this paper. The system includes data acquisition, data gateway and PV monitoring centre (PVMC) website. Firstly, the DSP-TMS320F28335 is applied to collect indicators of PV array using sensors, then the data are transmitted to data gateway through ZigBee network. Secondly, the data gateway receives the data from data acquisition part, obtains geographic information via GPS module, and captures the scenes around PV array via USB camera, then uploads them to PVMC website. Finally, the PVMC website based on Laravel framework receives all data from data gateway and displays them with abundant charts. Moreover, a fault diagnosis approach for PV array based on Extreme Learning Machine (ELM) is applied in PVMC. Once fault occurs, a user alert can be sent via E-mail. The designed system enables users to browse the operating conditions of PV array on PVMC website, including electrical, environmental parameters and video. Experimental results show that the presented monitoring system can efficiently real-time monitor the PV array, and the fault diagnosis approach reaches a high accuracy of 97.5%.

Incorporating Equipment Condition Assessment in Risk Monitors for Advanced Small Modular Reactors

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

Coble, Jamie B.; Coles, Garill A.; Meyer, Ryan M.

2013-10-01

Advanced small modular reactors (aSMRs) can complement the current fleet of large light-water reactors in the USA for baseload and peak demand power production and process heat applications (e.g., water desalination, shale oil extraction, hydrogen production). The day-to-day costs of aSMRs are expected to be dominated by operations and maintenance (O&M); however, the effect of diverse operating missions and unit modularity on O&M is not fully understood. These costs could potentially be reduced by optimized scheduling, with risk-informed scheduling of maintenance, repair, and replacement of equipment. Currently, most nuclear power plants have a “living” probabilistic risk assessment (PRA), which reflectsmore » the as-operated, as-modified plant and combine event probabilities with population-based probability of failure (POF) for key components. “Risk monitors” extend the PRA by incorporating the actual and dynamic plant configuration (equipment availability, operating regime, environmental conditions, etc.) into risk assessment. In fact, PRAs are more integrated into plant management in today’s nuclear power plants than at any other time in the history of nuclear power. However, population-based POF curves are still used to populate fault trees; this approach neglects the time-varying condition of equipment that is relied on during standard and non-standard configurations. Equipment condition monitoring techniques can be used to estimate the component POF. Incorporating this unit-specific estimate of POF in the risk monitor can provide a more accurate estimate of risk in different operating and maintenance configurations. This enhanced risk assessment will be especially important for aSMRs that have advanced component designs, which don’t have an available operating history to draw from, and often use passive design features, which present challenges to PRA. This paper presents the requirements and technical gaps for developing a framework to integrate unit-specific estimates of POF into risk monitors, resulting in enhanced risk monitors that support optimized operation and maintenance of aSMRs.« less

Use of FBG sensors for health monitoring of pipelines

NASA Astrophysics Data System (ADS)

Felli, Ferdinando; Paolozzi, Antonio; Vendittozzi, Cristian; Paris, Claudio; Asanuma, Hiroshi

2016-04-01

The infrastructures for oil and gas production and distribution need reliable monitoring systems. The risks for pipelines, in particular, are not only limited to natural disasters (landslides, earthquakes, extreme environmental conditions) and accidents, but involve also the damages related to criminal activities, such as oil theft. The existing monitoring systems are not adequate for detecting damages from oil theft, and in several occasion the illegal activities resulted in leakage of oil and catastrophic environmental pollution. Systems based on fiber optic FBG (Fiber Bragg Grating) sensors present a number of advantages for pipeline monitoring. FBG sensors can withstand harsh environment, are immune to interferences, and can be used to develop a smart system for monitoring at the same time several physical characteristics, such as strain, temperature, acceleration, pressure, and vibrations. The monitoring station can be positioned tens of kilometers away from the measuring points, lowering the costs and the complexity of the system. This paper describes tests on a sensor, based on FBG technology, developed specifically for detecting damages of pipeline due to illegal activities (drilling of the pipes), that can be integrated into a smart monitoring chain.

Generic Raman-based calibration models enabling real-time monitoring of cell culture bioreactors.

PubMed

Mehdizadeh, Hamidreza; Lauri, David; Karry, Krizia M; Moshgbar, Mojgan; Procopio-Melino, Renee; Drapeau, Denis

2015-01-01

Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration. © 2015 American Institute of Chemical Engineers.

MARVEL: A knowledge-based productivity enhancement tool for real-time multi-mission and multi-subsystem spacecraft operations

NASA Astrophysics Data System (ADS)

Schwuttke, Ursula M.; Veregge, John, R.; Angelino, Robert; Childs, Cynthia L.

1990-10-01

The Monitor/Analyzer of Real-time Voyager Engineering Link (MARVEL) is described. It is the first automation tool to be used in an online mode for telemetry monitoring and analysis in mission operations. MARVEL combines standard automation techniques with embedded knowledge base systems to simultaneously provide real time monitoring of data from subsystems, near real time analysis of anomaly conditions, and both real time and non-real time user interface functions. MARVEL is currently capable of monitoring the Computer Command Subsystem (CCS), Flight Data Subsystem (FDS), and Attitude and Articulation Control Subsystem (AACS) for both Voyager spacecraft, simultaneously, on a single workstation. The goal of MARVEL is to provide cost savings and productivity enhancement in mission operations and to reduce the need for constant availability of subsystem expertise.

Chemical Sensor Platform for Non-Invasive Monitoring of Activity and Dehydration

PubMed Central

Solovei, Dmitry; Žák, Jaromír; Majzlíková, Petra; Sedláček, Jiří; Hubálek, Jaromír

2015-01-01

A non-invasive solution for monitoring of the activity and dehydration of organisms is proposed in the work. For this purpose, a wireless standalone chemical sensor platform using two separate measurement techniques has been developed. The first approach for activity monitoring is based on humidity measurement. Our solution uses new humidity sensor based on a nanostructured TiO2 surface for sweat rate monitoring. The second technique is based on monitoring of potassium concentration in urine. High level of potassium concentration denotes clear occurrence of dehydration. Furthermore, a Wireless Body Area Network (WBAN) was developed for this sensor platform to manage data transfer among devices and the internet. The WBAN coordinator controls the sensor devices and collects and stores the measured data. The collected data is particular to individuals and can be shared with physicians, emergency systems or athletes' coaches. Long-time monitoring of activity and potassium concentration in urine can help maintain the appropriate water intake of elderly people or athletes and to send warning signals in the case of near dehydration. The created sensor system was calibrated and tested in laboratory and real conditions as well. The measurement results are discussed. PMID:25594591

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.

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.

An energy-efficient communication method based on the relationships between biological signals for ubiquitous health monitoring.

PubMed

Kwon, Hyok Chon; Na, Doosu; Ko, Byung Geun; Lee, Songjun

2008-01-01

Wireless sensor networks have been studied in the area of intelligent transportation systems, disaster perception, environment monitoring, ubiquitous healthcare, home network, and so on. For the ubiquitous healthcare, the previous systems collect the sensed health related data at portable devices without regard to correlations of various biological signals to determine the health conditions. It is not the energy-efficient method to gather a lot of information into a specific node to decide the health condition. Since the biological signals are related with each other to estimate certain body condition, it is necessary to be collected selectively by their relationship for energy efficiency of the networked nodes. One of researches about low power consumption is the reduction of the amount of packet transmission. In this paper, a health monitoring system, which allows the transmission of the reduced number of packets by means of setting the routing path considered the relations of biological signals, is proposed.

Radiation-Tolerance Assessment of a Redundant Wireless Device

NASA Astrophysics Data System (ADS)

Huang, Q.; Jiang, J.

2018-01-01

This paper presents a method to evaluate radiation-tolerance without physical tests for a commercial off-the-shelf (COTS)-based monitoring device for high level radiation fields, such as those found in post-accident conditions in a nuclear power plant (NPP). This paper specifically describes the analysis of radiation environment in a severe accident, radiation damages in electronics, and the redundant solution used to prolong the life of the system, as well as the evaluation method for radiation protection and the analysis method of system reliability. As a case study, a wireless monitoring device with redundant and diversified channels is evaluated by using the developed method. The study results and system assessment data show that, under the given radiation condition, performance of the redundant device is more reliable and more robust than those non-redundant devices. The developed redundant wireless monitoring device is therefore able to apply in those conditions (up to 10 M Rad (Si)) during a severe accident in a NPP.

IoT based Growth Monitoring System of Guava (Psidium guajava L.) Fruits

NASA Astrophysics Data System (ADS)

Slamet, W.; Irham, N. M.; Sutan, M. S. A.

2018-05-01

Growth monitoring of plant is important especially to evaluate the influence of environment or growing condition on its productivity. One way to monitor the plant growth is by measuring the radial growth (i.e., the change of circumference) of certain part of plant such as trunk, branch, and fruit. In this study we develop an internet of things (IoT) based monitoring system of radial growth of plant using a low-cost optoelectronic sensor. The system was applied to monitor radial growth of guava fruits (Psidium guajava L.). The principle of the developed sensor is based on the optoelectronic sensor which detects alternating white and black narrow bar printed on reflective tapes. Reflective tape was installed encircling the fruit. The movement of reflective tapes will follow the radial growth of the fruit so that the infrared sensor on the optoelectronic would response reflective tapes movement. This device is designed to measure object continuously and long-term monitor with minimum maintenance. The data collected by the sensors are then sent to the server and also can be monitored in real-time. Based on field test, at current stage, the developed sensor could measure the radial growth of the fruits with a maximum error 2 mm. In term of data transfer, the success rate of the developed system was 97.54%. The result indicated that the developed system can be used as an effective tool for growth monitoring of plant.

Unintended changes in cognition, mood, and behavior arising from cell-based interventions for neurological conditions: ethical challenges.

PubMed

Duggan, P S; Siegel, A W; Blass, D M; Bok, H; Coyle, J T; Faden, R; Finkel, J; Gearhart, J D; Greely, H T; Hillis, A; Hoke, A; Johnson, R; Johnston, M; Kahn, J; Kerr, D; King, P; Kurtzberg, J; Liao, S M; McDonald, J W; McKhann, G; Nelson, K B; Rao, M; Regenberg, A; Smith, K; Solter, D; Song, H; Sugarman, J; Traystman, R J; Vescovi, A; Yanofski, J; Young, W; Mathews, D J H

2009-05-01

The prospect of using cell-based interventions (CBIs) to treat neurological conditions raises several important ethical and policy questions. In this target article, we focus on issues related to the unique constellation of traits that characterize CBIs targeted at the central nervous system. In particular, there is at least a theoretical prospect that these cells will alter the recipients' cognition, mood, and behavior-brain functions that are central to our concept of the self. The potential for such changes, although perhaps remote, is cause for concern and careful ethical analysis. Both to enable better informed consent in the future and as an end in itself, we argue that early human trials of CBIs for neurological conditions must monitor subjects for changes in cognition, mood, and behavior; further, we recommend concrete steps for that monitoring. Such steps will help better characterize the potential risks and benefits of CBIs as they are tested and potentially used for treatment.

A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

di, L.; Yang, Z.

2009-12-01

Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the adjustment of NASS survey data. This presentation will discuss the architecture, Earth observation data, and the crop progress model used in the decision support system.

40 CFR 63.1258 - Monitoring Requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... new operating scenario is implemented based on process knowledge and representative operating data... specified for control scenarios in Table 4 of this subpart and in paragraphs (b)(1)(ii) through (xi) of this.... The minimum scrubber flowrate or pressure drop shall be based on the conditions anticipated under...

Potential for DNA-based ID of Great Lakes fauna: Species inventories vs. barcode libraries

EPA Science Inventory

DNA-based identification of mixed-organism samples offers the potential to greatly reduce the need for resource-intensive morphological identification, which would be of value both to biotic condition assessment and non-native species early-detection monitoring. However the abil...

The Effects of Continuous Vs. Intermittent Self-Monitoring on the Duration and Magnitude of Behavior Change.

ERIC Educational Resources Information Center

Schayer, Laurel L.; Schroeder, Harold E.

Continuous self-monitoring (CSM) was compared with a demand characteristics control condition (non self-monitoring), with intermittent self-monitoring (ISM) and with another control condition. It was predicted that both self-monitoring conditions would produce effects over and above the demand characteristics inherent in the self-monitoring…

Total On-line Access Data System (TOADS): Phase II Final Report for the Period August 2002 - August 2004

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

Yuracko, K. L.; Parang, M.; Landguth, D. C.

2004-09-13

TOADS (Total On-line Access Data System) is a new generation of real-time monitoring and information management system developed to support unattended environmental monitoring and long-term stewardship of U.S. Department of Energy facilities and sites. TOADS enables project managers, regulators, and stakeholders to view environmental monitoring information in realtime over the Internet. Deployment of TOADS at government facilities and sites will reduce the cost of monitoring while increasing confidence and trust in cleanup and long term stewardship activities. TOADS: Reliably interfaces with and acquires data from a wide variety of external databases, remote systems, and sensors such as contaminant monitors, areamore » monitors, atmospheric condition monitors, visual surveillance systems, intrusion devices, motion detectors, fire/heat detection devices, and gas/vapor detectors; Provides notification and triggers alarms as appropriate; Performs QA/QC on data inputs and logs the status of instruments/devices; Provides a fully functional data management system capable of storing, analyzing, and reporting on data; Provides an easy-to-use Internet-based user interface that provides visualization of the site, data, and events; and Enables the community to monitor local environmental conditions in real time. During this Phase II STTR project, TOADS has been developed and successfully deployed for unattended facility, environmental, and radiological monitoring at a Department of Energy facility.« less

Monitoring the condition of natural resources in US national parks.

PubMed

Fancy, S G; Gross, J E; Carter, S L

2009-04-01

The National Park Service has developed a long-term ecological monitoring program for 32 ecoregional networks containing more than 270 parks with significant natural resources. The monitoring program assists park managers in developing a broad-based understanding of the status and trends of park resources as a basis for making decisions and working with other agencies and the public for the long-term protection of park ecosystems. We found that the basic steps involved in planning and designing a long-term ecological monitoring program were the same for a range of ecological systems including coral reefs, deserts, arctic tundra, prairie grasslands, caves, and tropical rainforests. These steps involve (1) clearly defining goals and objectives, (2) compiling and summarizing existing information, (3) developing conceptual models, (4) prioritizing and selecting indicators, (5) developing an overall sampling design, (6) developing monitoring protocols, and (7) establishing data management, analysis, and reporting procedures. The broad-based, scientifically sound information obtained through this systems-based monitoring program will have multiple applications for management decision-making, research, education, and promoting public understanding of park resources. When combined with an effective education program, monitoring results can contribute not only to park issues, but also to larger quality-of-life issues that affect surrounding communities and can contribute significantly to the environmental health of the nation.

Body-monitoring with photonic textiles: a reflective heartbeat sensor based on polymer optical fibres

PubMed Central

Braun, Fabian; Ferrario, Damien; Rossi, René M.; Scheel-Sailer, Anke; Wolf, Martin; Bona, Gian-Luca; Hufenus, Rudolf; Scherer, Lukas J.

2017-01-01

Knowledge of an individual's skin condition is important for pressure ulcer prevention. Detecting early changes in skin through perfusion, oxygen saturation values, and pressure on tissue and subsequent therapeutic intervention could increase patients' quality of life drastically. However, most existing sensing options create additional risk of ulcer development due to further pressure on and chafing of the skin. Here, as a first component, we present a flexible, photonic textile-based sensor for the continuous monitoring of the heartbeat and blood flow. Polymer optical fibres (POFs) are melt-spun continuously and characterized optically and mechanically before being embroidered. The resulting sensor shows flexibility when embroidered into a moisture-wicking fabric, and withstands disinfection with hospital-type laundry cycles. Additionally, the new sensor textile shows a lower static coefficient of friction (COF) than conventionally used bedsheets in both dry and sweaty conditions versus a skin model. Finally, we demonstrate the functionality of our sensor by measuring the heartbeat at the forehead in reflection mode and comparing it with commercial finger photoplethysmography for several subjects. Our results will allow the development of flexible, individualized, and fully textile-integrated wearable sensors for sensitive skin conditions and general long-term monitoring of patients with risk for pressure ulcer. PMID:28275123

Body-monitoring with photonic textiles: a reflective heartbeat sensor based on polymer optical fibres.

PubMed

Quandt, Brit M; Braun, Fabian; Ferrario, Damien; Rossi, René M; Scheel-Sailer, Anke; Wolf, Martin; Bona, Gian-Luca; Hufenus, Rudolf; Scherer, Lukas J; Boesel, Luciano F

2017-03-01

Knowledge of an individual's skin condition is important for pressure ulcer prevention. Detecting early changes in skin through perfusion, oxygen saturation values, and pressure on tissue and subsequent therapeutic intervention could increase patients' quality of life drastically. However, most existing sensing options create additional risk of ulcer development due to further pressure on and chafing of the skin. Here, as a first component, we present a flexible, photonic textile-based sensor for the continuous monitoring of the heartbeat and blood flow. Polymer optical fibres (POFs) are melt-spun continuously and characterized optically and mechanically before being embroidered. The resulting sensor shows flexibility when embroidered into a moisture-wicking fabric, and withstands disinfection with hospital-type laundry cycles. Additionally, the new sensor textile shows a lower static coefficient of friction (COF) than conventionally used bedsheets in both dry and sweaty conditions versus a skin model. Finally, we demonstrate the functionality of our sensor by measuring the heartbeat at the forehead in reflection mode and comparing it with commercial finger photoplethysmography for several subjects. Our results will allow the development of flexible, individualized, and fully textile-integrated wearable sensors for sensitive skin conditions and general long-term monitoring of patients with risk for pressure ulcer. © 2017 The Author(s).

The Implementation Internet of Things(IoT) Technology in Real Time Monitoring of Electrical Quantities

NASA Astrophysics Data System (ADS)

Despa, D.; Nama, G. F.; Muhammad, M. A.; Anwar, K.

2018-04-01

Electrical quantities such as Voltage, Current, Power, Power Factor, Energy, and Frequency in electrical power system tends to fluctuate, as a result of load changes, disturbances, or other abnormal states. The change-state in electrical quantities should be identify immediately, otherwise it can lead to serious problem for whole system. Therefore a necessity is required to determine the condition of electricity change-state quickly and appropriately in order to make effective decisions. Online monitoring of power distribution system based on Internet of Things (IoT) technology was deploy and implemented on Department of Mechanical Engineering University of Lampung (Unila), especially at three-phase main distribution panel H-building. The measurement system involve multiple sensors such current sensors and voltage sensors, while data processing conducted by Arduino, the measurement data stored in to the database server and shown in a real-time through a web-based application. This measurement system has several important features especially for realtime monitoring, robust data acquisition and logging, system reporting, so it will produce an important information that can be used for various purposes of future power analysis such estimation and planning. The result of this research shown that the condition of electrical power system at H-building performed unbalanced load, which often leads to drop-voltage condition

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

Systems and methods of monitoring acoustic pressure to detect a flame condition in a gas turbine

DOEpatents

Ziminsky, Willy Steve [Simpsonville, SC; Krull, Anthony Wayne [Anderson, SC; Healy, Timothy Andrew , Yilmaz, Ertan

2011-05-17

A method may detect a flashback condition in a fuel nozzle of a combustor. The method may include obtaining a current acoustic pressure signal from the combustor, analyzing the current acoustic pressure signal to determine current operating frequency information for the combustor, and indicating that the flashback condition exists based at least in part on the current operating frequency information.

Personnel reliability impact on petrochemical facilities monitoring system's failure skipping probability

NASA Astrophysics Data System (ADS)

Kostyukov, V. N.; Naumenko, A. P.

2017-08-01

The paper dwells upon urgent issues of evaluating impact of actions conducted by complex technological systems operators on their safe operation considering application of condition monitoring systems for elements and sub-systems of petrochemical production facilities. The main task for the research is to distinguish factors and criteria of monitoring system properties description, which would allow to evaluate impact of errors made by personnel on operation of real-time condition monitoring and diagnostic systems for machinery of petrochemical facilities, and find and objective criteria for monitoring system class, considering a human factor. On the basis of real-time condition monitoring concepts of sudden failure skipping risk, static and dynamic error, monitoring systems, one may solve a task of evaluation of impact that personnel's qualification has on monitoring system operation in terms of error in personnel or operators' actions while receiving information from monitoring systems and operating a technological system. Operator is considered as a part of the technological system. Although, personnel's behavior is usually a combination of the following parameters: input signal - information perceiving, reaction - decision making, response - decision implementing. Based on several researches on behavior of nuclear powers station operators in USA, Italy and other countries, as well as on researches conducted by Russian scientists, required data on operator's reliability were selected for analysis of operator's behavior at technological facilities diagnostics and monitoring systems. The calculations revealed that for the monitoring system selected as an example, the failure skipping risk for the set values of static (less than 0.01) and dynamic (less than 0.001) errors considering all related factors of data on reliability of information perception, decision-making, and reaction fulfilled is 0.037, in case when all the facilities and error probability are under control - not more than 0.027. In case when only pump and compressor units are under control, the failure skipping risk is not more than 0.022, when the probability of error in operator's action is not more than 0.011. The work output shows that on the basis of the researches results an assessment of operators' reliability can be made in terms of almost any kind of production, but considering only technological capabilities, since operators' psychological and general training considerable vary in different production industries. Using latest technologies of engineering psychology and design of data support systems, situation assessment systems, decision-making and responding system, as well as achievement in condition monitoring in various production industries one can evaluate hazardous condition skipping risk probability considering static, dynamic errors and human factor.

Monitoring and modeling conditions for regional shallow landslide initiation in the San Francisco Bay area, California

NASA Astrophysics Data System (ADS)

Collins, B. D.; Stock, J. D.; Godt, J. W.

2012-12-01

Intense winter storms in the San Francisco Bay area (SFBA) of California often trigger widespread landsliding, including debris flows that originate as shallow (<3 m) landslides. The strongest storms result in the loss of lives and millions of dollars in damage. Whereas precipitation-based rainfall intensity-duration landslide initiation thresholds are available for the SFBA, antecedent soil moisture conditions also play a major role in determining the likelihood for landslide generation from a given storm. Previous research has demonstrated that antecedent triggering conditions can be obtained using pre-storm precipitation thresholds (e.g., 250-400 mm of seasonal pre-storm rainfall). However, these types of thresholds do not account for the often cyclic pattern of wetting and drying that can occur early in the winter storm season (i.e. October - December), and which may skew the applicability of precipitation-only based thresholds. To account for these cyclic and constantly evolving soil moisture conditions, we have pursued methods to measure soil moisture directly and integrate these measurements into predictive analyses. During the past three years, the USGS installed a series of four subsurface hydrology monitoring stations in shallow landslide-prone locations of the SFBA to establish a soil-moisture-based antecedent threshold. In addition to soil moisture sensors, the monitoring stations are each equipped with piezometers to record positive pore water pressure that is likely required for shallow landslide initiation and a rain gauge to compare storm intensities with existing precipitation-based thresholds. Each monitoring station is located on a natural, grassy hillslope typically composed of silty sands, underlain by sandstone, sloping at approximately 30°, and with a depth to bedrock of approximately 1 meter - conditions typical of debris flow generation in the SFBA. Our observations reveal that various locations respond differently to seasonal precipitation, with some areas (e.g., Marin County) remaining at higher levels of saturation for longer periods of time during the winter compared to other areas (e.g., the East Bay Hills). In general, this coincides directly with relative precipitation totals in each region (i.e., Marin county typically receives more rainfall over a longer period of time than the East Bay). In those areas that are saturated for longer periods, the shallow landslide hazard is prolonged because these conditions are first needed for storm-related precipitation to subsequently generate positive pore pressure on the failure plane. Both piezometric field measurements and limit equilibrium slope stability analyses indicate that positive pore pressure is required for most shallow landslide failures to occur in the study regions. Based on measurements from two of the sites, our analyses further indicate that at least 2 kPa of pressure is required to trigger shallow landsliding. We measured this pressure at one of our sites in 2011, where more than 30 landslides, including several that mobilized into debris flows, occurred. Additional monitoring at these sites will be used to further constrain and refine antecedent moisture-based thresholds for shallow landslide initiation.

40 CFR 147.2925 - Standard permit conditions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... three years. (3) Monitoring records shall include: (i) Date, exact place and time of sampling or... document and all attachments and that, based on my inquiry of those individuals immediately responsible for...

Characterization of cement-based materials using a reusable piezoelectric impedance-based sensor

NASA Astrophysics Data System (ADS)

Tawie, R.; Lee, H. K.

2011-08-01

This paper proposes a reusable sensor, which employs a piezoceramic (PZT) plate as an active sensing transducer, for non-destructive monitoring of cement-based materials based on the electromechanical impedance (EMI) sensing technique. The advantage of the sensor design is that the PZT can be easily removed from the set-up and re-used for repetitive tests. The applicability of the sensor was demonstrated for monitoring of the setting of cement mortar. EMI measurements were performed using an impedance analyzer and the transformation of the specimen from the plastic to solid state was monitored by automatically measuring the changes in the PZT conductance spectra with respect to curing time using the root mean square deviation (RMSD) algorithm. In another experiment, drying-induced moisture loss of a hardened mortar specimen at saturated surface dry (SSD) condition was measured, and monitored using the reusable sensor to establish a correlation between the RMSD values and moisture loss rate. The reusable sensor was also demonstrated for detecting progressive damages imparted on a mortar specimen attached with the sensor under several loading levels before allowing it to load to failure. Overall, the reusable sensor is an effective and efficient monitoring device that could possibly be used for field application in characterization of cement-based materials.

Study of nuclear medicine practices in Portugal from an internal dosimetry perspective.

PubMed

Bento, J; Teles, P; Neves, M; Santos, A I; Cardoso, G; Barreto, A; Alves, F; Guerreiro, C; Rodrigues, A; Santos, J A M; Capelo, C; Parafita, R; Martins, B

2012-05-01

Nuclear medicine practices involve the handling of a wide range of pharmaceuticals labelled with different radionuclides, for diagnostic and therapeutic purposes. This work intends to evaluate the potential risks of internal contamination of nuclear medicine staff in several Portuguese nuclear medicine services and to conclude about the requirement of a routine internal monitoring. A methodology proposed by the International Atomic Energy Agency (IAEA), providing a set of criteria to determine the need, or not, for an internal monitoring programme, was applied. The evaluation of the risk of internal contaminations in a given set of working conditions is based on the type and amount of radionuclides being handled, as well as the safety conditions with which they are manipulated. The application of the IAEA criteria showed that 73.1% of all the workers included in this study should be integrated in a routine monitoring programme for internal contaminations; more specifically, 100% of workers performing radioimmunoassay techniques should be monitored. This study suggests that a routine monitoring programme for internal exposures should be implemented in Portugal for most nuclear medicine workers.

Portable water quality monitoring system

NASA Astrophysics Data System (ADS)

Nizar, N. B.; Ong, N. R.; Aziz, M. H. A.; Alcain, J. B.; Haimi, W. M. W. N.; Sauli, Z.

2017-09-01

Portable water quality monitoring system was a developed system that tested varied samples of water by using different sensors and provided the specific readings to the user via short message service (SMS) based on the conditions of the water itself. In this water quality monitoring system, the processing part was based on a microcontroller instead of Lead and Copper Rule (LCR) machines to receive the results. By using four main sensors, this system obtained the readings based on the detection of the sensors, respectively. Therefore, users can receive the readings through SMS because there was a connection between Arduino Uno and GSM Module. This system was designed to be portable so that it would be convenient for users to carry it anywhere and everywhere they wanted to since the processor used is smaller in size compared to the LCR machines. It was also developed to ease the user to monitor and control the water quality. However, the ranges of the sensors' detection still a limitation in this study.

A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications

PubMed Central

Costa, Daniel G.; Collotta, Mario; Pau, Giovanni; Duran-Faundez, Cristian

2017-01-01

The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field. PMID:28067777

A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications.

PubMed

Costa, Daniel G; Collotta, Mario; Pau, Giovanni; Duran-Faundez, Cristian

2017-01-05

The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field.

Snow Cover Mapping and Ice Avalanche Monitoring from the Satellite Data of the Sentinels

NASA Astrophysics Data System (ADS)

Wang, S.; Yang, B.; Zhou, Y.; Wang, F.; Zhang, R.; Zhao, Q.

2018-04-01

In order to monitor ice avalanches efficiently under disaster emergency conditions, a snow cover mapping method based on the satellite data of the Sentinels is proposed, in which the coherence and backscattering coefficient image of Synthetic Aperture Radar (SAR) data (Sentinel-1) is combined with the atmospheric correction result of multispectral data (Sentinel-2). The coherence image of the Sentinel-1 data could be segmented by a certain threshold to map snow cover, with the water bodies extracted from the backscattering coefficient image and removed from the coherence segment result. A snow confidence map from Sentinel-2 was used to map the snow cover, in which the confidence values of the snow cover were relatively high. The method can make full use of the acquired SAR image and multispectral image under emergency conditions, and the application potential of Sentinel data in the field of snow cover mapping is exploited. The monitoring frequency can be ensured because the areas obscured by thick clouds are remedied in the monitoring results. The Kappa coefficient of the monitoring results is 0.946, and the data processing time is less than 2 h, which meet the requirements of disaster emergency monitoring.

Zebrafish Transgenic Line huORFZ Is an Effective Living Bioindicator for Detecting Environmental Toxicants

PubMed Central

Chu, Chien; Li, Hong-Ping; Tsai, Huai-Jen

2014-01-01

Reliable animal models are invaluable for monitoring the extent of pollution in the aquatic environment. In this study, we demonstrated the potential of huORFZ, a novel transgenic zebrafish line that harbors a human upstream open reading frame of the chop gene fused with GFP reporter, as an animal model for monitoring environmental pollutants and stress-related cellular processes. When huORFZ embryos were kept under normal condition, no leaked GFP signal could be detected. When treated with hazardous chemicals, including heavy metals and endocrine-disrupting chemicals near their sublethal concentrations (LC50), huORFZ embryos exhibited different tissue-specific GFP expression patterns. For further analysis, copper (Cu2+), cadmium (Cd2+) and Chlorpyrifos were applied. Cu2+ triggered GFP responses in skin and muscle, whereas Cd2+ treatment triggered GFP responses in skin, olfactory epithelium and pronephric ducts. Moreover, fluorescence intensity, as exhibited by huORFZ embryos, was dose-dependent. After surviving treated embryos were returned to normal condition, survival rates, as well as TUNEL signals, returned to pretreatment levels with no significant morphological defects observed. Such results indicated the reversibility of treatment conditions used in this study, as long as embryos survived such conditions. Notably, GFP signals decreased along with recovery, suggesting that GFP signaling of huORFZ embryos likely reflected the overall physiological condition of the individual. To examine the performance of the huORFZ line under real-world conditions, we placed huORFZ embryos in different river water samples. We found that the huORFZ embryos correctly detected the presence of various kinds of pollutants. Based on these findings, we concluded that such uORFchop-based system can be integrated into a first-line water alarm system monitoring the discharge of hazardous pollutants. PMID:24594581

Multi-Fibre Optode Microsensors: affordable designs for monitoring oxygen in soils under varying environmental conditions

NASA Astrophysics Data System (ADS)

Rezanezhad, F.; Milojevic, T.; Parsons, C. T.; Smeaton, C. M.; Van Cappellen, P.

2017-12-01

Molecular oxygen (O2) measurements in field and laboratory soil and sediment systems provide useful insight into the biogeochemical functioning of natural environments. However, monitoring soil and sediment O2 is often challenging due to high costs, analyte consumption, and limited customizability and durability of existing O2 sensors. To meet this challenge, an in-house luminescence-based Multi Fibre Optode (MuFO) microsensor system was developed to monitor O2 levels under changing moisture and temperature regimes. The design is simplified by the use of a basic DSLR camera, LED light and fibre optic cables. The technique is based on O2 quenching the luminescent light intensity emitted from a luminophore (platinum(II) meso-tetra(pentafluorophenyl)porphyrin, PtTFPP) that is dip-coated onto the tips of the fibre optic cables, where increasing O2 corresponds to decreasing light intensity, based on the classic Stern-Volmer relationship. High-resolution digital images of the sensor-emitted light are then converted into % O2 saturation. The method was successfully tested in two artificial soil (20% peat, 80% sand) column experiments designed to simulate freeze-thaw cycles (temperature cycling from -10°C to 25°C) and water table fluctuations under controlled conditions. Depth distributions of O2 levels were monitored without interruption for multiple freeze-thaw and water table cycles. No degradation of optode performance or O2 signals were observed for the duration of the column experiments, which supports the long-term deployment of the microsensors for continuous O2 monitoring in field and laboratory settings. The technical specifications of the system are fair, with a detection limit of 0.2% O2 saturation. The main advantages of the MuFO system over commercial applications are the comparatively low cost ($1,800 USD; about ¼ the cost of commercial versions) and ease of customizability. The system has been further developed for near real-time monitoring in the field, where the imaged data is transmitted remotely using a photo-logging system. The MuFO sensor is currently being tested at a Southern Ontario field site in a year-long experiment. Here we present the field and laboratory results of soil O2 monitoring by this newly developed MuFO microsensor system under varying environmental conditions.

Graphite Based Electrode for ECG Monitoring: Evaluation under Freshwater and Saltwater Conditions.

PubMed

Thap, Tharoeun; Yoon, Kwon-Ha; Lee, Jinseok

2016-04-15

We proposed new electrodes that are applicable for electrocardiogram (ECG) monitoring under freshwater- and saltwater-immersion conditions. Our proposed electrodes are made of graphite pencil lead (GPL), a general-purpose writing pencil. We have fabricated two types of electrode: a pencil lead solid type (PLS) electrode and a pencil lead powder type (PLP) electrode. In order to assess the qualities of the PLS and PLP electrodes, we compared their performance with that of a commercial Ag/AgCl electrode, under a total of seven different conditions: dry, freshwater immersion with/without movement, post-freshwater wet condition, saltwater immersion with/without movement, and post-saltwater wet condition. In both dry and post-freshwater wet conditions, all ECG-recorded PQRST waves were clearly discernible, with all types of electrodes, Ag/AgCl, PLS, and PLP. On the other hand, under the freshwater- and saltwater-immersion conditions with/without movement, as well as post-saltwater wet conditions, we found that the proposed PLS and PLP electrodes provided better ECG waveform quality, with significant statistical differences compared with the quality provided by Ag/AgCl electrodes.

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.

Laser based structural health monitoring for civil, mechanical, and aerospace systems

NASA Astrophysics Data System (ADS)

Sohn, Hoon

2012-04-01

This paper provides an overview of ongoing laser ultrasonics based structural health monitoring (SHM) activities being performed by the author. Particular focus is given to (1) the development of a fully noncontact laser ultrasonic system that can easily visualize defects with high spatial resolution, (2) laser based wireless power and data transmission schemes for remote guided waves and impedance measurements, (3) minimization of false alarms due to varying operational and environmental conditions, and (4) extension to embedded laser ultrasonic excitation and sensing. SHM examples ranging from bridges to airplanes, as well as nuclear power plants, high-speed rails and wind turbines are also presented.

Spectroscopic On-Line Monitoring of Cu/W Contacts Erosion in HVCBs Using Optical-Fibre Based Sensor and Chromatic Methodology

PubMed Central

Wang, Zhixiang; Jones, Gordon R.; Spencer, Joseph W.; Wang, Xiaohua; Rong, Mingzhe

2017-01-01

Contact erosion is one of the most crucial factors affecting the electrical service lifetime of high-voltage circuit breakers (HVCBs). On-line monitoring the contacts’ erosion degree is increasingly in demand for the sake of condition based maintenance to guarantee the functional operation of HVCBs. A spectroscopic monitoring system has been designed based upon a commercial 245 kV/40 kA SF6 live tank circuit breaker with copper–tungsten (28 wt % and 72 wt %) arcing contacts at atmospheric SF6 pressure. Three optical-fibre based sensors are used to capture the time-resolved spectra of arcs. A novel approach using chromatic methods to process the time-resolved spectral signal has been proposed. The processed chromatic parameters have been interpreted to show that the time variation of spectral emission from the contact material and quenching gas are closely correlated to the mass loss and surface degradation of the plug arcing contact. The feasibility of applying this method to online monitoring of contact erosion is indicated. PMID:28272295

Spectroscopic On-Line Monitoring of Cu/W Contacts Erosion in HVCBs Using Optical-Fibre Based Sensor and Chromatic Methodology.

PubMed

Wang, Zhixiang; Jones, Gordon R; Spencer, Joseph W; Wang, Xiaohua; Rong, Mingzhe

2017-03-06

Contact erosion is one of the most crucial factors affecting the electrical service lifetime of high-voltage circuit breakers (HVCBs). On-line monitoring the contacts' erosion degree is increasingly in demand for the sake of condition based maintenance to guarantee the functional operation of HVCBs. A spectroscopic monitoring system has been designed based upon a commercial 245 kV/40 kA S F 6 live tank circuit breaker with copper-tungsten (28 wt % and 72 wt %) arcing contacts at atmospheric S F 6 pressure. Three optical-fibre based sensors are used to capture the time-resolved spectra of arcs. A novel approach using chromatic methods to process the time-resolved spectral signal has been proposed. The processed chromatic parameters have been interpreted to show that the time variation of spectral emission from the contact material and quenching gas are closely correlated to the mass loss and surface degradation of the plug arcing contact. The feasibility of applying this method to online monitoring of contact erosion is indicated.

Electromechanical impedance-based health diagnosis for tendon and anchorage zone in a nuclear containment structure

NASA Astrophysics Data System (ADS)

Min, Jiyoung; Shim, Hyojin; Yun, Chung-Bang

2012-04-01

For a nuclear containment structure, the structural health monitoring is essential because of its high potential risk and grave social impact. In particular, the tendon and anchorage zone are to be monitored because they are under high tensile or compressive stress. In this paper, a method to monitor the tendon force and the condition of the anchorage zone is presented by using the impedance-based health diagnosis system. First, numerical simulations were conducted for cases with various loose tensile forces on the tendon as well as damages on the bearing plate and concrete structure. Then, experimental studies were carried out on a scaled model of the anchorage system. The relationship between the loose tensile force and the impedance-based damage index was analyzed by a regression analysis. When a structure gets damaged, the damage index increases so that the status of damage can be identified. The results of the numerical and experimental studies indicate a big potential of the proposed impedance-based method for monitoring the tendon and anchorage system.

Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring

PubMed Central

Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K. K.

2018-01-01

The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor. PMID:29360749

Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring.

PubMed

Wei, Peng; Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K K

2018-01-23

The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), and oxidants (O x ) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO₂ and ozone on a newly introduced oxidant sensor.

Comparison of a brain-based adaptive system and a manual adaptable system for invoking automation.

PubMed

Bailey, Nathan R; Scerbo, Mark W; Freeman, Frederick G; Mikulka, Peter J; Scott, Lorissa A

2006-01-01

Two experiments are presented examining adaptive and adaptable methods for invoking automation. Empirical investigations of adaptive automation have focused on methods used to invoke automation or on automation-related performance implications. However, no research has addressed whether performance benefits associated with brain-based systems exceed those in which users have control over task allocations. Participants performed monitoring and resource management tasks as well as a tracking task that shifted between automatic and manual modes. In the first experiment, participants worked with an adaptive system that used their electroencephalographic signals to switch the tracking task between automatic and manual modes. Participants were also divided between high- and low-reliability conditions for the system-monitoring task as well as high- and low-complacency potential. For the second experiment, participants operated an adaptable system that gave them manual control over task allocations. Results indicated increased situation awareness (SA) of gauge instrument settings for individuals high in complacency potential using the adaptive system. In addition, participants who had control over automation performed more poorly on the resource management task and reported higher levels of workload. A comparison between systems also revealed enhanced SA of gauge instrument settings and decreased workload in the adaptive condition. The present results suggest that brain-based adaptive automation systems may enhance perceptual level SA while reducing mental workload relative to systems requiring user-initiated control. Potential applications include automated systems for which operator monitoring performance and high-workload conditions are of concern.

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.

Multiple Sensing Application on Wireless Sensor Network Simulation using NS3

NASA Astrophysics Data System (ADS)

Kurniawan, I. F.; Bisma, R.

2018-01-01

Hardware enhancement provides opportunity to install various sensor device on single monitoring node which then enables users to acquire multiple data simultaneously. Constructing multiple sensing application in NS3 is a challenging task since numbers of aspects such as wireless communication, packet transmission pattern, and energy model must be taken into account. Despite of numerous types of monitoring data available, this study only considers two types such as periodic, and event-based data. Periodical data will generate monitoring data follows configured interval, while event-based transmit data when certain determined condition is met. Therefore, this study attempts to cover mentioned aspects in NS3. Several simulations are performed with different number of nodes on arbitrary communication scheme.

A low-cost microcontroller-based system to monitor crop temperature and water status

USDA-ARS?s Scientific Manuscript database

A prototype microcontroller-based system was developed to automate the measurement and recording of soil-moisture status and canopy-, air-, and soil-temperature levels in cropped fields. Measurements of these conditions within the cropping system are often used to assess plant stress, and can assis...

Potential for DNA-based identification of Great Lakes fauna: Match and mismatch between taxa inventories and DNA barcode libraries

EPA Science Inventory

DNA-based identification of mixed-organism samples offers the potential to greatly reduce the need for resource-intensive morphological identification, which would be of value both to biotic condition assessment and non-native species early-detection monitoring. However, the abi...

Recommendations for strengthening the infrared technology component of any condition monitoring program

NASA Astrophysics Data System (ADS)

Nicholas, Jack R., Jr.; Young, R. K.

1999-03-01

This presentation provides insights of a long term 'champion' of many condition monitoring technologies and a Level III infra red thermographer. The co-authors present recommendations based on their observations of infra red and other components of predictive, condition monitoring programs in manufacturing, utility and government defense and energy activities. As predictive maintenance service providers, trainers, informal observers and formal auditors of such programs, the co-authors provide a unique perspective that can be useful to practitioners, managers and customers of advanced programs. Each has over 30 years experience in the field of machinery operation, maintenance, and support the origins of which can be traced to and through the demanding requirements of the U.S. Navy nuclear submarine forces. They have over 10 years each of experience with programs in many different countries on 3 continents. Recommendations are provided on the following: (1) Leadership and Management Support (For survival); (2) Life Cycle View (For establishment of a firm and stable foundation for a program); (3) Training and Orientation (For thermographers as well as operators, managers and others); (4) Analyst Flexibility (To innovate, explore and develop their understanding of machinery condition); (5) Reports and Program Justification (For program visibility and continued expansion); (6) Commitment to Continuous Improvement of Capability and Productivity (Through application of updated hardware and software); (7) Mutual Support by Analysts (By those inside and outside of the immediate organization); (8) Use of Multiple Technologies and System Experts to Help Define Problems (Through the use of correlation analysis of data from up to 15 technologies. An example correlation analysis table for AC and DC motors is provided.); (9) Root Cause Analysis (Allows a shift from reactive to proactive stance for a program); (10) Master Equipment Identification and Technology Application (To place the condition monitoring program in perspective); (11) Use of procedures for Predictive, Condition Monitoring and maintenance in general (To get consistent results); (12) Developing a scheme for predictive, condition monitoring personnel qualification and certification (To provide a career path and incentive to advance skill level and value to the company); (13) Analyst Assignment to Technologies and Related Duties (To make intelligent use of the skills of individuals assigned); (14) Condition Monitoring Analyst Selection Criteria (Key attributes for success are mentioned.); (15) Design and Modification to Support Monitoring (For old and new machinery to facilitate data acquisition); (16) Establishment of a Museum of Components and Samples Pulled from Service for Cause (For orientation and awareness training of operators and managers and exchange of information between analysts); (17) Goals (To promote a proactive program approach for machinery condition improvement).

Sentinel-1 and ground-based sensors for a continuous monitoring of the Corvara landslide kinematic (South Tirol, Italy)

NASA Astrophysics Data System (ADS)

Schlögel, Romy; Darvishi, Mehdi; Cuozzo, Giovanni; Kofler, Christian; Rutzinger, Martin; Zieher, Thomas; Toschi, Isabella; Remondino, Fabio

2017-04-01

Sentinel-1 mission allows us to have Synthetic Aperture Radar (SAR) acquisitions over large areas every 6 days with spatial resolution of 20 m. This new open-source generation of satellites has enhanced the capabilities for continuously studying earth surface changes. Over the past two decades, several studies have demonstrated the potential of Differential Synthetic Aperture Radar Interferometry (DInSAR) for detecting and quantifying land surface deformation. DInSAR limitations and challenges are linked to the SAR properties and the field conditions (especially in Alpine environments) leading to spatial and temporal decorrelation of the SAR signal. High temporal decorrelation can be caused by changes in vegetation (particularly in non-urban areas), atmospheric conditions or high ground surface velocity. In this study, kinematics of the complex and vegetated Corvara landslide, situated in Val Badia (South Tirol, Italy), are monitored by a network of 3 permanent and 13 monthly Differential Global Positioning System (DGPS) stations. The slope displacement rates are found to be highly unsteady and reach several meters a year. This analysis focuses on evaluating the limitations of Sentinel-1 imagery processed with Small Baseline Subset (SBAS) technique in comparison to ground-based measurements for assessing the landslide kinematic linked to meteorological conditions. Selecting some particular acquisitions, coherence thresholds and unwrapping processes gives various results in terms of reliability and accuracy supporting the understanding of the landslide velocity field. The evolution of the coherence and phase signals are studied according to the changing field conditions and the monitored ground-based displacements. DInSAR deformation maps and residual topographic heights are finally compared with difference of high resolution Digital Elevation Models at local scale. This research is conducted within the project LEMONADE (http://lemonade.mountainresearch.at) funded by the Euregio Science Fund.

A National Crop Progress Monitoring System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Zhang, B.; Deng, M.; Yang, Z.

2011-12-01

Crop progress is an important piece of information for food security and agricultural commodities. Timely monitoring and reporting are mandated for the operation of agricultural statistical agencies. Traditionally, the weekly reporting issued by the National Agricultural Statistics Service (NASS) of the United States Department of Agriculture (USDA) is based on reports from the knowledgeable state and county agricultural officials and farmers. The results are spatially coarse and subjective. In this project, a remote-sensing-supported crop progress monitoring system is being developed intensively using the data and derived products from NASA Earth Observing satellites. Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 product - MOD09 (Surface Reflectance) is used for deriving daily normalized vegetation index (NDVI), vegetation condition index (VCI), and mean vegetation condition index (MVCI). Ratio change to previous year and multiple year mean can be also produced on demand. The time-series vegetation condition indices are further combined with the NASS' remote-sensing-derived Cropland Data Layer (CDL) to estimate crop condition and progress crop by crop. To facilitate the operational requirement and increase the accessibility of data and products by different users, each component of the system has being developed and implemented following open specifications under the Web Service reference model of Open Geospatial Consortium Inc. Sensor observations and data are accessed through Web Coverage Service (WCS), Web Feature Service (WFS), or Sensor Observation Service (SOS) if available. Products are also served through such open-specification-compliant services. For rendering and presentation, Web Map Service (WMS) is used. A Web-service based system is set up and deployed at dss.csiss.gmu.edu/NDVIDownload. Further development will adopt crop growth models, feed the models with remotely sensed precipitation and soil moisture information, and incorporate the model results with vegetation-index time series for crop progress stage estimation.

Techniques for monitoring and controlling yaw attitude of a GPS satellite

NASA Technical Reports Server (NTRS)

Lichten, Stephen M. (Inventor); Bar-Sever, Yoaz (Inventor); Zumberge, James (Inventor); Bertiger, William I. (Inventor); Muellerschoen, Ronald J. (Inventor); Wu, Sien-Chong (Inventor); Hurst, Kenneth (Inventor); Blewitt, Geoff (Inventor); Yunck, Thomas (Inventor); Thornton, Catherine (Inventor)

2001-01-01

Techniques for monitoring and controlling yawing of a GPS satellite in an orbit that has an eclipsing portion out of the sunlight based on the orbital conditions of the GPS satellite. In one embodiment, a constant yaw bias is generated in the attitude control system of the GPS satellite to control the yawing of the GPS satellite when it is in the shadow of the earth.

Intelligent Chemical Sensor Systems for In-space Safety Applications

NASA Technical Reports Server (NTRS)

Hunter, G. W.; Xu, J. C.; Neudeck, P. G.; Makel, D. B.; Ward, B.; Liu, C. C.

2006-01-01

Future in-space and lunar operations will require significantly improved monitoring and Integrated System Health Management (ISHM) throughout the mission. In particular, the monitoring of chemical species is an important component of an overall monitoring system for space vehicles and operations. For example, in leak monitoring of propulsion systems during launch, inspace, and on lunar surfaces, detection of low concentrations of hydrogen and other fuels is important to avoid explosive conditions that could harm personnel and damage the vehicle. Dependable vehicle operation also depends on the timely and accurate measurement of these leaks. Thus, the development of a sensor array to determine the concentration of fuels such as hydrogen, hydrocarbons, or hydrazine as well as oxygen is necessary. Work has been on-going to develop an integrated smart leak detection system based on miniaturized sensors to detect hydrogen, hydrocarbons, or hydrazine, and oxygen. The approach is to implement Microelectromechanical Systems (MEMS) based sensors incorporated with signal conditioning electronics, power, data storage, and telemetry enabling intelligent systems. The final sensor system will be self-contained with a surface area comparable to a postage stamp. This paper discusses the development of this "Lick and Stick" leak detection system and it s application to In-Space Transportation and other Exploration applications.

WEclMon - A simple and robust camera-based system to monitor Drosophila eclosion under optogenetic manipulation and natural conditions.

PubMed

Ruf, Franziska; Fraunholz, Martin; Öchsner, Konrad; Kaderschabek, Johann; Wegener, Christian

2017-01-01

Eclosion in flies and other insects is a circadian-gated behaviour under control of a central and a peripheral clock. It is not influenced by the motivational state of an animal, and thus presents an ideal paradigm to study the relation and signalling pathways between central and peripheral clocks, and downstream peptidergic regulatory systems. Little is known, however, about eclosion rhythmicity under natural conditions, and research into this direction is hampered by the physically closed design of current eclosion monitoring systems. We describe a novel open eclosion monitoring system (WEclMon) that allows the puparia to come into direct contact with light, temperature and humidity. We demonstrate that the system can be used both in the laboratory and outdoors, and shows a performance similar to commercial closed funnel-type monitors. Data analysis is semi-automated based on a macro toolset for the open imaging software Fiji. Due to its open design, the WEclMon is also well suited for optogenetic experiments. A small screen to identify putative neuroendocrine signals mediating time from the central clock to initiate eclosion showed that optogenetic activation of ETH-, EH and myosuppressin neurons can induce precocious eclosion. Genetic ablation of myosuppressin-expressing neurons did, however, not affect eclosion rhythmicity.

WEclMon – A simple and robust camera-based system to monitor Drosophila eclosion under optogenetic manipulation and natural conditions

PubMed Central

Ruf, Franziska; Fraunholz, Martin; Öchsner, Konrad; Kaderschabek, Johann

2017-01-01

Eclosion in flies and other insects is a circadian-gated behaviour under control of a central and a peripheral clock. It is not influenced by the motivational state of an animal, and thus presents an ideal paradigm to study the relation and signalling pathways between central and peripheral clocks, and downstream peptidergic regulatory systems. Little is known, however, about eclosion rhythmicity under natural conditions, and research into this direction is hampered by the physically closed design of current eclosion monitoring systems. We describe a novel open eclosion monitoring system (WEclMon) that allows the puparia to come into direct contact with light, temperature and humidity. We demonstrate that the system can be used both in the laboratory and outdoors, and shows a performance similar to commercial closed funnel-type monitors. Data analysis is semi-automated based on a macro toolset for the open imaging software Fiji. Due to its open design, the WEclMon is also well suited for optogenetic experiments. A small screen to identify putative neuroendocrine signals mediating time from the central clock to initiate eclosion showed that optogenetic activation of ETH-, EH and myosuppressin neurons can induce precocious eclosion. Genetic ablation of myosuppressin-expressing neurons did, however, not affect eclosion rhythmicity. PMID:28658318

Multisource Data-Based Integrated Agricultural Drought Monitoring in the Huai River Basin, China

NASA Astrophysics Data System (ADS)

Sun, Peng; Zhang, Qiang; Wen, Qingzhi; Singh, Vijay P.; Shi, Peijun

2017-10-01

Drought monitoring is critical for early warning of drought hazard. This study attempted to develop an integrated remote sensing drought monitoring index (IRSDI), based on meteorological data for 2003-2013 from 40 meteorological stations and soil moisture data from 16 observatory stations, as well as Moderate Resolution Imaging Spectroradiometer data using a linear trend detection method, and standardized precipitation evapotranspiration index. The objective was to investigate drought conditions across the Huai River basin in both space and time. Results indicate that (1) the proposed IRSDI monitors and describes drought conditions across the Huai River basin reasonably well in both space and time; (2) frequency of drought and severe drought are observed during April-May and July-September. The northeastern and eastern parts of Huai River basin are dominated by frequent droughts and intensified drought events. These regions are dominated by dry croplands, grasslands, and highly dense population and are hence more sensitive to drought hazards; (3) intensified droughts are detected during almost all months except January, August, October, and December. Besides, significant intensification of droughts is discerned mainly in eastern and western Huai River basin. The duration and regions dominated by intensified drought events would be a challenge for water resources management in view of agricultural and other activities in these regions in a changing climate.

Social importance enhances prospective memory: evidence from an event-based task.

PubMed

Walter, Stefan; Meier, Beat

2017-07-01

Prospective memory performance can be enhanced by task importance, for example by promising a reward. Typically, this comes at costs in the ongoing task. However, previous research has suggested that social importance (e.g., providing a social motive) can enhance prospective memory performance without additional monitoring costs in activity-based and time-based tasks. The aim of the present study was to investigate the influence of social importance in an event-based task. We compared four conditions: social importance, promising a reward, both social importance and promising a reward, and standard prospective memory instructions (control condition). The results showed enhanced prospective memory performance for all importance conditions compared to the control condition. Although ongoing task performance was slowed in all conditions with a prospective memory task when compared to a baseline condition with no prospective memory task, additional costs occurred only when both the social importance and reward were present simultaneously. Alone, neither social importance nor promising a reward produced an additional slowing when compared to the cost in the standard (control) condition. Thus, social importance and reward can enhance event-based prospective memory at no additional cost.

Interactive effects in transfer-appropriate processing for event-based prospective memory: the roles of effort, ongoing task, and PM cue properties.

PubMed

Abney, Drew H; McBride, Dawn M; Petrella, Samantha N

2013-10-01

Past studies (e.g., Marsh, Hicks, & Cook Journal of Experimental Psychology: Learning, Memory, and Cognition 31:68-75, 2005; Meiser & Schult European Journal of Cognitive Psychology 20:290-311, 2008) have shown that transfer-appropriate processing (TAP) effects in event-based prospective memory (PM) depend on the effort directed toward the ongoing task. In the present study, we addressed mixed findings from these studies and examined monitoring in TAP and transfer-inappropriate processing (TIP) conditions. In two experiments, a semantic or orthographic ongoing task was paired with a PM cue that either was matched in processing (TAP) or did not match in processing (TIP). Within each condition, effort was varied across trials. The results indicated that PM accuracy was higher in TAP than in TIP conditions, regardless of effort condition, supporting the findings reported by Meiser and Schult. Ex-Gaussian functions were fit to the mean reaction times (cf. Brewer Journal of Psychology 219:117-124, 2011) in order to examine monitoring across conditions. The analysis of distributional skew (τ parameter) showed sensitivity to ongoing task instructions and properties of the PM cues. These results support Meiser and Schult's suggestion that TIP conditions require more attentional processing, and they also afford novel discussion on the interactive effects of ongoing task condition, PM cue properties, and manipulations of effort.

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.

Passive in-home health and wellness monitoring: overview, value and examples.

PubMed

Alwan, Majd

2009-01-01

Modern sensor and communication technology, coupled with advances in data analysis and artificial intelligence techniques, is causing a paradigm shift in remote management and monitoring of chronic disease. In-home monitoring technology brings the added benefit of measuring individualized health status and reporting it to the care provider and caregivers alike, allowing timely and targeted preventive interventions, even in home and community based settings. This paper presents a paradigm for geriatric care based on monitoring older adults passively in their own living settings through placing sensors in their living environments or the objects they use. Activity and physiological data can be analyzed, archived and mined to detect indicators of early disease onset or changes in health conditions at various levels. Examples of monitoring systems are discussed and results from field evaluation pilot studies are summarized. The approach has shown great promise for a significant value proposition to all the stakeholders involved in caring for older adults. The paradigm would allow care providers to extend their services into the communities they serve.

Monitoring the corrosion process of reinforced concrete using BOTDA and FBG sensors.

PubMed

Mao, Jianghong; Chen, Jiayun; Cui, Lei; Jin, Weiliang; Xu, Chen; He, Yong

2015-04-15

Expansion and cracking induced by the corrosion of reinforcement concrete is the major factor in the failure of concrete durability. Therefore, monitoring of concrete cracking is critical for evaluating the safety of concrete structures. In this paper, we introduce a novel monitoring method combining Brillouin optical time domain analysis (BOTDA) and fiber Bragg grating (FBG), based on mechanical principles of concrete expansion cracking. BOTDA monitors concrete expansion and crack width, while FBG identifies the time and position of cracking. A water-pressure loading simulation test was carried out to determine the relationship between fiber strain, concrete expansion and crack width. An electrical accelerated corrosion test was also conducted to evaluate the ability of this novel sensor to monitor concrete cracking under practical conditions.

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.

Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

NASA Astrophysics Data System (ADS)

Jin, Seung-Seop; Jung, Hyung-Jo

2014-03-01

It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative study with conventional methods (i.e., fixed reference scheme) demonstrates the superior performance of the proposed method for structural damage detection.

Risk factors for post-transplant lymphoproliferative disorder after Thymoglobulin-conditioned hematopoietic cell transplantation.

PubMed

Kalra, Amit; Roessner, Cameron; Jupp, Jennifer; Williamson, Tyler; Tellier, Raymond; Chaudhry, Ahsan; Khan, Faisal; Taparia, Minakshi; Jimenez-Zepeda, Victor H; Stewart, Douglas A; Daly, Andrew; Storek, Jan

2018-01-01

Epstein-Barr virus (EBV)-induced post-transplant lymphoproliferative disorder (PTLD) occurs frequently when rabbit antithymocyte globulin (ATG) is used in hematopoietic cell transplant (HCT) conditioning. We retrospectively studied 554 patients undergoing ATG-conditioned myeloablative HCT. Strategies used to minimize mortality due to PTLD were either therapy of biopsy-diagnosed PTLD in the absence of EBV DNAemia monitoring (n = 266) or prompt therapy of presumed PTLD (based on clinical/radiologic signs and high EBV DNAemia, in the setting of weekly EBV DNAemia monitoring) (n = 199). Both strategies resulted in similar mortality due to PTLD (0.7% vs 1% at 2 years, P = .43) and similar overall survival (63% vs 67% at 2 years, P = .23) even though there was a trend toward higher PTLD incidence with the prompt therapy. Donor positive with recipient negative EBV (D+R-) serostatus was a risk factor for developing PTLD. Older patient age, HLA-mismatched donor, and graft-versus-host disease were not associated with increased risk of PTLD. In summary, in ATG-conditioned HCT, D+R- serostatus, but not older age, mismatched donor or GVHD is a risk factor for developing PTLD. EBV DNAemia monitoring may be a weak risk factor for developing/diagnosing PTLD; the monitoring coupled with prompt therapy does not improve survival. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Personalized Health Monitoring System for Managing Well-Being in Rural Areas.

PubMed

Nedungadi, Prema; Jayakumar, Akshay; Raman, Raghu

2017-12-14

Rural India lacks easy access to health practitioners and medical centers, depending instead on community health workers. In these areas, common ailments that are easy to manage with medicines, often lead to medical escalations and even fatalities due to lack of awareness and delayed diagnosis. The introduction of wearable health devices has made it easier to monitor health conditions and to connect doctors and patients in urban areas. However, existing initiatives have not succeeded in providing adequate health monitoring to rural and low-literate patients, as current methods are expensive, require consistent connectivity and expect literate users. Our design considerations address these concerns by providing low-cost medical devices connected to a low-cost health platform, along with personalized guidance based on patient physiological parameters in local languages, and alerts to medical practitioners in case of emergencies. This patient-centric integrated healthcare system is designed to manage the overall health of villagers with real-time health monitoring of patients, to offer guidance on preventive care, and to increase health awareness and self-monitoring at an affordable price. This personalized health monitoring system addresses the health-related needs in remote and rural areas by (1) empowering health workers in monitoring of basic health conditions for rural patients in order to prevent escalations, (2) personalized feedback regarding nutrition, exercise, diet, preventive Ayurveda care and yoga postures based on vital parameters and (3) reporting of patient data to the patient's health center with emergency alerts to doctor and patient. The system supports community health workers in the diagnostic procedure, management, and reporting of rural patients, and functions well even with only intermittent access to Internet.

Development of an integrated sensor module for a non-invasive respiratory monitoring system

NASA Astrophysics Data System (ADS)

Kang, Seok-Won; Chang, Keun-Shik

2013-09-01

A respiratory monitoring system has been developed for analyzing the carbon dioxide (CO2) and oxygen (O2) concentrations in the expired air using gas sensors. The data can be used to estimate some medical conditions, including diffusion capability of the lung membrane, oxygen uptake, and carbon dioxide output. For this purpose, a 3-way valve derived from a servomotor was developed, which operates synchronously with human respiratory signals. In particular, the breath analysis system includes an integrated sensor module for valve control, data acquisition through the O2 and CO2 sensors, and respiratory rate monitoring, as well as software dedicated to analysis of respiratory gasses. In addition, an approximation technique for experimental data based on Haar-wavelet-based decomposition is explored to remove noise as well as to reduce the file size of data for long-term monitoring.

Enhance wound healing monitoring through a thermal imaging based smartphone app

NASA Astrophysics Data System (ADS)

Yi, Steven; Lu, Minta; Yee, Adam; Harmon, John; Meng, Frank; Hinduja, Saurabh

2018-03-01

In this paper, we present a thermal imaging based app to augment traditional appearance based wound growth monitoring. Accurate diagnose and track of wound healing enables physicians to effectively assess, document, and individualize the treatment plan given to each wound patient. Currently, wounds are primarily examined by physicians through visual appearance and wound area. However, visual information alone cannot present a complete picture on a wound's condition. In this paper, we use a smartphone attached thermal imager and evaluate its effectiveness on augmenting visual appearance based wound diagnosis. Instead of only monitoring wound temperature changes on a wound, our app presents physicians a comprehensive measurements including relative temperature, wound healing thermal index, and wound blood flow. Through the rat wound experiments and by monitoring the integrated thermal measurements over 3 weeks of time frame, our app is able to show the underlying healing process through the blood flow. The implied significance of our app design and experiment includes: (a) It is possible to use a low cost smartphone attached thermal imager for added value on wound assessment, tracking, and treatment; and (b) Thermal mobile app can be used for remote wound healing assessment for mobile health based solution.

EEMD-Based Steady-State Indexes and Their Applications to Condition Monitoring and Fault Diagnosis of Railway Axle Bearings

PubMed Central

Fan, Wei; Tsui, Kwok-Leung; Lin, Jianhui

2018-01-01

Railway axle bearings are one of the most important components used in vehicles and their failures probably result in unexpected accidents and economic losses. To realize a condition monitoring and fault diagnosis scheme of railway axle bearings, three dimensionless steadiness indexes in a time domain, a frequency domain, and a shape domain are respectively proposed to measure the steady states of bearing vibration signals. Firstly, vibration data collected from some designed experiments are pre-processed by using ensemble empirical mode decomposition (EEMD). Then, the coefficient of variation is introduced to construct two steady-state indexes from pre-processed vibration data in a time domain and a frequency domain, respectively. A shape function is used to construct a steady-state index in a shape domain. At last, to distinguish normal and abnormal bearing health states, some guideline thresholds are proposed. Further, to identify axle bearings with outer race defects, a pin roller defect, a cage defect, and coupling defects, the boundaries of all steadiness indexes are experimentally established. Experimental results showed that the proposed condition monitoring and fault diagnosis scheme is effective in identifying different bearing health conditions. PMID:29495446

Advances in air quality prediction with the use of integrated systems

NASA Astrophysics Data System (ADS)

Dragani, R.; Benedetti, A.; Engelen, R. J.; Peuch, V. H.

2017-12-01

Recent years have seen the rise of global operational atmospheric composition forecasting systems for several applications including climate monitoring, provision of boundary conditions for regional air quality forecasting, energy sector applications, to mention a few. Typically, global forecasts are provided in the medium-range up to five days ahead and are initialized with an analysis based on satellite data. In this work we present the latest advances in data assimilation using the ECMWF's 4D-Var system extended to atmospheric composition which is currently operational under the Copernicus Atmosphere Monitoring Service of the European Commission. The service is based on acquisition of all relevant data available in near-real-time, the processing of these datasets in the assimilation and the subsequent dissemination of global forecasts at ECMWF. The global forecasts are used by the CAMS regional models as boundary conditions for the European forecasts based on a multi-model ensemble. The global forecasts are also used to provide boundary conditions for other parts of the world (e.g., China) and are freely available to all interested entities. Some of the regional models also perform assimilation of satellite and ground-based observations. All products are assessed, validated and made publicly available on https://atmosphere.copernicus.eu/.

Monitoring water phase dynamics in winter clouds

NASA Astrophysics Data System (ADS)

Campos, Edwin F.; Ware, Randolph; Joe, Paul; Hudak, David

2014-10-01

This work presents observations of water phase dynamics that demonstrate the theoretical Wegener-Bergeron-Findeisen concepts in mixed-phase winter storms. The work analyzes vertical profiles of air vapor pressure, and equilibrium vapor pressure over liquid water and ice. Based only on the magnitude ranking of these vapor pressures, we identified conditions where liquid droplets and ice particles grow or deplete simultaneously, as well as the conditions where droplets evaporate and ice particles grow by vapor diffusion. The method is applied to ground-based remote-sensing observations during two snowstorms, using two distinct microwave profiling radiometers operating in different climatic regions (North American Central High Plains and Great Lakes). The results are compared with independent microwave radiometer retrievals of vertically integrated liquid water, cloud-base estimates from a co-located ceilometer, reflectivity factor and Doppler velocity observations by nearby vertically pointing radars, and radiometer estimates of liquid water layers aloft. This work thus makes a positive contribution toward monitoring and nowcasting the evolution of supercooled droplets in winter clouds.

Monitoring water phase dynamics in winter clouds

DOE PAGES

Campos, Edwin F.; Ware, Randolph; Joe, Paul; ...

2014-10-01

This work presents observations of water phase dynamics that demonstrate the theoretical Wegener–Bergeron–Findeisen concepts in mixed-phase winter storms. The work analyzes vertical profiles of air vapor pressure, and equilibrium vapor pressure over liquid water and ice. Based only on the magnitude ranking of these vapor pressures, we identified conditions where liquid droplets and ice particles grow or deplete simultaneously, as well as the conditions where droplets evaporate and ice particles grow by vapor diffusion. The method is applied to ground-based remote-sensing observations during two snowstorms, using two distinct microwave profiling radiometers operating in different climatic regions (North American Central Highmore » Plains and Great Lakes). The results are compared with independent microwave radiometer retrievals of vertically integrated liquid water, cloud-base estimates from a co-located ceilometer, reflectivity factor and Doppler velocity observations by nearby vertically pointing radars, and radiometer estimates of liquid water layers aloft. This work thus makes a positive contribution toward monitoring and now casting the evolution of supercooled droplets in winter clouds.« less

FEASIBILITY STUDY FOR IDENTIFICATION OF STATIC AND DYNAMIC EXPOSURE USING CCD IMAGING TECHNIQUE FOR Caso4:Dy TL DOSEMETERS.

PubMed

Srivastava, Kshama; Soin, Seepika; Sapra, B K; Ratna, P; Datta, D

2017-11-01

The occupational exposure incurred by the radiation workers due to the external radiation is estimated using personal dosemeter placed on the human body during the monitoring period. In certain situations, it is required to determine whether the dosemeter alone was exposed accidentally/intentionally in radiation field (static exposure) or was exposed while being worn by a worker moving in his workplace (dynamic exposure). The present thermoluminscent (TL) based personnel monitoring systems are not capable of distinguishing between the above stated (static and dynamic) exposure conditions. The feasibility of a new methodology developed using the charge coupled device based imaging technique for identification of the static/dynamic exposure of CaSO4:Dy based TL detectors for low energy photons has been investigated. The techniques for the qualitative and the quantitative assessments of the exposure conditions are presented in this paper. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

On the use of temperature for online condition monitoring of geared systems - A review

NASA Astrophysics Data System (ADS)

Touret, T.; Changenet, C.; Ville, F.; Lalmi, M.; Becquerelle, S.

2018-02-01

Gear unit condition monitoring is a key factor for mechanical system reliability management. When they are subjected to failure, gears and bearings may generate excessive vibration, debris and heat. Vibratory, acoustic or debris analyses are proven approaches to perform condition monitoring. An alternative to those methods is to use temperature as a condition indicator to detect gearbox failure. The review focuses on condition monitoring studies which use this thermal approach. According to the failure type and the measurement method, it exists a distinction whether it is contact (e.g. thermocouple) or non-contact temperature sensor (e.g. thermography). Capabilities and limitations of this approach are discussed. It is shown that the use of temperature for condition monitoring has a clear potential as an alternative to vibratory or acoustic health monitoring.

Benzene patterns in different urban environments and a prediction model for benzene rates based on NOx values

NASA Astrophysics Data System (ADS)

Paz, Shlomit; Goldstein, Pavel; Kordova-Biezuner, Levana; Adler, Lea

2017-04-01

Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. The aims of the study were to compare benzene rates in different urban environments (region with heavy traffic and industrial region), to analyse the relationship between benzene and meteorological parameters in a Mediterranean climate type, to estimate the linkages between benzene and NOx and to suggest a prediction model for benzene rates based on NOx levels in order contribute to a better estimation of benzene. Data were used from two different monitoring stations, located on the eastern Mediterranean coast: 1) a traffic monitoring station in Tel Aviv, Israel (TLV) located in an urban region with heavy traffic; 2) a general air quality monitoring station in Haifa Bay (HIB), located in Israel's main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NOx, mean temperature, relative humidity, inversion level, and temperature gradient were analysed over three years: 2008, 2009, and 2010. A prediction model for benzene rates based on NOx levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station (TLV) than at the general air quality station (HIB), despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NOx and benzene allowed the development of a prediction model for benzene rates, based on NOx, the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year (except for September). The severity of benzene pollution was found to be considerably higher at the traffic station (TLV) than at the general air quality station (HIB), despite being located in an industrial area. Hourly, daily, seasonal, and annual patterns of benzene rates have been shown to coincide with anthropogenic activities (traffic), day of the week, and atmospheric conditions. A prediction model for benzene rates was developed, based on NOx, the day of the week, and the month. The model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.

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.

Detecting, Monitoring, and Reporting Possible Adverse Drug Events Using an Arden-Syntax-based Rule Engine.

PubMed

Fehre, Karsten; Plössnig, Manuela; Schuler, Jochen; Hofer-Dückelmann, Christina; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

2015-01-01

The detection of adverse drug events (ADEs) is an important aspect of improving patient safety. The iMedication system employs predefined triggers associated with significant events in a patient's clinical data to automatically detect possible ADEs. We defined four clinically relevant conditions: hyperkalemia, hyponatremia, renal failure, and over-anticoagulation. These are some of the most relevant ADEs in internal medical and geriatric wards. For each patient, ADE risk scores for all four situations are calculated, compared against a threshold, and judged to be monitored, or reported. A ward-based cockpit view summarizes the results.

Artificial Intelligence in Autonomous Telescopes

NASA Astrophysics Data System (ADS)

Mahoney, William; Thanjavur, Karun

2011-03-01

Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

Structure and dynamics of an upland old-growth forest at Redwood National Park, California

Treesearch

Phillip J. van Mantgem; John D. Stuart

2012-01-01

Many current redwood forest management targets are based on old-growth conditions, so it is critical that we understand the variability and range of conditions that constitute these forests. Here we present information on the structure and dynamics from six one-hectare forest monitoring plots in an upland old-growth forest at Redwood National Park, California. We...

Engine condition monitoring: CF6 family 60's through the 80's

NASA Technical Reports Server (NTRS)

Kent, H. J.; Dienger, G.

1981-01-01

The on condition program is described in terms of its effectiveness as a maintenance tool both at the line station as well as at home base by the early detection of engine faults, erroneous instrumentation signals and by verification of engine health. The system encompasses all known methods from manual procedures to the fully automated airborne integrated data system.

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.

Research on cloud-based remote measurement and analysis system

NASA Astrophysics Data System (ADS)

Gao, Zhiqiang; He, Lingsong; Su, Wei; Wang, Can; Zhang, Changfan

2015-02-01

The promising potential of cloud computing and its convergence with technologies such as cloud storage, cloud push, mobile computing allows for creation and delivery of newer type of cloud service. Combined with the thought of cloud computing, this paper presents a cloud-based remote measurement and analysis system. This system mainly consists of three parts: signal acquisition client, web server deployed on the cloud service, and remote client. This system is a special website developed using asp.net and Flex RIA technology, which solves the selective contradiction between two monitoring modes, B/S and C/S. This platform supplies customer condition monitoring and data analysis service by Internet, which was deployed on the cloud server. Signal acquisition device is responsible for data (sensor data, audio, video, etc.) collection and pushes the monitoring data to the cloud storage database regularly. Data acquisition equipment in this system is only conditioned with the function of data collection and network function such as smartphone and smart sensor. This system's scale can adjust dynamically according to the amount of applications and users, so it won't cause waste of resources. As a representative case study, we developed a prototype system based on Ali cloud service using the rotor test rig as the research object. Experimental results demonstrate that the proposed system architecture is feasible.

Detection and classification of alarm threshold violations in condition monitoring systems working in highly varying operational conditions

NASA Astrophysics Data System (ADS)

Strączkiewicz, M.; Barszcz, T.; Jabłoński, A.

2015-07-01

All commonly used condition monitoring systems (CMS) enable defining alarm thresholds that enhance efficient surveillance and maintenance of dynamic state of machinery. The thresholds are imposed on the measured values such as vibration-based indicators, temperature, pressure, etc. For complex machinery such as wind turbine (WT) the total number of thresholds might be counted in hundreds multiplied by the number of operational states. All the parameters vary not only due to possible machinery malfunctions, but also due to changes in operating conditions and these changes are typically much stronger than the former ones. Very often, such a behavior may lead to hundreds of false alarms. Therefore, authors propose a novel approach based on parameterized description of the threshold violation. For this purpose the novelty and severity factors are introduced. The first parameter refers to the time of violation occurrence while the second one describes the impact of the indicator-increase to the entire machine. Such approach increases reliability of the CMS by providing the operator with the most useful information of the system events. The idea of the procedure is presented on a simulated data similar to those from a wind turbine.

Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

NASA Astrophysics Data System (ADS)

Mejia-Aguilar, Abraham

2016-04-01

In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

Development of IoT-based Urban Sinkhole and Road Collapse Monitoring System

NASA Astrophysics Data System (ADS)

Jung, B.; Bang, E.; Lee, H. J.; Jeong, S. W.; Ryu, D.; Kim, S. W.; Kim, B. K.; Yum, B. W.; Lee, I. H.

2015-12-01

The consortium of Korean government-funded research institutes is developing IoT- (Internet of things) based underground safety monitoring and alerting system to manage risks arisen from land subsidence and road collapses in metropolitan areas in South Korea. The system consists of four major functional units: subsurface monitoring sensors sending data directly through the internet, centralized servers capable of collecting and processing big data, computational modules providing physical and statistical models for predicting high-risk areas, and geologic information service platforms visualizing underground safety maps for the public. The target urban area will be regionally covered by multi-sensors monitoring soil and groundwater conditions, and by high resolution satellite InSAR images filtering vertical land movements in a centimeter scale. Integrity of buried water supply and sewer lines are also monitored for the possibility of underground cavity formation. Once high-risk area is predicted, more tangible surveying methods such as ground penetrating radar (GPR) and resistivity survey can be applied for locating the cavities. Additionally, laboratory and field experiments are performed to understand overall road collapsing mechanism from the initial cavity creation to its progressive development depending on soil types, degree of compaction, and groundwater condition. Acquired results will update existing fully-coupled hydromechanical models for more accurate prediction of the collapsing-vulnerable area. Preliminary laboratory experiments show that the upward propagation of subsurface cavity is closely related to the soil properties, such as sand-clay ratios and moisture contents, and groundwater dynamics.

[Microinjection Monitoring System Design Applied to MRI Scanning].

PubMed

Xu, Yongfeng

2017-09-30

A microinjection monitoring system applied to the MRI scanning was introduced. The micro camera probe was used to stretch into the main magnet for real-time video injection monitoring of injection tube terminal. The programming based on LabVIEW was created to analysis and process the real-time video information. The feedback signal was used for intelligent controlling of the modified injection pump. The real-time monitoring system can make the best use of injection under the condition that the injection device was away from the sample which inside the magnetic room and unvisible. 9.4 T MRI scanning experiment showed that the system in ultra-high field can work stability and doesn't affect the MRI scans.

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures.

PubMed

Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico; Moriello, Rosario Schiano Lo; Bonavolontà, Francesco; Fabbrocino, Francesco

2017-11-07

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

An illustration of new methods in machine condition monitoring, Part I: stochastic resonance

NASA Astrophysics Data System (ADS)

Worden, K.; Antoniadou, I.; Marchesiello, S.; Mba, C.; Garibaldi, L.

2017-05-01

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The first paper in the pair will deal with feature extraction. Although some papers have appeared in the recent past considering stochastic resonance as a means of amplifying damage information in signals, they have largely relied on ad hoc specifications of the resonator used. In contrast, the current paper will adopt a principled optimisation-based approach to the resonator design. The paper will also show that a discrete dynamical system can provide all the benefits of a continuous system, but also provide a considerable speed-up in terms of simulation time in order to facilitate the optimisation approach.

Development of ecological indicator guilds for land management

USGS Publications Warehouse

Krzysik, A.J.; Balbach, H.E.; Duda, J.J.; Emlen, J.M.; Freeman, D.C.; Graham, J.H.; Kovacic, D.A.; Smith, L.M.; Zak, J.C.

2005-01-01

Agency land-use must be efficiently and cost-effectively monitored to assess conditions and trends in ecosystem processes and natural resources relevant to mission requirements and legal mandates. Ecological Indicators represent important land management tools for tracking ecological changes and preventing irreversible environmental damage in disturbed landscapes. The overall objective of the research was to develop both individual and integrated sets (i.e., statistically derived guilds) of Ecological Indicators to: quantify habitat conditions and trends, track and monitor ecological changes, provide early warning or threshold detection, and provide guidance for land managers. The derivation of Ecological Indicators was based on statistical criteria, ecosystem relevance, reliability and robustness, economy and ease of use for land managers, multi-scale performance, and stress response criteria. The basis for the development of statistically based Ecological Indicators was the identification of ecosystem metrics that analytically tracked a landscape disturbance gradient.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

PubMed

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

PubMed Central

Segreto, Tiziana; Karam, Sara; Teti, Roberto

2017-01-01

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions. PMID:29231864

Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations.

PubMed

Zhang, Cunji; Yao, Xifan; Zhang, Jianming; Jin, Hong

2016-05-31

Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time-frequency domains. The key features are selected based on Pearson's Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL.

An inversion strategy for energy saving in smart building through wireless monitoring

NASA Astrophysics Data System (ADS)

Anselmi, N.; Moriyama, T.

2017-10-01

The building plants represent one of the main sources of power consumption and of greenhouse gases emission in urban scenarios. The efficiency of energy management is also related to the indoor environmental conditions that reflect on the user comfort. The constant monitoring of comfort indicators enables the accurate management of building plants with the final objective of reducing energy waste and satisfying the user needs. This paper presents an inversion methodology based on support vector regression for the reconstruction and forecasting of the thermal comfort of users starting from the indoor environmental features of the building. The environmental monitoring is performed by means of a wireless sensor network, which pervasively measures the spatial variability of indoor conditions. The proposed system has been experimentally validated in a real test-site to assess the advantages and the limitations in supporting the management of the building plants towards energy saving.

Damage evaluation by a guided wave-hidden Markov model based method

NASA Astrophysics Data System (ADS)

Mei, Hanfei; Yuan, Shenfang; Qiu, Lei; Zhang, Jinjin

2016-02-01

Guided wave based structural health monitoring has shown great potential in aerospace applications. However, one of the key challenges of practical engineering applications is the accurate interpretation of the guided wave signals under time-varying environmental and operational conditions. This paper presents a guided wave-hidden Markov model based method to improve the damage evaluation reliability of real aircraft structures under time-varying conditions. In the proposed approach, an HMM based unweighted moving average trend estimation method, which can capture the trend of damage propagation from the posterior probability obtained by HMM modeling is used to achieve a probabilistic evaluation of the structural damage. To validate the developed method, experiments are performed on a hole-edge crack specimen under fatigue loading condition and a real aircraft wing spar under changing structural boundary conditions. Experimental results show the advantage of the proposed method.

Low-Cost Oil Quality Sensor Based on Changes in Complex Permittivity

PubMed Central

Pérez, Angel Torres; Hadfield, Mark

2011-01-01

Real time oil quality monitoring techniques help to protect important industry assets, minimize downtime and reduce maintenance costs. The measurement of a lubricant’s complex permittivity is an effective indicator of the oil degradation process and it can be useful in condition based maintenance (CBM) to select the most adequate oil replacement maintenance schedules. A discussion of the working principles of an oil quality sensor based on a marginal oscillator to monitor the losses of the dielectric at high frequencies (>1 MHz) is presented. An electronic design procedure is covered which results in a low cost, effective and ruggedized sensor implementation suitable for use in harsh environments. PMID:22346666

Technology review: prototyping platforms for monitoring ambient conditions.

PubMed

Afolaranmi, Samuel Olaiya; Ramis Ferrer, Borja; Martinez Lastra, Jose Luis

2018-05-08

The monitoring of ambient conditions in indoor spaces is very essential owing to the amount of time spent indoors. Specifically, the monitoring of air quality is significant because contaminated air affects the health, comfort and productivity of occupants. This research work presents a technology review of prototyping platforms for monitoring ambient conditions in indoor spaces. It involves the research on sensors (for CO 2 , air quality and ambient conditions), IoT platforms, and novel and commercial prototyping platforms. The ultimate objective of this review is to enable the easy identification, selection and utilisation of the technologies best suited for monitoring ambient conditions in indoor spaces. Following the review, it is recommended to use metal oxide sensors, optical sensors and electrochemical sensors for IAQ monitoring (including NDIR sensors for CO 2 monitoring), Raspberry Pi for data processing, ZigBee and Wi-Fi for data communication, and ThingSpeak IoT platform for data storage, analysis and visualisation.

Subtlenoise: sonification of distributed computing operations

NASA Astrophysics Data System (ADS)

Love, P. A.

2015-12-01

The operation of distributed computing systems requires comprehensive monitoring to ensure reliability and robustness. There are two components found in most monitoring systems: one being visually rich time-series graphs and another being notification systems for alerting operators under certain pre-defined conditions. In this paper the sonification of monitoring messages is explored using an architecture that fits easily within existing infrastructures based on mature opensource technologies such as ZeroMQ, Logstash, and Supercollider (a synth engine). Message attributes are mapped onto audio attributes based on broad classification of the message (continuous or discrete metrics) but keeping the audio stream subtle in nature. The benefits of audio rendering are described in the context of distributed computing operations and may provide a less intrusive way to understand the operational health of these systems.

Inverter ratio failure detector

NASA Technical Reports Server (NTRS)

Wagner, A. P.; Ebersole, T. J.; Andrews, R. E. (Inventor)

1974-01-01

A failure detector which detects the failure of a dc to ac inverter is disclosed. The inverter under failureless conditions is characterized by a known linear relationship of its input and output voltages and by a known linear relationship of its input and output currents. The detector includes circuitry which is responsive to the detector's input and output voltages and which provides a failure-indicating signal only when the monitored output voltage is less by a selected factor, than the expected output voltage for the monitored input voltage, based on the known voltages' relationship. Similarly, the detector includes circuitry which is responsive to the input and output currents and provides a failure-indicating signal only when the input current exceeds by a selected factor the expected input current for the monitored output current based on the known currents' relationship.

Monitoring industrial facilities using principles of integration of fiber classifier and local sensor networks

NASA Astrophysics Data System (ADS)

Korotaev, Valery V.; Denisov, Victor M.; Rodrigues, Joel J. P. C.; Serikova, Mariya G.; Timofeev, Andrey V.

2015-05-01

The paper deals with the creation of integrated monitoring systems. They combine fiber-optic classifiers and local sensor networks. These systems allow for the monitoring of complex industrial objects. Together with adjacent natural objects, they form the so-called geotechnical systems. An integrated monitoring system may include one or more spatially continuous fiber-optic classifiers based on optic fiber and one or more arrays of discrete measurement sensors, which are usually combined in sensor networks. Fiber-optic classifiers are already widely used for the control of hazardous extended objects (oil and gas pipelines, railways, high-rise buildings, etc.). To monitor local objects, discrete measurement sensors are generally used (temperature, pressure, inclinometers, strain gauges, accelerometers, sensors measuring the composition of impurities in the air, and many others). However, monitoring complex geotechnical systems require a simultaneous use of continuous spatially distributed sensors based on fiber-optic cable and connected local discrete sensors networks. In fact, we are talking about integration of the two monitoring methods. This combination provides an additional way to create intelligent monitoring systems. Modes of operation of intelligent systems can automatically adapt to changing environmental conditions. For this purpose, context data received from one sensor (e.g., optical channel) may be used to change modes of work of other sensors within the same monitoring system. This work also presents experimental results of the prototype of the integrated monitoring system.

Remote sensing of Northern mines: supporting operation and environmental monitoring in cold conditions

NASA Astrophysics Data System (ADS)

Tuomela, Anne; Davids, Corine; Knutsson, Sven; Knutsson, Roger; Rauhala, Anssi; Rossi, Pekka M.; Rouyet, Line

2017-04-01

Northern areas of Finland, Sweden and Norway have mineral-rich deposits. There are several active mines in the area but also closed ones and deposits with plans for future mining. With increasing demand for environmental protection in the sensitive Northern conditions, there is a need for more comprehensive monitoring of the mining environment. In our study, we aim to develop new opportunities to use remote sensing data from satellites and unmanned aerial vehicles (UAVs) in improving mining safety and monitoring, for example in the case of mine waste storage facilities. Remote sensing methods have evolved fast, and could in many cases enable precise, reliable, and cost-efficient data collection over large areas. The study has focused on four mining areas in Northern Fennoscandia. Freely available medium-resolution (e.g. Sentinel-1), commercial high-resolution (e.g. TerraSAR-X) and Synthetic Aperture Radar (SAR) data has been collected during 2015-2016 to study how satellite remote sensing could be used e.g. for displacement monitoring using SAR Interferometry (InSAR). Furthermore, UAVs have been utilized in similar data collection in a local scale, and also in collection of thermal infrared data for hydrological monitoring of the areas. The development and efficient use of the methods in mining areas requires experts from several fields. In addition, the Northern conditions with four distinct seasons bring their own challenges for the efficient use of remote sensing, and further complicate their integration as standardised monitoring methods for mine environments. Based on the initial results, remote sensing could especially enhance the monitoring of large-scale structures in mine areas such as tailings impoundments.

Real time monitoring of water level and temperature in storage fuel pools through optical fibre sensors.

PubMed

Rizzolo, S; Périsse, J; Boukenter, A; Ouerdane, Y; Marin, E; Macé, J-R; Cannas, M; Girard, S

2017-08-18

We present an innovative architecture of a Rayleigh-based optical fibre sensor for the monitoring of water level and temperature inside storage nuclear fuel pools. This sensor, able to withstand the harsh constraints encountered under accidental conditions such as those pointed-out during the Fukushima-Daiichi event (temperature up to 100 °C and radiation dose level up to ~20 kGy), exploits the Optical Frequency Domain Reflectometry technique to remotely monitor a radiation resistant silica-based optical fibre i.e. its sensing probe. We validate the efficiency and the robustness of water level measurements, which are extrapolated from the temperature profile along the fibre length, in a dedicated test bench allowing the simulation of the environmental operating and accidental conditions. The conceived prototype ensures an easy, practical and no invasive integration into existing nuclear facilities. The obtained results represent a significant breakthrough and comfort the ability of the developed system to overcome both operating and accidental constraints providing the distributed profiles of the water level (0-to-5 m) and temperature (20-to-100 °C) with a resolution that in accidental condition is better than 3 cm and of ~0.5 °C respectively. These new sensors will be able, as safeguards, to contribute and reinforce the safety in existing and future nuclear power plants.

Using Amazon Web Services (AWS) to enable real-time, remote sensing of biophysical and anthropogenic conditions in green infrastructure systems in Philadelphia, an ultra-urban application of the Internet of Things (IoT)

NASA Astrophysics Data System (ADS)

Montalto, F. A.; Yu, Z.; Soldner, K.; Israel, A.; Fritch, M.; Kim, Y.; White, S.

2017-12-01

Urban stormwater utilities are increasingly using decentralized "green" infrastructure (GI) systems to capture stormwater and achieve compliance with regulations. Because environmental conditions, and design varies by GSI facility, monitoring of GSI systems under a range of conditions is essential. Conventional monitoring efforts can be costly because in-field data logging requires intense data transmission rates. The Internet of Things (IoT) can be used to more cost-effectively collect, store, and publish GSI monitoring data. Using 3G mobile networks, a cloud-based database was built on an Amazon Web Services (AWS) EC2 virtual machine to store and publish data collected with environmental sensors deployed in the field. This database can store multi-dimensional time series data, as well as photos and other observations logged by citizen scientists through a public engagement mobile app through a new Application Programming Interface (API). Also on the AWS EC2 virtual machine, a real-time QAQC flagging algorithm was developed to validate the sensor data streams.

Testing ZigBee Motes for Monitoring Refrigerated Vegetable Transportation under Real Conditions

PubMed Central

Ruiz-Garcia, Luis; Barreiro, Pilar; Robla, Jose Ignacio; Lunadei, Loredana

2010-01-01

Quality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous ‘cold chain’ from producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper illustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during shipments. PMID:22399917

Testing ZigBee motes for monitoring refrigerated vegetable transportation under real conditions.

PubMed

Ruiz-Garcia, Luis; Barreiro, Pilar; Robla, Jose Ignacio; Lunadei, Loredana

2010-01-01

Quality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous 'cold chain' from producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper illustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during shipments.

Process-based reference conditions: An alternative approach for managed river systems

NASA Astrophysics Data System (ADS)

Grams, P.; Melis, T.; Wright, S.; Schmidt, J.; Topping, D.

2008-12-01

Physical reference conditions, whether based on historic information or the condition of nearby less impaired systems, provide necessary information that contributes to an assessment of stream condition and the nature of channel transformation. In many cases, however, the utility of this traditional 'reference' approach may end at the assessment stage and not be applicable to establishing and implementing restoration goals. Ongoing impacts such as continued existence of an upstream dam or the persistence of invasive vegetation may render restoration based on a physical reference infeasible. In these circumstances, an alternative approach is to identify and describe reference processes in place of physical reference conditions. This is the case for the Colorado River where large dams, a commitment to hydropower production, and legal mandates for regional distribution and off- channel consumption of water greatly reduce the relevance of historical conditions in setting goals for rehabilitation. In this setting, two strategies are available for setting reference conditions. One is maintenance of post-dam sediment mass balance, which attempts to ensure that the channel does not continue to degrade or aggrade and that riverine habitats do not continue to diverge from their historical condition. Post- dam sediment mass balance can be quantified at a reconnaissance or project scale. The second strategy is to define key processes that maintain the native ecosystem. These processes may, or may not, be consistent with maintenance of sediment mass balance, but they may be key to rejuvenation of spawning and rearing habitats, maintenance of historical ranges of temperature and turbidity, maintenance of a sustainable food base for the native aquatic community, or maintaining other riverine resources. Both strategies require careful monitoring of processes (e.g. sediment flux), which may add considerably to the cost and complexity of a monitoring program. An additional challenge in adopting the second strategy is that it is difficult to define when a process is adequately restored, since many ecosystem processes collectively limit recovery of populations of native communities.

A semi-analytical bearing model considering outer race flexibility for model based bearing load monitoring

NASA Astrophysics Data System (ADS)

Kerst, Stijn; Shyrokau, Barys; Holweg, Edward

2018-05-01

This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.

Design and implementation of PAVEMON: A GIS web-based pavement monitoring system based on large amounts of heterogeneous sensors data

NASA Astrophysics Data System (ADS)

Shahini Shamsabadi, Salar

A web-based PAVEment MONitoring system, PAVEMON, is a GIS oriented platform for accommodating, representing, and leveraging data from a multi-modal mobile sensor system. Stated sensor system consists of acoustic, optical, electromagnetic, and GPS sensors and is capable of producing as much as 1 Terabyte of data per day. Multi-channel raw sensor data (microphone, accelerometer, tire pressure sensor, video) and processed results (road profile, crack density, international roughness index, micro texture depth, etc.) are outputs of this sensor system. By correlating the sensor measurements and positioning data collected in tight time synchronization, PAVEMON attaches a spatial component to all the datasets. These spatially indexed outputs are placed into an Oracle database which integrates seamlessly with PAVEMON's web-based system. The web-based system of PAVEMON consists of two major modules: 1) a GIS module for visualizing and spatial analysis of pavement condition information layers, and 2) a decision-support module for managing maintenance and repair (Mℝ) activities and predicting future budget needs. PAVEMON weaves together sensor data with third-party climate and traffic information from the National Oceanic and Atmospheric Administration (NOAA) and Long Term Pavement Performance (LTPP) databases for an organized data driven approach to conduct pavement management activities. PAVEMON deals with heterogeneous and redundant observations by fusing them for jointly-derived higher-confidence results. A prominent example of the fusion algorithms developed within PAVEMON is a data fusion algorithm used for estimating the overall pavement conditions in terms of ASTM's Pavement Condition Index (PCI). PAVEMON predicts PCI by undertaking a statistical fusion approach and selecting a subset of all the sensor measurements. Other fusion algorithms include noise-removal algorithms to remove false negatives in the sensor data in addition to fusion algorithms developed for identifying features on the road. PAVEMON offers an ideal research and monitoring platform for rapid, intelligent and comprehensive evaluation of tomorrow's transportation infrastructure based on up-to-date data from heterogeneous sensor systems.

A fully automated health-care monitoring at home without attachment of any biological sensors and its clinical evaluation.

PubMed

Motoi, Kosuke; Ogawa, Mitsuhiro; Ueno, Hiroshi; Kuwae, Yutaka; Ikarashi, Akira; Yuji, Tadahiko; Higashi, Yuji; Tanaka, Shinobu; Fujimoto, Toshiro; Asanoi, Hidetsugu; Yamakoshi, Ken-ichi

2009-01-01

Daily monitoring of health condition is important for an effective scheme for early diagnosis, treatment and prevention of lifestyle-related diseases such as adiposis, diabetes, cardiovascular diseases and other diseases. Commercially available devices for health care monitoring at home are cumbersome in terms of self-attachment of biological sensors and self-operation of the devices. From this viewpoint, we have been developing a non-conscious physiological monitor installed in a bath, a lavatory, and a bed for home health care and evaluated its measurement accuracy by simultaneous recordings of a biological sensors directly attached to the body surface. In order to investigate its applicability to health condition monitoring, we have further developed a new monitoring system which can automatically monitor and store the health condition data. In this study, by evaluation on 3 patients with cardiac infarct or sleep apnea syndrome, patients' health condition such as body and excretion weight in the toilet and apnea and hypopnea during sleeping were successfully monitored, indicating that the system appears useful for monitoring the health condition during daily living.

Monitoring the Corrosion Process of Reinforced Concrete Using BOTDA and FBG Sensors

PubMed Central

Mao, Jianghong; Chen, Jiayun; Cui, Lei; Jin, Weiliang; Xu, Chen; He, Yong

2015-01-01

Expansion and cracking induced by the corrosion of reinforcement concrete is the major factor in the failure of concrete durability. Therefore, monitoring of concrete cracking is critical for evaluating the safety of concrete structures. In this paper, we introduce a novel monitoring method combining Brillouin optical time domain analysis (BOTDA) and fiber Bragg grating (FBG), based on mechanical principles of concrete expansion cracking. BOTDA monitors concrete expansion and crack width, while FBG identifies the time and position of cracking. A water-pressure loading simulation test was carried out to determine the relationship between fiber strain, concrete expansion and crack width. An electrical accelerated corrosion test was also conducted to evaluate the ability of this novel sensor to monitor concrete cracking under practical conditions. PMID:25884790

Invisible work of using and monitoring knowledge by parents (end-users) of children with chronic conditions.

PubMed

Lagosky, Stephanie; Bartlett, Doreen; Shaw, Lynn

2016-01-01

Parents who care for young children with chronic conditions are knowledge users. Their efforts, time, and energy to source, consider and monitor information add to the 'invisible' work of parents in making decisions about care, school transitions, and interventions. Little is known or understood about the work of parents as knowledge users. To understand the knowledge use patterns and how these patterns may be monitored in parents caring for their young children with cerebral palsy (CP). An embedded case study methodology was used. In-depth qualitative interviews and visual mapping were employed to collect and analyze data based on the experiences of three mothers of young children with CP. Knowledge use in parents caring for their young children with CP is multi-factorial, complex and temporal. Findings resulted in a provisional model elaborating on the ways knowledge is used by parents and how it may be monitored. The visual mapping of pathways and actions of parents as end users makes the processes of knowledge use more visible and open to be valued as well as appreciated by others. The provisional model has implications for knowledge mobilization as a strategy in childhood rehabilitation and the facilitation of knowledge use in the lives of families with children with chronic health conditions.

Fetal heart rate monitoring device using condenser microphone sensor: Validation and comparison to standard devices.

PubMed

Ahmad, Husna Azyan Binti; El-Badawy, Ismail M; Singh, Om Prakash; Hisham, Rozana Binti; Malarvili, M B

2018-04-27

Fetal heart rate (FHR) monitoring device is highly demanded to assess the fetus health condition in home environments. Conventional standard devices such as ultrasonography and cardiotocography are expensive, bulky and uncomfortable and consequently not suitable for long-term monitoring. Herein, we report a device that can be used to measure fetal heart rate in clinical and home environments. The proposed device measures and displays the FHR on a screen liquid crystal display (LCD). The device consists of hardware that comprises condenser microphone sensor, signal conditioning, microcontroller and LCD, and software that involves the algorithm used for processing the conditioned fetal heart signal prior to FHR display. The device's performance is validated based on analysis of variance (ANOVA) test. FHR data was recorded from 22 pregnant women during the 17th to 37th week of gestation using the developed device and two standard devices; AngelSounds and Electronic Stethoscope. The results show that F-value (1.5) is less than F, (3.1) and p-value (p> 0.05). Accordingly, there is no significant difference between the mean readings of the developed and existing devices. Hence, the developed device can be used for monitoring FHR in clinical and home environments.

Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

2014-05-01

Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety of land cover types. Remote sensing data from the Tropical Rainfall Measuring Mission satellite (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sensors were obtained for the period from 2000 to 2012, and observation data from 99 weather stations, 441 streamflow gauges, as well as the gridded observation data from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE) were obtained for validation. The objective blends of multiple indicators helped better assessment of various types of drought, and can be useful for drought early warning system. Since the improved SDCI is based on remotely sensed data, it can be easily applied to regions with limited or no observation data for drought assessment and monitoring.

The Transmission Channel Tower Identification and Landslide Disaster Monitoring Based on Insar

NASA Astrophysics Data System (ADS)

Li, G.; Tan, Q.; Xie, C.; Fei, X.; Ma, X.; Zhao, B.; Ou, W.; Yang, Z.; Wang, J.; Fang, H.

2018-04-01

The transmission distance of transmission lines is long, the line affected by the diversity of climate and topography of the corridors of transmission lines, differences in regional geological structure conditions, variability of rock and soil types, and the complexity of groundwater. Under the influence of extreme weather conditions (ice-covered, strong wind, etc.) and sudden geological disasters (such as mudslides, flash floods, earthquakes, etc.), catastrophic damage and basic deformation problems of the tower foundations are prone, and even tower collapse accidents occur in severe cases, which affect the safe operation of transmission lines. Monitoring the deformation of power transmission towers and surrounding grounds, it is critical to ensuring the normal operation of transmission lines by assessing and controlling potential risks in advance. In this paper, using ALOS-2 PALSAR radar satellite data, differential interferometry was used to monitor surface deformation near the Sichuan Jinsu line transmission channel. The analysis found that a significant landslide hazard was found near the transmission channel tower in Yibin-Zhaotong section of Jinsu, Sichuan Province, the cumulative deformation reaches 9cm. The results of this paper can provide new monitoring means for safety monitoring of transmission towers.

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

Diagnostics monitor of the braking efficiency in the on board diagnostics system for the motor vehicles

NASA Astrophysics Data System (ADS)

Gajek, Andrzej

2016-09-01

The article presents diagnostics monitor for control of the efficiency of brakes in various road conditions in cars equipped with pressure sensor in brake (ESP) system. Now the brake efficiency of the vehicles is estimated periodically in the stand conditions on the base of brake forces measurement or in the road conditions on the base of the brake deceleration. The presented method allows to complete the stand - periodical tests of the brakes by current on board diagnostics system OBD for brakes. First part of the article presents theoretical dependences between deceleration of the vehicle and brake pressure. The influence of the vehicle mass, initial speed of braking, temperature of brakes, aerodynamic drag, rolling resistance, engine resistance, state of the road surface, angle of the road sloping on the deceleration have been analysed. The manner of the appointed of these parameters has been analysed. The results of the initial investigation have been presented. At the end of the article the strategy of the estimation and signalization of the irregular value of the deceleration are presented.

Operation Reliability Assessment for Cutting Tools by Applying a Proportional Covariate Model to Condition Monitoring Information

PubMed Central

Cai, Gaigai; Chen, Xuefeng; Li, Bing; Chen, Baojia; He, Zhengjia

2012-01-01

The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of identical units under given and fixed conditions. However, it has limited effectiveness in depicting the operational characteristics of a cutting tool. To overcome this limitation, this paper proposes an approach to assess the operation reliability of cutting tools. A proportional covariate model is introduced to construct the relationship between operation reliability and condition monitoring information. The wavelet packet transform and an improved distance evaluation technique are used to extract sensitive features from vibration signals, and a covariate function is constructed based on the proportional covariate model. Ultimately, the failure rate function of the cutting tool being assessed is calculated using the baseline covariate function obtained from a small sample of historical data. Experimental results and a comparative study show that the proposed method is effective for assessing the operation reliability of cutting tools. PMID:23201980

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

PubMed Central

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-01-01

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization. PMID:26343660

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

PubMed

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-08-27

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

Why do water quality monitoring programs succeed or fail? A qualitative comparative analysis of regulated testing systems in sub-Saharan Africa.

PubMed

Peletz, Rachel; Kisiangani, Joyce; Bonham, Mateyo; Ronoh, Patrick; Delaire, Caroline; Kumpel, Emily; Marks, Sara; Khush, Ranjiv

2018-05-31

Water quality testing is critical for guiding water safety management and ensuring public health. In many settings, however, water suppliers and surveillance agencies do not meet regulatory requirements for testing frequencies. This study examines the conditions that promote successful water quality monitoring in Africa, with the goal of providing evidence for strengthening regulated water quality testing programs. We compared monitoring programs among 26 regulated water suppliers and surveillance agencies across six African countries. These institutions submitted monthly water quality testing results over 18 months. We also collected qualitative data on the conditions that influenced testing performance via approximately 821 h of semi-structured interviews and observations. Based on our qualitative data, we developed the Water Capacity Rating Diagnostic (WaterCaRD) to establish a scoring framework for evaluating the effects of the following conditions on testing performance: accountability, staffing, program structure, finances, and equipment & services. We summarized the qualitative data into case studies for each of the 26 institutions and then used the case studies to score the institutions against the conditions captured in WaterCaRD. Subsequently, we applied fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare these scores against performance outcomes for water quality testing. We defined the performance outcomes as the proportion of testing Targets Achieved (outcome 1) and Testing Consistency (outcome 2) based on the monthly number of microbial water quality tests conducted by each institution. Our analysis identified motivation & leadership, knowledge, staff retention, and transport as institutional conditions that were necessary for achieving monitoring targets. In addition, equipment, procurement, infrastructure, and enforcement contributed to the pathways that resulted in strong monitoring performance. Our identification of institutional commitment, comprising motivation & leadership, knowledge, and staff retention, as a key driver of monitoring performance was not surprising: in weak regulatory environments, individuals and their motivations take-on greater importance in determining institutional and programmatic outcomes. Nevertheless, efforts to build data collection capacity in low-resource settings largely focus on supply-side interventions: the provision of infrastructure, equipment, and training sessions. Our results indicate that these interventions will continue to have limited long-term impacts and sustainability without complementary strategies for motivating or incentivizing water supply and surveillance agency managers to achieve testing goals. More broadly, our research demonstrates both an experimental approach for diagnosing the systems that underlie service provision and an analytical strategy for identifying appropriate interventions. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

River water pollution condition in upper part of Brantas River and Bengawan Solo River

NASA Astrophysics Data System (ADS)

Roosmini, D.; Septiono, M. A.; Putri, N. E.; Shabrina, H. M.; Salami, I. R. S.; Ariesyady, H. D.

2018-01-01

Wastewater and solid waste from both domestic and industry have been known to give burden on river water quality. Most of river water quality problem in Indonesia has start in the upper part of river due to anthropogenic activities, due to inappropriate land use management including the poor wastewater infrastructure. Base on Upper Citarum River Water pollution problem, it is interesting to study the other main river in Java Island. Bengawan Solo River and Brantas River were chosen as the sample in this study. Parameters assessed in this study are as follows: TSS, TDS, pH, DO, and hexavalent chromium. The status of river water quality are assess using STORET method. Based on (five) parameters, STORET value showed that in Brantas River, Pagerluyung monitoring point had the worst quality relatively compared to other monitoring point in Brantas River with exceeding copper, lead and tin compared to the stream standard in East Java Provincial Regulation No. 2 in 2008. Brantas River was categorized as lightly polluted river based on monitoring period 2011-2015 in 5 monitoring points, namely Pendem, Sengguruh, Kademangan, Meritjan and Kertosono.

A global drought monitoring system: insights of an approach integrating remote sensing data and vulnerability to food insecurity

NASA Astrophysics Data System (ADS)

Angeluccetti, Irene; Perez, Francesca; Cámaro, Walther; Demarchi, Alessandro

2015-04-01

Early Warning Systems (EWS) for drought are currently underdeveloped compared to those related to other natural hazards. Both forecasting and monitoring of drought events are still posing challenges to the scientific community. In fact, the multifaceted nature of drought (i.e. hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. Similarly, drought impacts are various and complex thus difficult to be univocally measured. In the present study an approach for monitoring drought in near-real time and for estimating its impacts is presented. The EWS developed runs on a global extent and is mainly based on the early detection and monitoring of vegetation stress. On the one hand the monitoring of vegetation phenological parameters, whose extraction is based on the analysis of the MODIS-derived NDVI function, allows the fortnightly assessment of the vegetation productivity which could be expected at the end of the growing season. On the other hand, the Standardized Precipitation Index (SPI), calculated adapting TRMM-derived precipitation data in a selected distribution is used, before the growing season start, in order to early detect meteorological conditions which could give rise to vegetation stress events. During the growing season the SPI is used as check information for vegetation conditions. The relationships between rainfall and vegetation dynamics have been statistically analyzed considering different types of vegetation, in order to identify the most suitable rainfall cumulating interval to be used for the proposed monitoring procedures in different areas. A simplified vulnerability model, coupled with the above-mentioned hazard data, returns food security conditions, i.e. the estimated impacts over an investigated area. The model includes a set of agricultural indicators that accounts for the diversity of cultivated crops, the percentage of irrigated area and the suitability of soils. In addition the people's strategy to supply food is mapped through the use of gravity spatial choice models. This leads to the definition of hazard-specific risk zones, upon which to base the allocation of the calculated alerts. The performances of the proposed EWS were evaluated, for a selection of national case studies, with comparable ground-truth data derived from local food security assessments. The system is deployed on a WebGIS platform for its use by the widest possible audience.

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.

Monitoring and Assessment of Military Installation Land Condition under Training Disturbance Using Remote Sensing

NASA Astrophysics Data System (ADS)

Rijal, Santosh

Various military training activities are conducted in more than 11.3 million hectares of land (> 5,500 training sites) in the United States (U.S.). These training activities directly and indirectly degrade the land. Land degradation can impede continuous military training. In order to sustain long term training missions and Army combat readiness, the environmental conditions of the military installations need to be carefully monitored and assessed. Furthermore, the National Environmental Policy Act of 1969 (NEPA) and the U.S. Army Regulation 200-2 require the DoD to minimize the environmental impacts of training and document the environmental consequences of their actions. To achieve these objectives, the Department of Army initiated an Integrated Training Area Management (ITAM) program to manage training lands through assessing their environmental requirements and establishing policies and procedures to achieve optimum, sustainable use of training lands. One of the programs under ITAM, Range and Training Land Assessment (RTLA) was established to collect field-based data for monitoring installation's environmental condition. Due to high cost and inefficiencies involved in the collection of field data, the RTLA program was stopped in several military installations. Therefore, there has been a strong need to develop an efficient and low cost remote sensing based methodology for assessing and monitoring land conditions of military installations. It is also important to make a long-term assessment of installation land condition for understanding cumulative impacts of continuous military training activities. Additionally, it is unclear that compared to non-military land condition, to what extent military training activities have led to the degradation of land condition for military installations. The first paper of this dissertation developed a soil erosion relevant and image derived cover factor (ICF) based on linear spectral mixture (LSM) analysis to assess and monitor the land condition of military land and compare it with non-military land. The results from this study can provide FR land managers with the information of the spatial variation and temporal trend of land condition in FR. Fort Riley land managers can also use this method for monitoring their land condition at a very low cost. This method can thus be applied to other military installations as well as non-military lands. Furthermore, one of the most significant environmental problems in military installations of the U.S. is the formation of gullies due to the intensive use of military vehicle. However, to our knowledge, no remote sensing based method has been developed and used to assess the detection of gullies in military installations. In the second paper of this dissertation, light detection and ranging (LiDAR) derived digital elevation model (DEM) of 2010 and WorldView-2 images of 2010 were used to quantify the gullies in FR. This method can be easily applied to assess gullies in non-military installations. On the other hand, modeling the land condition of military installation is critical to understand the spatial and temporal pattern of military training induced disturbance and land recovery. In the third paper, it was assumed that the military training induced disturbance was spatially auto-correlated and thus four regression models including i) linear stepwise regression (LSR) ii) logistic regression (LR), iii) geographically weighted linear regression (GWR), and iv) geographically weighted logistic regression (GWLR) were developed and compared using remote sensing image derived spectral variables for years 1990, 1997, 1998, 1999, and 2001. It was found that the spatial distribution of the military training disturbance was well demonstrated by all the regression models with higher intensities of military training disturbance in the northwest and central west parts of the installation. Compared to other regression models, GWR accurately estimated the land condition of FR. This result provided the applicability of using local variability based regression model to accurately predict land condition. Different plant communities of military installations respond differently to military training induced disturbance. The information of the spatial distribution of plant species in military installations is important to gain insight of the resilient capacity of the land following disturbances. For the purpose, in the fourth paper, hyperspectral in-situ data were collected from FR and KPBS in the summer of 2015 using a hyperspectral instrument. Principal component analysis (PCA) and band relative importance (BRI) were used to identify relative importance of each of the spectral bands. The results from this study provided useful information about the optimal wavelengths that help distinguish different plant species of FR and can be easily used with high resolution hyperspectral images for mapping the spatial distribution of the plant species. This information will be helpful for the sustainable management of the tallgrass prairie ecosystem. (Abstract shortened by ProQuest.).

An Integrated Architecture for On-Board Aircraft Engine Performance Trend Monitoring and Gas Path Fault Diagnostics

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2010-01-01

Aircraft engine performance trend monitoring and gas path fault diagnostics are closely related technologies that assist operators in managing the health of their gas turbine engine assets. Trend monitoring is the process of monitoring the gradual performance change that an aircraft engine will naturally incur over time due to turbomachinery deterioration, while gas path diagnostics is the process of detecting and isolating the occurrence of any faults impacting engine flow-path performance. Today, performance trend monitoring and gas path fault diagnostic functions are performed by a combination of on-board and off-board strategies. On-board engine control computers contain logic that monitors for anomalous engine operation in real-time. Off-board ground stations are used to conduct fleet-wide engine trend monitoring and fault diagnostics based on data collected from each engine each flight. Continuing advances in avionics are enabling the migration of portions of the ground-based functionality on-board, giving rise to more sophisticated on-board engine health management capabilities. This paper reviews the conventional engine performance trend monitoring and gas path fault diagnostic architecture commonly applied today, and presents a proposed enhanced on-board architecture for future applications. The enhanced architecture gains real-time access to an expanded quantity of engine parameters, and provides advanced on-board model-based estimation capabilities. The benefits of the enhanced architecture include the real-time continuous monitoring of engine health, the early diagnosis of fault conditions, and the estimation of unmeasured engine performance parameters. A future vision to advance the enhanced architecture is also presented and discussed

Research on a Banknote Printing Wastewater Monitoring System based on Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Li, B. B.; Yuan, Z. F.

2006-10-01

In this paper, a banknote printing wastewater monitoring system based on WSN is presented in line with the system demands and actual condition of the worksite for a banknote printing factory. In Physical Layer, the network node is a nRF9e5-centric embedded instrument, which can realize the multi-function such as data collecting, status monitoring, wireless data transmission and so on. Limited by the computing capability, memory capability, communicating energy and others factors, it is impossible for the node to get every detail information of the network, so the communication protocol on WSN couldn't be very complicated. The competitive-based MACA (Multiple Access with Collision Avoidance) Protocol is introduced in MAC, which can decide the communication process and working mode of the nodes, avoid the collision of data transmission, hidden and exposed station problem of nodes. On networks layer, the routing protocol in charge of the transmitting path of the data, the networks topology structure is arranged based on address assignation. Accompanied with some redundant nodes, the network performances stabile and expandable. The wastewater monitoring system is a tentative practice of WSN theory in engineering. Now, the system has passed test and proved efficiently.

Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring.

PubMed

Netterberg, Ida; Nielsen, Elisabet I; Friberg, Lena E; Karlsson, Mats O

2017-08-01

To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today. Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements. The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17. Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated.

A personalized health-monitoring system for elderly by combining rules and case-based reasoning.

PubMed

Ahmed, Mobyen Uddin

2015-01-01

Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly's medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.

Vibration-based structural health monitoring of highway bridges.

DOT National Transportation Integrated Search

2008-12-01

In recent years, the condition of aging transportation infrastructure has drawn attention to the maintenance and : inspection of highway bridges. With the increasing importance of life-lines, such as highways, to the national economy : and the well-b...

LANDSCAPE CHARACTERIZATION AND CHANGE DETECTION METHODS DEVELOPMENT RESEARCH (2005-2007)

EPA Science Inventory

The characterization of land-cover (LC) type, extent, and distribution represent important landscape characterization element required for monitoring ecosystem conditions and for primary data input to biogenic emission and atmospheric deposition models. Current spectral-based ch...

40 CFR 63.526 - Monitoring requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... vent. (D) Design analysis based on accepted chemical engineering principles, measurable process.... (i) For the purpose of determining de minimis status for emission points, engineering assessment may... operating conditions expected to yield the highest flow rate and concentration. Engineering assessment...

40 CFR 63.526 - Monitoring requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... vent. (D) Design analysis based on accepted chemical engineering principles, measurable process.... (i) For the purpose of determining de minimis status for emission points, engineering assessment may... operating conditions expected to yield the highest flow rate and concentration. Engineering assessment...

40 CFR 63.526 - Monitoring requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... vent. (D) Design analysis based on accepted chemical engineering principles, measurable process.... (i) For the purpose of determining de minimis status for emission points, engineering assessment may... operating conditions expected to yield the highest flow rate and concentration. Engineering assessment...

SHM-Based Probabilistic Fatigue Life Prediction for Bridges Based on FE Model Updating

PubMed Central

Lee, Young-Joo; Cho, Soojin

2016-01-01

Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and evaluate the long-term structural performance of bridges. For example, SHM data can be used to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as mode shapes and natural frequencies, based on the ambient vibration under passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal properties; and (3) predicting the probabilistic fatigue life using the updated FE model. The proposed method is demonstrated by application to a numerical model of a bridge, and the impact of FE model updating on the bridge fatigue life is discussed. PMID:26950125

The knowledge-based framework for a nuclear power plant operator advisor

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

Miller, D.W.; Hajek, B.K.

1989-01-01

An important facet in the design, development, and evaluation of aids for complex systems is the identification of the tasks performed by the operator. Operator aids utilizing artificial intelligence, or more specifically knowledge-based systems, require identification of these tasks in the context of a knowledge-based framework. In this context, the operator responses to the plant behavior are to monitor and comprehend the state of the plant, identify normal and abnormal plant conditions, diagnose abnormal plant conditions, predict plant response to specific control actions, and select the best available control action, implement a feasible control action, monitor system response to themore » control action, and correct for any inappropriate responses. These tasks have been identified to formulate a knowledge-based framework for an operator advisor under development at Ohio State University that utilizes the generic task methodology proposed by Chandrasekaran. The paper lays the foundation to identify the responses as a knowledge-based set of tasks in accordance with the expected human operator responses during an event. Initial evaluation of the expert system indicates the potential for an operator aid that will improve the operator's ability to respond to both anticipated and unanticipated events.« less

Assessment of fire effects based on Forest Inventory and Analysis data and a long-term fire mapping data set

Treesearch

John D. Shaw; Sara A. Goeking; James Menlove; Charles E. Werstak

2017-01-01

Integration of Forest Inventory and Analysis (FIA) plot data with Monitoring Trends in Burn Severity (MTBS) data can provide new information about fire effects on forests. This integration allowed broad-scale assessment of the cover types burned in large fires, the relationship between prefire stand conditions and fire severity, and postfire stand conditions. Of the 42...

Using secondary metabolites in the monitoring of the condition of tree stands under industrial pollution

Treesearch

L. L. Fuksman

2000-01-01

The aim of this paper is to determine tile optimal physiological indicator in diagnosing the condition of tree stands under the stress of industrial pollution. Based on experimental results of the fumigation on pine seedlings with sulphur dioxide, acid rain treatment, and the effect of heavy metals on the seedlings, it is reasonable to use the secondary substances or...

Polyspectral signal analysis techniques for condition based maintenance of helicopter drive-train system

NASA Astrophysics Data System (ADS)

Hassan Mohammed, Mohammed Ahmed

For an efficient maintenance of a diverse fleet of air- and rotorcraft, effective condition based maintenance (CBM) must be established based on rotating components monitored vibration signals. In this dissertation, we present theory and applications of polyspectral signal processing techniques for condition monitoring of critical components in the AH-64D helicopter tail rotor drive train system. Currently available vibration-monitoring tools are mostly built around auto- and cross-power spectral analysis which have limited performance in detecting frequency correlations higher than second order. Studying higher order correlations and their Fourier transforms, higher order spectra, provides more information about the vibration signals which helps in building more accurate diagnostic models of the mechanical system. Based on higher order spectral analysis, different signal processing techniques are developed to assess health conditions of different critical rotating-components in the AH-64D helicopter drive-train. Based on cross-bispectrum, quadratic nonlinear transfer function is presented to model second order nonlinearity in a drive-shaft running between the two hanger bearings. Then, quadratic-nonlinearity coupling coefficient between frequency harmonics of the rotating shaft is used as condition metric to study different seeded shaft faults compared to baseline case, namely: shaft misalignment, shaft imbalance, and combination of shaft misalignment and imbalance. The proposed quadratic-nonlinearity metric shows better capabilities in distinguishing the four studied shaft settings than the conventional linear coupling based on cross-power spectrum. We also develop a new concept of Quadratic-Nonlinearity Power-Index spectrum, QNLPI(f), that can be used in signal detection and classification, based on bicoherence spectrum. The proposed QNLPI(f) is derived as a projection of the three-dimensional bicoherence spectrum into two-dimensional spectrum that quantitatively describes how much of the mean square power at certain frequency f is generated due to nonlinear quadratic interaction between different frequency components. The proposed index, QNLPI(f), can be used to simplify the study of bispectrum and bicoherence signal spectra. It also inherits useful characteristics from the bicoherence such as high immunity to additive Gaussian noise, high capability of nonlinear-systems identifications, and amplification invariance. The quadratic-nonlinear power spectral density PQNL(f) and percentage of quadratic nonlinear power PQNLP are also introduced based on the QNLPI(f). Concept of the proposed indices and their computational considerations are discussed first using computer generated data, and then applied to real-world vibration data to assess health conditions of different rotating components in the drive train including drive-shaft, gearbox, and hanger bearing faults. The QNLPI(f) spectrum enables us to gain more details about nonlinear harmonic generation patterns that can be used to distinguish between different cases of mechanical faults, which in turn helps to gaining more diagnostic/prognostic capabilities.

Bacteriophage-based Probiotic Preparation for Managing Shigella Infections

DTIC Science & Technology

2015-04-16

for a probiotic preparation – based on naturally occurring bacteriophages – as a way to condition the GI tract’s microflora gently and favorably...10-Apr-2013 Approved for Public Release; Distribution Unlimited Final Report: Bacteriophage-based Probiotic Preparation for Managing Shigella...Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Phage, Shigella, probiotics REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S

AgroClimate: Simulating and Monitoring the Risk of Extreme Weather Events from a Crop Phenology Perspective

NASA Astrophysics Data System (ADS)

Fraisse, C.; Pequeno, D.; Staub, C. G.; Perry, C.

2016-12-01

Climate variability, particularly the occurrence of extreme weather conditions such as dry spells and heat stress during sensitive crop developmental phases can substantially increase the prospect of reduced crop yields. Yield losses or crop failure risk due to stressful weather conditions vary mainly due to stress severity and exposure time and duration. The magnitude of stress effects is also crop specific, differing in terms of thresholds and adaptation to environmental conditions. To help producers in the Southeast USA mitigate and monitor the risk of crop losses due to extreme weather events we developed a web-based tool that evaluates the risk of extreme weather events during the season taking into account the crop development stages. Producers can enter their plans for the upcoming season in a given field (e.g. crop, variety, planting date, acreage etc.), select or not a specific El Nino Southern Oscillation (ENSO) phase, and will be presented with the probabilities (ranging from 0 -100%) of extreme weather events occurring during sensitive phases of the growing season for the selected conditions. The DSSAT models CERES-Maize, CROPGRO-Soybean, CROPGRO-Cotton, and N-Wheat phenology models have been translated from FORTRAN to a standalone versions in R language. These models have been tested in collaboration with Extension faculty and producers during the 2016 season and their usefulness for risk mitigation and monitoring evaluated. A companion AgroClimate app was also developed to help producers track and monitor phenology development during the cropping season.

Intelligent, Self-Diagnostic Thermal Protection System for Future Spacecraft

NASA Technical Reports Server (NTRS)

Hyers, Robert W.; SanSoucie, Michael P.; Pepyne, David; Hanlon, Alaina B.; Deshmukh, Abhijit

2005-01-01

The goal of this project is to provide self-diagnostic capabilities to the thermal protection systems (TPS) of future spacecraft. Self-diagnosis is especially important in thermal protection systems (TPS), where large numbers of parts must survive extreme conditions after weeks or years in space. In-service inspections of these systems are difficult or impossible, yet their reliability must be ensured before atmospheric entry. In fact, TPS represents the greatest risk factor after propulsion for any transatmospheric mission. The concepts and much of the technology would be applicable not only to the Crew Exploration Vehicle (CEV), but also to ablative thermal protection for aerocapture and planetary exploration. Monitoring a thermal protection system on a Shuttle-sized vehicle is a daunting task: there are more than 26,000 components whose integrity must be verified with very low rates of both missed faults and false positives. The large number of monitored components precludes conventional approaches based on centralized data collection over separate wires; a distributed approach is necessary to limit the power, mass, and volume of the health monitoring system. Distributed intelligence with self-diagnosis further improves capability, scalability, robustness, and reliability of the monitoring subsystem. A distributed system of intelligent sensors can provide an assurance of the integrity of the system, diagnosis of faults, and condition-based maintenance, all with provable bounds on errors.

Recommendations Service for Chronic Disease Patient in Multimodel Sensors Home Environment

PubMed Central

Hussain, Maqbool; Ali, Taqdir; Khan, Wajahat Ali; Afzal, Muhammad; Latif, Khalid

2015-01-01

Abstract With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC3). SC3 services were limited to monitoring ADL of elderly people with Alzheimer's disease and providing non-medication recommendations to the patient. In this article, we propose a system called the Smart Clinical Decision Support System (CDSS) as an integral part of the SC3 platform. Using the Smart CDSS, patients are provided with access to medication recommendations of expert physicians. Physicians are provided with an interface to create clinical knowledge for medication recommendations and to observe the patient's condition. The clinical knowledge created by physicians as the knowledge base of the Smart CDSS produces recommendations to the caregiver for medications based on each patient's symptoms. PMID:25559934

Recommendations service for chronic disease patient in multimodel sensors home environment.

PubMed

Hussain, Maqbool; Ali, Taqdir; Khan, Wajahat Ali; Afzal, Muhammad; Lee, Sungyoung; Latif, Khalid

2015-03-01

With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC(3)). SC(3) services were limited to monitoring ADL of elderly people with Alzheimer's disease and providing non-medication recommendations to the patient. In this article, we propose a system called the Smart Clinical Decision Support System (CDSS) as an integral part of the SC(3) platform. Using the Smart CDSS, patients are provided with access to medication recommendations of expert physicians. Physicians are provided with an interface to create clinical knowledge for medication recommendations and to observe the patient's condition. The clinical knowledge created by physicians as the knowledge base of the Smart CDSS produces recommendations to the caregiver for medications based on each patient's symptoms.

Reporters to monitor cellular MMP12 activity

NASA Astrophysics Data System (ADS)

Cobos-Correa, Amanda; Mall, Marcus A.; Schultz, Carsten

2010-02-01

Macrophage elastase, also called MMP12, belongs to a family of proteolytic enzymes whose best known physiological function is the remodeling of the extracellular matrix. Under certain pathological conditions, including inflammation, chronic overexpression of MMP12 has been observed and its elevated proteolytic activity has been suggested to be the cause of pulmonary emphysema. However, it was until recently impossible to monitor the activity of MMP12 under disease conditions, mainly due to a lack of detection methods. Recent development of new reporters for monitoring MMP12 activity in living cells, such as LaRee1, provided novel insights into the pathobiology of MMP12 in pulmonary inflammation.1 In the future, these reporters might contribute to improved diagnosis and in finding better treatments for chronic inflammatory lung diseases and emphysema. Our approach for visualizing MMP12 activity is based on peptidic, membrane-targeted FRET (Foerster Resonance Energy Transfer) reporters. Here we describe a set of new reporters containing different fluorophore pairs as well as modifications in the membrane-targeting lipid moiety. We studied the influence of these modifications on reporter performance and the reporter mobility on live cell membranes by FRAP (fluorescence recovery after photobleaching). Finally, we generated several new fluorescently labeled MMP inhibitors based on the peptidic reporter structures as prototypes for future tools to inhibit and monitor MMP activity at the same time.

Assessing Self-Awareness through Gaze Agency

PubMed Central

Crespi, Sofia Allegra; de’Sperati, Claudio

2016-01-01

We define gaze agency as the awareness of the causal effect of one’s own eye movements in gaze-contingent environments, which might soon become a widespread reality with the diffusion of gaze-operated devices. Here we propose a method for measuring gaze agency based on self-monitoring propensity and sensitivity. In one task, naïf observers watched bouncing balls on a computer monitor with the goal of discovering the cause of concurrently presented beeps, which were generated in real-time by their saccades or by other events (Discovery Task). We manipulated observers’ self-awareness by pre-exposing them to a condition in which beeps depended on gaze direction or by focusing their attention to their own eyes. These manipulations increased propensity to agency discovery. In a second task, which served to monitor agency sensitivity at the sensori-motor level, observers were explicitly asked to detect gaze agency (Detection Task). Both tasks turned out to be well suited to measure both increases and decreases of gaze agency. We did not find evident oculomotor correlates of agency discovery or detection. A strength of our approach is that it probes self-monitoring propensity–difficult to evaluate with traditional tasks based on bodily agency. In addition to putting a lens on this novel cognitive function, measuring gaze agency could reveal subtle self-awareness deficits in pathological conditions and during development. PMID:27812138

[The Jena Anxiety Monitoring List (JAMoL) - a tool for the evidence-based treatment of panic disorder with or without agoraphobia in primary care].

PubMed

Hiller, Thomas Stephan; Freytag, Antje; Breitbart, Jörg; Teismann, Tobias; Schöne, Elisabeth; Blank, Wolfgang; Schelle, Mercedes; Vollmar, Horst Christian; Margraf, Jürgen; Gensichen, Jochen

2018-04-01

Behavior therapy-oriented methods are recommended for treating anxiety disorders in primary care. The treatment of patients with long-term conditions can be improved by case management and structured clinical monitoring. The present paper describes the rationale, design and application of the 'Jena Anxiety Monitoring List' (JAMoL), a monitoring tool for the treatment of patients with panic disorder, with or without agoraphobia, in primary care. JAMoL's design was based on established clinical measures, the rationale of exposure-based anxiety treatment, and research on family practice-based case management. After piloting, the JAMoL was used in the clinical study 'Jena-PARADISE' (ISRCTN64669297), where non-physician practice staff monitored patients with panic disorder by telephone. Using semi-structured interviews in concomitant studies, study participants were asked about the instrument's functionality. The JAMoL assesses the severity of anxiety symptoms (6 items) as well as the patient's adherence to therapy (4 items) and fosters the case management-related information exchange (3 items). An integrated traffic light scheme facilitates the evaluation of monitoring results. Within the clinical study, non-physician practice staff carried out a total of 1,525 JAMoL-supported monitoring calls on 177 patients from 30 primary care practices (median calls per patient: 10 [interquartile range, 9-10]). Qualitative analyses revealed that most practice teams and patients rated the JAMoL as a practicable and treatment-relevant tool. The JAMoL enables primary care practice teams to continuously monitor anxiety symptoms and treatment adherence in patients with panic disorder with or without agoraphobia. Within the behavior therapy-oriented treatment program 'Jena-PARADISE', the JAMoL constitutes an important case management tool. Copyright © 2018. Published by Elsevier GmbH.

Advanced Signal Processing for High Temperatures Health Monitoring of Condensed Water Height in Steam Pipes

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Bar-Cohen, Yoseph; Lee, Hyeong Jae; Takano, Nobuyuki; Bao, Xiaoqi

2013-01-01

An advanced signal processing methodology is being developed to monitor the height of condensed water thru the wall of a steel pipe while operating at temperatures as high as 250deg. Using existing techniques, previous study indicated that, when the water height is low or there is disturbance in the environment, the predicted water height may not be accurate. In recent years, the use of the autocorrelation and envelope techniques in the signal processing has been demonstrated to be a very useful tool for practical applications. In this paper, various signal processing techniques including the auto correlation, Hilbert transform, and the Shannon Energy Envelope methods were studied and implemented to determine the water height in the steam pipe. The results have shown that the developed method provides a good capability for monitoring the height in the regular conditions. An alternative solution for shallow water or no water conditions based on a developed hybrid method based on Hilbert transform (HT) with a high pass filter and using the optimized windowing technique is suggested. Further development of the reported methods would provide a powerful tool for the identification of the disturbances of water height inside the pipe.

Clinical application of pulse transit time and correlation with intrapartum fetal heart rate monitoring: a preliminary study of 18 full-term infants.

PubMed

Kawagoe, Yasuyuki; Sameshima, Hiroshi; Ikenoue, Tsuyomu

2008-07-01

The authors show that pulse transit time and blood pressure are reciprocal in fetal goat models. They applied this technique in clinical settings to correlate changes in pulse transit time with fetal heart rate monitoring patterns and acid-base status. In 18 uncomplicated pregnancies, pulse transit time was obtained from electrocardiograms to pulse oximeter waveform and averaged during each baseline period, defined by the interpretation of fetal heart rate monitoring. According to a > 10% change from the control value, chronological changes were categorized into shortened, unchanged, and prolonged. Pulse transit time was available in 82% +/- 11% of the recordings. In 15 fetuses, 2 (13%) showed prolonged, 7 (47%) showed shortened, and 6 (40%) showed unchanged conditions. Comparisons of the shortened and unchanged categories revealed that severe variable deceleration was significantly increased, and half or more fetuses showed hypoxemia in the shortened category. Shortening of pulse transit time, theoretically indicating a hypertensive condition, was more frequently associated with severe variable decelerations, suggesting that the pulse transit time may supplement the interpretation of fetal heart rate monitoring.

Strengthening Agricultural Decisions in Countries at Risk of Food Insecurity: The GEOGLAM Crop Monitor for Early Warning

NASA Astrophysics Data System (ADS)

Becker-Reshef, I.; Barker, B.; McGaughey, K.; Humber, M. L.; Sanchez, A.; Justice, C. O.; Rembold, F.; Verdin, J. P.

2016-12-01

Timely, reliable information on crop conditions, and prospects at the subnational scale, is critical for making informed policy and agricultural decisions for ensuring food security, particularly for the most vulnerable countries. However, such information is often incomplete or lacking. As such, the Crop Monitor for Early Warning (CM for EW) was developed with the goal to reduce uncertainty and strengthen decision support by providing actionable information on a monthly basis to national, regional and global food security agencies through timely consensus assessments of crop conditions. This information is especially critical in recent years, given the extreme weather conditions impacting food supplies including the most recent El Nino event. This initiative brings together the main international food security monitoring agencies and organizations to develop monthly crop assessments based on satellite observations, meteorological information, field observations and ground reports, which reflect an international consensus. This activity grew out of the successful Crop Monitor for the G20 Agricultural Market Information System (AMIS), which provides operational monthly crop assessments of the main producing countries of the world. The CM for EW was launched in February 2016 and has already become a trusted source of information internationally and regionally. Its assessments have been featured in a large number of news articles, reports, and press releases, including a joint statement by the USAID's FEWS NET, UN World Food Program, European Commission Joint Research Center, and the UN Food and Agriculture Organziation, on the devastating impacts of the southern African drought due to El Nino. One of the main priorities for this activity going forward is to expand its partnership with regional and national monitoring agencies, and strengthen capacity for national crop condition assessments.

Condition Based vs. Time Based Maintenance: Case Study on Hypergolic Pumps

NASA Technical Reports Server (NTRS)

Gibson, Lewis J.

2007-01-01

Two Pad 39B Ox pumps were monitored with the Baker Instruments Explorer Motor tester. Using the torque spectrum it was determined that Ox pump #2 had a significant peak at a frequency, which indicated lubricant fluid whirl. Similar testing on Ox pump #1 didn't indicate this peak, an indication that this pump was in good mechanical condition. Subsequent disassembly of both motors validated these findings. Ox pump #2 rear bearing showed significant wear, the front bearing showed little wear. Ox pump #1 was still within manufacturers tolerances.

Arduino Based Infant Monitoring System

NASA Astrophysics Data System (ADS)

Farhanah Mohamad Ishak, Daing Noor; Jamil, Muhammad Mahadi Abdul; Ambar, Radzi

2017-08-01

This paper proposes a system for monitoring infant in an incubator and records the relevant data into a computer. The data recorded by the system can be further referred by the neonatal intensive care unit (NICU) personnel for diagnostic or research purposes. The study focuses on designing the monitoring system that consists of an incubator equipped with humidity sensor to measure the humidity level, and a pulse sensor that can be attached on an infant placed inside the incubator to monitor infant’s heart pulse. The measurement results which are the pulse rate and humidity level are sent to the PC via Arduino microcontroller. The advantage of this system will be that in the future, it may also enable doctors to closely monitor the infant condition through local area network and internet. This work is aimed as an example of an application that contributes towards remote tele-health monitoring system.

Aircraft signal definition for flight safety system monitoring system

NASA Technical Reports Server (NTRS)

Gibbs, Michael (Inventor); Omen, Debi Van (Inventor)

2003-01-01

A system and method compares combinations of vehicle variable values against known combinations of potentially dangerous vehicle input signal values. Alarms and error messages are selectively generated based on such comparisons. An aircraft signal definition is provided to enable definition and monitoring of sets of aircraft input signals to customize such signals for different aircraft. The input signals are compared against known combinations of potentially dangerous values by operational software and hardware of a monitoring function. The aircraft signal definition is created using a text editor or custom application. A compiler receives the aircraft signal definition to generate a binary file that comprises the definition of all the input signals used by the monitoring function. The binary file also contains logic that specifies how the inputs are to be interpreted. The file is then loaded into the monitor function, where it is validated and used to continuously monitor the condition of the aircraft.

Developments in seismic monitoring for risk reduction

USGS Publications Warehouse

Celebi, M.

2007-01-01

This paper presents recent state-of-the-art developments to obtain displacements and drift ratios for seismic monitoring and damage assessment of buildings. In most cases, decisions on safety of buildings following seismic events are based on visual inspections of the structures. Real-time instrumental measurements using GPS or double integration of accelerations, however, offer a viable alternative. Relevant parameters, such as the type of connections and structural characteristics (including storey geometry), can be estimated to compute drifts corresponding to several pre-selected threshold stages of damage. Drift ratios determined from real-time monitoring can then be compared to these thresholds in order to estimate damage conditions drift ratios. This approach is demonstrated in three steel frame buildings in San Francisco, California. Recently recorded data of strong shaking from these buildings indicate that the monitoring system can be a useful tool in rapid assessment of buildings and other structures following an earthquake. Such systems can also be used for risk monitoring, as a method to assess performance-based design and analysis procedures, for long-term assessment of structural characteristics of a building, and as a possible long-term damage detection tool.

In-situ monitoring of H2O2 degradation by live cells using voltammetric detection in a lab-on-valve system.

PubMed

Lähdesmäki, Ilkka; Park, Young K; Carroll, Andrea D; Decuir, Michael; Ruzicka, Jaromir

2007-08-01

This paper describes a method for monitoring the degradation of hydrogen peroxide by cells immobilized on a beaded support. The detection is based on the voltammetric reduction of hydrogen peroxide on a mercury film working electrode, whilst combining the concept of sequential injection (SI) with the lab-on-valve (LOV) manifold allows the measurements to be carried out in real time and automatically, in well-defined conditions. The method is shown to be capable of simultaneously monitoring hydrogen peroxide in the 10-1000 microM range and oxygen in the 160-616 microM range. A correction algorithm has been used to ensure reliable H2O2 results in the presence of varying oxygen levels. The method has been successfully applied to monitoring the degradation of H2O2 by wild-type cells and by catalase-overexpressing mouse embryonic fibroblasts. Since the technique allows the monitoring of the initial response rate, it provides data not accessible by current methods that are end-point-based measurements.

Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing, China

NASA Astrophysics Data System (ADS)

Chen, Hui; Wu, Wei; Liu, Hong-Bin

2018-04-01

Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.

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.

Examining Big Brother's Purpose for Using Electronic Performance Monitoring

ERIC Educational Resources Information Center

Bartels, Lynn K.; Nordstrom, Cynthia R.

2012-01-01

We examined whether the reason offered for electronic performance monitoring (EPM) influenced participants' performance, stress, motivation, and satisfaction. Participants performed a data-entry task in one of five experimental conditions. In one condition, participants were not electronically monitored. In the remaining conditions, participants…

Smart homes and home health monitoring technologies for older adults: A systematic review.

PubMed

Liu, Lili; Stroulia, Eleni; Nikolaidis, Ioanis; Miguel-Cruz, Antonio; Rios Rincon, Adriana

2016-07-01

Around the world, populations are aging and there is a growing concern about ways that older adults can maintain their health and well-being while living in their homes. The aim of this paper was to conduct a systematic literature review to determine: (1) the levels of technology readiness among older adults and, (2) evidence for smart homes and home-based health-monitoring technologies that support aging in place for older adults who have complex needs. We identified and analyzed 48 of 1863 relevant papers. Our analyses found that: (1) technology-readiness level for smart homes and home health monitoring technologies is low; (2) the highest level of evidence is 1b (i.e., one randomized controlled trial with a PEDro score ≥6); smart homes and home health monitoring technologies are used to monitor activities of daily living, cognitive decline and mental health, and heart conditions in older adults with complex needs; (3) there is no evidence that smart homes and home health monitoring technologies help address disability prediction and health-related quality of life, or fall prevention; and (4) there is conflicting evidence that smart homes and home health monitoring technologies help address chronic obstructive pulmonary disease. The level of technology readiness for smart homes and home health monitoring technologies is still low. The highest level of evidence found was in a study that supported home health technologies for use in monitoring activities of daily living, cognitive decline, mental health, and heart conditions in older adults with complex needs. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Global, long-term surface reflectance records from Landsat

USDA-ARS?s Scientific Manuscript database

Global, long-term monitoring of changes in Earth’s land surface requires quantitative comparisons of satellite images acquired under widely varying atmospheric conditions. Although physically based estimates of surface reflectance (SR) ultimately provide the most accurate representation of Earth’s s...

42 CFR 494.90 - Condition: Patient plan of care.

Code of Federal Regulations, 2010 CFR

2010-10-01

...-based professionally-accepted clinical nutrition indicators may be monitored, as appropriate. (3... achieve and sustain the clinically appropriate hemoglobin/hematocrit level. The patient's hemoglobin... is a change in transplant candidate status. (d) Standard: Patient education and training. The patient...

Multimetric Fish Indices for Midcontinent (USA) Great Rivers

EPA Science Inventory

As part of the Environmental Monitoring and Assessment Program for Great River Ecosystems we developed a fish-assemblage based multimetric index (Great River Fish Index,GRFIn) as an indicator of ecological conditions in the Lower Missouri, impounded Upper Mississippi, unimpounded...

Taking the pulse of a river system: first 20 years

USGS Publications Warehouse

Leake, Linda; Johnson, Barry

2006-01-01

Your doctor would not base decisions for your health care today on one physical examination when you were age three! You would reasonably expect decisions to be based on records from over your lifetime. Likewise, those responsible for monitoring the health of the Upper Mississippi River System want a more comprehensive way to diagnose problems and find treatment options. To begin developing a comprehensive view of the river, the five neighboring states of the Upper Mississippi River System and several Federal agencies formed a partnership in 1986 to monitor river conditions and long-term trends in the Upper Mississippi and Illinois Rivers.

Steel Bar corrosion monitoring based on encapsulated piezoelectric sensors

NASA Astrophysics Data System (ADS)

Xu, Ying; Tang, Tianyou

2018-05-01

The durability of reinforced concrete has a great impact on the structural bearing capacity, while the corrosion of steel bars is the main reason for the degradation of structural durability. In this paper, a new type of encapsulated cement based piezoelectric sensor is developed and its working performance is verified. The consistency of the finite element simulation and the experimental results shows the feasibility of monitoring the corrosion of steel bars using encapsulated piezoelectric sensors. The research results show that the corrosion conditions of the steel bars can be determined by the relative amplitude of the measured signal through the encapsulated piezoelectric sensor.

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.

Monitoring rangeland dynamics in Senegal with advanced very high resolution radiometer data

USGS Publications Warehouse

Tappan, G. Gray; Tyler, Dean J.; Wehde, M. E.; Moore, Donald G.

1992-01-01

Time‐series Normalized Difference Vegetation Index (NDVI) data, computed from Advanced Very High Resolution Radiometer data, are being used by regional and national programs in the African Sahel to monitor seasonal rangeland conditions. The data are often used as indicators of grazing conditions and drought. However, distinguishing rangelands from other vegetation cover types on NDVI images is difficult. A second complication is that rangeland types and their associated productivity vary geographically by soil type. To effectively assess rangeland conditions, seasonal fluctuations (due to climatic cycles) must be isolated from long‐term production characteristics associated with vegetation type and soil differences. Rangeland NDVI dynamics, including qualitative assessments of rangeland production, and the timing and length of the growing season in Senegal were examined by using 7.4‐km global area coverage satellite data. Analyses were based on 10‐day NDVI composite image data from 1982 through 1989. The NDVI image data were stratified by rangeland and soil polygons derived from locally available resource maps. Time‐series NDVI statistics were calculated from the resource polygons that had been interpreted into high, medium, and low production rangelands. Analysts monitoring rangeland conditions can better identify seasonal anomalies such as drought by comparing production potential within homogeneous; resource polygons with the current NDVI data.

Continuous and embedded solutions for SHM of concrete structures using changing electrical potential in self-sensing cement-based composites

NASA Astrophysics Data System (ADS)

Downey, Austin; Garcia-Macias, Enrique; D'Alessandro, Antonella; Laflamme, Simon; Castro-Triguero, Rafael; Ubertini, Filippo

2017-04-01

Interest in the concept of self-sensing structural materials has grown in recent years due to its potential to enable continuous low-cost monitoring of next-generation smart-structures. The development of cement-based smart sensors appears particularly well suited for monitoring applications due to their numerous possible field applications, their ease of use and long-term stability. Additionally, cement-based sensors offer a unique opportunity for structural health monitoring of civil structures because of their compatibility with new or existing infrastructure. Particularly, the addition of conductive carbon nanofillers into a cementitious matrix provides a self-sensing structural material with piezoresistive characteristics sensitive to deformations. The strain-sensing ability is achieved by correlating the external loads with the variation of specific electrical parameters, such as the electrical resistance or impedance. Selection of the correct electrical parameter for measurement to correlate with features of interest is required for the condition assessment task. In this paper, we investigate the potential of using altering electrical potential in cement-based materials doped with carbon nanotubes to measure strain and detect damage in concrete structures. Experimental validation is conducted on small-scale specimens including a steel-reinforced beam of conductive cement paste. Comparisons are made with constant electrical potential and current methods commonly found in the literature. Experimental results demonstrate the ability of the changing electrical potential at detecting features important for assessing the condition of a structure.

Hydrochemical processes in lowland rivers: insights from in situ, high-resolution monitoring

NASA Astrophysics Data System (ADS)

Wade, A. J.; Palmer-Felgate, E. J.; Halliday, S. J.; Skeffington, R. A.; Loewenthal, M.; Jarvie, H. P.; Bowes, M. J.; Greenway, G. M.; Haswell, S. J.; Bell, I. M.; Joly, E.; Fallatah, A.; Neal, C.; Williams, R. J.; Gozzard, E.; Newman, J. R.

2012-11-01

This paper introduces new insights into the hydrochemical functioning of lowland river systems using field-based spectrophotometric and electrode technologies. The streamwater concentrations of nitrogen species and phosphorus fractions were measured at hourly intervals on a continuous basis at two contrasting sites on tributaries of the River Thames - one draining a rural catchment, the River Enborne, and one draining a more urban system, The Cut. The measurements complement those from an existing network of multi-parameter water quality sondes maintained across the Thames catchment and weekly monitoring based on grab samples. The results of the sub-daily monitoring show that streamwater phosphorus concentrations display highly complex dynamics under storm conditions dependent on the antecedent catchment wetness, and that diurnal phosphorus and nitrogen cycles occur under low flow conditions. The diurnal patterns highlight the dominance of sewage inputs in controlling the streamwater phosphorus and nitrogen concentrations at low flows, even at a distance of 7 km from the nearest sewage treatment works in the rural River Enborne. The time of sample collection is important when judging water quality against ecological thresholds or standards. An exhaustion of the supply of phosphorus from diffuse and multiple septic tank sources during storm events was evident and load estimation was not improved by sub-daily monitoring beyond that achieved by daily sampling because of the eventual reduction in the phosphorus mass entering the stream during events. The results highlight the utility of sub-daily water quality measurements and the discussion considers the practicalities and challenges of in situ, sub-daily monitoring.

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.

Multimodal Imaging and Lighting Bias Correction for Improved μPAD-based Water Quality Monitoring via Smartphones

NASA Astrophysics Data System (ADS)

McCracken, Katherine E.; Angus, Scott V.; Reynolds, Kelly A.; Yoon, Jeong-Yeol

2016-06-01

Smartphone image-based sensing of microfluidic paper analytical devices (μPADs) offers low-cost and mobile evaluation of water quality. However, consistent quantification is a challenge due to variable environmental, paper, and lighting conditions, especially across large multi-target μPADs. Compensations must be made for variations between images to achieve reproducible results without a separate lighting enclosure. We thus developed a simple method using triple-reference point normalization and a fast-Fourier transform (FFT)-based pre-processing scheme to quantify consistent reflected light intensity signals under variable lighting and channel conditions. This technique was evaluated using various light sources, lighting angles, imaging backgrounds, and imaging heights. Further testing evaluated its handle of absorbance, quenching, and relative scattering intensity measurements from assays detecting four water contaminants - Cr(VI), total chlorine, caffeine, and E. coli K12 - at similar wavelengths using the green channel of RGB images. Between assays, this algorithm reduced error from μPAD surface inconsistencies and cross-image lighting gradients. Although the algorithm could not completely remove the anomalies arising from point shadows within channels or some non-uniform background reflections, it still afforded order-of-magnitude quantification and stable assay specificity under these conditions, offering one route toward improving smartphone quantification of μPAD assays for in-field water quality monitoring.

Rapid Prototyping of a Smart Device-based Wireless Reflectance Photoplethysmograph

PubMed Central

Ghamari, M.; Aguilar, C.; Soltanpur, C.; Nazeran, H.

2017-01-01

This paper presents the design, fabrication, and testing of a wireless heart rate (HR) monitoring device based on photoplethysmography (PPG) and smart devices. PPG sensors use infrared (IR) light to obtain vital information to assess cardiac health and other physiologic conditions. The PPG data that are transferred to a computer undergo further processing to derive the Heart Rate Variability (HRV) signal, which is analyzed to generate quantitative markers of the Autonomic Nervous System (ANS). The HRV signal has numerous monitoring and diagnostic applications. To this end, wireless connectivity plays an important role in such biomedical instruments. The photoplethysmograph consists of an optical sensor to detect the changes in the light intensity reflected from the illuminated tissue, a signal conditioning unit to prepare the reflected light for further signal conditioning through amplification and filtering, a low-power microcontroller to control and digitize the analog PPG signal, and a Bluetooth module to transmit the digital data to a Bluetooth-based smart device such as a tablet. An Android app is then used to enable the smart device to acquire and digitally display the received analog PPG signal in real-time on the smart device. This article is concluded with the prototyping of the wireless PPG followed by the verification procedures of the PPG and HRV signals acquired in a laboratory environment. PMID:28959119

Monitoring physiology and behavior using Android in phobias.

PubMed

Cruz, Telmo; Brás, Susana; Soares, Sandra C; Fernandes, José Maria

2015-08-01

In this paper, we present an Android-based system Application - AWARE - for the assessment of the person's physiology and behavior outside of the laboratory. To accomplish this purpose, AWARE delivers context dependent audio-visual stimuli, embedded into the subject's real-world perception, via marker/vision-based augmented reality (AR) technology. In addition, it employs external measuring resources connected via Bluetooth, as well as the smartphone's integrated resources. It synchronously acquires the experiment's video (camera input with AR overlay), physiologic responses (with a dedicated ECG measuring device) and behavior (through movement and location, with accelerometer/gyroscope and GPS, respectively). Psychological assessment is heavily based on laboratory procedures, even though it is known that these settings disturb the subjects' natural reactions and condition. The major idea of this application is to evaluate the participant condition, mimicking his/her real life conditions. Given that phobias are rather context specific, they represent the ideal candidate for assessing the feasibility of a mobile system application. AWARE allowed presenting AR stimuli (e.g., 3D spiders) and quantifying the subjects' reactions non-intrusively (e.g., heart rate variation) - more emphatic in the phobic volunteer when presented with spider vs non phobic stimulus. Although still a proof of concept, AWARE proved to be flexible, and straightforward to setup, with the potential to support ecologically valid monitoring experiments.

Rapid Prototyping of a Smart Device-based Wireless Reflectance Photoplethysmograph.

PubMed

Ghamari, M; Aguilar, C; Soltanpur, C; Nazeran, H

2016-03-01

This paper presents the design, fabrication, and testing of a wireless heart rate (HR) monitoring device based on photoplethysmography (PPG) and smart devices. PPG sensors use infrared (IR) light to obtain vital information to assess cardiac health and other physiologic conditions. The PPG data that are transferred to a computer undergo further processing to derive the Heart Rate Variability (HRV) signal, which is analyzed to generate quantitative markers of the Autonomic Nervous System (ANS). The HRV signal has numerous monitoring and diagnostic applications. To this end, wireless connectivity plays an important role in such biomedical instruments. The photoplethysmograph consists of an optical sensor to detect the changes in the light intensity reflected from the illuminated tissue, a signal conditioning unit to prepare the reflected light for further signal conditioning through amplification and filtering, a low-power microcontroller to control and digitize the analog PPG signal, and a Bluetooth module to transmit the digital data to a Bluetooth-based smart device such as a tablet. An Android app is then used to enable the smart device to acquire and digitally display the received analog PPG signal in real-time on the smart device. This article is concluded with the prototyping of the wireless PPG followed by the verification procedures of the PPG and HRV signals acquired in a laboratory environment.

A Comparative Experimental Study on the Use of Machine Learning Approaches for Automated Valve Monitoring Based on Acoustic Emission Parameters

NASA Astrophysics Data System (ADS)

Ali, Salah M.; Hui, K. H.; Hee, L. M.; Salman Leong, M.; Al-Obaidi, M. A.; Ali, Y. H.; Abdelrhman, Ahmed M.

2018-03-01

Acoustic emission (AE) analysis has become a vital tool for initiating the maintenance tasks in many industries. However, the analysis process and interpretation has been found to be highly dependent on the experts. Therefore, an automated monitoring method would be required to reduce the cost and time consumed in the interpretation of AE signal. This paper investigates the application of two of the most common machine learning approaches namely artificial neural network (ANN) and support vector machine (SVM) to automate the diagnosis of valve faults in reciprocating compressor based on AE signal parameters. Since the accuracy is an essential factor in any automated diagnostic system, this paper also provides a comparative study based on predictive performance of ANN and SVM. AE parameters data was acquired from single stage reciprocating air compressor with different operational and valve conditions. ANN and SVM diagnosis models were subsequently devised by combining AE parameters of different conditions. Results demonstrate that ANN and SVM models have the same results in term of prediction accuracy. However, SVM model is recommended to automate diagnose the valve condition in due to the ability of handling a high number of input features with low sampling data sets.

FPGA-based smart sensor for drought stress detection in tomato plants using novel physiological variables and discrete wavelet transform.

PubMed

Duarte-Galvan, Carlos; Romero-Troncoso, Rene de J; Torres-Pacheco, Irineo; Guevara-Gonzalez, Ramon G; Fernandez-Jaramillo, Arturo A; Contreras-Medina, Luis M; Carrillo-Serrano, Roberto V; Millan-Almaraz, Jesus R

2014-10-09

Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases, a device capable of detecting and quantifying the impact of drought stress in plants is desirable. This article focuses on testing if the monitoring of physiological process through a gas exchange methodology provides enough information to detect drought stress conditions in plants. The experiment consists of using a set of smart sensors based on Field Programmable Gate Arrays (FPGAs) to monitor a group of plants under controlled drought conditions. The main objective was to use different digital signal processing techniques such as the Discrete Wavelet Transform (DWT) to explore the response of plant physiological processes to drought. Also, an index-based methodology was utilized to compensate the spatial variation inside the greenhouse. As a result, differences between treatments were determined to be independent of climate variations inside the greenhouse. Finally, after using the DWT as digital filter, results demonstrated that the proposed system is capable to reject high frequency noise and to detect drought conditions.

Public Health Practice of Population-Based Birth Defects Surveillance Programs in the United States.

PubMed

Mai, Cara T; Kirby, Russell S; Correa, Adolfo; Rosenberg, Deborah; Petros, Michael; Fagen, Michael C

2016-01-01

Birth defects remain a leading cause of infant mortality in the United States and contribute substantially to health care costs and lifelong disabilities. State population-based surveillance systems have been established to monitor birth defects, yet no recent systematic examination of their efforts in the United States has been conducted. To understand the current population-based birth defects surveillance practices in the United States. The National Birth Defects Prevention Network conducted a survey of US population-based birth defects activities that included questions about operational status, case ascertainment methodology, program infrastructure, data collection and utilization, as well as priorities and challenges for surveillance programs. Birth defects contacts in the United States, including District of Columbia and Puerto Rico, received the survey via e-mail; follow-up reminders via e-mails and telephone were used to ensure a 100% response rate. Forty-three states perform population-based surveillance for birth defects, covering approximately 80% of the live births in the United States. Seventeen primarily use an active case-finding approach and 26 use a passive case-finding approach. These programs all monitor major structural malformations; however, passive case-finding programs more often monitor a broader list of conditions, including developmental conditions and newborn screening conditions. Active case-finding programs more often use clinical reviewers, cover broader pregnancy outcomes, and collect more extensive information, such as family history. More than half of the programs (24 of 43) reported an ability to conduct follow-up studies of children with birth defects. The breadth and depth of information collected at a population level by birth defects surveillance programs in the United States serve as an important data source to guide public health action. Collaborative efforts at the state and national levels can help harmonize data collection and increase utility of birth defects programs.

Aligned carbon nanotube based ultrasonic microtransducers for durability monitoring in civil engineering.

PubMed

Lebental, B; Chainais, P; Chenevier, P; Chevalier, N; Delevoye, E; Fabbri, J-M; Nicoletti, S; Renaux, P; Ghis, A

2011-09-30

Structural health monitoring of porous materials such as concrete is becoming a major component in our resource-limited economy, as it conditions durable exploitation of existing facilities. Durability in porous materials depends on nanoscale features which need to be monitored in situ with nanometric resolution. To address this problem, we put forward an approach based on the development of a new nanosensor, namely a capacitive micrometric ultrasonic transducer whose vibrating membrane is made of aligned single-walled carbon nanotubes (SWNT). Such sensors are meant to be embedded in large numbers within a porous material in order to provide information on its durability by monitoring in situ neighboring individual micropores. In the present paper, we report on the feasibility of the key building block of the proposed sensor: we have fabricated well-aligned, ultra-thin, dense SWNT membranes that show above-nanometer amplitudes of vibration over a large range of frequencies spanning from 100 kHz to 5 MHz.

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.

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures

PubMed Central

Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico

2017-01-01

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions. PMID:29112128

Monitoring the CMS strip tracker readout system

NASA Astrophysics Data System (ADS)

Mersi, S.; Bainbridge, R.; Baulieu, G.; Bel, S.; Cole, J.; Cripps, N.; Delaere, C.; Drouhin, F.; Fulcher, J.; Giassi, A.; Gross, L.; Hahn, K.; Mirabito, L.; Nikolic, M.; Tkaczyk, S.; Wingham, M.

2008-07-01

The CMS Silicon Strip Tracker at the LHC comprises a sensitive area of approximately 200 m2 and 10 million readout channels. Its data acquisition system is based around a custom analogue front-end chip. Both the control and the readout of the front-end electronics are performed by off-detector VME boards in the counting room, which digitise the raw event data and perform zero-suppression and formatting. The data acquisition system uses the CMS online software framework to configure, control and monitor the hardware components and steer the data acquisition. The first data analysis is performed online within the official CMS reconstruction framework, which provides many services, such as distributed analysis, access to geometry and conditions data, and a Data Quality Monitoring tool based on the online physics reconstruction. The data acquisition monitoring of the Strip Tracker uses both the data acquisition and the reconstruction software frameworks in order to provide real-time feedback to shifters on the operational state of the detector, archiving for later analysis and possibly trigger automatic recovery actions in case of errors. Here we review the proposed architecture of the monitoring system and we describe its software components, which are already in place, the various monitoring streams available, and our experiences of operating and monitoring a large-scale system.

On-Line Modal State Monitoring of Slowly Time-Varying Structures

NASA Technical Reports Server (NTRS)

Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

1997-01-01

Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

Multi-parameter monitoring of electrical machines using integrated fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Fabian, Matthias; Hind, David; Gerada, Chris; Sun, Tong; Grattan, Kenneth T. V.

2017-04-01

In this paper a sensor system for multi-parameter electrical machine condition monitoring is reported. The proposed FBG-based system allows for the simultaneous monitoring of machine vibration, rotor speed and position, torque, spinning direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution reduces the component count of conventional sensor systems, i.e., all 48 sensing elements are contained within the machine operated by a single sensing interrogation unit. In this work, the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

KSC00padig049

NASA Image and Video Library

2000-10-01

Jan Zysko (left) and Rich Mizell (right) test a Personal Cabin Pressure Altitude Monitor in an altitude chamber at Tyndall Air Force Base in Florida. Zysko invented the pager-sized monitor that alerts wearers of a potentially dangerous or deteriorating cabin pressure altitude condition, which can lead to life-threatening hypoxia. Zysko is chief of the KSC Spaceport Engineering and Technology directorate's data and electronic systems branch. Mizell is a Shuttle processing engineer. The monitor, which has drawn the interest of such organizations as the Federal Aviation Administration for use in commercial airliners and private aircraft, was originally designed to offer Space Shuttle and Space Station crew members added independent notification about any depressurization

KSC-00padig049

NASA Image and Video Library

2000-10-01

Jan Zysko (left) and Rich Mizell (right) test a Personal Cabin Pressure Altitude Monitor in an altitude chamber at Tyndall Air Force Base in Florida. Zysko invented the pager-sized monitor that alerts wearers of a potentially dangerous or deteriorating cabin pressure altitude condition, which can lead to life-threatening hypoxia. Zysko is chief of the KSC Spaceport Engineering and Technology directorate's data and electronic systems branch. Mizell is a Shuttle processing engineer. The monitor, which has drawn the interest of such organizations as the Federal Aviation Administration for use in commercial airliners and private aircraft, was originally designed to offer Space Shuttle and Space Station crew members added independent notification about any depressurization

Augmented Reality as a Countermeasure for Sleep Deprivation.

PubMed

Baumeister, James; Dorrlan, Jillian; Banks, Siobhan; Chatburn, Alex; Smith, Ross T; Carskadon, Mary A; Lushington, Kurt; Thomas, Bruce H

2016-04-01

Sleep deprivation is known to have serious deleterious effects on executive functioning and job performance. Augmented reality has an ability to place pertinent information at the fore, guiding visual focus and reducing instructional complexity. This paper presents a study to explore how spatial augmented reality instructions impact procedural task performance on sleep deprived users. The user study was conducted to examine performance on a procedural task at six time points over the course of a night of total sleep deprivation. Tasks were provided either by spatial augmented reality-based projections or on an adjacent monitor. The results indicate that participant errors significantly increased with the monitor condition when sleep deprived. The augmented reality condition exhibited a positive influence with participant errors and completion time having no significant increase when sleep deprived. The results of our study show that spatial augmented reality is an effective sleep deprivation countermeasure under laboratory conditions.

The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness

USGS Publications Warehouse

Tadesse, T.; Wardlow, B.; Hayes, M.; Svoboda, M.; Brown, J.

2010-01-01

The vegetation outlook (VegOut) is a geospatial tool for predicting general vegetation condition patterns across large areas. VegOut predicts a standardized seasonal greenness (SSG) measure, which represents a general indicator of relative vegetation health. VegOut predicts SSG values at multiple time steps (two to six weeks into the future) based on the analysis of "historical patterns" (i.e., patterns at each 1 km grid cell and time of the year) of satellite, climate, and oceanic data over an 18-year period (1989 to 2006). The model underlying VegOut capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation, ENSO) expressed over the 18-year data record and also considers several environmental characteristics (e.g., land use/cover type and soils) that influence vegetation's response to weather conditions to produce 1 km maps that depict future general vegetation conditions. VegOut provides regionallevel vegetation monitoring capabilities with local-scale information (e.g., county to sub-county level) that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. In this paper, the VegOut approach is discussed and a case study over the central United States for selected periods of the 2008 growing season is presented to demonstrate the potential of this new tool for assessing and predicting vegetation conditions.

15 CFR 970.522 - Monitoring requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... exploration activities in accordance with a monitoring plan approved and issued by the Administrator as... 15 Commerce and Foreign Trade 3 2014-01-01 2014-01-01 false Monitoring requirements. 970.522..., Conditions and Restrictions Terms, Conditions, and Restrictions § 970.522 Monitoring requirements. Each...

15 CFR 970.522 - Monitoring requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... exploration activities in accordance with a monitoring plan approved and issued by the Administrator as... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Monitoring requirements. 970.522..., Conditions and Restrictions Terms, Conditions, and Restrictions § 970.522 Monitoring requirements. Each...

15 CFR 970.522 - Monitoring requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... exploration activities in accordance with a monitoring plan approved and issued by the Administrator as... 15 Commerce and Foreign Trade 3 2013-01-01 2013-01-01 false Monitoring requirements. 970.522..., Conditions and Restrictions Terms, Conditions, and Restrictions § 970.522 Monitoring requirements. Each...

15 CFR 971.424 - Monitoring requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 15 Commerce and Foreign Trade 3 2013-01-01 2013-01-01 false Monitoring requirements. 971.424...: Terms, Conditions and Restrictions Terms, Conditions and Restrictions § 971.424 Monitoring requirements... recovery activities to: (1) Monitor activities at times, and to the extent, the Administrator deems...

15 CFR 971.424 - Monitoring requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 15 Commerce and Foreign Trade 3 2014-01-01 2014-01-01 false Monitoring requirements. 971.424...: Terms, Conditions and Restrictions Terms, Conditions and Restrictions § 971.424 Monitoring requirements... recovery activities to: (1) Monitor activities at times, and to the extent, the Administrator deems...

15 CFR 970.522 - Monitoring requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... exploration activities in accordance with a monitoring plan approved and issued by the Administrator as... 15 Commerce and Foreign Trade 3 2012-01-01 2012-01-01 false Monitoring requirements. 970.522..., Conditions and Restrictions Terms, Conditions, and Restrictions § 970.522 Monitoring requirements. Each...

15 CFR 971.424 - Monitoring requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 15 Commerce and Foreign Trade 3 2012-01-01 2012-01-01 false Monitoring requirements. 971.424...: Terms, Conditions and Restrictions Terms, Conditions and Restrictions § 971.424 Monitoring requirements... recovery activities to: (1) Monitor activities at times, and to the extent, the Administrator deems...

15 CFR 970.522 - Monitoring requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... exploration activities in accordance with a monitoring plan approved and issued by the Administrator as... 15 Commerce and Foreign Trade 3 2011-01-01 2011-01-01 false Monitoring requirements. 970.522..., Conditions and Restrictions Terms, Conditions, and Restrictions § 970.522 Monitoring requirements. Each...

15 CFR 971.424 - Monitoring requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Monitoring requirements. 971.424...: Terms, Conditions and Restrictions Terms, Conditions and Restrictions § 971.424 Monitoring requirements... recovery activities to: (1) Monitor activities at times, and to the extent, the Administrator deems...

15 CFR 971.424 - Monitoring requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 15 Commerce and Foreign Trade 3 2011-01-01 2011-01-01 false Monitoring requirements. 971.424...: Terms, Conditions and Restrictions Terms, Conditions and Restrictions § 971.424 Monitoring requirements... recovery activities to: (1) Monitor activities at times, and to the extent, the Administrator deems...

Noncontacting measurement technologies for space propulsion condition monitoring

NASA Technical Reports Server (NTRS)

Randall, M. R.; Barkhoudarian, S.; Collins, J. J.; Schwartzbart, A.

1987-01-01

This paper describes four noncontacting measurement technologies that can be used in a turbopump condition monitoring system. The isotope wear analyzer, fiberoptic deflectometer, brushless torque-meter, and fiberoptic pyrometer can be used to monitor component wear, bearing degradation, instantaneous shaft torque, and turbine blade cracking, respectively. A complete turbopump condition monitoring system including these four technologies could predict remaining component life, thus reducing engine operating costs and increasing reliability.

Online Vibration Monitoring of a Water Pump Machine to Detect Its Malfunction Components Based on Artificial Neural Network

NASA Astrophysics Data System (ADS)

Rahmawati, P.; Prajitno, P.

2018-04-01

Vibration monitoring is a measurement instrument used to identify, predict, and prevent failures in machine instruments[6]. This is very needed in the industrial applications, cause any problem with the equipment or plant translates into economical loss and they are mostly monitored component off-line[2]. In this research, a system has been developed to detect the malfunction of the components of Shimizu PS-128BT water pump machine, such as capacitor, bearing and impeller by online measurements. The malfunction components are detected by taking vibration data using a Micro-Electro-Mechanical System(MEMS)-based accelerometer that are acquired by using Raspberry Pi microcomputer and then the data are converted into the form of Relative Power Ratio(RPR). In this form the signal acquired from different components conditions have different patterns. The collected RPR used as the base of classification process for recognizing the damage components of the water pump that are conducted by Artificial Neural Network(ANN). Finally, the damage test result will be sent via text message using GSM module that are connected to Raspberry Pi microcomputer. The results, with several measurement readings, with each reading in 10 minutes duration for each different component conditions, all cases yield 100% of accuracies while in the case of defective capacitor yields 90% of accuracy.

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.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Diagnostics of Technical Condition of Gear Units of Belt Conveyors for the Aggregate of Methods of Nondestructive Testing

NASA Astrophysics Data System (ADS)

Kuzin, Evgeny G.; Gerike, Boris L.; Drozdenko, Yuriy V.; Lupiy, Michael G.; Grigoryeva, Natalya V.

2017-10-01

The article reviews the issues of complex use of methods of technical diagnostics of gearboxes for belt conveyors, with the aim of creating an effective system of maintenance. The article is showing the results of the evaluation of the technical condition of the drives of belt conveyors based on vibration monitoring and thermal parameters, and analysis of lubricating oil.

Improving the Accuracy of Structural Fatigue Life Tracking Through Dynamic Strain Sensor Calibration

DTIC Science & Technology

2011-09-01

strength corrosion resistant 7075 -T6 alloy, and included hinge lugs, a bulkhead, spars, and wing skins that were fastened together using welds, rivets...release, distribution unlimited 13. SUPPLEMENTARY NOTES See also ADA580921. International Workshop on Structural Health Monitoring: From Condition -based...greater than 10% under the same loading conditions [1]. These differences must be accounted for to have acceptable accuracy levels in the ultimate

Improving crop condition monitoring at field scale by using optimal Landsat and MODIS images

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing data at coarse resolution (kilometers) have been widely used in monitoring crop condition for decades. However, crop condition monitoring at field scale requires high resolution data in both time and space. Although a large number of remote sensing instruments with different...

A New Corrosion Sensor to Determine the Start and Development of Embedded Rebar Corrosion Process at Coastal Concrete

PubMed Central

Xu, Chen; Li, Zhiyuan; Jin, Weiliang

2013-01-01

The corrosion of reinforcements induced by chloride has resulted to be one of the most frequent causes of their premature damage. Most corrosion sensors were designed to monitor corrosion state in concrete, such as Anode-Ladder-System and Corrowatch System, which are widely used to monitor chloride ingress in marine concrete. However, the monitoring principle of these corrosion sensors is based on the macro-cell test method, so erroneous information may be obtained, especially from concrete under drying or saturated conditions due to concrete resistance taking control in macro-cell corrosion. In this paper, a fast weak polarization method to test corrosion state of reinforcements based on electrochemical polarization dynamics was proposed. Furthermore, a new corrosion sensor for monitoring the corrosion state of concrete cover was developed based on the proposed test method. The sensor was tested in cement mortar, with dry-wet cycle tests to accelerate the chloride ingress rate. The results show that the corrosion sensor can effectively monitor chloride penetration into concrete with little influence of the relative humidity in the concrete. With a reasonable corrosion sensor electrode arrangement, it seems the Ohm-drop effect measured by EIS can be ignored, which makes the tested electrochemical parameters more accurate. PMID:24084117

A new corrosion sensor to determine the start and development of embedded rebar corrosion process at coastal concrete.

PubMed

Xu, Chen; Li, Zhiyuan; Jin, Weiliang

2013-09-30

The corrosion of reinforcements induced by chloride has resulted to be one of the most frequent causes of their premature damage. Most corrosion sensors were designed to monitor corrosion state in concrete, such as Anode-Ladder-System and Corrowatch System, which are widely used to monitor chloride ingress in marine concrete. However, the monitoring principle of these corrosion sensors is based on the macro-cell test method, so erroneous information may be obtained, especially from concrete under drying or saturated conditions due to concrete resistance taking control in macro-cell corrosion. In this paper, a fast weak polarization method to test corrosion state of reinforcements based on electrochemical polarization dynamics was proposed. Furthermore, a new corrosion sensor for monitoring the corrosion state of concrete cover was developed based on the proposed test method. The sensor was tested in cement mortar, with dry-wet cycle tests to accelerate the chloride ingress rate. The results show that the corrosion sensor can effectively monitor chloride penetration into concrete with little influence of the relative humidity in the concrete. With a reasonable corrosion sensor electrode arrangement, it seems the Ohm-drop effect measured by EIS can be ignored, which makes the tested electrochemical parameters more accurate.

Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

2013-03-01

The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

Industrial application of ultrasound based in-line rheometry: From stationary to pulsating pipe flow of chocolate suspension in precrystallization process

NASA Astrophysics Data System (ADS)

Ouriev, Boris; Windhab, Erich; Braun, Peter; Birkhofer, Beat

2004-10-01

In-line visualization and on-line characterization of nontransparent fluids becomes an important subject for process development in food and nonfood industries. In our work, a noninvasive Doppler ultrasound-based technique is introduced. Such a technique is applied for investigation of nonstationary flow in the chocolate precrystallization process. Unstable flow conditions were induced by abrupt flow interruption and were followed up by strong flow pulsations in the piping system. While relying on available process information, such as absolute pressures and temperatures, no analyses of flow conditions or characterization of suspension properties could possibly be done. It is obvious that chocolate flow properties are sensitive to flow boundary conditions. Therefore, it becomes essential to perform reliable structure state monitoring and particularly in application to nonstationary flow processes. Such flow instabilities in chocolate processing can often lead to failed product quality with interruption of the mainstream production. As will be discussed, a combination of flow velocity profiles, on-line fit into flow profiles, and pressure difference measurement are sufficient for reliable analyses of fluid properties and flow boundary conditions as well as monitoring of the flow state. Analyses of the flow state and flow properties of chocolate suspension are based on on-line measurement of one-dimensional velocity profiles across the flow channel and their on-line characterization with the power-law model. Conclusions about flow boundary conditions were drawn from a calculated velocity standard mean deviation, the parameters of power-law fit into velocity profiles, and volumetric flow rate information.

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

NASA Technical Reports Server (NTRS)

Van Donkelaar, Aaron; Martin, Randall V.; Brauer, Michael; Hsu, N. Christina; Kahn, Ralph A.; Levy, Robert C.; Lyapustin, Alexei; Sayer, Andrew M.; Winker, David M.

2016-01-01

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998-2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

Nondestructive detection of total viable count changes of chilled pork in high oxygen storage condition based on hyperspectral technology

NASA Astrophysics Data System (ADS)

Zheng, Xiaochun; Peng, Yankun; Li, Yongyu; Chao, Kuanglin; Qin, Jianwei

2017-05-01

The plate count method is commonly used to detect the total viable count (TVC) of bacteria in pork, which is timeconsuming and destructive. It has also been used to study the changes of the TVC in pork under different storage conditions. In recent years, many scholars have explored the non-destructive methods on detecting TVC by using visible near infrared (VIS/NIR) technology and hyperspectral technology. The TVC in chilled pork was monitored under high oxygen condition in this study by using hyperspectral technology in order to evaluate the changes of total bacterial count during storage, and then evaluate advantages and disadvantages of the storage condition. The VIS/NIR hyperspectral images of samples stored in high oxygen condition was acquired by a hyperspectral system in range of 400 1100nm. The actual reference value of total bacteria was measured by standard plate count method, and the results were obtained in 48 hours. The reflection spectra of the samples are extracted and used for the establishment of prediction model for TVC. The spectral preprocessing methods of standard normal variate transformation (SNV), multiple scatter correction (MSC) and derivation was conducted to the original reflectance spectra of samples. Partial least squares regression (PLSR) of TVC was performed and optimized to be the prediction model. The results show that the near infrared hyperspectral technology based on 400-1100nm combined with PLSR model can describe the growth pattern of the total bacteria count of the chilled pork under the condition of high oxygen very vividly and rapidly. The results obtained in this study demonstrate that the nondestructive method of TVC based on NIR hyperspectral has great potential in monitoring of edible safety in processing and storage of meat.

Modeling the Soil Water and Energy Balance of a Mixed Grass Rangeland and Evaluating a Soil Water Based Drought Index in Wyoming

NASA Astrophysics Data System (ADS)

Engda, T. A.; Kelleners, T. J.; Paige, G. B.

2013-12-01

Soil water content plays an important role in the complex interaction between terrestrial ecosystems and the atmosphere. Automated soil water content sensing is increasingly being used to assess agricultural drought conditions. A one-dimensional vertical model that calculates incoming solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow-soil heat exchange is applied to calculate water flow and heat transport in a Rangeland soil located near Lingel, Wyoming. The model is calibrated and validated using three years of measured soil water content data. Long-term average soil water content dynamics are calculated using a 30 year historical data record. The difference between long-term average soil water content and observed soil water content is compared with plant biomass to evaluate the usefulness of soil water content as a drought indicator. Strong correlation between soil moisture surplus/deficit and plant biomass may prove our hypothesis that soil water content is a good indicator of drought conditions. Soil moisture based drought index is calculated using modeled and measured soil water data input and is compared with measured plant biomass data. A drought index that captures local drought conditions proves the importance of a soil water monitoring network for Wyoming Rangelands to fill the gap between large scale drought indices, which are not detailed enough to assess conditions at local level, and local drought conditions. Results from a combined soil moisture monitoring and computer modeling, and soil water based drought index soil are presented to quantify vertical soil water flow, heat transport, historical soil water variations and drought conditions in the study area.

FE-ANN based modeling of 3D simple reinforced concrete girders for objective structural health evaluation.

DOT National Transportation Integrated Search

2017-06-01

The structural deterioration of aging infrastructure systems and the costs of repairing these systems is an increasingly important issue worldwide. Structural health monitoring (SHM), most commonly visual inspection and condition rating, has proven t...

Generic Vehicle Speed Models Based On Traffic Simulation: Development and Application (Revision #1)

DOT National Transportation Integrated Search

1994-12-15

The findings of a research project to develop new methods of estimating speeds for inclusion in the Highway Performance Monitoring System (HPMS) Analytical Process are summarized. The paper focuses on the effects of traffic conditions excluding incid...

NATIONAL COASTAL ASSESSMENT

EPA Science Inventory

The purpose of the National Coastal Assessment (NCA) is to estimate the status and trends of the condition of the nation's coastal resources on a state, regional and national basis. Based on NCA monitoring from 1999-2001, 100% of the nation's estuarine waters (at over 2500 locati...

FRAMEWORK FOR STRUCTURAL ONLINE HEALTH MONITORING OF AGING AND DEGRADATION OF SECONDARY PIPING SYSTEMS DUE TO SOME ASPECTS OF EROSION

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

Gribok, Andrei V.; Agarwal, Vivek

This paper describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants (NPPs). The paper also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system, which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies thatmore » could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, in 2017, companies that operate the national nuclear energy fleet started the Delivering the Nuclear Promise Initiative, which is a 3 year program aimed at maintaining operational focus, increasing value, and improving efficiency. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.« less

Application of Smart Solid State Sensor Technology in Aerospace Applications

NASA Technical Reports Server (NTRS)

Hunter, Gary W.; Xu, Jennifer C.; Dungan, L.K.; Makel, D.; Ward, B.; Androjna, D.

2008-01-01

Aerospace applications require a range of chemical sensing technologies to monitor conditions in both space vehicles and aircraft operations. One example is the monitoring of oxygen. For example, monitoring of ambient oxygen (O2) levels is critical to ensuring the health, safety, and performance of humans living and working in space. Oxygen sensors can also be incorporated in detection systems to determine if hazardous leaks are occurring in space propulsion systems and storage facilities. In aeronautic applications, O2 detection has been investigated for fuel tank monitoring. However, as noted elsewhere, O2 is not the only species of interest in aerospace applications with a wide range of species of interest being relevant to understand an environmental or vehicle condition. These include combustion products such as CO, HF, HCN, and HCl, which are related to both the presence of a fire and monitoring of post-fire clean-up operations. This paper discusses the development of an electrochemical cell platform based on a polymer electrolyte, NAFION, and a three-electrode configuration. The approach has been to mature this basic platform for a range of applications and to test this system, combined with "Lick and Stick" electronics, for its viability to monitor an environment related to astronaut crew health and safety applications with an understanding that a broad range of applications can be addressed with a core technology.

In silico vs. Over the Clouds: On-the-Fly Mental State Estimation of Aircraft Pilots, Using a Functional Near Infrared Spectroscopy Based Passive-BCI

PubMed Central

Gateau, Thibault; Ayaz, Hasan; Dehais, Frédéric

2018-01-01

There is growing interest for implementing tools to monitor cognitive performance in naturalistic work and everyday life settings. The emerging field of research, known as neuroergonomics, promotes the use of wearable and portable brain monitoring sensors such as functional near infrared spectroscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. The objective of this study was to implement an on-line passive fNIRS-based brain computer interface to discriminate two levels of working memory load during highly ecological aircraft piloting tasks. Twenty eight recruited pilots were equally split into two groups (flight simulator vs. real aircraft). In both cases, identical approaches and experimental stimuli were used (serial memorization task, consisting in repeating series of pre-recorded air traffic control instructions, easy vs. hard). The results show pilots in the real flight condition committed more errors and had higher anterior prefrontal cortex activation than pilots in the simulator, when completing cognitively demanding tasks. Nevertheless, evaluation of single trial working memory load classification showed high accuracy (>76%) across both experimental conditions. The contributions here are two-fold. First, we demonstrate the feasibility of passively monitoring cognitive load in a realistic and complex situation (live piloting of an aircraft). In addition, the differences in performance and brain activity between the two experimental conditions underscore the need for ecologically-valid investigations. PMID:29867411

In silico vs. Over the Clouds: On-the-Fly Mental State Estimation of Aircraft Pilots, Using a Functional Near Infrared Spectroscopy Based Passive-BCI.

PubMed

Gateau, Thibault; Ayaz, Hasan; Dehais, Frédéric

2018-01-01

There is growing interest for implementing tools to monitor cognitive performance in naturalistic work and everyday life settings. The emerging field of research, known as neuroergonomics, promotes the use of wearable and portable brain monitoring sensors such as functional near infrared spectroscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. The objective of this study was to implement an on-line passive fNIRS-based brain computer interface to discriminate two levels of working memory load during highly ecological aircraft piloting tasks. Twenty eight recruited pilots were equally split into two groups (flight simulator vs. real aircraft). In both cases, identical approaches and experimental stimuli were used (serial memorization task, consisting in repeating series of pre-recorded air traffic control instructions, easy vs. hard). The results show pilots in the real flight condition committed more errors and had higher anterior prefrontal cortex activation than pilots in the simulator, when completing cognitively demanding tasks. Nevertheless, evaluation of single trial working memory load classification showed high accuracy (>76%) across both experimental conditions. The contributions here are two-fold. First, we demonstrate the feasibility of passively monitoring cognitive load in a realistic and complex situation (live piloting of an aircraft). In addition, the differences in performance and brain activity between the two experimental conditions underscore the need for ecologically-valid investigations.

Atmospheric monitoring and model applications at the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Keilhauer, Bianca

2015-03-01

The Pierre Auger Observatory detects high-energy cosmic rays with energies above ˜1017 eV. It is built as a multi-hybrid detector measuring extensive air showers with different techniques. For the reconstruction of extensive air showers, the atmospheric conditions at the site of the Observatory have to be known quite well. This is particularly true for reconstructions based on data obtained by the fluorescence technique. For these data, not only the weather conditions near ground are relevant, most important are altitude-dependent atmospheric profiles. The Pierre Auger Observatory has set up a dedicated atmospheric monitoring programme at the site in the Mendoza province, Argentina. Beyond this, exploratory studies were performed in Colorado, USA, for possible installations in the northern hemisphere. In recent years, the atmospheric monitoring programme at the Pierre Auger Observatory was supplemented by applying data from atmospheric models. Both GDAS and HYSPLIT are developments by the US weather department NOAA and the data are freely available. GDAS is a global model of the atmospheric state parameters on a 1 degree geographical grid, based on real-time measurements and numeric weather predictions, providing a full altitude-dependent data set every 3 hours. HYSPLIT is a powerful tool to track the movement of air masses at various heights, and with it the aerosols. Combining local measurements of the atmospheric state variables and aerosol scattering with the given model data, advanced studies about atmospheric conditions can be performed and high precision air shower reconstructions are achieved.

Integrating NASA Earth Science Enterprise (ESE) Data Into Global Agricultural Decision Support Systems

NASA Astrophysics Data System (ADS)

Teng, W.; Kempler, S.; Chiu, L.; Doraiswamy, P.; Liu, Z.; Milich, L.; Tetrault, R.

2003-12-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of U.S. agricultural products and for global food security. Two major operational users of satellite remote sensing for global crop monitoring are the USDA Foreign Agricultural Service (FAS) and the U.N. World Food Programme (WFP). The primary goal of FAS is to improve foreign market access for U.S. agricultural products. The WFP uses food to meet emergency needs and to support economic and social development. Both use global agricultural decision support systems that can integrate and synthesize a variety of data sources to provide accurate and timely information on global crop conditions. The Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (GES DAAC) has begun a project to provide operational solutions to FAS and WFP, by fully leveraging results from previous work, as well as from existing capabilities of the users. The GES DAAC has effectively used its recently developed prototype TRMM Online Visualization and Analysis System (TOVAS) to provide ESE data and information to the WFP for its agricultural drought monitoring efforts. This prototype system will be evolved into an Agricultural Information System (AIS), which will operationally provide ESE and other data products (e.g., rainfall, land productivity) and services, to be integrated into and thus enhance the existing GIS-based, decision support systems of FAS and WFP. Agriculture-oriented, ESE data products (e.g., MODIS-based, crop condition assessment product; TRMM derived, drought index product) will be input to a crop growth model in collaboration with the USDA Agricultural Research Service, to generate crop condition and yield prediction maps. The AIS will have the capability for remotely accessing distributed data, by being compliant with community-based interoperability standards, enabling easy access to agriculture-related products from other data producers. The AIS? system approach will provide a generic mechanism for easily incorporating new products and making them accessible to users.

Wear detection by means of wavelet-based acoustic emission analysis

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2015-08-01

Wear detection and monitoring during operation are complex and difficult tasks especially for materials under sliding conditions. Due to the permanent contact and repetitive motion, the material surface remains during tests non-accessible for optical inspection so that attrition of the contact partners cannot be easily detected. This paper introduces the relevant scientific components of reliable and efficient condition monitoring system for online detection and automated classification of wear phenomena by means of acoustic emission (AE) and advanced signal processing approaches. The related experiments were performed using a tribological system consisting of two martensitic plates, sliding against each other. High sensitive piezoelectric transducer was used to provide the continuous measurement of AE signals. The recorded AE signals were analyzed mainly by time-frequency analysis. A feature extraction module using a novel combination of Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were used for the first time. A detailed correlation analysis between complex signal characteristics and the surface damage resulting from contact fatigue was investigated. Three wear process stages were detected and could be distinguished. To obtain quantitative and detailed information about different wear phases, the AE energy was calculated using STFT and decomposed into a suitable number of frequency levels. The individual energy distribution and the cumulative AE energy of each frequency components were analyzed using CWT. Results show that the behavior of individual frequency component changes when the wear state changes. Here, specific frequency ranges are attributed to the different wear states. The study reveals that the application of the STFT-/CWT-based AE analysis is an appropriate approach to distinguish and to interpret the different damage states occurred during sliding contact. Based on this results a new generation of condition monitoring systems can be build, able to evaluate automatically the surface condition of machine components with sliding surfaces.

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.

40 CFR Appendix 4 to Subpart A of... - Protocol for the Determination of Degradation of Non-Aqueous Base Fluids in a Marine Closed...

Code of Federal Regulations, 2014 CFR

2014-07-01

... test evaluates base fluid biodegradation rates by monitoring gas production due to microbial... ppm) evaluates the anaerobic (redox) condition of the bottles (dye is blue when oxygen is present... this publication is for descriptive use only, and does not constitute endorsement by EPA or the authors...

40 CFR Appendix 4 to Subpart A of... - Protocol for the Determination of Degradation of Non-Aqueous Base Fluids in a Marine Closed...

Code of Federal Regulations, 2012 CFR

2012-07-01

... test evaluates base fluid biodegradation rates by monitoring gas production due to microbial... ppm) evaluates the anaerobic (redox) condition of the bottles (dye is blue when oxygen is present... this publication is for descriptive use only, and does not constitute endorsement by EPA or the authors...

40 CFR Appendix 4 to Subpart A of... - Protocol for the Determination of Degradation of Non-Aqueous Base Fluids in a Marine Closed...

Code of Federal Regulations, 2013 CFR

2013-07-01

... test evaluates base fluid biodegradation rates by monitoring gas production due to microbial... ppm) evaluates the anaerobic (redox) condition of the bottles (dye is blue when oxygen is present... this publication is for descriptive use only, and does not constitute endorsement by EPA or the authors...

The Modular Borehole Monitoring Program. A research program to optimize well-based monitoring for geologic carbon sequestration

DOE PAGES

Freifeld, Barry; Daley, Tom; Cook, Paul; ...

2014-12-31

Understanding the impacts caused by injection of large volumes of CO 2 in the deep subsurface necessitates a comprehensive monitoring strategy. While surface-based and other remote geophysical methods can provide information on the general morphology of a CO 2 plume, verification of the geochemical conditions and validation of the remote sensing data requires measurements from boreholes that penetrate the storage formation. Unfortunately, the high cost of drilling deep wellbores and deploying instrumentation systems constrains the number of dedicated monitoring borings as well as limits the technologies that can be incorporated in a borehole completion. The objective of the Modular Boreholemore » Monitoring (MBM) Program was to develop a robust suite of well-based tools optimized for subsurface monitoring of CO 2 that could meet the needs of a comprehensive well-based monitoring program. It should have enough flexibility to be easily reconfigured for various reservoir geometries and geologies. The MBM Program sought to provide storage operators with a turn-key fully engineered design that incorporated key technologies, function over the decades long time-span necessary for post-closure reservoir monitoring, and meet industry acceptable risk profiles for deep-well installations. While still within the conceptual design phase of the MBM program, the SECARB Anthropogenic Test in Citronelle, Alabama, USA was identified as a deployment site for our engineered monitoring systems. The initial step in designing the Citronelle MBM system was to down-select from the various monitoring tools available to include technologies that we considered essential to any program. Monitoring methods selected included U-tube geochemical sampling, discrete quartz pressure and temperature gauges, an integrated fibre-optic bundle consisting of distributed temperature and heat-pulse sensing, and a sparse string of conventional 3C-geophones. While not originally planned within the initial MBM work scope, the fibre-optic cable was able to also be used for the emergent technology of distributed acoustic sensing. The MBM monitoring string was installed in March, 2012. To date, the Citronelle MBM instruments continue to operate reliably. Results and lessons learned from the Citronelle MBM deployment are addressed along with examples of data being collected.« less