On the pilot's behavior of detecting a system parameter change
NASA Technical Reports Server (NTRS)
Morizumi, N.; Kimura, H.
1986-01-01
The reaction of a human pilot, engaged in compensatory control, to a sudden change in the controlled element's characteristics is described. Taking the case where the change manifests itself as a variance change of the monitored signal, it is shown that the detection time, defined to be the time elapsed until the pilot detects the change, is related to the monitored signal and its derivative. Then, the detection behavior is modeled by an optimal controller, an optimal estimator, and a variance-ratio test mechanism that is performed for the monitored signal and its derivative. Results of a digital simulation show that the pilot's detection behavior can be well represented by the model proposed here.
Matthews, Stephen G; Miller, Amy L; Clapp, James; Plötz, Thomas; Kyriazakis, Ilias
2016-11-01
Early detection of health and welfare compromises in commercial piggeries is essential for timely intervention to enhance treatment success, reduce impact on welfare, and promote sustainable pig production. Behavioural changes that precede or accompany subclinical and clinical signs may have diagnostic value. Often referred to as sickness behaviour, this encompasses changes in feeding, drinking, and elimination behaviours, social behaviours, and locomotion and posture. Such subtle changes in behaviour are not easy to quantify and require lengthy observation input by staff, which is impractical on a commercial scale. Automated early-warning systems may provide an alternative by objectively measuring behaviour with sensors to automatically monitor and detect behavioural changes. This paper aims to: (1) review the quantifiable changes in behaviours with potential diagnostic value; (2) subsequently identify available sensors for measuring behaviours; and (3) describe the progress towards automating monitoring and detection, which may allow such behavioural changes to be captured, measured, and interpreted and thus lead to automation in commercial, housed piggeries. Multiple sensor modalities are available for automatic measurement and monitoring of behaviour, which require humans to actively identify behavioural changes. This has been demonstrated for the detection of small deviations in diurnal drinking, deviations in feeding behaviour, monitoring coughs and vocalisation, and monitoring thermal comfort, but not social behaviour. However, current progress is in the early stages of developing fully automated detection systems that do not require humans to identify behavioural changes; e.g., through automated alerts sent to mobile phones. Challenges for achieving automation are multifaceted and trade-offs are considered between health, welfare, and costs, between analysis of individuals and groups, and between generic and compromise-specific behaviours. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Thundat, Thomas G.; Wachter, Eric A.
1998-01-01
An improved microcantilever sensor is fabricated with at least one microcantilever attached to a piezoelectric transducer. The microcantilever is partially surface treated with a compound selective substance having substantially exclusive affinity for a targeted compound in a monitored atmosphere. The microcantilever sensor is also provided with a frequency detection means and a bending detection means. The frequency detection means is capable of detecting changes in the resonance frequency of the vibrated microcantilever in the monitored atmosphere. The bending detection means is capable of detecting changes in the bending of the vibrated microcantilever in the monitored atmosphere coactively with the frequency detection means. The piezoelectric transducer is excited by an oscillator means which provides a signal driving the transducer at a resonance frequency inducing a predetermined order of resonance on the partially treated microcantilever. Upon insertion into a monitored atmosphere, molecules of the targeted chemical attach to the treated regions of the microcantilever resulting in a change in oscillating mass as well as a change in microcantilever spring constant thereby influencing the resonant frequency of the microcantilever oscillation. Furthermore, the molecular attachment of the target chemical to the treated regions induce areas of mechanical strain in the microcantilever consistent with the treated regions thereby influencing microcantilever bending. The rate at which the treated microcantilever accumulates the target chemical is a function of the target chemical concentration. Consequently, the extent of microcantilever oscillation frequency change and bending is related to the concentration of target chemical within the monitored atmosphere.
Thundat, T.G.; Wachter, E.A.
1998-02-17
An improved microcantilever sensor is fabricated with at least one microcantilever attached to a piezoelectric transducer. The microcantilever is partially surface treated with a compound selective substance having substantially exclusive affinity for a targeted compound in a monitored atmosphere. The microcantilever sensor is also provided with a frequency detection means and a bending detection means. The frequency detection means is capable of detecting changes in the resonance frequency of the vibrated microcantilever in the monitored atmosphere. The bending detection means is capable of detecting changes in the bending of the vibrated microcantilever in the monitored atmosphere coactively with the frequency detection means. The piezoelectric transducer is excited by an oscillator means which provides a signal driving the transducer at a resonance frequency inducing a predetermined order of resonance on the partially treated microcantilever. Upon insertion into a monitored atmosphere, molecules of the targeted chemical attach to the treated regions of the microcantilever resulting in a change in oscillating mass as well as a change in microcantilever spring constant thereby influencing the resonant frequency of the microcantilever oscillation. Furthermore, the molecular attachment of the target chemical to the treated regions induce areas of mechanical strain in the microcantilever consistent with the treated regions thereby influencing microcantilever bending. The rate at which the treated microcantilever accumulates the target chemical is a function of the target chemical concentration. Consequently, the extent of microcantilever oscillation frequency change and bending is related to the concentration of target chemical within the monitored atmosphere. 16 figs.
NASA Technical Reports Server (NTRS)
Strassberg, Gil; Scanlon, Bridget R.; Rodell, Matthew
2007-01-01
This study presents the first direct comparison of variations in seasonal GWS derived from GRACE TWS and simulated SM with GW-level measurements in a semiarid region. Results showed that variations in GWS and SM are the main sources controlling TWS changes over the High Plains, with negligible storage changes from surface water, snow, and biomass. Seasonal variations in GRACE TWS compare favorably with combined GWS from GW-level measurements (total 2,700 wells, average 1,050 GW-level measurements per season) and simulated SM from the Noah land surface model (R = 0.82, RMSD = 33 mm). Estimated uncertainty in seasonal GRACE-derived TWS is 8 mm, and estimated uncertainty in TWS changes is 11 mm. Estimated uncertainty in SM changes is 11 mm and combined uncertainty for TWS-SM changes is 15 mm. Seasonal TWS changes are detectable in 7 out of 9 monitored periods and maximum changes within a year (e.g. between winter and summer) are detectable in all 5 monitored periods. Grace-derived GWS calculated from TWS-SM generally agrees with estimates based on GW-level measurements (R = 0.58, RMSD = 33 mm). Seasonal TWS-SM changes are detectable in 5 out of the 9 monitored periods and maximum changes are detectable in all 5 monitored periods. Good correspondence between GRACE data and GW-level measurements from the intensively monitored High Plains aquifer validates the potential for using GRACE TWS and simulated SM to monitor GWS changes and aquifer depletion in semiarid regions subjected to intensive irrigation pumpage. This method can be used to monitor regions where large-scale aquifer depletion is ongoing, and in situ measurements are limited, such as the North China Plain or western India. This potential should be enhanced by future advances in GRACE processing, which will improve the spatial and temporal resolution of TWS changes, and will further increase applicability of GRACE data for monitoring GWS.
McAnally, Ken I.; Morris, Adam P.; Best, Christopher
2017-01-01
Metacognitive monitoring and control of situation awareness (SA) are important for a range of safety-critical roles (e.g., air traffic control, military command and control). We examined the factors affecting these processes using a visual change detection task that included representative tactical displays. SA was assessed by asking novice observers to detect changes to a tactical display. Metacognitive monitoring was assessed by asking observers to estimate the probability that they would correctly detect a change, either after study of the display and before the change (judgement of learning; JOL) or after the change and detection response (judgement of performance; JOP). In Experiment 1, observers failed to detect some changes to the display, indicating imperfect SA, but JOPs were reasonably well calibrated to objective performance. Experiment 2 examined JOLs and JOPs in two task contexts: with study-time limits imposed by the task or with self-pacing to meet specified performance targets. JOPs were well calibrated in both conditions as were JOLs for high performance targets. In summary, observers had limited SA, but good insight about their performance and learning for high performance targets and allocated study time appropriately. PMID:28915244
Developing Best Practices for Detecting Change at Marine Renewable Energy Sites
NASA Astrophysics Data System (ADS)
Linder, H. L.; Horne, J. K.
2016-02-01
In compliance with the National Environmental Policy Act (NEPA), an evaluation of environmental effects is mandatory for obtaining permits for any Marine Renewable Energy (MRE) project in the US. Evaluation includes an assessment of baseline conditions and on-going monitoring during operation to determine if biological conditions change relative to the baseline. Currently, there are no best practices for the analysis of MRE monitoring data. We have developed an approach to evaluate and recommend analytic models used to characterize and detect change in biological monitoring data. The approach includes six steps: review current MRE monitoring practices, identify candidate models to analyze data, fit models to a baseline dataset, develop simulated scenarios of change, evaluate model fit to simulated data, and produce recommendations on the choice of analytic model for monitoring data. An empirical data set from a proposed tidal turbine site at Admiralty Inlet, Puget Sound, Washington was used to conduct the model evaluation. Candidate models that were evaluated included: linear regression, time series, and nonparametric models. Model fit diagnostics Root-Mean-Square-Error and Mean-Absolute-Scaled-Error were used to measure accuracy of predicted values from each model. A power analysis was used to evaluate the ability of each model to measure and detect change from baseline conditions. As many of these models have yet to be applied in MRE monitoring studies, results of this evaluation will generate comprehensive guidelines on choice of model to detect change in environmental monitoring data from MRE sites. The creation of standardized guidelines for model selection enables accurate comparison of change between life stages of a MRE project, within life stages to meet real time regulatory requirements, and comparison of environmental changes among MRE sites.
Applicability Assessment of Uavsar Data in Wetland Monitoring: a Case Study of Louisiana Wetland
NASA Astrophysics Data System (ADS)
Zhao, J.; Niu, Y.; Lu, Z.; Yang, J.; Li, P.; Liu, W.
2018-04-01
Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sensing data can be obtained to monitor wetland. UAVSAR is a NASA L-band synthetic aperture radar (SAR) sensor compact pod-mounted polarimetric instrument for interferometric repeat-track observations. Moreover, UAVSAR images can accurately map crustal deformations associated with natural hazards, such as volcanoes and earthquakes. And its polarization agility facilitates terrain and land-use classification and change detection. In this paper, the multi-temporal UAVSAR data are applied for monitoring the wetland change. Using the multi-temporal polarimetric SAR (PolSAR) data, the change detection maps are obtained by unsupervised and supervised method. And the coherence is extracted from the interfometric SAR (InSAR) data to verify the accuracy of change detection map. The experimental results show that the multi-temporal UAVSAR data is fit for wetland monitor.
Improving Aquatic Warbler Population Assessments by Accounting for Imperfect Detection
Oppel, Steffen; Marczakiewicz, Piotr; Lachmann, Lars; Grzywaczewski, Grzegorz
2014-01-01
Monitoring programs designed to assess changes in population size over time need to account for imperfect detection and provide estimates of precision around annual abundance estimates. Especially for species dependent on conservation management, robust monitoring is essential to evaluate the effectiveness of management. Many bird species of temperate grasslands depend on specific conservation management to maintain suitable breeding habitat. One such species is the Aquatic Warbler (Acrocephalus paludicola), which breeds in open fen mires in Central Europe. Aquatic Warbler populations have so far been assessed using a complete survey that aims to enumerate all singing males over a large area. Because this approach provides no estimate of precision and does not account for observation error, detecting moderate population changes is challenging. From 2011 to 2013 we trialled a new line transect sampling monitoring design in the Biebrza valley, Poland, to estimate abundance of singing male Aquatic Warblers. We surveyed Aquatic Warblers repeatedly along 50 randomly placed 1-km transects, and used binomial mixture models to estimate abundances per transect. The repeated line transect sampling required 150 observer days, and thus less effort than the traditional ‘full count’ approach (175 observer days). Aquatic Warbler abundance was highest at intermediate water levels, and detection probability varied between years and was influenced by vegetation height. A power analysis indicated that our line transect sampling design had a power of 68% to detect a 20% population change over 10 years, whereas raw count data had a 9% power to detect the same trend. Thus, by accounting for imperfect detection we increased the power to detect population changes. We recommend to adopt the repeated line transect sampling approach for monitoring Aquatic Warblers in Poland and in other important breeding areas to monitor changes in population size and the effects of habitat management. PMID:24713994
Chew, Emily Y; Clemons, Traci E; Bressler, Susan B; Elman, Michael J; Danis, Ronald P; Domalpally, Amitha; Heier, Jeffrey S; Kim, Judy E; Garfinkel, Richard A
2014-03-01
To evaluate the effects of a home-monitoring device with tele-monitoring compared with standard care in detection of progression to choroidal neovascularization (CNV) associated with age-related macular degeneration (AMD), the leading cause of blindness in the US. Participants, aged 55 to 90 years, at high risk of developing CNV associated with AMD were recruited to the HOme Monitoring of Eye (HOME) Study, an unmasked, multi-center, randomized trial of the ForeseeHome (FH) device plus standard care vs. standard care alone. The FH device utilizes preferential hyperacuity perimetry and tele-monitoring to detect changes in vision function associated with development of CNV, potentially prior to symptom and visual acuity loss. After establishing baseline measurements, subsequent changes on follow-up are detected by the device, causing the monitoring center to alert the clinical center to recall participants for an exam. Standard care consists of instructions for self-monitoring visual changes with subsequent self-report to the clinical center. The primary objective of this study is to determine whether home monitoring plus standard care in comparison with standard care alone, results in earlier detection of incident CNV with better present visual acuity. The primary outcome is the decline in visual acuity at CNV diagnosis from baseline. Detection of CNV prior to substantial vision loss is critical as vision outcome following anti-angiogenic therapy is dependent on the visual acuity at initiation of treatment. HOME Study is the first large scale study to test the use of home tele-monitoring system in the management of AMD patients. Published by Elsevier Inc.
Takase, Mai; Murata, Masataka; Hibi, Kyoko; Huifeng, Ren; Endo, Hideaki
2014-04-01
We developed a wireless monitoring system to monitor fish condition by tracking the change in whole cholesterol concentration. The whole cholesterol concentration of fish is a source of steroid hormones or indicator of immunity level, which makes its detection important for tracking physiological condition of fish. Wireless monitoring system comprises of mediator-type biosensor and wireless transmission device. Biosensor is implantable to fish body, and transmission device is so light, in that fish is allowed to swim freely during monitoring. Cholesterol esterase and oxidase were fixated on to the detection site of biosensor and used to detect the whole cholesterol concentration. However, cholesterol oxidase incorporates oxidation-reduction reaction of oxygen for detection, which concentration fluctuates easily due to change in environmental condition. Meanwhile, mediator-type biosensor enables monitoring of whole cholesterol concentration by using mediator to substitute that oxidation-reduction reaction of oxygen. Characteristic of fabricated mediator-type biosensor was tested. The sensor output current of mediator-type biosensor remained stable compared to output current of non-mediator-type biosensor under fluctuating oxygen concentration of 0-8 ppm, which implied that this sensor is less affected by change in dissolved oxygen concentration. That biosensor was then implanted into fish for wireless monitoring. As a result, approximately 48 h of real-time monitoring was successful.
Detecting Change in Landscape Greenness over Large Areas: An Example for New Mexico, USA
Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can potentially detect large-scale, slow changes (e.g., climate change), as well as more local and rapid changes (e.g., fire, land development). A useful indicator for detecting change i...
Landsat change detection can aid in water quality monitoring
NASA Technical Reports Server (NTRS)
Macdonald, H. C.; Steele, K. F.; Waite, W. P.; Shinn, M. R.
1977-01-01
Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.
Detection and monitoring of invasive exotic plants: a comparison of four sampling methods
Cynthia D. Huebner
2007-01-01
The ability to detect and monitor exotic invasive plants is likely to vary depending on the sampling method employed. Methods with strong qualitative thoroughness for species detection often lack the intensity necessary to monitor vegetation change. Four sampling methods (systematic plot, stratified-random plot, modified Whittaker, and timed meander) in hemlock and red...
Climate driven variability and detectability of temporal trends in low flow indicators for Ireland
NASA Astrophysics Data System (ADS)
Hall, Julia; Murphy, Conor; Harrigan, Shaun
2013-04-01
Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a fixed magnitude are presented. Depending on the indicator selected, the sample variance and trend magnitude very different detection time estimates are obtained and in most cases not within the time required for anticipatory adaptation in the water resources sector. Additionally, the minimum changes in low flow indicators required to be detectable are large and changes are unlikely to be statistically detectable for many years. This means that water management and planning for anticipated future climatic changes will be required to take place without these changes being formally statistically detectable.Waiting for these trends to become formally detectable with the traditional statistical methods might not be an option for water resources management. Within the monitoring network, a considerable difference is apparent between stations in terms of detection times and changes required for detection. The existence of flow monitoring stations showing short detection times for specific indicators confirms the potential for identifying stations that may be first responders to climate induced changes. Identifying sentinel stations can increase the ability to more effectively optimise the deployment of resources for monitoring the influences of climatic change in a hydrometric reference network.
NASA Astrophysics Data System (ADS)
Kanawade, Rajesh; Stelzle, Florian; Schmidt, Michael
This paper presents a novel methodology in early detection of clinical shock by monitoring hemodynamic changes using diffuse reflectance measurement technique. Detailed prototype of the reflectance measurement system and data analysis technique of hemodynamic monitoring was carried out in our laboratory. The real time in-vivo measurements were done from the index finger. This study demonstrates preliminary results of real time monitoring of reduced/- oxyhemoglobin changes during clogging and unclogging of blood flow in the finger tip. The obtained results were verified with pulse-oximeter values, connected to the tip of the same index finger.
Lopes Antunes, Ana Carolina; Dórea, Fernanda; Halasa, Tariq; Toft, Nils
2016-05-01
Surveillance systems are critical for accurate, timely monitoring and effective disease control. In this study, we investigated the performance of univariate process monitoring control algorithms in detecting changes in seroprevalence for endemic diseases. We also assessed the effect of sample size (number of sentinel herds tested in the surveillance system) on the performance of the algorithms. Three univariate process monitoring control algorithms were compared: Shewart p Chart(1) (PSHEW), Cumulative Sum(2) (CUSUM) and Exponentially Weighted Moving Average(3) (EWMA). Increases in seroprevalence were simulated from 0.10 to 0.15 and 0.20 over 4, 8, 24, 52 and 104 weeks. Each epidemic scenario was run with 2000 iterations. The cumulative sensitivity(4) (CumSe) and timeliness were used to evaluate the algorithms' performance with a 1% false alarm rate. Using these performance evaluation criteria, it was possible to assess the accuracy and timeliness of the surveillance system working in real-time. The results showed that EWMA and PSHEW had higher CumSe (when compared with the CUSUM) from week 1 until the end of the period for all simulated scenarios. Changes in seroprevalence from 0.10 to 0.20 were more easily detected (higher CumSe) than changes from 0.10 to 0.15 for all three algorithms. Similar results were found with EWMA and PSHEW, based on the median time to detection. Changes in the seroprevalence were detected later with CUSUM, compared to EWMA and PSHEW for the different scenarios. Increasing the sample size 10 fold halved the time to detection (CumSe=1), whereas increasing the sample size 100 fold reduced the time to detection by a factor of 6. This study investigated the performance of three univariate process monitoring control algorithms in monitoring endemic diseases. It was shown that automated systems based on these detection methods identified changes in seroprevalence at different times. Increasing the number of tested herds would lead to faster detection. However, the practical implications of increasing the sample size (such as the costs associated with the disease) should also be taken into account. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
de Alwis Pitts, Dilkushi A.; So, Emily
2017-12-01
The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequently updated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results. The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and adds existing knowledge into the processing to enhance change detection. It also allows targeting specific types of changes pertaining to similar man-made objects such as buildings and critical facilities. The change detection method is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters within the object and a set of training data. More emphasis is put on the building edges to capture the structural damage in quantifying change after disaster. Once the change is quantified, based on training data, the method can be used automatically to detect change in order to observe recovery over time in potentially large areas. Analysis over time can also contribute to obtaining a full picture of the recovery and development after disaster, thereby giving managers a better understanding of productive management and recovery practices. The recovery and monitoring can be analyzed using the index in zones extending from to epicentre of disaster or administrative boundaries over time.
Guidelines for collecting and maintaining archives for genetic monitoring
Jackson, Jennifer A.; Laikre, Linda; Baker, C. Scott; Kendall, Katherine C.; ,
2012-01-01
Rapid advances in molecular genetic techniques and the statistical analysis of genetic data have revolutionized the way that populations of animals, plants and microorganisms can be monitored. Genetic monitoring is the practice of using molecular genetic markers to track changes in the abundance, diversity or distribution of populations, species or ecosystems over time, and to follow adaptive and non-adaptive genetic responses to changing external conditions. In recent years, genetic monitoring has become a valuable tool in conservation management of biological diversity and ecological analysis, helping to illuminate and define cryptic and poorly understood species and populations. Many of the detected biodiversity declines, changes in distribution and hybridization events have helped to drive changes in policy and management. Because a time series of samples is necessary to detect trends of change in genetic diversity and species composition, archiving is a critical component of genetic monitoring. Here we discuss the collection, development, maintenance, and use of archives for genetic monitoring. This includes an overview of the genetic markers that facilitate effective monitoring, describes how tissue and DNA can be stored, and provides guidelines for proper practice.
Method of noncontacting ultrasonic process monitoring
Garcia, Gabriel V.; Walter, John B.; Telschow, Kenneth L.
1992-01-01
A method of monitoring a material during processing comprising the steps of (a) shining a detection light on the surface of a material; (b) generating ultrasonic waves at the surface of the material to cause a change in frequency of the detection light; (c) detecting a change in the frequency of the detection light at the surface of the material; (d) detecting said ultrasonic waves at the surface point of detection of the material; (e) measuring a change in the time elapsed from generating the ultrasonic waves at the surface of the material and return to the surface point of detection of the material, to determine the transit time; and (f) comparing the transit time to predetermined values to determine properties such as, density and the elastic quality of the material.
Deep learning on temporal-spectral data for anomaly detection
NASA Astrophysics Data System (ADS)
Ma, King; Leung, Henry; Jalilian, Ehsan; Huang, Daniel
2017-05-01
Detecting anomalies is important for continuous monitoring of sensor systems. One significant challenge is to use sensor data and autonomously detect changes that cause different conditions to occur. Using deep learning methods, we are able to monitor and detect changes as a result of some disturbance in the system. We utilize deep neural networks for sequence analysis of time series. We use a multi-step method for anomaly detection. We train the network to learn spectral and temporal features from the acoustic time series. We test our method using fiber-optic acoustic data from a pipeline.
NASA Astrophysics Data System (ADS)
Ajadi, Olaniyi A.
Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.
1990-09-01
I C4 -44 0 i r Uo IP Stop I Designation of Site-Specific Managerial Needs and Objectives Step 2 Identification of Physical and Chemical Parameters...improved as experience dictates. Emphasis is placed on the establishment of concise objectives and hypotheses, the use of multidisciplinary approaches to...resulting monitoring can thus focus on the detection of changes in specific conditions rather than identifying any or all detectable changes. A monitoring
Detection of emetic activity in the cat by monitoring venous pressure and audio signals
NASA Technical Reports Server (NTRS)
Nagahara, A.; Fox, Robert A.; Daunton, Nancy G.; Elfar, S.
1991-01-01
To investigate the use of audio signals as a simple, noninvasive measure of emetic activity, the relationship between the somatic events and sounds associated with retching and vomiting was studied. Thoracic venous pressure obtained from an implanted external jugular catheter was shown to provide a precise measure of the somatic events associated with retching and vomiting. Changes in thoracic venous pressure monitored through an indwelling external jugular catheter with audio signals, obtained from a microphone located above the animal in a test chamber, were compared. In addition, two independent observers visually monitored emetic episodes. Retching and vomiting were induced by injection of xylazine (0.66mg/kg s.c.), or by motion. A unique audio signal at a frequency of approximately 250 Hz is produced at the time of the negative thoracic venous pressure change associated with retching. Sounds with higher frequencies (around 2500 Hz) occur in conjunction with the positive pressure changes associated with vomiting. These specific signals could be discriminated reliably by individuals reviewing the audio recordings of the sessions. Retching and those emetic episodes associated with positive venous pressure changes were detected accurately by audio monitoring, with 90 percent of retches and 100 percent of emetic episodes correctly identified. Retching was detected more accurately (p is less than .05) by audio monitoring than by direct visual observation. However, with visual observation a few incidents in which stomach contents were expelled in the absence of positive pressure changes or detectable sounds were identified. These data suggest that in emetic situations, the expulsion of stomach contents may be accomplished by more than one neuromuscular system and that audio signals can be used to detect emetic episodes associated with thoracic venous pressure changes.
Monitoring programs need to take into account imperfect species detectability
Kery, M.; Schmid, Hans
2004-01-01
Biodiversiry monitoring is important to identify biological units in need of conservation and to check the effectiveness of conservation actions. Programs generally monitor species richness and its changes (trend). Usually, no correction is made for imperfect species detectability. Instead, it is assumed that each species present has the same probability of being recorded and that there is no difference in this detectability across space and time, e.g. among observers and habitats. Consequently, species richness is determined by enumeration as the sum of species recorded. In Switzerland, the federal government has recently launched a comprehensive program that aims at detecting changes in biodiversity at all levels of biological integration. Birds are an important part of that program. Since 1999, 23 visits per breeding season are made to each of >250 1 km2 squares to map the territories of all detected breeding bird species. Here, we analyse data from three squares to illustrate the use of capture-recapture models in monitoring to obtain detectability-corrected estimates of species richness and trend. Species detectability averaged only 85%. Hence an estimated 15% of species present remained overlooked even after three visits. Within a square, changes in detectability for different years were of the same magnitude when surveys were conducted by the same observer as when they were by different observers. Estimates of trend were usually biased and community turnover was overestimated when based on enumeration. Here we use bird data as an illustration of methods. However, species detectability for any taxon is unlikely ever to be perfect or even constant across categories to be compared. Therefore, monitoring programs should correct for species detectability.
NASA Technical Reports Server (NTRS)
Macdonald, H.; Steele, K. (Principal Investigator); Waite, W.; Rice, R.; Shinn, M.; Dillard, T.; Petersen, C.
1977-01-01
The author has identified the following significant results. Comparison between LANDSAT 1 and 2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing LANDSAT change detection analyses.
LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA
Monitoring the locations and spatial distributions of land-cover changes and patterns is important for establishing links between policy decisions, regulatory actions and resulting landuse activities. The monitoring of change patterns across the landscape can also supply valuable...
IMPACTS OF IMAGERY TEMPORAL FREQUENCES ON LAND-COVER CHANGE DETECTION MONITORING
An important consideration for monitoring land~cover (LC) change is the nominal temporal frequency of remote sensor data acquisitions required to adequately characterize change events, Ecosystem specific regeneration rates are an important consideration for determining the requir...
Schilling, K.E.; Thompson, C.A.
2000-01-01
Land use and surface water data for nitrogen and pesticides (1995 to 1997) are reported for the Walnut Creek Watershed Monitoring Project, Jasper County Iowa. The Walnut Creek project was established in 1995 as a nonpoint source monitoring program in relation to watershed habitat restoration and agricultural management changes implemented at the Neal Smith National Wildlife Refuge by the U.S. Fish and Wildlife Service. The monitoring project utilizes a paired-watershed approach (Walnut and Squaw creeks) as well as upstream/downstream comparisons on Walnut for analysis and tracking of trends. From 1992 to 1997, 13.4 percent of the watershed was converted from row crop to native prairie in the Walnut Creek watershed. Including another 6 percent of watershed farmed on a cash-rent basis, land use changes have been implemented on 19.4 percent of the watershed by the USFWS. Nitrogen and pesticide applications were reduced an estimated 18 percent and 28 percent in the watershed from land use changes. Atrazine was detected most often in surface water with frequencies of detection ranging from 76-86 percent. No significant differences were noted in atrazine concentrations between Walnut and Squaw Creek. Nitrate-N concentrations measured in both watersheds were similar; both basins showed a similar pattern of detection and an overall reduction in nitrate-N concentrations from upstream to downstream monitoring sites. Water quality improvements are suggested by nitrate-N and chloride ratios less than one in the Walnut Creek watershed and low nitrate-N concentrations measured in the subbasin of Walnut Creek containing the greatest amount of land use changes. Atrazine and nitrate-N concentrations from the lower portion of the Walnut Creek watershed (including the prairie restoration area) may be decreasing in relation to the upstream untreated component of the watershed. The frequencies of pesticide detections and mean nitrate-N concentrations appear related to the percentage of row crop in the basins and subbasins. Although some results are encouraging, definitive water quality improvements have not been observed during the first three years of monitoring. Possible reasons include: (1) more time is needed to adequately detect changes; (2) the size of the watershed is too large to detect improvements; (3) land use changes are not located in the area of the watershed where they would have greatest effect; or (4) water quality improvements have occurred but have been missed by the project monitoring design. Longer-term monitoring will allow better evaluation of the impact of restoration activities on water quality.An overview is given on the Walnut Creek Watershed Monitoring Project established as a nonpoint source monitoring program in relation to watershed habitat restoration and agricultural management changes implemented at the Neal Smith National Wildlife Refuge by the U.S. Fish and Wildlife Services. Focus is on land use and surface water data for nitrogen and pesticides. Initial results obtained for the first three years of monitoring are discussed.
Wagner, Tyler; Irwin, Brian J.; James R. Bence,; Daniel B. Hayes,
2016-01-01
Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.
Change detection from remotely sensed images: From pixel-based to object-based approaches
NASA Astrophysics Data System (ADS)
Hussain, Masroor; Chen, Dongmei; Cheng, Angela; Wei, Hui; Stanley, David
2013-06-01
The appetite for up-to-date information about earth's surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection.
Evaluation of change detection techniques for monitoring coastal zone environments
NASA Technical Reports Server (NTRS)
Weismiller, R. A. (Principal Investigator); Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.
1977-01-01
The author has identified the following significant results. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. The post classification comparison technique reliably identified areas of change and was used as the standard for qualitatively evaluating the other three techniques. The layered spectral/temporal change classification and the delta data change detection results generally agreed with the post classification comparison technique results; however, many small areas of change were not identified. Major discrepancies existed between the post classification comparison and spectral/temporal change detection results.
Energy Change Detection to Assist in Tactical Intelligence Production
2009-06-01
COVERED Master’s Thesis 4. TITLE AND SUBTITLE Energy Change Detection to Assist in Tactical Intelligence Production 6. AUTHOR( S ) Derek Anthony Filipe...5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000 8. PERFORMING...ORGANIZATION REPORT NUMBER 9. SPONSORING /MONITORING AGENCY NAME( S ) AND ADDRESS(ES) N/A 10. SPONSORING/MONITORING AGENCY REPORT NUMBER 11
Graph-based structural change detection for rotating machinery monitoring
NASA Astrophysics Data System (ADS)
Lu, Guoliang; Liu, Jie; Yan, Peng
2018-01-01
Detection of structural changes is critically important in operational monitoring of a rotating machine. This paper presents a novel framework for this purpose, where a graph model for data modeling is adopted to represent/capture statistical dynamics in machine operations. Meanwhile we develop a numerical method for computing temporal anomalies in the constructed graphs. The martingale-test method is employed for the change detection when making decisions on possible structural changes, where excellent performance is demonstrated outperforming exciting results such as the autoregressive-integrated-moving average (ARIMA) model. Comprehensive experimental results indicate good potentials of the proposed algorithm in various engineering applications. This work is an extension of a recent result (Lu et al., 2017).
Method and apparatus for real time weld monitoring
Leong, Keng H.; Hunter, Boyd V.
1997-01-01
An improved method and apparatus are provided for real time weld monitoring. An infrared signature emitted by a hot weld surface during welding is detected and this signature is compared with an infrared signature emitted by the weld surface during steady state conditions. The result is correlated with weld penetration. The signal processing is simpler than for either UV or acoustic techniques. Changes in the weld process, such as changes in the transmitted laser beam power, quality or positioning of the laser beam, change the resulting weld surface features and temperature of the weld surface, thereby resulting in a change in the direction and amount of infrared emissions. This change in emissions is monitored by an IR sensitive detecting apparatus that is sensitive to the appropriate wavelength region for the hot weld surface.
A new approach for structural health monitoring by applying anomaly detection on strain sensor data
NASA Astrophysics Data System (ADS)
Trichias, Konstantinos; Pijpers, Richard; Meeuwissen, Erik
2014-03-01
Structural Health Monitoring (SHM) systems help to monitor critical infrastructures (bridges, tunnels, etc.) remotely and provide up-to-date information about their physical condition. In addition, it helps to predict the structure's life and required maintenance in a cost-efficient way. Typically, inspection data gives insight in the structural health. The global structural behavior, and predominantly the structural loading, is generally measured with vibration and strain sensors. Acoustic emission sensors are more and more used for measuring global crack activity near critical locations. In this paper, we present a procedure for local structural health monitoring by applying Anomaly Detection (AD) on strain sensor data for sensors that are applied in expected crack path. Sensor data is analyzed by automatic anomaly detection in order to find crack activity at an early stage. This approach targets the monitoring of critical structural locations, such as welds, near which strain sensors can be applied during construction and/or locations with limited inspection possibilities during structural operation. We investigate several anomaly detection techniques to detect changes in statistical properties, indicating structural degradation. The most effective one is a novel polynomial fitting technique, which tracks slow changes in sensor data. Our approach has been tested on a representative test structure (bridge deck) in a lab environment, under constant and variable amplitude fatigue loading. In both cases, the evolving cracks at the monitored locations were successfully detected, autonomously, by our AD monitoring tool.
Dolan, T E; Lynch, P D; Karazsia, J L; Serafy, J E
2016-03-01
An expansion is underway of a nuclear power plant on the shoreline of Biscayne Bay, Florida, USA. While the precise effects of its construction and operation are unknown, impacts on surrounding marine habitats and biota are considered by experts to be likely. The objective of the present study was to determine the adequacy of an ongoing monitoring survey of fish communities associated with mangrove habitats directly adjacent to the power plant to detect fish community changes, should they occur, at three spatial scales. Using seasonally resolved data recorded during 532 fish surveys over an 8-year period, power analyses were performed for four mangrove fish metrics (fish diversity, fish density, and the occurrence of two ecologically important fish species: gray snapper (Lutjanus griseus) and goldspotted killifish (Floridichthys carpio). Results indicated that the monitoring program at current sampling intensity allows for detection of <33% changes in fish density and diversity metrics in both the wet and the dry season in the two larger study areas. Sampling effort was found to be insufficient in either season to detect changes at this level (<33%) in species-specific occurrence metrics for the two fish species examined. The option of supplementing ongoing, biological monitoring programs for improved, focused change detection deserves consideration from both ecological and cost-benefit perspectives.
LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA
Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be perfo...
Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Imagery
Monitoring the locations and distributions of land-cover change is important for establishing linkages between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be perfor...
PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA
Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...
Spatial Analysis for Monitoring Forest Health
Francis A. Roesch
1994-01-01
A plan for the spatial analysis for the sample design for the detection monitoring phase in the joint USDA Forest Service/EPA Forest Health Monitoring Program (FHM) in the United States is discussed. The spatial analysis procedure is intended to more quickly identify changes in forest health by providing increased sensitivity to localized changes. The procedure is...
NASA Astrophysics Data System (ADS)
Yang, C. H.; Kenduiywo, B. K.; Soergel, U.
2016-06-01
Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.
Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images
NASA Astrophysics Data System (ADS)
Yang, C. H.; Pang, Y.; Soergel, U.
2017-05-01
Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moody, Daniela Irina
An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detectmore » geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.« less
Goodson, Agnessa Gadeliya; Florell, Scott R.; Hyde, Mark; Bowen, Glen M.; Grossman, Douglas
2011-01-01
Background Our previous experience monitoring nevi in high risk patients by serial digital epiluminescence microscopy (DELM) photography achieved low biopsy rates, but was limited by melanomas presenting as new lesions or arising from nevi that had not been photographed. Objective To determine whether biopsy rates, efficiency of melanoma detection, and melanoma origin (de novo vs. nevus-derived) differed in a similar patient population monitored by total body (TB) photography. Methods 1076 patients (including 187 from prior cohort) underwent TB photography and were monitored using photographs obtained at the initial visit. Risk factors and median monitoring periods for these patients were comparable to patients previously monitored by DELM photography. Results 275 biopsies were performed in 467 patients on follow-up visits. Of 12 melanomas detected on follow-up, five were invasive; five presented as changing lesions and two as new lesions; nine arose de novo and the remainder was nevus-derived. Conclusions In our experience with both approaches, monitoring patients at risk for melanoma by TB (compared to DELM) photography was associated with lower biopsy rates and lower nevus to melanoma ratios, and facilitated detection of both new and changing lesions. In both cohorts, the majority of melanomas detected on follow-up arose de novo. PMID:20653722
Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim
2017-05-01
In the current study, dual-task performance is examined with multiple-object tracking as a primary task and target-change detection as a secondary task. The to-be-detected target changes in conditions of either change type (form vs. motion; Experiment 1) or change salience (stop vs. slowdown; Experiment 2), with changes occurring at either near (5°-10°) or far (15°-20°) eccentricities (Experiments 1 and 2). The aim of the study was to test whether changes can be detected solely with peripheral vision. By controlling for saccades and computing gaze distances, we could show that participants used peripheral vision to monitor the targets and, additionally, to perceive changes at both near and far eccentricities. Noticeably, gaze behavior was not affected by the actual target change. Detection rates as well as response times generally varied as a function of change condition and eccentricity, with faster detections for motion changes and near changes. However, in contrast to the effects found for motion changes, sharp declines in detection rates and increased response times were observed for form changes as a function of the eccentricities. This result can be ascribed to properties of the visual system, namely to the limited spatial acuity in the periphery and the comparably receptive motion sensitivity of peripheral vision. These findings show that peripheral vision is functional for simultaneous target monitoring and target-change detection as saccadic information suppression can be avoided and covert attention can be optimally distributed to all targets. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Wajs, Jaroslaw
2018-01-01
The paper presents satellite imagery from active SENTINEL-1A and passive SENTINEL-2A/2B sensors for their application in the monitoring of mining areas focused on detecting land changes. Multispectral scenes of SENTINEL-2A/2B have allowed for detecting changes in land-cover near the region of interest (ROI), i.e. the Szczercow dumping site in the Belchatow open cast lignite mine, central Poland, Europe. Scenes from SENTINEL-1A/1B satellite have also been used in the research. Processing of the SLC signal enabled creating a return intensity map in VV polarization. The obtained SAR scene was reclassified and shows a strong return signal from the dumping site and the open pit. This fact may be used in detection and monitoring of changes occurring within the analysed engineering objects.
Mixing geometric and radiometric features for change classification
NASA Astrophysics Data System (ADS)
Fournier, Alexandre; Descombes, Xavier; Zerubia, Josiane
2008-02-01
Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data.
NASA Astrophysics Data System (ADS)
Wang, Hung-Ta; Kang, B. S.; Ren, F.; Fitch, R. C.; Gillespie, J. K.; Moser, N.; Jessen, G.; Jenkins, T.; Dettmer, R.; Via, D.; Crespo, A.; Gila, B. P.; Abernathy, C. R.; Pearton, S. J.
2005-10-01
Pt-gated AlGaN /GaN high electron mobility transistors can be used as room-temperature hydrogen gas sensors at hydrogen concentrations as low as 100ppm. A comparison of the changes in drain and gate current-voltage (I-V) characteristics with the introduction of 500ppm H2 into the measurement ambient shows that monitoring the change in drain-source current provides a wider gate voltage operation range for maximum detection sensitivity and higher total current change than measuring the change in gate current. However, over a narrow gate voltage range, the relative sensitivity of detection by monitoring the gate current changes is up to an order of magnitude larger than that of drain-source current changes. In both cases, the changes are fully reversible in <2-3min at 25°C upon removal of the hydrogen from the ambient.
Goddard, Erin; Clifford, Colin W G
2013-04-22
Attending selectively to changes in our visual environment may help filter less important, unchanging information within a scene. Here, we demonstrate that color changes can go unnoticed even when they occur throughout an otherwise static image. The novelty of this demonstration is that it does not rely upon masking by a visual disruption or stimulus motion, nor does it require the change to be very gradual and restricted to a small section of the image. Using a two-interval, forced-choice change-detection task and an odd-one-out localization task, we showed that subjects were slowest to respond and least accurate (implying that change was hardest to detect) when the color changes were isoluminant, smoothly varying, and asynchronous with one another. This profound change blindness offers new constraints for theories of visual change detection, implying that, in the absence of transient signals, changes in color are typically monitored at a coarse spatial scale.
An approach to online network monitoring using clustered patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Jinoh; Sim, Alex; Suh, Sang C.
Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less
Smart storage technologies applied to fresh foods: A review.
Wang, Jingyu; Zhang, Min; Gao, Zhongxue; Adhikari, Benu
2017-06-30
Fresh foods are perishable, seasonal and regional in nature and their storage, transportation, and preservation of freshness are quite challenging. Smart storage technologies can online detection and monitor the changes of quality parameters and storage environment of fresh foods during storage, so that operators can make timely adjustments to reduce the loss. This article reviews the smart storage technologies from two aspects: online detection technologies and smartly monitoring technologies for fresh foods. Online detection technologies include electronic nose, nuclear magnetic resonance (NMR), near infrared spectroscopy (NIRS), hyperspectral imaging and computer vision. Smartly monitoring technologies mainly include some intelligent indicators for monitoring the change of storage environment. Smart storage technologies applied to fresh foods need to be highly efficient and nondestructive and need to be competitively priced. In this work, we have critically reviewed the principles, applications, and development trends of smart storage technologies.
An approach to online network monitoring using clustered patterns
Kim, Jinoh; Sim, Alex; Suh, Sang C.; ...
2017-03-13
Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less
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.
Two visual systems in monitoring of dynamic traffic: effects of visual disruption.
Zheng, Xianjun Sam; McConkie, George W
2010-05-01
Studies from neurophysiology and neuropsychology provide support for two separate object- and location-based visual systems, ventral and dorsal. In the driving context, a study was conducted using a change detection paradigm to explore drivers' ability to monitor the dynamic traffic flow, and the effects of visual disruption on these two visual systems. While driving, a discrete change, such as vehicle location, color, or identity, was occasionally made in one of the vehicles on the road ahead of the driver. Experiment results show that without visual disruption, all changes were detected very well; yet, these equally perceivable changes were disrupted differently by a brief blank display (150 ms): the detection of location changes was especially reduced. The disruption effects were also bigger for the parked vehicle compared to the moving ones. The findings support the different roles for two visual systems in monitoring the dynamic traffic: the "where", dorsal system, tracks vehicle spatiotemporal information on perceptual level, encoding information in a coarse and transient manner; whereas the "what", ventral system, monitors vehicles' featural information, encoding information more accurately and robustly. Both systems work together contributing to the driver's situation awareness of traffic. Benefits and limitations of using the driving simulation are also discussed. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Scholtz, P.; Smyth, P.
1992-01-01
This article describes an investigation of a statistical hypothesis testing method for detecting changes in the characteristics of an observed time series. The work is motivated by the need for practical automated methods for on-line monitoring of Deep Space Network (DSN) equipment to detect failures and changes in behavior. In particular, on-line monitoring of the motor current in a DSN 34-m beam waveguide (BWG) antenna is used as an example. The algorithm is based on a measure of the information theoretic distance between two autoregressive models: one estimated with data from a dynamic reference window and one estimated with data from a sliding reference window. The Hinkley cumulative sum stopping rule is utilized to detect a change in the mean of this distance measure, corresponding to the detection of a change in the underlying process. The basic theory behind this two-model test is presented, and the problem of practical implementation is addressed, examining windowing methods, model estimation, and detection parameter assignment. Results from the five fault-transition simulations are presented to show the possible limitations of the detection method, and suggestions for future implementation are given.
Assessment of error rates in acoustic monitoring with the R package monitoR
Katz, Jonathan; Hafner, Sasha D.; Donovan, Therese
2016-01-01
Detecting population-scale reactions to climate change and land-use change may require monitoring many sites for many years, a process that is suited for an automated system. We developed and tested monitoR, an R package for long-term, multi-taxa acoustic monitoring programs. We tested monitoR with two northeastern songbird species: black-throated green warbler (Setophaga virens) and ovenbird (Seiurus aurocapilla). We compared detection results from monitoR in 52 10-minute surveys recorded at 10 sites in Vermont and New York, USA to a subset of songs identified by a human that were of a single song type and had visually identifiable spectrograms (e.g. a signal:noise ratio of at least 10 dB: 166 out of 439 total songs for black-throated green warbler, 502 out of 990 total songs for ovenbird). monitoR’s automated detection process uses a ‘score cutoff’, which is the minimum match needed for an unknown event to be considered a detection and results in a true positive, true negative, false positive or false negative detection. At the chosen score cut-offs, monitoR correctly identified presence for black-throated green warbler and ovenbird in 64% and 72% of the 52 surveys using binary point matching, respectively, and 73% and 72% of the 52 surveys using spectrogram cross-correlation, respectively. Of individual songs, 72% of black-throated green warbler songs and 62% of ovenbird songs were identified by binary point matching. Spectrogram cross-correlation identified 83% of black-throated green warbler songs and 66% of ovenbird songs. False positive rates were for song event detection.
Field Tests of Real-time In-situ Dissolved CO2 Monitoring for CO2 Leakage Detection in Groundwater
NASA Astrophysics Data System (ADS)
Yang, C.; Zou, Y.; Delgado, J.; Guzman, N.; Pinedo, J.
2016-12-01
Groundwater monitoring for detecting CO2 leakage relies on groundwater sampling from water wells drilled into aquifers. Usually groundwater samples are required be collected periodically in field and analyzed in the laboratory. Obviously groundwater sampling is labor and cost-intensive for long-term monitoring of large areas. Potential damage and contamination of water samples during the sampling process can degrade accuracy, and intermittent monitoring may miss changes in the geochemical parameters of groundwater, and therefore signs of CO2 leakage. Real-time in-situ monitoring of geochemical parameters with chemical sensors may play an important role for CO2 leakage detection in groundwater at a geological carbon sequestration site. This study presents field demonstration of a real-time in situ monitoring system capable of covering large areas for detection of low levels of dissolved CO2 in groundwater and reliably differentiating natural variations of dissolved CO2 concentration from small changes resulting from leakage. The sand-alone system includes fully distributed fiber optic sensors for carbon dioxide detection with a unique sensor technology developed by Intelligent Optical Systems. The systems were deployed to the two research sites: the Brackenridge Field Laboratory where the aquifer is shallow at depths of 10-20 ft below surface and the Devine site where the aquifer is much deeper at depths of 140 to 150 ft. Groundwater samples were periodically collected from the water wells which were installed with the chemical sensors and further compared to the measurements of the chemical sensors. Our study shows that geochemical monitoring of dissolved CO2 with fiber optic sensors could provide reliable CO2 leakage signal detection in groundwater as long as CO2 leakage signals are stronger than background noises at the monitoring locations.
Stevenson, Ryan A; Schlesinger, Joseph J; Wallace, Mark T
2013-02-01
Anesthesiology requires performing visually oriented procedures while monitoring auditory information about a patient's vital signs. A concern in operating room environments is the amount of competing information and the effects that divided attention has on patient monitoring, such as detecting auditory changes in arterial oxygen saturation via pulse oximetry. The authors measured the impact of visual attentional load and auditory background noise on the ability of anesthesia residents to monitor the pulse oximeter auditory display in a laboratory setting. Accuracies and response times were recorded reflecting anesthesiologists' abilities to detect changes in oxygen saturation across three levels of visual attention in quiet and with noise. Results show that visual attentional load substantially affects the ability to detect changes in oxygen saturation concentrations conveyed by auditory cues signaling 99 and 98% saturation. These effects are compounded by auditory noise, up to a 17% decline in performance. These deficits are seen in the ability to accurately detect a change in oxygen saturation and in speed of response. Most anesthesia accidents are initiated by small errors that cascade into serious events. Lack of monitor vigilance and inattention are two of the more commonly cited factors. Reducing such errors is thus a priority for improving patient safety. Specifically, efforts to reduce distractors and decrease background noise should be considered during induction and emergence, periods of especially high risk, when anesthesiologists has to attend to many tasks and are thus susceptible to error.
Unobtrusive monitoring of computer interactions to detect cognitive status in elders.
Jimison, Holly; Pavel, Misha; McKanna, James; Pavel, Jesse
2004-09-01
The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.
Land use change monitoring in Maryland using a probabilistic sample and rapid photointerpretation
Tonya Lister; Andrew Lister; Eunice Alexander
2014-01-01
The U.S. state of Maryland needs to monitor land use change in order to address land management objectives. This paper presents a change detection method that, through automation and standard geographic information system (GIS) techniques, facilitates the estimation of landscape change via photointerpretation. Using the protocols developed, we show a net loss of forest...
Spatially-Aware Temporal Anomaly Mapping of Gamma Spectra
NASA Astrophysics Data System (ADS)
Reinhart, Alex; Athey, Alex; Biegalski, Steven
2014-06-01
For security, environmental, and regulatory purposes it is useful to continuously monitor wide areas for unexpected changes in radioactivity. We report on a temporal anomaly detection algorithm which uses mobile detectors to build a spatial map of background spectra, allowing sensitive detection of any anomalies through many days or months of monitoring. We adapt previously-developed anomaly detection methods, which compare spectral shape rather than count rate, to function with limited background data, allowing sensitive detection of small changes in spectral shape from day to day. To demonstrate this technique we collected daily observations over the period of six weeks on a 0.33 square mile research campus and performed source injection simulations.
Potential for the Use of Wireless Sensor Networks for Monitoring of CO2 Leakage Risks
NASA Astrophysics Data System (ADS)
Pawar, R.; Illangasekare, T. H.; Han, Q.; Jayasumana, A.
2015-12-01
Storage of supercritical CO2 in deep saline geologic formation is under study as a means to mitigate potential global climate change from green house gas loading to the atmosphere. Leakage of CO2 from these formations poses risk to the storage permanence goal of 99% of injected CO2 remaining sequestered from the atmosphere,. Leaked CO2 that migrates into overlying groundwater aquifers may cause changes in groundwater quality that pose risks to environmental and human health. For these reasons, technologies for monitoring, measuring and accounting of injected CO2 are necessary for permitting of CO2 sequestration projects under EPA's class VI CO2 injection well regulations. While the probability of leakage related to CO2 injection is thought to be small at characterized and permitted sites, it is still very important to protect the groundwater resources and develop methods that can efficiently and accurately detect CO2 leakage. Methods that have been proposed for leakage detection include remote sensing, soil gas monitoring, geophysical techniques, pressure monitoring, vegetation stress and eddy covariance measurements. We have demonstrated the use of wireless sensor networks (WSN) for monitoring of subsurface contaminant plumes. The adaptability of this technology for leakage monitoring of CO2 through geochemical changes in the shallow subsurface is explored. For this technology to be viable, it is necessary to identify geochemical indicators such as pH or electrical conductivity that have high potential for significant change in groundwater in the event of CO2 leakage. This talk presents a conceptual approach to use WSNs for CO2 leakage monitoring. Based on our past work on the use of WSN for subsurface monitoring, some of the challenges that need to be over come for this technology to be viable for leakage detection will be discussed.
Trajectory-based change detection for automated characterization of forest disturbance dynamics
Robert E. Kennedy; Warren B. Cohen; Todd A. Schroeder
2007-01-01
Satellite sensors are well suited to monitoring changes on the Earth's surface through provision of consistent and repeatable measurements at a spatial scale appropriate for many processes causing change on the land surface. Here, we describe and test a new conceptual approach to change detection of forests using a dense temporal stack of Landsat Thematic Mapper (...
NASA Astrophysics Data System (ADS)
Kumar, Manish; Raghuwanshi, Sanjeev Kumar
2018-02-01
In recent years, food safety issues caused by contamination of chemical substances or microbial species have raised a major area of concern to mankind. The conventional chromatography-based methods for detection of chemical are based on human-observation and slow for real-time monitoring. The surface plasmon resonance (SPR) sensors offers the capability of detection of very low concentrations of adulterated chemical and biological agents for real-time by monitoring. Thus, adulterant agent in food gives change in refractive index of pure food result in corresponding phase change. These changes can be detected at the output and can be related to the concentration of the chemical species present at the point.
Eddy current gauge for monitoring displacement using printed circuit coil
Visioli, Jr., Armando J.
1977-01-01
A proximity detection system for non-contact displacement and proximity measurement of static or dynamic metallic or conductive surfaces is provided wherein the measurement is obtained by monitoring the change in impedance of a flat, generally spiral-wound, printed circuit coil which is excited by a constant current, constant frequency source. The change in impedance, which is detected as a corresponding change in voltage across the coil, is related to the eddy current losses in the distant conductive material target. The arrangement provides for considerable linear displacement range with increased accuracies, stability, and sensitivity over the entire range.
Uchiyama, Jumpei; Kato, Yoshiteru; Uemoto, Yoshifumi
2014-08-01
In the process design of tablet manufacturing, understanding and control of the lubrication process is important from various viewpoints. A detailed analysis of thermal effusivity data in the lubrication process was conducted in this study. In addition, we evaluated the risk and benefit in the lubrication process by a detailed investigation. It was found that monitoring of thermal effusivity detected mainly the physical change of bulk density, which was changed by dispersal of the lubricant and the coating powder particle by the lubricant. The monitoring of thermal effusivity was almost the monitoring of bulk density, thermal effusivity could have a high correlation with tablet hardness. Moreover, as thermal effusivity sensor could detect not only the change of the conventional bulk density but also the fractional change of thermal conductivity and thermal capacity, two-phase progress of lubrication process could be revealed. However, each contribution of density, thermal conductivity, or heat capacity to thermal effusivity has the risk of fluctuation by formulation. After carefully considering the change factor with the risk to be changed by formulation, thermal effusivity sensor can be a useful tool for monitoring as process analytical technology, estimating tablet hardness and investigating the detailed mechanism of the lubrication process.
Campbell, Patrick; Comiskey, James; Alonso, Alfonso; Dallmeier, Francisco; Nuñez, Percy; Beltran, Hamilton; Baldeon, Severo; Nauray, William; de la Colina, Rafael; Acurio, Lucero; Udvardy, Shana
2002-05-01
Resource exploitation in lowland tropical forests is increasing and causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We propose the use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests. We established MWPs at 4 sites to: (1) describe and compare composition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs), and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similar species composition and abundance and that both perform equally well at detecting rare species. However, MWPs tend to record more species, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees > or = 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees > or =10 cm dbh. The value of MWPs for assessment and monitoring is discussed, along with recommendations for improving the sampling design to increase power.
Patricia N. Manley; Leif Mortenson; James J. Halperin; Nguyen Hanh Quyen
2013-01-01
Changes in forest carbon stocks can be detected through monitoring of deforestation (conversion of| forests to some other cover type), forest degradation (forests that remain forests), and/or reforestation| (restoration of forests). Techniques for monitoring deforestation and resultant changes to forest carbon| stocks are widespread and well published. However,...
Long-term ecosystem monitoring and change detection: the Sonoran initiative
Robert Lozar; Charles Ehlschlaeger
2005-01-01
Ecoregional Systems Heritage and Encroachment Monitoring (ESHEM) examines issues of land management at an ecosystem level using remote sensing. Engineer Research and Development Center (ERDC), in partnership with Western Illinois University, has developed an ecoregional database and monitoring capability covering the Sonoran region. The monitoring time horizon will...
Single-molecule enzymology based on the principle of the Millikan oil drop experiment.
Leiske, Danielle L; Chow, Andrea; Dettloff, Roger; Farinas, Javier
2014-03-01
The ability to monitor the progress of single-molecule enzyme reactions is often limited by the need to use fluorogenic substrates. A method based on the principle of the Millikan oil drop experiment was developed to monitor the change in charge of substrates bound to a nanoparticle and offers a means of detecting single-enzyme reactions without fluorescence detection. As a proof of principle of the ability to monitor reactions that result in a change in substrate charge, polymerization on a single DNA template was detected. A custom oligonucleotide was synthesized that allowed for the attachment of single DNA templates to gold nanoparticles with a single polymer tether. The nanoparticles were then tethered to the surface of a microfluidic channel where the positions of the nanoparticles, subjected to an oscillating electric field, were monitored using dark field microscopy. With short averaging times, the signal-to-noise level was low enough to discriminate changes in charge of less than 1.2%. Polymerization of a long DNA template demonstrated the ability to use the system to monitor single-molecule enzymatic activity. Finally, nanoparticle surfaces were modified with thiolated moieties to reduce and/or shield the number of unproductive charges and allow for improved sensitivity. Copyright © 2013 Elsevier Inc. All rights reserved.
Single-Molecule Enzymology Based On The Principle Of The Millikan Oil Drop Experiment
Leiske, Danielle L.; Chow, Andrea; Dettloff, Roger; Farinas, Javier
2014-01-01
The ability to monitor the progress of single molecule enzyme reactions is often limited by the need to use fluorogenic substrates. A method based on the principle of the Millikan Oil Drop Experiment was developed to monitor the change in charge of substrates bound to a nanoparticle and offers a means of detecting single enzyme reactions without fluorescence detection. As a proof of principle of the ability to monitor reactions which result in a change in substrate charge, polymerization on a single DNA template was detected. A custom oligonucleotide was synthesized which allowed for the attachment of single DNA templates to gold nanoparticles with a single polymer tether. The nanoparticles were then tethered to the surface of a microfluidic channel where the positions of the nanoparticles, subjected to an oscillating electric field, were monitored using darkfield microscopy. With short averaging times, the signal-to-noise level was low enough to discriminate changes in charge of less than 1.2%. Polymerization of a long DNA template demonstrated the ability to use the system to monitor single molecule enzymatic activity. Finally, nanoparticle surfaces were modified with thiolated moieties in order to reduce and/or shield the number of unproductive charges and allow for improved sensitivity. PMID:24291542
A magnetostatic-coupling based remote query sensor for environmental monitoring
NASA Technical Reports Server (NTRS)
Grimes, C. A.; Stoyanov, P. G.; Liu, Y.; Tong, C.; Ong, K. G.; Loiselle, K.; Shaw, M.; Doherty, S. A.; Seitz, W. R.
1999-01-01
A new type of in situ, remotely monitored magnetism-based sensor is presented that is comprised of an array of magnetically soft, magnetostatically-coupled ferromagnetic thin-film elements or particles combined with a chemically responsive material that swells or shrinks in response to the analyte of interest. As the chemically responsive material changes size the distance between the ferromagnetic elements changes, altering the inter-element magnetostatic coupling. This in turn changes the coercive force of the sensor, the amplitude of the voltage spikes detected in nearby pick-up coils upon magnetization reversal and the number of higher-order harmonics generated by the flux reversal. Since the sensor is monitored through changes in magnetic flux, no physical connections such as wires or cables are needed to obtain sensor information, nor is line of sight alignment required as with laser telemetry; the sensors can be detected from within sealed, opaque or thin metallic enclosures.
NASA Astrophysics Data System (ADS)
Kromer, Ryan A.; Abellán, Antonio; Hutchinson, D. Jean; Lato, Matt; Chanut, Marie-Aurelie; Dubois, Laurent; Jaboyedoff, Michel
2017-05-01
We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals. The purpose of developing the system was to fill the gap of high-temporal-resolution TLS monitoring studies of earth surface processes and to offer a cost-effective, light, portable alternative to ground-based interferometric synthetic aperture radar (GB-InSAR) deformation monitoring. During the study, we detected the flux of talus, displacement of the landslide and pre-failure deformation of discrete rockfall events. Additionally, we found the ATLS system to be an effective tool in monitoring landslide and rockfall processes despite missing points due to poor atmospheric conditions or rainfall. Furthermore, such a system has the potential to help us better understand a wide variety of slope processes at high levels of temporal detail.
Automated Monitoring with a BSP Fault-Detection Test
NASA Technical Reports Server (NTRS)
Bickford, Randall L.; Herzog, James P.
2003-01-01
The figure schematically illustrates a method and procedure for automated monitoring of an asset, as well as a hardware- and-software system that implements the method and procedure. As used here, asset could signify an industrial process, power plant, medical instrument, aircraft, or any of a variety of other systems that generate electronic signals (e.g., sensor outputs). In automated monitoring, the signals are digitized and then processed in order to detect faults and otherwise monitor operational status and integrity of the monitored asset. The major distinguishing feature of the present method is that the fault-detection function is implemented by use of a Bayesian sequential probability (BSP) technique. This technique is superior to other techniques for automated monitoring because it affords sensitivity, not only to disturbances in the mean values, but also to very subtle changes in the statistical characteristics (variance, skewness, and bias) of the monitored signals.
NASA Technical Reports Server (NTRS)
Wolf, J. A.
1978-01-01
The Highly maneuverable aircraft technology (HIMAT) remotely piloted research vehicle (RPRV) uses cross-ship comparison monitoring of the actuator RAM positions to detect a failure in the aileron, canard, and elevator control surface servosystems. Some possible sources of nuisance trips for this failure detection technique are analyzed. A FORTRAN model of the simplex servosystems and the failure detection technique were utilized to provide a convenient means of changing parameters and introducing system noise. The sensitivity of the technique to differences between servosystems and operating conditions was determined. The cross-ship comparison monitoring method presently appears to be marginal in its capability to detect an actual failure and to withstand nuisance trips.
BIRD COMMUNITIES AND HABITAT AS ECOLOGICAL INDICATORS OF FOREST CONDITION IN REGIONAL MONITORING
Ecological indicators for long-term monitoring programs are needed to detect and assess changing environmental conditions, We developed and tested community-level environmental indicators for monitoring forest bird populations and associated habitat. We surveyed 197 sampling plo...
A symmetry measure for damage detection with mode shapes
NASA Astrophysics Data System (ADS)
Chen, Justin G.; Büyüköztürk, Oral
2017-11-01
This paper introduces a feature for detecting damage or changes in structures, the continuous symmetry measure, which can quantify the amount of a particular rotational, mirror, or translational symmetry in a mode shape of a structure. Many structures in the built environment have geometries that are either symmetric or almost symmetric, however damage typically occurs in a local manner causing asymmetric changes in the structure's geometry or material properties, and alters its mode shapes. The continuous symmetry measure can quantify these changes in symmetry as a novel indicator of damage for data-based structural health monitoring approaches. This paper describes the concept as a basis for detecting changes in mode shapes and detecting structural damage. Application of the method is demonstrated in various structures with different symmetrical properties: a pipe cross-section with a finite element model and experimental study, the NASA 8-bay truss model, and the simulated IASC-ASCE structural health monitoring benchmark structure. The applicability and limitations of the feature in applying it to structures of varying geometries is discussed.
Molina, Iñigo; Martinez, Estibaliz; Arquero, Agueda; Pajares, Gonzalo; Sanchez, Javier
2012-01-01
Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth’s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution. PMID:22737023
Molina, Iñigo; Martinez, Estibaliz; Arquero, Agueda; Pajares, Gonzalo; Sanchez, Javier
2012-01-01
Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth's resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.
Monitoring the southwestern Wyoming landscape—A foundation for management and science
Manier, Daniel J.; Anderson, Patrick J.; Assal, Timothy J.; Chong, Geneva W.; Melcher, Cynthia P.
2017-08-29
Natural resource monitoring involves repeated collections of resource condition data and analyses to detect possible changes and identify underlying causes of changes. For natural resource agencies, monitoring provides the foundation for management and science. Specifically, analyses of monitoring data allow managers to better understand effects of land-use and other changes on important natural resources and to achieve their conservation and management goals. Examples of natural resources monitored on public lands include wildlife habitats, plant productivity, animal movements and population trends, soil chemistry, and water quality and quantity. Broader definitions of monitoring also recognize the need for scientifically valid data to help support planning efforts and informed decisions, to develop adaptive management strategies, and to provide the means for evaluating management outcomes.
SAR Interferometry as a Tool for Monitoring Coastal Changes in the Nile River Delta of Egypt
NASA Technical Reports Server (NTRS)
Aly, Mohamed H.; Klein, Andrew G.; Giardino, John R.
2005-01-01
The Nile River Delta is experiencing rapid rates of coastal change. The rate of both coastal retreat and accretion in the Eastern Nile Delta requires regular, accurate detection and measurement. Current techniques used to monitor coastal changes in the delta are point measurements and, thus, they provide a spatially limited view of the ongoing coastal changes. SAR interferometry can provide measurements of subtle coastal change at a significantly improved spatial resolution and over large areas (100 sq km). Using data provided by the ERS-1&2 satellites, monitoring can be accomplished as frequently as every 35 days when needed. Radar interferometry is employed in this study to detect segments of erosion and accretion during the 1993-2000 period. The average rates of erosion and accretion in the Eastern Nile Delta are measured to be -11.64 m/yr and +5.12 m/yr, respectively. The results of this interferometric study can be used effectively for coastal zone management and integrated sustainable development for the Nile River Delta.
Efficient species-level monitoring at the landscape scale.
Noon, Barry R; Bailey, Larissa L; Sisk, Thomas D; McKelvey, Kevin S
2012-06-01
Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance. ©2012 Society for Conservation Biology.
Invasive species change detection using artificial neural networks and CASI hyperspectral imagery
USDA-ARS?s Scientific Manuscript database
For monitoring and controlling the extent and intensity of an invasive species, a direct multi-date image classification method was applied in invasive species (saltcedar) change detection in the study area of Lovelock, Nevada. With multi-date Compact Airborne Spectrographic Imager (CASI) hyperspec...
Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data
Jessica Robin; Ralph Dubayah; Elena Sparrow; Elissa Levine
2008-01-01
This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region....
Two additional principles for determining which species to monitor.
Wilson, Howard B; Rhodes, Jonathan R; Possingham, Hugh P
2015-11-01
Monitoring to detect population declines is widespread, but also costly. There is, consequently, a need to optimize monitoring to maximize cost-effectiveness. Here we develop a quantitative decision analysis framework for how to optimally allocate resources for monitoring among species. By keeping the framework simple, we analytically establish two new principles about which species are optimal to monitor for detecting declines: (1) those that lie on the boundary between species being allocated resources for conservation action and species that are not and (2) those with the greatest uncertainty in whether they are declining. These two principles are in addition to other factors that are also important in monitoring decisions, such as complementarity. We demonstrate the efficacy of these principles when other factors are not present, and show how the two principles can be combined. This analysis demonstrates that the most cost-effective species to monitor are ones where the information gained from monitoring is most likely to change the allocation of funds for action, not necessarily the most vulnerable or endangered. We suggest these results are general and apply to all ecological monitoring, not just of biological species: monitoring and information are only valuable when they are likely to change how people act.
Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing
NASA Technical Reports Server (NTRS)
Chien, Steve A.; Tran, Daniel Q.; Doubleday, Joshua R.; Doggett, Thomas
2013-01-01
A generic software framework analyzes data from broad coverage sweeps or general larger areas of interest. Change detection methods are used to extract subsets of directed swath areas that intersect areas of change. These areas are prioritized and allocated to targetable assets. This method is deployed in an automatic fashion, and has operated without human monitoring or intervention for sustained periods of time (months).
Neurophysiological detection of impending spinal cord injury during scoliosis surgery.
Schwartz, Daniel M; Auerbach, Joshua D; Dormans, John P; Flynn, John; Drummond, Denis S; Bowe, J Andrew; Laufer, Samuel; Shah, Suken A; Bowen, J Richard; Pizzutillo, Peter D; Jones, Kristofer J; Drummond, Denis S
2007-11-01
Despite the many reports attesting to the efficacy of intraoperative somatosensory evoked potential monitoring in reducing the prevalence of iatrogenic spinal cord injury during corrective scoliosis surgery, these afferent neurophysiological signals can provide only indirect evidence of injury to the motor tracts since they monitor posterior column function. Early reports on the use of transcranial electric motor evoked potentials to monitor the corticospinal motor tracts directly suggested that the method holds great promise for improving detection of emerging spinal cord injury. We sought to compare the efficacy of these two methods of monitoring to detect impending iatrogenic neural injury during scoliosis surgery. We reviewed the intraoperative neurophysiological monitoring records of 1121 consecutive patients (834 female and 287 male) with adolescent idiopathic scoliosis (mean age, 13.9 years) treated between 2000 and 2004 at four pediatric spine centers. The same group of experienced surgical neurophysiologists monitored spinal cord function in all patients with use of a standardized multimodality technique with the patient under total intravenous anesthesia. A relevant neurophysiological change (an alert) was defined as a reduction in amplitude (unilateral or bilateral) of at least 50% for somatosensory evoked potentials and at least 65% for transcranial electric motor evoked potentials compared with baseline. Thirty-eight (3.4%) of the 1121 patients had recordings that met the criteria for a relevant signal change (i.e., an alert). Of those thirty-eight patients, seventeen showed suppression of the amplitude of transcranial electric motor evoked potentials in excess of 65% without any evidence of changes in somatosensory evoked potentials. In nine of the thirty-eight patients, the signal change was related to hypotension and was corrected with augmentation of the blood pressure. The remaining twenty-nine patients had an alert that was related directly to a surgical maneuver. Three alerts occurred following segmental vessel clamping, and the remaining twenty-six were related to posterior instrumentation and correction. Nine (35%) of these twenty-six patients with an instrumentation-related alert, or 0.8% of the cohort, awoke with a transient motor and/or sensory deficit. Seven of these nine patients presented solely with a motor deficit, which was detected by intraoperative monitoring of transcranial electric motor evoked potentials in all cases, and two patients had only sensory symptoms. Somatosensory evoked potential monitoring failed to identify a motor deficit in four of the seven patients with a confirmed motor deficit. Furthermore, when changes in somatosensory evoked potentials occurred, they lagged behind the changes in transcranial electric motor evoked potentials by an average of approximately five minutes. With an appropriate response to the alert, the motor or sensory deficit resolved in all nine patients within one to ninety days. This study underscores the advantage of monitoring the spinal cord motor tracts directly by recording transcranial electric motor evoked potentials in addition to somatosensory evoked potentials. Transcranial electric motor evoked potentials are exquisitely sensitive to altered spinal cord blood flow due to either hypotension or a vascular insult. Moreover, changes in transcranial electric motor evoked potentials are detected earlier than are changes in somatosensory evoked potentials, thereby facilitating more rapid identification of impending spinal cord injury.
2013-09-01
Hemodynamic Decompensation During Blood Loss in Humans PRINCIPAL INVESTIGATOR: Michael J. Joyner, M.D. CONTRACTING ORGANIZATION: Mayo Clinic...Medical Monitoring System for Early Detection of Potential Hemodynamic Decompensation During Blood Loss in Humans 5c. PROGRAM ELEMENT NUMBER 6...loss and hemorrhage in humans. The aim Is to be able to detect subtle changes in hemodynamic variables that provide prodromal clues to Impending
Jennifer E. Carlson; Douglas D. Piirto; John J. Keane; Samantha J. Gill
2015-01-01
Long-term monitoring programs that can detect a population change over time can be useful for managers interested in assessing population trends in response to forest management activities for a particular species. Such long-term monitoring programs have been designed for the Northern Goshawk (Accipiter gentilis), but not for the more elusive Sharp...
Network monitoring in the Tier2 site in Prague
NASA Astrophysics Data System (ADS)
Eliáš, Marek; Fiala, Lukáš; Horký, Jiří; Chudoba, Jiří; Kouba, Tomáš; Kundrát, Jan; Švec, Jan
2011-12-01
Network monitoring provides different types of view on the network traffic. It's output enables computing centre staff to make qualified decisions about changes in the organization of computing centre network and to spot possible problems. In this paper we present network monitoring framework used at Tier-2 in Prague in Institute of Physics (FZU). The framework consists of standard software and custom tools. We discuss our system for hardware failures detection using syslog logging and Nagios active checks, bandwidth monitoring of physical links and analysis of NetFlow exports from Cisco routers. We present tool for automatic detection of network layout based on SNMP. This tool also records topology changes into SVN repository. Adapted weathermap4rrd is used to visualize recorded data to get fast overview showing current bandwidth usage of links in network.
Multi-Dimensional Damage Detection
NASA Technical Reports Server (NTRS)
Gibson, Tracy L. (Inventor); Williams, Martha K. (Inventor); Roberson, Luke B. (Inventor); Lewis, Mark E. (Inventor); Snyder, Sarah J. (Inventor); Medelius, Pedro J. (Inventor)
2016-01-01
Methods and systems may provide for a structure having a plurality of interconnected panels, wherein each panel has a plurality of detection layers separated from one another by one or more non-detection layers. The plurality of detection layers may form a grid of conductive traces. Additionally, a monitor may be coupled to each grid of conductive traces, wherein the monitor is configured to detect damage to the plurality of interconnected panels in response to an electrical property change with respect to one or more of the conductive traces. In one example, the structure is part of an inflatable space platform such as a spacecraft or habitat.
NASA Technical Reports Server (NTRS)
Wilkins, J. R. (Inventor)
1981-01-01
The growth of microorganisms in a sample is detected and monitored by culturing microorganisms in a growth medium and detecting a change in potential between two electrodes, separated from the microbial growth by a barrier which is permeable to charged paticles but microorganism impermeable.
USDA-ARS?s Scientific Manuscript database
A change detection experiment for an invasive species, saltcedar, near Lovelock, Nevada, was conducted with multi-date Compact Airborne Spectrographic Imager (CASI) hyperspectral datasets. Classification and NDVI differencing change detection methods were tested, In the classification strategy, a p...
The Swift/BAT Hard X-ray Transient Monitor: A Status Report
NASA Astrophysics Data System (ADS)
Krimm, Hans A.; Bloom, J. S.; Markwardt, C.; Miler-Jones, J.; Gehrels, N.; Kennea, J. A.; Holland, S.; Sivakoff, G. R.; Swift/BAT Team
2013-04-01
The Swift/Burst Alert Telescope (BAT) hard X-ray transient monitor provides near real-time coverage of the X-ray sky in the energy range 15-50 keV. This monitor was first announced at the 2006 HEAD meeting. Seven years later, it continues to operate and provides near real-time light curves of more than 900 astrophysical sources. The BAT observes ~75% of the sky each day with a 3-sigma detection sensitivity of 7 mCrab for a full-day observation and a time resolution as fine as 64 seconds. The three main purposes of the monitor are (1) the discovery of new transient X-ray sources, (2) the detection of outbursts or other changes in the flux of known X-ray sources, and (3) the generation of archival light curves spanning nearly seven years. The primary interface for the BAT transient monitor is a public web page. Since February 2005, 223 sources have been detected in the monitor, 142 of them persistent and 81 detected only in outburst. From 2006-2013, fourteen new sources have been discovered by the BAT transient monitor. We will describe the methodology of the transient monitor, present a summary of its statistics, and discuss the detection of known and newly discovered sources.
The Swift/BAT Hard X-ray Transient Monitor: A Status Report
NASA Astrophysics Data System (ADS)
Krimm, Hans A.; Swift/BAT Team
2011-09-01
The Swift/Burst Alert Telescope (BAT) hard X-ray transient monitor provides near real-time coverage of the X-ray sky in the energy range 15-50 keV. This monitor was first announced at the 2006 HEAD meeting. Five years later, it continues to operate and provides near real-time light curves of more than 900 astrophysical sources. The BAT observes 75% of the sky each day with a 3-sigma detection sensitivity of 7 mCrab for a full-day observation and a time resolution as fine as 64 seconds. The three main purposes of the monitor are (1) the discovery of new transient X-ray sources, (2) the detection of outbursts or other changes in the flux of known X-ray sources, and (3) the generation of archival light curves spanning nearly seven years. The primary interface for the BAT transient monitor is a public web page. Since February 2005, 172 sources have been detected in the monitor, 89 of them persistent and 83 detected only in outburst. From 2006-2011, nine new sources have been discovered by the BAT transient monitor. We will describe the methodology of the transient monitor, present a summary of its statistics, and discuss the detection of known and newly discovered sources.
The Swift/BAT Hard X-ray Transient Monitor
NASA Technical Reports Server (NTRS)
Krimm, H. A.; Holland, S. T.; Corbet, R.H.D.; Pearlman, A. B.; Romano, P.; Kennea, J. A.; Bloom, J. S.; Barthelmy, S. D.; Baumgartner, W. H.; Cummings, J. R.;
2013-01-01
The Swift/Burst Alert Telescope (BAT) hard X-ray transient monitor provides near real-time coverage of the X-ray sky in the energy range 15-50 keV. The BAT observes 88% of the sky each day with a detection sensitivity of 5.3 mCrab for a full-day observation and a time resolution as ne as 64 seconds. The three main purposes of the monitor are (1) the discovery of new transient X-ray sources, (2) the detection of outbursts or other changes in the ux of known X-ray sources, and (3) the generation of light curves of more than 900 sources spanning over eight years. The primary interface for the BAT transient monitor is a public web page. Since 2005 February, 242 sources have been detected in the monitor, 149 of them persistent and 93 detected only in outburst. Among these sources, 16 were previously unknown and discovered in the transient monitor. In this paper, we discuss the methodology and the data processing and ltering for the BAT transient monitor and review its sensitivity and exposure. We provide a summary of the source detections and classify them according to the variability of their light curves. Finally, we review all new BAT monitor discoveries and present basic data analysis and interpretations for those sources with previously unpublished results.
NASA Astrophysics Data System (ADS)
Kranz, Olaf; Lang, Stefan; Schoepfer, Elisabeth
2017-09-01
Mining natural resources serve fundamental societal needs or commercial interests, but it may well turn into a driver of violence and regional instability. In this study, very high resolution (VHR) optical stereo satellite data are analysed to monitor processes and changes in one of the largest artisanal and small-scale mining sites in the Democratic Republic of the Congo, which is among the world's wealthiest countries in exploitable minerals To identify the subtle structural changes, the applied methodological framework employs object-based change detection (OBCD) based on optical VHR data and generated digital surface models (DSM). Results prove the DSM-based change detection approach enhances the assessment gained from sole 2D analyses by providing valuable information about changes in surface structure or volume. Land cover changes as analysed by OBCD reveal an increase in bare soil area by a rate of 47% between April 2010 and September 2010, followed by a significant decrease of 47.5% until March 2015. Beyond that, DSM differencing enabled the characterisation of small-scale features such as pits and excavations. The presented Earth observation (EO)-based monitoring of mineral exploitation aims at a better understanding of the relations between resource extraction and conflict, and thus providing relevant information for potential mitigation strategies and peace building.
Detecting the climatic effects of increasing carbon dioxide
DOE Office of Scientific and Technical Information (OSTI.GOV)
MacCracken, M C; Luther, F M
1985-12-01
This report documents what is known about detecting the CO2-induced changes in climate, and describes the uncertainties and unknowns associated with this monitoring and analysis effort. The various approaches for detecting CO2-induced climate changes are discussed first, followed by a review of applications of these strategies to the various climatic variables that are expected to be changing. Recommendations are presented for research and analysis activities. Separate abstracts have been prepared for the individual papers. (ACR)
NASA Astrophysics Data System (ADS)
Webb, N.; Chappell, A.; Van Zee, J.; Toledo, D.; Duniway, M.; Billings, B.; Tedela, N.
2017-12-01
Anthropogenic land use and land cover change (LULCC) influence global rates of wind erosion and dust emission, yet our understanding of the magnitude of the responses remains poor. Field measurements and monitoring provide essential data to resolve aeolian sediment transport patterns and assess the impacts of human land use and management intensity. Data collected in the field are also required for dust model calibration and testing, as models have become the primary tool for assessing LULCC-dust cycle interactions. However, there is considerable uncertainty in estimates of dust emission due to the spatial variability of sediment transport. Field sampling designs are currently rudimentary and considerable opportunities are available to reduce the uncertainty. Establishing the minimum detectable change is critical for measuring spatial and temporal patterns of sediment transport, detecting potential impacts of LULCC and land management, and for quantifying the uncertainty of dust model estimates. Here, we evaluate the effectiveness of common sampling designs (e.g., simple random sampling, systematic sampling) used to measure and monitor aeolian sediment transport rates. Using data from the US National Wind Erosion Research Network across diverse rangeland and cropland cover types, we demonstrate how only large changes in sediment mass flux (of the order 200% to 800%) can be detected when small sample sizes are used, crude sampling designs are implemented, or when the spatial variation is large. We then show how statistical rigour and the straightforward application of a sampling design can reduce the uncertainty and detect change in sediment transport over time and between land use and land cover types.
Pohl, Kilian M; Konukoglu, Ender; Novellas, Sebastian; Ayache, Nicholas; Fedorov, Andriy; Talos, Ion-Florin; Golby, Alexandra; Wells, William M; Kikinis, Ron; Black, Peter M
2011-03-01
Change detection is a critical component in the diagnosis and monitoring of many slowly evolving pathologies. This article describes a semiautomatic monitoring approach using longitudinal medical images. We test the method on brain scans of patients with meningioma, which experts have found difficult to monitor because the tumor evolution is very slow and may be obscured by artifacts related to image acquisition. We describe a semiautomatic procedure targeted toward identifying difficult-to-detect changes in brain tumor imaging. The tool combines input from a medical expert with state-of-the-art technology. The software is easy to calibrate and, in less than 5 minutes, returns the total volume of tumor change in mm. We test the method on postgadolinium, T1-weighted magnetic resonance images of 10 patients with meningioma and compare our results with experts' findings. We also perform benchmark testing with synthetic data. Our experiments indicated that experts' visual inspections are not sensitive enough to detect subtle growth. Measurements based on experts' manual segmentations were highly accurate but also labor intensive. The accuracy of our approach was comparable to the experts' results. However, our approach required far less user input and generated more consistent measurements. The sensitivity of experts' visual inspection is often too low to detect subtle growth of meningiomas from longitudinal scans. Measurements based on experts' segmentation are highly accurate but generally too labor intensive for standard clinical settings. We described an alternative metric that provides accurate and robust measurements of subtle tumor changes while requiring a minimal amount of user input.
Third National Aeronautics and Space Administration Weather and climate program science review
NASA Technical Reports Server (NTRS)
Kreins, E. R. (Editor)
1977-01-01
Research results of developing experimental and prototype operational systems, sensors, and space facilities for monitoring, and understanding the atmosphere are reported. Major aspects include: (1) detection, monitoring, and prediction of severe storms; (2) improvement of global forecasting; and (3) monitoring and prediction of climate change.
Monitoring watersheds and streams
Robert R. Ziemer
1998-01-01
Regulations increasingly require monitoring to detect changes caused by land management activities. Successful monitoring requires that objectives be clearly stated. Once objectives are clearly identified, it is important to map out all of the components and links that might affect the issues of concern. For each issue and each component that affects that issue, there...
Building Change Detection from Harvey using Unmanned Aerial System (UAS)
NASA Astrophysics Data System (ADS)
Chang, A.; Yeom, J.; Jung, J.; Choi, I.
2017-12-01
Unmanned Aerial System (UAS) is getting to be the most important technique in recent days since the fine spatial and high temporal resolution data previously unobtainable from traditional remote sensing platforms. Advanced UAS data can provide a great opportunity for disaster monitoring. Especially, building change detection is the one of the most important topics for damage assessment and recovery from disasters. This study is proposing a method to monitor building change with UAS data for Holiday Beach in Texas, where was directly hit by Harvey on 25 August 2017. This study adopted 3D change detection to monitor building damage and recovery levels with building height as well as natural color information. We used a rotorcraft UAS to collect RGB data twice on 9 September and 18 October 2017 after the hurricane. The UAS data was processed using Agisoft Photoscan Pro Software to generate super high resolution dataset including orthomosaic, DSM (Digital Surface Model), and 3D point cloud. We compared the processed dataset with an airborne image considerable as before-hurricane data, which was acquired on January 2016. Building damage and recovery levels were determined by height and color change. The result will show that UAS data is useful to assess building damage and recovery for affected area by the natural disaster such as Harvey.
Sanmartín, P; Vázquez-Nion, D; Silva, B; Prieto, B
2012-01-01
This paper addresses the detection and monitoring of the development of epilithic phototrophic biofilms on the granite façade of an institutional building in Santiago de Compostela (NW Spain), and reports a case study of preventive conservation. The results provide a basis for establishing criteria for the early detection of phototrophic colonization (greening) and for monitoring its development on granite buildings by the use of color changes recorded with a portable spectrophotometer and represented in the CIELAB color space. The results show that parameter b* (associated with changes of yellowness-blueness) provides the earliest indication of colonization and varies most over time, so that it is most important in determining the total color change. The limit of perception of the greening on a granite surface was also established in a psycho-physical experiment, as Δb*: +0.59 CIELAB units that correspond, in the present study, to 6.3 μg of biomass dry weight cm(-2) and (8.43 ± 0.24) × 10(-3) μg of extracted chlorophyll a cm(-2).
Development of new structural health monitoring techniques
NASA Astrophysics Data System (ADS)
Fekrmandi, Hadi
During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop -- DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.
Monitoring forest dynamics with multi-scale and time series imagery.
Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong
2016-05-01
To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.
Accidental Beam Losses and Protection in the LHC
NASA Astrophysics Data System (ADS)
Schmidt, R.; Working Group On Machine Protection
2005-06-01
At top energy (proton momentum 7 TeV/c) with nominal beam parameters, each of the two LHC proton beams has a stored energy of 350 MJ threatening to damage accelerator equipment in case of accidental beam loss. It is essential that the beams are properly extracted onto the dump blocks in case of failure since these are the only elements that can withstand full beam impact. Although the energy stored in the beams at injection (450 GeV/c) is about 15 times smaller compared to top energy, the beams must still be properly extracted in case of large accidental beam losses. Failures must be detected at a sufficiently early stage and initiate a beam dump. Quenches and power converter failures will be detected by monitoring the correct functioning of the hardware systems. In addition, safe operation throughout the cycle requires the use of beam loss monitors, collimators and absorbers. Ideas of detection of fast beam current decay, monitoring of fast beam position changes and monitoring of fast magnet current changes are discussed, to provide the required redundancy for machine protection.
Hou, Fang; Lesmes, Luis Andres; Kim, Woojae; Gu, Hairong; Pitt, Mark A.; Myung, Jay I.; Lu, Zhong-Lin
2016-01-01
The contrast sensitivity function (CSF) has shown promise as a functional vision endpoint for monitoring the changes in functional vision that accompany eye disease or its treatment. However, detecting CSF changes with precision and efficiency at both the individual and group levels is very challenging. By exploiting the Bayesian foundation of the quick CSF method (Lesmes, Lu, Baek, & Albright, 2010), we developed and evaluated metrics for detecting CSF changes at both the individual and group levels. A 10-letter identification task was used to assess the systematic changes in the CSF measured in three luminance conditions in 112 naïve normal observers. The data from the large sample allowed us to estimate the test–retest reliability of the quick CSF procedure and evaluate its performance in detecting CSF changes at both the individual and group levels. The test–retest reliability reached 0.974 with 50 trials. In 50 trials, the quick CSF method can detect a medium 0.30 log unit area under log CSF change with 94.0% accuracy at the individual observer level. At the group level, a power analysis based on the empirical distribution of CSF changes from the large sample showed that a very small area under log CSF change (0.025 log unit) could be detected by the quick CSF method with 112 observers and 50 trials. These results make it plausible to apply the method to monitor the progression of visual diseases or treatment effects on individual patients and greatly reduce the time, sample size, and costs in clinical trials at the group level. PMID:27120074
Aerial detection surveys in the United States
E. W. Johnson; D. Wittwer
2006-01-01
Aerial detection surveys, also known as aerial sketchmapping, is a remote sensing technique of observing forest change events from an aircraft and documenting them manually onto a map. Data from aerial surveys have become an important component of the Forest Health Monitoring, a national program designed to determine the status, changes, and trends in indicators of...
USDA-ARS?s Scientific Manuscript database
Lycopene is a major carotenoid in tomatoes and detecting changes in lycopene content can be used to monitor the ripening of tomatoes. Raman chemical imaging is a new technique that shows promise for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scanning...
Control for monitoring thickness of high temperature refractory
Caines, M.J.
1982-11-23
This invention teaches an improved monitoring device for detecting the changes in thickness of high-temperature refractory, the device consists of a probe having at least two electrically conductive generally parallel elements separated by a dielectric material. The probe is implanted or embedded directly in the refractory and is elongated to extend in line with the refractory thickness to be measured. Electrical inputs to the conductive elements provide that either or both the electrical conductance or capacitance can be found, so that charges over lapsed time periods can be compared in order to detect changes in the thickness of the refractory.
NASA Astrophysics Data System (ADS)
ui, Hirotaka; Moriuchi, Hiroyuki; Takemura, Yukiko; Tsuchida, Hiroko; Fujii, Iwao; Nakamura, Masaru
1988-09-01
Radon alpha tracks monitored at six sites increased gradually three months before (detected by microscopic counting), and increased remarkably 2 weeks before (detected by both mechanical and microscopic counting) the western Nagano Prefecture earthquake ( M 6.8) which occurred on September 14, 1984. The monitoring sites were located about 65 km northwest of the epicenter, on the shear zone of the Atotsugawa fault. The changes in radon emanation are considered to be related to the earthquake rather than to changes in meteorological conditions.
Monitoring on Xi'an ground fissures deformation with TerraSAR-X data
Zhao, C.; Zhang, Q.; Zhu, W.; Lu, Z.
2012-01-01
Owing to the fine resolution of TerraSAR-X data provided since 2007, this paper applied 6 TerraSAR data (strip mode) during 3rd Dec. 2009 to 23rd Mar. 2010 to detect and monitor the active fissures over Xi'an region. Three themes have been designed for high precision detection and monitoring of Xi'an-Chang'an fissures, as small baseline subsets (SBAS) to test the atmospheric effects of differential interferograms pair stepwise, 2-pass differential interferogram with very short baseline perpendicular to generate the whole deformation map with 44 days interval, and finally, corner reflector (CR) technique was used to closely monitor the relative deformation time series between two CRs settled crossing two ground fissures. Results showed that TerraSAR data are a good choice for small-scale ground fissures detection and monitoring, while special considerations should be taken for their great temporal and baseline decorrelation. Secondly, ground fissures in Xi'an were mostly detected at the joint section of stable and deformable regions. Lastly, CR-InSAR had potential ability to monitor relative deformation crossing fissures with millimeter precision.
Davies, David James; Clancy, Michael; Dehghani, Hamid; Lucas, Samuel John Edwin; Forcione, Mario; Yakoub, Kamal Makram; Belli, Antonio
2018-06-07
The cost and highly invasive nature of brain monitoring modality in traumatic brain injury patients currently restrict its utility to specialist neurological intensive care settings. We aim to test the abilities of a frequency domain near-infrared spectroscopy (FD-NIRS) device in predicting changes in invasively measured brain tissue oxygen tension. Individuals admitted to a United Kingdom specialist major trauma centre were contemporaneously monitored with an FD-NIRS device and invasively measured brain tissue oxygen tension probe. Area under the curve receiver operating characteristic (AUROC) statistical analysis was utilised to assess the predictive power of FD-NIRS in detecting both moderate and severe hypoxia (20 and 10 mmHg, respectively), as measured invasively. 16 individuals were prospectively recruited to the investigation. Severe hypoxic episodes were detected in 9 of these individuals, with the NIRS demonstrating a broad range of predictive abilities (AUROC 0.68-0.88) from relatively poor to good. Moderate hypoxic episodes were detected in seven individuals with similar predictive performance (AUROC 0.576 - 0.905). A variable performance in the predictive powers of this FD-NIRS device to detect changes in brain tissue oxygen was demonstrated. Consequently, this enhanced NIRS technology has not demonstrated sufficient ability to replace the established invasive measurement.
Forest genetic monitoring: an overview of concepts and definitions.
Fussi, Barbara; Westergren, Marjana; Aravanopoulos, Filippos; Baier, Roland; Kavaliauskas, Darius; Finzgar, Domen; Alizoti, Paraskevi; Bozic, Gregor; Avramidou, Evangelia; Konnert, Monika; Kraigher, Hojka
2016-08-01
Safeguarding sustainability of forest ecosystems with their habitat variability and all their functions is of highest priority. Therefore, the long-term adaptability of forest ecosystems to a changing environment must be secured, e.g., through sustainable forest management. High adaptability is based on biological variation starting at the genetic level. Thus, the ultimate goal of the Convention on Biological Diversity (CBD) to halt the ongoing erosion of biological variation is of utmost importance for forest ecosystem functioning and sustainability. Monitoring of biological diversity over time is needed to detect changes that threaten these biological resources. Genetic variation, as an integral part of biological diversity, needs special attention, and its monitoring can ensure its effective conservation. We compare forest genetic monitoring to other biodiversity monitoring concepts. Forest genetic monitoring (FGM) enables early detection of potentially harmful changes of forest adaptability before these appear at higher biodiversity levels (e.g., species or ecosystem diversity) and can improve the sustainability of applied forest management practices and direct further research. Theoretical genetic monitoring concepts developed up to now need to be evaluated before being implemented on a national and international scale. This article provides an overview of FGM concepts and definitions, discusses their advantages and disadvantages, and provides a flow chart of the steps needed for the optimization and implementation of FGM. FGM is an important module of biodiversity monitoring, and we define an effective FGM scheme as consisting of an assessment of a forest population's capacity to survive, reproduce, and persist under rapid environmental changes on a long-term scale.
NASA Astrophysics Data System (ADS)
Stone, Dáithí A.; Hansen, Gerrit
2016-09-01
Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the "confidence" language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies in considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.
Eric T. Linder; David A. Buehler
2005-01-01
In 1996, Region 8 of the U. S. Forest Service implemented a program to monitor landbirds on southeastern U.S. national forests. The goal was to develop a monitoring system that could document population trends and bird-habitat relationships. Using power analysis, we examined the ability of the monitoring program to detect population trends (3 percent annual change) at...
Intraoperative monitoring for intracranial aneurysms: the Michigan experience.
Sahaya, Kinshuk; Pandey, Aditya S; Thompson, Byron G; Bush, Brian R; Minecan, Daniela N
2014-12-01
Intraoperative neurophysiological monitoring is routinely used during the repair (endovascular or microsurgical) of intracranial aneurysms at major centers. There is a continued need of data sets from institutions with dedicated intraoperative neurophysiological monitoring services to further define the predictive factors of postoperative neurological deficits. We retrospectively reviewed and analyzed our database of all patients who underwent repair of intracranial aneurysms (endovascular or microsurgical). A total of 406 patients underwent 470 procedures. The changes were noted during monitoring in 3.83% of the cases. Most of the changes were first detected in somatosensory evoked potential (88.89%) followed by brainstem auditory evoked potential (16.67%). Changes were completely reversible in 44.44%, only partly reversible in 22.22%, and irreversible in 33.33% of cases. Intraoperative neurophysiological monitoring changes demonstrated high sensitivity, specificity, and negative predictive value for postoperative neurological deficits. The association between intraoperative neurophysiological monitoring changes and Glasgow outcome scale was significant for reversible changes compared against irreversible and partly reversible changes. Presence of any intraoperative neurophysiological monitoring modality change during repair of intracranial aneurysm may suggest a higher risk for postoperative neurological deficits. Reversibility of the changes is a favorable marker, whereas irreversible changes are predictive of postoperative neurological deficits with deterioration of Glasgow outcome scale on a longer follow-up.
NASA Astrophysics Data System (ADS)
Walther, Christian; Frei, Michaela
2017-04-01
Mining of so-called "conflict minerals" is often related with small-scale mining activities. The here discussed activities are located in forested areas in the eastern DRC, which are often remote, difficult to access and insecure for traditional geological field inspection. In order to accelerate their CTC (Certified Trading Chain)-certification process, remote sensing data are used for detection and monitoring of these small-scale mining operations. This requires a high image acquisition frequency due to mining site relocations and for compensation of year-round high cloud coverage, especially for optical data evaluation. Freely available medium resolution optical data of Sentinel-2 and Landsat-8 as well as SAR data of Sentinel-1 are used for detecting small mining targets with a minimum size of approximately 0.5 km2. The developed method enables a robust multi-temporal detection of mining sites, monitoring of mining site spatio-temporal relocations and environmental changes. Since qualitative and quantitative comparable results are generated, the followed change detection approach is objective and transparent and may push the certification process forward.
McCabe, Kevin M.; Hernandez, Mark
2010-01-01
Conventional temperature measurements rely on material responses to heat, which can be detected visually. When Galileo developed an air expansion based device to detect temperature changes, Santorio, a contemporary physician, added a scale to create the first thermometer. With this instrument, patients’ temperatures could be measured, recorded and related to changing health conditions. Today, advances in materials science and bioengineering provide new ways to report temperature at the molecular level in real time. In this review the scientific foundations and history of thermometry underpin a discussion of the discoveries emerging from the field of molecular thermometry. Intracellular nanogels and heat sensing biomolecules have been shown to accurately report temperature changes at the nano-scale. Various systems will soon provide the ability to accurately measure temperature changes at the tissue, cellular, and even sub-cellular level, allowing for detection and monitoring of very small changes in local temperature. In the clinic this will lead to enhanced detection of tumors and localized infection, and accurate and precise monitoring of hyperthermia based therapies. Some nanomaterial systems have even demonstrated a theranostic capacity for heat-sensitive, local delivery of chemotherapeutics. Just as early thermometry moved into the clinic, so too will these molecular thermometers. PMID:20139796
Temporal monitoring of vessels activity using day/night band in Suomi NPP on South China Sea
NASA Astrophysics Data System (ADS)
Yamaguchi, Takashi; Asanuma, Ichio; Park, Jong Geol; Mackin, Kenneth J.; Mittleman, John
2017-05-01
In this research, we focus on vessel detection using the satellite imagery of day/night band (DNB) on Suomi NPP in order to monitor the change of vessel activity on the region of South China Sea. In this paper, we consider the relation between the temporal change of vessel activities and the events on maritime environment based on the vessel traffic density estimation using DNB. DNB is a moderate resolution (350-700m) satellite imagery but can detect the fishing light of fishery boats in night time for every day. The advantage of DNB is the continuous monitoring on wide area compared to another vessel detection and locating system. However, DNB gave strong influence of cloud and lunar refection. Therefore, we additionally used Brightness Temperature at 3.7μm(BT3.7) for cloud information. In our previous research, we construct an empirical vessel detection model that based on the DNB contrast and the estimation of cloud condition using BT3.7. Moreover, we proposed a vessel traffic density estimation method based on empirical model. In this paper, we construct the time temporal density estimation map on South China Sea and East China Sea in order to extract the knowledge from vessel activities change.
Classification of change detection and change blindness from near-infrared spectroscopy signals
NASA Astrophysics Data System (ADS)
Tanaka, Hirokazu; Katura, Takusige
2011-08-01
Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.
Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery
Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.
2016-01-01
Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.
The Swift-BAT Hard X-Ray Transient Monitor
NASA Technical Reports Server (NTRS)
Krimm, H. A.; Holland, S. T.; Corbet, R. H. D.; Pearlman, A. B.; Romano, P.; Kennea, J. A.; Bloom, J. S.; Barthelmy, S. D.; Baumgartner, W. H.; Cummings, J. R.;
2013-01-01
The Swift/Burst Alert Telescope (BAT) hard X-ray transient monitor provides near real-time coverage of the X-ray sky in the energy range 15-50 keV. The BAT observes 88% of the sky each day with a detection sensitivity of 5.3 mCrab for a full-day observation and a time resolution as fine as 64 s. The three main purposes of the monitor are (1) the discovery of new transient X-ray sources, (2) the detection of outbursts or other changes in the flux of known X-ray sources, and (3) the generation of light curves of more than 900 sources spanning over eight years. The primary interface for the BAT transient monitor is a public Web site. Between 2005 February 12 and 2013 April 30, 245 sources have been detected in the monitor, 146 of them persistent and 99 detected only in outburst. Among these sources, 17 were previously unknown and were discovered in the transient monitor. In this paper, we discuss the methodology and the data processing and filtering for the BAT transient monitor and review its sensitivity and exposure.We provide a summary of the source detections and classify them according to the variability of their light curves. Finally, we review all new BAT monitor discoveries. For the new sources that are previously unpublished, we present basic data analysis and interpretations.
THE SWIFT/BAT HARD X-RAY TRANSIENT MONITOR
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krimm, H. A.; Holland, S. T.; Corbet, R. H. D.
2013-11-01
The Swift/Burst Alert Telescope (BAT) hard X-ray transient monitor provides near real-time coverage of the X-ray sky in the energy range 15-50 keV. The BAT observes 88% of the sky each day with a detection sensitivity of 5.3 mCrab for a full-day observation and a time resolution as fine as 64 s. The three main purposes of the monitor are (1) the discovery of new transient X-ray sources, (2) the detection of outbursts or other changes in the flux of known X-ray sources, and (3) the generation of light curves of more than 900 sources spanning over eight years. Themore » primary interface for the BAT transient monitor is a public Web site. Between 2005 February 12 and 2013 April 30, 245 sources have been detected in the monitor, 146 of them persistent and 99 detected only in outburst. Among these sources, 17 were previously unknown and were discovered in the transient monitor. In this paper, we discuss the methodology and the data processing and filtering for the BAT transient monitor and review its sensitivity and exposure. We provide a summary of the source detections and classify them according to the variability of their light curves. Finally, we review all new BAT monitor discoveries. For the new sources that are previously unpublished, we present basic data analysis and interpretations.« less
NASA Astrophysics Data System (ADS)
Corodeanu, S.; Chiriac, H.; Radulescu, L.; Lupu, N.
2014-05-01
Results on the development and testing of a novel magnetic sensor based on the detection of the magneto-impedance variation due to changes in the permeability of an amorphous wire are reported. The proposed application is the quasi-noncontact monitoring of the breathing frequency and heart rate for diagnosing sleep disorders. Patient discomfort is significantly decreased by transversally placing the sensitive element onto the surface of a flexible mattress in order to detect its deformation associated with cardiorespiratory activity and body movements. The developed sensor has a great application potential in monitoring the vital signs during sleep, with special advantages for children sleep monitoring.
Early Detection of Physical Activity for People With Type 1 Diabetes Mellitus.
Dasanayake, Isuru S; Bevier, Wendy C; Castorino, Kristin; Pinsker, Jordan E; Seborg, Dale E; Doyle, Francis J; Dassau, Eyal
2015-06-30
Early detection of exercise in individuals with type 1 diabetes mellitus (T1DM) may allow changes in therapy to prevent hypoglycemia. Currently there is limited experience with automated methods that detect the onset and end of exercise in this population. We sought to develop a novel method to quickly and reliably detect the onset and end of exercise in these individuals before significant changes in blood glucose (BG) occur. Sixteen adults with T1DM were studied as outpatients using a diary, accelerometer, heart rate monitor, and continuous glucose monitor for 2 days. These data were used to develop a principal component analysis based exercise detection method. Subjects also performed 60 and 30 minute exercise sessions at 30% and 50% predicted heart rate reserve (HRR), respectively. The detection method was applied to the exercise sessions to determine how quickly the detection of start and end of exercise occurred relative to change in BG. Mild 30% HRR and moderate 50% HRR exercise onset was identified in 6 ± 3 and 5 ± 2 (mean ± SD) minutes, while completion was detected in 3 ± 8 and 6 ± 5 minutes, respectively. BG change from start of exercise to detection time was 1 ± 6 and -1 ± 3 mg/dL, and, from the end of exercise to detection time was 6 ± 4 and -17 ± 13 mg/dL, respectively, for the 2 exercise sessions. False positive and negative ratios were 4 ± 2% and 21 ± 22%. The novel method for exercise detection identified the onset and end of exercise in approximately 5 minutes, with an average BG change of only -6 mg/dL. © 2015 Diabetes Technology Society.
NASA Astrophysics Data System (ADS)
Roessler, D.; Weber, B.; Ellguth, E.; Spazier, J.
2017-12-01
The geometry of seismic monitoring networks, site conditions and data availability as well as monitoring targets and strategies typically impose trade-offs between data quality, earthquake detection sensitivity, false detections and alert times. Network detection capabilities typically change with alteration of the seismic noise level by human activity or by varying weather and sea conditions. To give helpful information to operators and maintenance coordinators, gempa developed a range of tools to evaluate earthquake detection and network performance including qceval, npeval and sceval. qceval is a module which analyzes waveform quality parameters in real-time and deactivates and reactivates data streams based on waveform quality thresholds for automatic processing. For example, thresholds can be defined for latency, delay, timing quality, spikes and gaps count and rms. As changes in the automatic processing have a direct influence on detection quality and speed, another tool called "npeval" was designed to calculate in real-time the expected time needed to detect and locate earthquakes by evaluating the effective network geometry. The effective network geometry is derived from the configuration of stations participating in the detection. The detection times are shown as an additional layer on the map and updated in real-time as soon as the effective network geometry changes. Yet another new tool, "sceval", is an automatic module which classifies located seismic events (Origins) in real-time. sceval evaluates the spatial distribution of the stations contributing to an Origin. It confirms or rejects the status of Origins, adds comments or leaves the Origin unclassified. The comments are passed to an additional sceval plug-in where the end user can customize event types. This unique identification of real and fake events in earthquake catalogues allows to lower network detection thresholds. In real-time monitoring situations operators can limit the processing to events with unclassified Origins, reducing their workload. Classified Origins can be treated specifically by other procedures. These modules have been calibrated and fully tested by several complex seismic monitoring networks in the region of Indonesia and Northern Chile.
Zeng, Lizhang; Zhou, Jun; Li, Bo; Xing, Da
2015-01-01
Biotic stressors, especially pathogenic microorganisms, are rather difficult to detect. In plants, one of the earliest cellular responses following pathogen infection is the production of reactive oxygen species (ROS). In this study, a novel optical device for the early monitoring of Pseudomonas attack was developed; this device measures the ROS level via oxidation-sensitive 2′, 7′-dichlorodihydrofluorescein diacetate (H2DCFDA)-mediated fluorescence, which could provide early monitoring of attacks by a range of plant pathogen; ROS bursts were detected in vivo in Arabidopsis thaliana with higher sensitivity and accuracy than those of a commercial luminescence spectrophotometer. Additionally, the DCF fluorescence truly reflected early changes in the ROS level, as indicated by an evaluation of the H2O2 content and the tight association between the ROS and Pseudomonas concentration. Moreover, compared with traditional methods for detecting plant pathogen attacks based on physiological and biochemical measurements, our proposed technique also offers significant advantages, such as low cost, simplicity, convenient operation and quick turnaround. These results therefore suggest that the proposed optical device could be useful for the rapid monitoring of attacks by plant pathogen and yield results considerably earlier than the appearance of visual changes in plant morphology or growth. PMID:25767474
Results of neutron irradiation of GEM detector for plasma radiation detection
NASA Astrophysics Data System (ADS)
Jednorog, S.; Bienkowska, B.; Chernyshova, M.; Łaszynska, E.; Prokopowicz, R.; Ziołkowski, A.
2015-09-01
The detecting devices dedicated for plasma monitoring will be exposed for massive fluxes of neutron, photons as well as other rays that are components of fusion reactions and their product interactions with plasma itself or surroundings. In result detecting module metallic components will be activated becoming a source of radiation. Moreover, electronics components could change their electronic properties. The prototype GEM detector constructed for monitoring soft X-ray radiation in ITER oriented tokamaks was used for plasma monitoring during experimental campaign on tokamak ASDEX Upgrade. After that it became a source of gamma radiation caused by neutrons. The present work contains description of detector activation in the laboratory conditions.
Cheng, Mengzhu; Wang, Lihong; Yang, Qing; Huang, Xiaohua
2018-08-30
The pollution of rare earth elements (REEs) in ecosystem is becoming more and more serious, so it is urgent to establish methods for monitoring the pollution of REEs. Monitoring environmental pollution via the response of plants to pollutants has become the most stable and accurate method compared with traditional methods, but scientists still need to find the primary response of plants to pollutants to improve the sensitivity and speed of this method. Based on the facts that the initiation of endocytosis is the primary cellular response of the plant leaf cells to REEs and the detection of endocytosis is complex and expensive, we constructed a detection method in living plant cells for rapidly monitoring the response of plants to exogenous lanthanum [La(III), a representative of REEs] by designing a new immuno-electrochemical method for detecting the content change in extracellular vitronectin-like protein (VN) that are closely related to endocytosis. Results showed that when 30 μM La(III) initiated a small amount of endocytosis, the content of extracellular VN increased by 5.46 times, but the structure and function of plasma membrane were not interfered by La(III); when 80 μM La(III) strongly initiated a large amount of endocytosis, the content of extracellular VN increased by 119 times, meanwhile, the structure and function of plasma membrane were damaged. In summary, the detection method can reflect the response of plants to La(III) via detecting the content change in extracellular VN, which provides an effective and convenient way to monitor the response of plants to exogenous REEs. Copyright © 2018. Published by Elsevier Inc.
NASA Astrophysics Data System (ADS)
Stolz, Martin; Gottardi, Riccardo; Raiteri, Roberto; Miot, Sylvie; Martin, Ivan; Imer, Raphaël; Staufer, Urs; Raducanu, Aurelia; Düggelin, Marcel; Baschong, Werner; Daniels, A. U.; Friederich, Niklaus F.; Aszodi, Attila; Aebi, Ueli
2009-03-01
The pathological changes in osteoarthritis-a degenerative joint disease prevalent among older people-start at the molecular scale and spread to the higher levels of the architecture of articular cartilage to cause progressive and irreversible structural and functional damage. At present, there are no treatments to cure or attenuate the degradation of cartilage. Early detection and the ability to monitor the progression of osteoarthritis are therefore important for developing effective therapies. Here, we show that indentation-type atomic force microscopy can monitor age-related morphological and biomechanical changes in the hips of normal and osteoarthritic mice. Early damage in the cartilage of osteoarthritic patients undergoing hip or knee replacements could similarly be detected using this method. Changes due to aging and osteoarthritis are clearly depicted at the nanometre scale well before morphological changes can be observed using current diagnostic methods. Indentation-type atomic force microscopy may potentially be developed into a minimally invasive arthroscopic tool to diagnose the early onset of osteoarthritis in situ.
rSPACE: Spatially based power analysis for conservation and ecology
Martha M. Ellis; Jacob S. Ivan; Jody M. Tucker; Michael K. Schwartz
2015-01-01
1.) Power analysis is an important step in designing effective monitoring programs to detect trends in plant or animal populations. Although project goals often focus on detecting changes in population abundance, logistical constraints may require data collection on population indices, such as detection/non-detection data for occupancy estimation. 2.) We describe the...
A Behaviour Monitoring System (BMS) for Ambient Assisted Living
Eisa, Samih
2017-01-01
Unusual changes in the regular daily mobility routine of an elderly person at home can be an indicator or early symptom of developing health problems. Sensor technology can be utilised to complement the traditional healthcare systems to gain a more detailed view of the daily mobility of a person at home when performing everyday tasks. We hypothesise that data collected from low-cost sensors such as presence and occupancy sensors can be analysed to provide insights on the daily mobility habits of the elderly living alone at home and to detect routine changes. We validate this hypothesis by designing a system that automatically learns the daily room-to-room transitions and permanence habits in each room at each time of the day and generates alarm notifications when deviations are detected. We present an algorithm to process the sensors’ data streams and compute sensor-driven features that describe the daily mobility routine of the elderly as part of the developed Behaviour Monitoring System (BMS). We are able to achieve low detection delay with confirmation time that is high enough to convey the detection of a set of common abnormal situations. We illustrate and evaluate BMS with synthetic data, generated by a developed data generator that was designed to mimic different user’s mobility profiles at home, and also with a real-life dataset collected from prior research work. Results indicate BMS detects several mobility changes that can be symptoms of common health problems. The proposed system is a useful approach for learning the mobility habits at the home environment, with the potential to detect behaviour changes that occur due to health problems, and therefore, motivating progress toward behaviour monitoring and elder’s care. PMID:28837105
Quantitative monitoring of subsurface CO2 emplacement and leakage using muon tomography
NASA Astrophysics Data System (ADS)
Coleman, M. L.; Kudryavtsev, V.; Spooner, N.; Gluyas, J.; Fung, C.
2011-12-01
Monitoring CO2 emplacement and possible leakage is a major challenge; methods, such as repeat seismic surveys, are episodic and expensive. A relevant alternative approach will use detection of cosmic ray muons, which has been used previously in archaeological and geological research as a technique for mapping features hidden underground. We developed a model to test if this concept would work for monitoring CO2 storage and show that muon detection is a viable method. To achieve this we used the well-established MUSUN/MUSIC computer codes to model changes in muon fluxes resulting from the introduction of supercritical CO2 into a simulated sandstone reservoir. Results from our first simulation indicate that we could detect as little as 0.4% change in the mean reservoir density at about 1 km depth, resulting from changing the relative proportions of CO2 and existing brine pore fluid. This change is equivalent to 7% of the pore volume in this particular case. However, other scenarios offer the promise of considerable increase in sensitivity. We will show how practical implementation can be achieved using state of the art drilling technology to place an array of detectors in short-radius side-track horizontal wells beneath the storage site. We conclude that with an appropriate design it will be possible to monitor and image the migration or loss of injected CO2 continuously using cosmic ray muons, a significant step towards implementing widescale CCS safely and help rapid introduction of this essential technology.
NASA Astrophysics Data System (ADS)
Zhu, Yunqiang; Zhu, Huazhong; Lu, Heli; Ni, Jianguang; Zhu, Shaoxia
2005-10-01
Remote sensing dynamic monitoring of land use can detect the change information of land use and update the current land use map, which is important for rational utilization and scientific management of land resources. This paper discusses the technological procedure of remote sensing dynamic monitoring of land use including the process of remote sensing images, the extraction of annual change information of land use, field survey, indoor post processing and accuracy assessment. Especially, we emphasize on comparative research on the choice of remote sensing rectifying models, image fusion algorithms and accuracy assessment methods. Taking Anning district in Lanzhou as an example, we extract the land use change information of the district during 2002-2003, access monitoring accuracy and analyze the reason of land use change.
Digital photo monitoring for tree crown
Neil Clark; Sang-Mook Lee
2007-01-01
Assessing change in the amount of foliage within a treeâs crown is the goal of crown transparency estimation, a component in many forest health assessment programs. Many sources of variability limit analysis and interpretation of crown condition data. Increased precision is needed to detect more subtle changes that are important for detection of health problems....
Nicol, Samuel; Roach, Jennifer K.; Griffith, Brad
2013-01-01
Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.
NASA Astrophysics Data System (ADS)
Kara, Can; Akçit, Nuhcan
2016-08-01
Land-cover change is considered one of the central components in current strategies for managing natural resources and monitoring environmental changes. It is important to manage land resources in a sustainable manner which targets at compacting and consolidating urban development. From 2005 to 2015,urban growth in Kyrenia has been quite dramatic, showing a wide and scattered pattern, lacking proper plan. As a result of this unplanned/unorganized expansion, agricultural areas, vegetation and water bodies have been lost in the region. Therefore, it has become a necessity to analyze the results of this urban growth and compare the losses between land-cover changes. With this goal in mind, a case study of Kyrenia region has been carried out using a supervised image classification method and Landsat TM images acquired in 2005 and 2015 to map and extract land-cover changes. This paper tries to assess urban-growth changes detected in the region by using Remote Sensing and GIS. The study monitors the changes between different land cover types. Also, it shows the urban occupation of primary soil loss and the losses in forest areas, open areas, etc.
Pan-Arctic river discharge: Prioritizing monitoring of future climate change hot spots
NASA Astrophysics Data System (ADS)
Bring, Arvid; Shiklomanov, Alexander; Lammers, Richard B.
2017-01-01
The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flows to detect, observe, and understand changes and provide adaptation information. There has, however, been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska, and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.
Pan-Arctic River Discharge: Where Can We Improve Monitoring of Future Change?
NASA Astrophysics Data System (ADS)
Bring, A.; Shiklomanov, A. I.; Lammers, R. B.
2016-12-01
The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flow to detect, observe and understand changes and provide adaptation information. There has however been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change, and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.
NASA Astrophysics Data System (ADS)
De Rango, Floriano; Lupia, Andrea
2016-05-01
MANETs allow mobile nodes communicating to each other using the wireless medium. A key aspect of these kind of networks is the security, because their setup is done without an infrastructure, so external nodes could interfere in the communication. Mobile nodes could be compromised, misbehaving during the multi-hop transmission of data, or they could have a selfish behavior to save energy, which is another important constraint in MANETs. The detection of these behaviors need a framework that takes into account the latest interactions among nodes, so malicious or selfish nodes could be detected also if their behavior is changed over time. The monitoring activity increases the energy consumption, so our proposal takes into account this issue reducing the energy required by the monitoring system, keeping the effectiveness of the intrusion detection system. The results show an improvement in the saved energy, improving the detection performance too.
Using forest health monitoring data to integrate above and below ground carbon information
Barbara L. Conkling; Coeli M. Hoover; William D. Smith; Craig J. Palmer
2002-01-01
The national Forest Health Monitoring (FHM) program conducted a remeasurement study in 1999 to evaluate the usefulness and feasibility of collecting data needed for investigating carbon budgets in forests. This study indicated that FHM data are adequate for detecting a 20% change over 10 years (2% change per year) in percent total carbon and carbon content (MgC/ha)...
Forest health monitoring indicators and their interpretability: a Lithuanian case study
Romualdas Kuknys; Algirdas Augustaitis
1998-01-01
Growth and productivity of forests are important indicators for understanding the general condition and health of forests. It is very important that indicators detected during monitoring procedures afford an opportunity for direct or indirect evaluation of forest productivity and its natural and anthropogenic changes. Analysis of the U.S. Forest Health Monitoring (FHM...
Simulating future uncertainty to guide the selection of survey designs for long-term monitoring
Garman, Steven L.; Schweiger, E. William; Manier, Daniel J.; Gitzen, Robert A.; Millspaugh, Joshua J.; Cooper, Andrew B.; Licht, Daniel S.
2012-01-01
A goal of environmental monitoring is to provide sound information on the status and trends of natural resources (Messer et al. 1991, Theobald et al. 2007, Fancy et al. 2009). When monitoring observations are acquired by measuring a subset of the population of interest, probability sampling as part of a well-constructed survey design provides the most reliable and legally defensible approach to achieve this goal (Cochran 1977, Olsen et al. 1999, Schreuder et al. 2004; see Chapters 2, 5, 6, 7). Previous works have described the fundamentals of sample surveys (e.g. Hansen et al. 1953, Kish 1965). Interest in survey designs and monitoring over the past 15 years has led to extensive evaluations and new developments of sample selection methods (Stevens and Olsen 2004), of strategies for allocating sample units in space and time (Urquhart et al. 1993, Overton and Stehman 1996, Urquhart and Kincaid 1999), and of estimation (Lesser and Overton 1994, Overton and Stehman 1995) and variance properties (Larsen et al. 1995, Stevens and Olsen 2003) of survey designs. Carefully planned, “scientific” (Chapter 5) survey designs have become a standard in contemporary monitoring of natural resources. Based on our experience with the long-term monitoring program of the US National Park Service (NPS; Fancy et al. 2009; Chapters 16, 22), operational survey designs tend to be selected using the following procedures. For a monitoring indicator (i.e. variable or response), a minimum detectable trend requirement is specified, based on the minimum level of change that would result in meaningful change (e.g. degradation). A probability of detecting this trend (statistical power) and an acceptable level of uncertainty (Type I error; see Chapter 2) within a specified time frame (e.g. 10 years) are specified to ensure timely detection. Explicit statements of the minimum detectable trend, the time frame for detecting the minimum trend, power, and acceptable probability of Type I error (α) collectively form the quantitative sampling objective.
Maintaining the Health of Software Monitors
NASA Technical Reports Server (NTRS)
Person, Suzette; Rungta, Neha
2013-01-01
Software health management (SWHM) techniques complement the rigorous verification and validation processes that are applied to safety-critical systems prior to their deployment. These techniques are used to monitor deployed software in its execution environment, serving as the last line of defense against the effects of a critical fault. SWHM monitors use information from the specification and implementation of the monitored software to detect violations, predict possible failures, and help the system recover from faults. Changes to the monitored software, such as adding new functionality or fixing defects, therefore, have the potential to impact the correctness of both the monitored software and the SWHM monitor. In this work, we describe how the results of a software change impact analysis technique, Directed Incremental Symbolic Execution (DiSE), can be applied to monitored software to identify the potential impact of the changes on the SWHM monitor software. The results of DiSE can then be used by other analysis techniques, e.g., testing, debugging, to help preserve and improve the integrity of the SWHM monitor as the monitored software evolves.
Effects of Sampling and Spatio/Temporal Granularity in Traffic Monitoring on Anomaly Detectability
NASA Astrophysics Data System (ADS)
Ishibashi, Keisuke; Kawahara, Ryoichi; Mori, Tatsuya; Kondoh, Tsuyoshi; Asano, Shoichiro
We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.
Optimising 4-D surface change detection: an approach for capturing rockfall magnitude-frequency
NASA Astrophysics Data System (ADS)
Williams, Jack G.; Rosser, Nick J.; Hardy, Richard J.; Brain, Matthew J.; Afana, Ashraf A.
2018-02-01
We present a monitoring technique tailored to analysing change from near-continuously collected, high-resolution 3-D data. Our aim is to fully characterise geomorphological change typified by an event magnitude-frequency relationship that adheres to an inverse power law or similar. While recent advances in monitoring have enabled changes in volume across more than 7 orders of magnitude to be captured, event frequency is commonly assumed to be interchangeable with the time-averaged event numbers between successive surveys. Where events coincide, or coalesce, or where the mechanisms driving change are not spatially independent, apparent event frequency must be partially determined by survey interval.The data reported have been obtained from a permanently installed terrestrial laser scanner, which permits an increased frequency of surveys. Surveying from a single position raises challenges, given the single viewpoint onto a complex surface and the need for computational efficiency associated with handling a large time series of 3-D data. A workflow is presented that optimises the detection of change by filtering and aligning scans to improve repeatability. An adaptation of the M3C2 algorithm is used to detect 3-D change to overcome data inconsistencies between scans. Individual rockfall geometries are then extracted and the associated volumetric errors modelled. The utility of this approach is demonstrated using a dataset of ˜ 9 × 103 surveys acquired at ˜ 1 h intervals over 10 months. The magnitude-frequency distribution of rockfall volumes generated is shown to be sensitive to monitoring frequency. Using a 1 h interval between surveys, rather than 30 days, the volume contribution from small (< 0.1 m3) rockfalls increases from 67 to 98 % of the total, and the number of individual rockfalls observed increases by over 3 orders of magnitude. High-frequency monitoring therefore holds considerable implications for magnitude-frequency derivatives, such as hazard return intervals and erosion rates. As such, while high-frequency monitoring has potential to describe short-term controls on geomorphological change and more realistic magnitude-frequency relationships, the assessment of longer-term erosion rates may be more suited to less-frequent data collection with lower accumulative errors.
Time-lapse seismic waveform inversion for monitoring near-surface microbubble injection
NASA Astrophysics Data System (ADS)
Kamei, R.; Jang, U.; Lumley, D. E.; Mouri, T.; Nakatsukasa, M.; Takanashi, M.
2016-12-01
Seismic monitoring of the Earth provides valuable information regarding the time-varying changes in subsurface physical properties that are caused by natural or man-made processes. However, the resulting changes in subsurface properties are often small both in terms of magnitude and spatial extent, leading to seismic data differences that are difficult to detect at typical non-repeatable noise levels. In order to better extract information from the time-lapse data, exploiting the full seismic waveform information can be critical, since detected amplitude or traveltime changes may be minimal. We explore methods of waveform inversion that estimate an optimal model of time-varying elastic parameters at the wavelength scale to fit the observed time-lapse seismic data with modelled waveforms based on numerical solutions of the wave equation. We apply acoustic waveform inversion to time-lapse cross-well monitoring surveys of 64-m well intervals, and estimate the velocity changes that occur during the injection of microbubble water into shallow unconsolidated Quaternary sediments in the Kanto basin of Japan at a depth of 25 m below the surface. Microbubble water is comprised of water infused with air bubbles of a diameter less than 0.1mm, and may be useful to improve resistance to ground liquefaction during major earthquakes. Monitoring the space-time distribution and physical properties of microbubble injection is therefore important to understanding the full potential of the technique. Repeated monitoring surveys (>10) reveal transient behaviours in waveforms during microbubble injection. Time-lapse waveform inversion detects changes in P-wave velocity of less than 1 percent, initially as velocity increases and subsequently as velocity decreases. The velocity changes are mainly imaged within a thin (1 m) layer between the injection and the receiver well, inferring the fluid-flow influence of the fluvial sediment depositional environment. The resulting velocity models fit the observed waveforms very well, supporting the validity of the estimated velocity changes. In order to further improve the estimation of velocity changes, we investigate the limitations of acoustic waveform inversion, and apply elastic waveform inversion to the time-lapse data set.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-05-31
... detection instrumentation to operable status; establish alternate methods of monitoring RCS leakage when one... the RCS leakage detection instrumentation. These changes are consistent with NRC-approved Revision 3... requirements for the RCS leakage detection instrumentation and reduces the time allowed for the plant to...
30 CFR 250.1629 - Additional production and fuel gas system requirements.
Code of Federal Regulations, 2014 CFR
2014-07-01
... structure. (4) Fire- and gas-detection system. (i) Fire (flame, heat, or smoke) sensors shall be installed... explosive limit. One approved method of providing adequate ventilation is a change of air volume each 5... detection systems shall be capable of continuous monitoring. Fire-detection systems and portions of...
30 CFR 250.1629 - Additional production and fuel gas system requirements.
Code of Federal Regulations, 2013 CFR
2013-07-01
... structure. (4) Fire- and gas-detection system. (i) Fire (flame, heat, or smoke) sensors shall be installed... explosive limit. One approved method of providing adequate ventilation is a change of air volume each 5... detection systems shall be capable of continuous monitoring. Fire-detection systems and portions of...
Health status monitoring for ICU patients based on locally weighted principal component analysis.
Ding, Yangyang; Ma, Xin; Wang, Youqing
2018-03-01
Intelligent status monitoring for critically ill patients can help medical stuff quickly discover and assess the changes of disease and then make appropriate treatment strategy. However, general-type monitoring model now widely used is difficult to adapt the changes of intensive care unit (ICU) patients' status due to its fixed pattern, and a more robust, efficient and fast monitoring model should be developed to the individual. A data-driven learning approach combining locally weighted projection regression (LWPR) and principal component analysis (PCA) is firstly proposed and applied to monitor the nonlinear process of patients' health status in ICU. LWPR is used to approximate the complex nonlinear process with local linear models, in which PCA could be further applied to status monitoring, and finally a global weighted statistic will be acquired for detecting the possible abnormalities. Moreover, some improved versions are developed, such as LWPR-MPCA and LWPR-JPCA, which also have superior performance. Eighteen subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and two vital signs of each subject were chosen for online monitoring. The proposed method was compared with several existing methods including traditional PCA, Partial least squares (PLS), just in time learning combined with modified PCA (L-PCA), and Kernel PCA (KPCA). The experimental results demonstrated that the mean fault detection rate (FDR) of PCA can be improved by 41.7% after adding LWPR. The mean FDR of LWPR-MPCA was increased by 8.3%, compared with the latest reported method L-PCA. Meanwhile, LWPR spent less training time than others, especially KPCA. LWPR is first introduced into ICU patients monitoring and achieves the best monitoring performance including adaptability to changes in patient status, sensitivity for abnormality detection as well as its fast learning speed and low computational complexity. The algorithm is an excellent approach to establishing a personalized model for patients, which is the mainstream direction of modern medicine in the following development, as well as improving the global monitoring performance. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
Automated health alerts from Kinect-based in-home gait measurements.
Stone, Erik E; Skubic, Marjorie; Back, Jessica
2014-01-01
A method for automatically generating alerts to clinicians in response to changes in in-home gait parameters is investigated. Kinect-based gait measurement systems were installed in apartments in a senior living facility. The systems continuously monitored the walking speed, stride time, and stride length of apartment residents. A framework for modeling uncertainty in the residents' gait parameter estimates, which is critical for robust change detection, is developed; along with an algorithm for detecting changes that may be clinically relevant. Three retrospective case studies, of individuals who had their gait monitored for periods ranging from 12 to 29 months, are presented to illustrate use of the alert method. Evidence suggests that clinicians could be alerted to health changes at an early stage, while they are still small and interventions may be most successful. Additional potential uses are also discussed.
Yeh, Paul; Hunter, Tane; Sinha, Devbarna; Ftouni, Sarah; Wallach, Elise; Jiang, Damian; Chan, Yih-Chih; Wong, Stephen Q; Silva, Maria Joao; Vedururu, Ravikiran; Doig, Kenneth; Lam, Enid; Arnau, Gisela Mir; Semple, Timothy; Wall, Meaghan; Zivanovic, Andjelija; Agarwal, Rishu; Petrone, Pasquale; Jones, Kate; Westerman, David; Blombery, Piers; Seymour, John F; Papenfuss, Anthony T; Dawson, Mark A; Tam, Constantine S; Dawson, Sarah-Jane
2017-03-17
Several novel therapeutics are poised to change the natural history of chronic lymphocytic leukaemia (CLL) and the increasing use of these therapies has highlighted limitations of traditional disease monitoring methods. Here we demonstrate that circulating tumour DNA (ctDNA) is readily detectable in patients with CLL. Importantly, ctDNA does not simply mirror the genomic information contained within circulating malignant lymphocytes but instead parallels changes across different disease compartments following treatment with novel therapies. Serial ctDNA analysis allows clonal dynamics to be monitored over time and identifies the emergence of genomic changes associated with Richter's syndrome (RS). In addition to conventional disease monitoring, ctDNA provides a unique opportunity for non-invasive serial analysis of CLL for molecular disease monitoring.
NASA Astrophysics Data System (ADS)
Harrild, M.; Webley, P. W.; Dehn, J.
2016-12-01
An effective early warning system to detect volcanic activity is an invaluable tool, but often very expensive. Detecting and monitoring precursory events, thermal signatures, and ongoing eruptions in near real-time is essential, but conventional methods are often logistically challenging, expensive, and difficult to maintain. Our investigation explores the use of `off the shelf' webcams and low-light cameras, operating in the visible to near-infrared portions of the electromagnetic spectrum, to detect and monitor volcanic incandescent activity. Large databases of webcam imagery already exist at institutions around the world, but are often extremely underutilised and we aim to change this. We focus on the early detection of thermal signatures at volcanoes, using automated scripts to analyse individual images for changes in pixel brightness, allowing us to detect relative changes in thermally incandescent activity. Primarily, our work focuses on freely available streams of webcam images from around the world, which we can download and analyse in near real-time. When changes in activity are detected, an alert is sent to the users informing them of the changes in activity and a need for further investigation. Although relatively rudimentary, this technique provides constant monitoring for volcanoes in remote locations and developing nations, where it is not financially viable to deploy expensive equipment. We also purchased several of our own cameras, which were extensively tested in controlled laboratory settings with a black body source to determine their individual spectral response. Our aim is to deploy these cameras at active volcanoes knowing exactly how they will respond to varying levels of incandescence. They are ideal for field deployments as they are cheap (0-1,000), consume little power, are easily replaced, and can provide telemetered near real-time data. Data from Shiveluch volcano, Russia and our spectral response lab experiments are presented here.
Framework for ecological monitoring on lands of Alaska National Wildlife Refuges and their partners
Woodward, Andrea; Beever, Erik A.
2010-01-01
National Wildlife Refuges in Alaska and throughout the U.S. have begun developing a spatially comprehensive monitoring program to inform management decisions, and to provide data to broader research projects. In an era of unprecedented rates of climate change, monitoring is essential to detecting, understanding, communicating and mitigating climate-change effects on refuge and other resources under the protection of U.S. Fish and Wildlife Service, and requires monitoring results to address spatial scales broader than individual refuges. This document provides guidance for building a monitoring program for refuges in Alaska that meets refuge-specific management needs while also allowing synthesis and summary of ecological conditions at the ecoregional and statewide spatial scales.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Saenz, D; Gutierrez, A
Purpose: The ScandiDos Discover has obtained FDA clearance and is now clinically released. We studied the essential attenuation and beam hardening components as well as tested the diode array’s ability to detect changes in absolute dose and MLC leaf positions. Methods: The ScandiDos Discover was mounted on the heads of an Elekta VersaHD and a Varian 23EX. Beam attenuation measurements were made at 10 cm depth for 6 MV and 18 MV beam energies. The PDD(10) was measured as a metric for the effect on beam quality. Next, a plan consisting of two orthogonal 10 × 10 cm2 fields wasmore » used to adjust the dose per fraction by scaling monitor units to test the absolute dose detection sensitivity of the Discover. A second plan (conformal arc) was then delivered several times independently on the Elekta VersaHD. Artificially introduced MLC position errors in the four central leaves were then added. The errors were incrementally increased from 1 mm to 4 mm and back across seven control points. Results: The absolute dose measured at 10 cm depth decreased by 1.2% and 0.7% for 6 MV and 18 MV beam with the Discover, respectively. Attenuation depended slightly on the field size but only changed the attenuation by 0.1% across 5 × 5 cm{sup 2} and 20 − 20 cm{sup 2} fields. The change in PDD(10) for a 10 − 10 cm{sup 2} field was +0.1% and +0.6% for 6 MV and 18 MV, respectively. Changes in monitor units from −5.0% to 5.0% were faithfully detected. Detected leaf errors were within 1.0 mm of intended errors. Conclusion: A novel in-vivo dosimeter monitoring the radiation beam during treatment was examined through its attenuation and beam hardening characteristics. The device tracked with changes in absolute dose as well as introduced leaf position deviations.« less
DeRocco, Vanessa; Anderson, Trevor; Piehler, Jacob; Erie, Dorothy A; Weninger, Keith
2010-11-01
To enable studies of conformational changes within multimolecular complexes, we present a simultaneous, four-color single molecule fluorescence methodology implemented with total internal reflection illumination and camera-based, wide-field detection. We further demonstrate labeling histidine-tagged proteins noncovalently with Tris-nitrilotriacetic acid (Tris-NTA)-conjugated dyes to achieve single molecule detection. We combine these methods to colocalize the mismatch repair protein MutSα on DNA while monitoring MutSα-induced DNA bending using Förster resonance energy transfer (FRET) and to monitor assembly of membrane-tethered SNARE protein complexes.
DeRocco, Vanessa C.; Anderson, Trevor; Piehler, Jacob; Erie, Dorothy A.; Weninger, Keith
2010-01-01
To allow studies of conformational changes within multi-molecular complexes, we present a simultaneous, 4-color single molecule fluorescence methodology implemented with total internal reflection illumination and camera based, wide-field detection. We further demonstrate labeling histidine-tagged proteins non-covalently with tris-Nitrilotriacetic acid (tris-NTA) conjugated dyes to achieve single molecule detection. We combine these methods to co-localize the mismatch repair protein MutSα on DNA while monitoring MutSα-induced DNA bending using Förster resonance energy transfer (FRET) and to monitor assembly of membrane-tethered SNARE protein complexes. PMID:21091445
NIR light propagation in a digital head model for traumatic brain injury (TBI)
Francis, Robert; Khan, Bilal; Alexandrakis, George; Florence, James; MacFarlane, Duncan
2015-01-01
Near infrared spectroscopy (NIRS) is capable of detecting and monitoring acute changes in cerebral blood volume and oxygenation associated with traumatic brain injury (TBI). Wavelength selection, source-detector separation, optode density, and detector sensitivity are key design parameters that determine the imaging depth, chromophore separability, and, ultimately, clinical usefulness of a NIRS instrument. We present simulation results of NIR light propagation in a digital head model as it relates to the ability to detect intracranial hematomas and monitor the peri-hematomal tissue viability. These results inform NIRS instrument design specific to TBI diagnosis and monitoring. PMID:26417498
Stone, Daithi A.; Hansen, Gerrit
2015-11-21
Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the “confidence” language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies inmore » considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.« less
NASA Astrophysics Data System (ADS)
Falco, N.; Pedersen, G. B. M.; Vilmunandardóttir, O. K.; Belart, J. M. M. C.; Sigurmundsson, F. S.; Benediktsson, J. A.
2016-12-01
The project "Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS)" aims at providing fast and reliable mapping and monitoring techniques on a big spatial scale with a high temporal resolution of the Icelandic landscape. Such mapping and monitoring will be crucial to both mitigate and understand the scale of processes and their often complex interlinked feedback mechanisms.In the EMMIRS project, the Hekla volcano area is one of the main sites under study, where the volcanic eruptions, extreme weather and human activities had an extensive impact on the landscape degradation. The development of innovative remote sensing approaches to compute earth observation variables as automatically as possible is one of the main tasks of the EMMIRS project. Furthermore, a temporal remote sensing archive is created and composed by images acquired by different sensors (Landsat, RapidEye, ASTER and SPOT5). Moreover, historical aerial stereo photos allowed decadal reconstruction of the landscape by reconstruction of digital elevation models. Here, we propose a novel architecture for automatic unsupervised change detection analysis able to ingest multi-source data in order to detect landscape changes in the Hekla area. The change detection analysis is based on multi-scale analysis, which allows the identification of changes at different level of abstraction, from pixel-level to region-level. For this purpose, operators defined in mathematical morphology framework are implemented to model the contextual information, represented by the neighbour system of a pixel, allowing the identification of changes related to both geometrical and spectral domains. Automatic radiometric normalization strategy is also implemented as pre-processing step, aiming at minimizing the effect of different acquisition conditions. The proposed architecture is tested on multi-temporal data sets acquired over different time periods coinciding with the last three eruptions (1980-1981, 1991, 2000) occurred on Hekla volcano. The results reveal emplacement of new lava flows and the initial vegetation succession, providing insightful information on the evolving of vegetation in such environment. Shadow and snow patch changes are resolved in post-processing by exploiting the available spectral information.
SPECIES-SPECIFIC DETECTION OF HYDROCARBON UTILIZING BACTERIA. (R825810)
Rapid detection and quantitative assessment of specific microbial species in environmental samples is desirable for monitoring changes in ecosystems and for tracking natural or introduced microbial species during bioremediation of contaminated sites. In the interests of develo...
Detecting cell death with optical coherence tomography and envelope statistics
NASA Astrophysics Data System (ADS)
Farhat, Golnaz; Yang, Victor X. D.; Czarnota, Gregory J.; Kolios, Michael C.
2011-02-01
Currently no standard clinical or preclinical noninvasive method exists to monitor cell death based on morphological changes at the cellular level. In our past work we have demonstrated that quantitative high frequency ultrasound imaging can detect cell death in vitro and in vivo. In this study we apply quantitative methods previously used with high frequency ultrasound to optical coherence tomography (OCT) to detect cell death. The ultimate goal of this work is to use these methods for optically-based clinical and preclinical cancer treatment monitoring. Optical coherence tomography data were acquired from acute myeloid leukemia cells undergoing three modes of cell death. Significant increases in integrated backscatter were observed for cells undergoing apoptosis and mitotic arrest, while necrotic cells induced a decrease. These changes appear to be linked to structural changes observed in histology obtained from the cell samples. Signal envelope statistics were analyzed from fittings of the generalized gamma distribution to histograms of envelope intensities. The parameters from this distribution demonstrated sensitivities to morphological changes in the cell samples. These results indicate that OCT integrated backscatter and first order envelope statistics can be used to detect and potentially differentiate between modes of cell death in vitro.
Passman, Rod S; Rogers, John D; Sarkar, Shantanu; Reiland, Jerry; Reisfeld, Erin; Koehler, Jodi; Mittal, Suneet
2017-07-01
Undersensing of premature ventricular beats and low-amplitude R waves are primary causes for inappropriate bradycardia and pause detections in insertable cardiac monitors (ICMs). The purpose of this study was to develop and validate an enhanced algorithm to reduce inappropriately detected bradycardia and pause episodes. Independent data sets to develop and validate the enhanced algorithm were derived from a database of ICM-detected bradycardia and pause episodes in de-identified patients monitored for unexplained syncope. The original algorithm uses an auto-adjusting sensitivity threshold for R-wave sensing to detect tachycardia and avoid T-wave oversensing. In the enhanced algorithm, a second sensing threshold is used with a long blanking and fixed lower sensitivity threshold, looking for evidence of undersensed signals. Data reported includes percent change in appropriate and inappropriate bradycardia and pause detections as well as changes in episode detection sensitivity and positive predictive value with the enhanced algorithm. The validation data set, from 663 consecutive patients, consisted of 4904 (161 patients) bradycardia and 2582 (133 patients) pause episodes, of which 2976 (61%) and 996 (39%) were appropriately detected bradycardia and pause episodes. The enhanced algorithm reduced inappropriate bradycardia and pause episodes by 95% and 47%, respectively, with 1.7% and 0.6% reduction in appropriate episodes, respectively. The average episode positive predictive value improved by 62% (P < .001) for bradycardia detection and by 26% (P < .001) for pause detection, with an average relative sensitivity of 95% (P < .001) and 99% (P = .5), respectively. The enhanced dual sense algorithm for bradycardia and pause detection in ICMs substantially reduced inappropriate episode detection with a minimal reduction in true episode detection. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Surface plasmon resonance application for herbicide detection
NASA Astrophysics Data System (ADS)
Chegel, Vladimir I.; Shirshov, Yuri M.; Piletskaya, Elena V.; Piletsky, Sergey A.
1998-01-01
The optoelectronic biosensor, based on Surface Plasmon Resonance (SPR) for detection of photosynthesis-inhibiting herbicides in aqueous solutions is presented. The pesticide capability to replace plastoquinone from its complex with D1 protein is used for the detection. This replacement reaction results in the changes of the optical characteristics of protein layer, immobilized on the gold surface. Monitoring of these changes with SPR-technique permit to determine 0.1 - 5.0 mkg/ml herbicide in solution within one hour.
Surface plasmon resonance application for herbicide detection
NASA Astrophysics Data System (ADS)
Chegel, Vladimir I.; Shirshov, Yuri M.; Piletskaya, Elena V.; Piletsky, Sergey A.
1997-12-01
The optoelectronic biosensor, based on Surface Plasmon Resonance (SPR) for detection of photosynthesis-inhibiting herbicides in aqueous solutions is presented. The pesticide capability to replace plastoquinone from its complex with D1 protein is used for the detection. This replacement reaction results in the changes of the optical characteristics of protein layer, immobilized on the gold surface. Monitoring of these changes with SPR-technique permit to determine 0.1 - 5.0 mkg/ml herbicide in solution within one hour.
Acoustic change detection algorithm using an FM radio
NASA Astrophysics Data System (ADS)
Goldman, Geoffrey H.; Wolfe, Owen
2012-06-01
The U.S. Army is interested in developing low-cost, low-power, non-line-of-sight sensors for monitoring human activity. One modality that is often overlooked is active acoustics using sources of opportunity such as speech or music. Active acoustics can be used to detect human activity by generating acoustic images of an area at different times, then testing for changes among the imagery. A change detection algorithm was developed to detect physical changes in a building, such as a door changing positions or a large box being moved using acoustics sources of opportunity. The algorithm is based on cross correlating the acoustic signal measured from two microphones. The performance of the algorithm was shown using data generated with a hand-held FM radio as a sound source and two microphones. The algorithm could detect a door being opened in a hallway.
Stability of the nine sky quality meters in the Dutch night sky brightness monitoring network.
den Outer, Peter; Lolkema, Dorien; Haaima, Marty; van der Hoff, Rene; Spoelstra, Henk; Schmidt, Wim
2015-04-22
In the context of monitoring abundance of artificial light at night, the year-to-year stability of Sky Quality Meters (SQMs) is investigated by analysing intercalibrations derived from two measurement campaigns that were held in 2011 and 2012. An intercalibration comprises a light sensitivity factor and an offset for each SQM. The campaigns were concerned with monitoring measurements, each lasting one month. Nine SQMs, together forming the Night Sky Brightness Monitoring network (MHN) in The Netherlands, were involved in both campaigns. The stability of the intercalibration of these instruments leads to a year-to-year uncertainty (standard deviation) of 5% in the measured median luminance occurring at the MHN monitoring locations. For the 10-percentiles and 90-percentiles, we find 8% and 4%, respectively. This means that, for urban and industrial areas, changes in the sky brightness larger than 5% become detectable. Rural and nature areas require an 8%-9% change of the median luminance to be detectable. The light sensitivety agrees within 8% for the whole group of SQMs.
Comparison of power curve monitoring methods
NASA Astrophysics Data System (ADS)
Cambron, Philippe; Masson, Christian; Tahan, Antoine; Torres, David; Pelletier, Francis
2017-11-01
Performance monitoring is an important aspect of operating wind farms. This can be done through the power curve monitoring (PCM) of wind turbines (WT). In the past years, important work has been conducted on PCM. Various methodologies have been proposed, each one with interesting results. However, it is difficult to compare these methods because they have been developed using their respective data sets. The objective of this actual work is to compare some of the proposed PCM methods using common data sets. The metric used to compare the PCM methods is the time needed to detect a change in the power curve. Two power curve models will be covered to establish the effect the model type has on the monitoring outcomes. Each model was tested with two control charts. Other methodologies and metrics proposed in the literature for power curve monitoring such as areas under the power curve and the use of statistical copulas have also been covered. Results demonstrate that model-based PCM methods are more reliable at the detecting a performance change than other methodologies and that the effectiveness of the control chart depends on the types of shift observed.
Accounting for complementarity to maximize monitoring power for species management.
Tulloch, Ayesha I T; Chadès, Iadine; Possingham, Hugh P
2013-10-01
To choose among conservation actions that may benefit many species, managers need to monitor the consequences of those actions. Decisions about which species to monitor from a suite of different species being managed are hindered by natural variability in populations and uncertainty in several factors: the ability of the monitoring to detect a change, the likelihood of the management action being successful for a species, and how representative species are of one another. However, the literature provides little guidance about how to account for these uncertainties when deciding which species to monitor to determine whether the management actions are delivering outcomes. We devised an approach that applies decision science and selects the best complementary suite of species to monitor to meet specific conservation objectives. We created an index for indicator selection that accounts for the likelihood of successfully detecting a real trend due to a management action and whether that signal provides information about other species. We illustrated the benefit of our approach by analyzing a monitoring program for invasive predator management aimed at recovering 14 native Australian mammals of conservation concern. Our method selected the species that provided more monitoring power at lower cost relative to the current strategy and traditional approaches that consider only a subset of the important considerations. Our benefit function accounted for natural variability in species growth rates, uncertainty in the responses of species to the prescribed action, and how well species represent others. Monitoring programs that ignore uncertainty, likelihood of detecting change, and complementarity between species will be more costly and less efficient and may waste funding that could otherwise be used for management. © 2013 Society for Conservation Biology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coble, Jamie; Orton, Christopher; Schwantes, Jon
Abstract—The Multi-Isotope Process (MIP) Monitor provides an efficient approach to monitoring the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of reprocessing streams in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor), initial enrichment, burn up, and cooling time. Simulated gamma spectra were used to develop and test threemore » fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type. Locally weighted PLS models were fitted on-the-fly to estimate continuous fuel characteristics. Burn up was predicted within 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment within approximately 2% RMSPE. This automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters and material diversions.« less
Al-Chokhachy, R.; Budy, P.; Conner, M.
2009-01-01
Using empirical field data for bull trout (Salvelinus confluentus), we evaluated the trade-off between power and sampling effort-cost using Monte Carlo simulations of commonly collected mark-recapture-resight and count data, and we estimated the power to detect changes in abundance across different time intervals. We also evaluated the effects of monitoring different components of a population and stratification methods on the precision of each method. Our results illustrate substantial variability in the relative precision, cost, and information gained from each approach. While grouping estimates by age or stage class substantially increased the precision of estimates, spatial stratification of sampling units resulted in limited increases in precision. Although mark-resight methods allowed for estimates of abundance versus indices of abundance, our results suggest snorkel surveys may be a more affordable monitoring approach across large spatial scales. Detecting a 25% decline in abundance after 5 years was not possible, regardless of technique (power = 0.80), without high sampling effort (48% of study site). Detecting a 25% decline was possible after 15 years, but still required high sampling efforts. Our results suggest detecting moderate changes in abundance of freshwater salmonids requires considerable resource and temporal commitments and highlight the difficulties of using abundance measures for monitoring bull trout populations.
The effect of increased monitoring load on vigilance performance using a simulated radar display.
DOT National Transportation Integrated Search
1977-07-01
The present study examined the extent to which level of target density influences the ability to sustain attention to a complex monitoring task requiring only a detection response to simple stimulus change. The visual display was designed to approxim...
The United States Environmental Protection Agency (U.S. EPA) is working with its regional offices, states, tribes, and other entities to establish Regional Monitoring Networks (RMNs) at which biological, thermal, and hydrologic data are collected from freshwater wadeable streams ...
Use of acoustic tools to reveal otherwise cryptic responses of forest elephants to oil exploration.
Wrege, Peter H; Rowland, Elizabeth D; Thompson, Bruce G; Batruch, Nikolas
2010-12-01
Most evaluations of the effects of human activities on wild animals have focused on estimating changes in abundance and distribution of threatened species; however, ecosystem disturbances also affect aspects of animal behavior such as short-term movement, activity budgets, and reproduction. It may take a long time for changes in behavior to manifest as changes in abundance or distribution. Therefore, it is important to have methods with which to detect short-term behavioral responses to human activity. We used continuous acoustic and seismic monitoring to evaluate the short-term effects of seismic prospecting for oil on forest elephants (Loxodonta cyclotis) in Gabon, Central Africa. We monitored changes in elephant abundance and activity as a function of the frequency and intensity of acoustic and seismic signals from dynamite detonation and human activity. Elephants did not flee the area being explored; the relative number of elephants increased in a seasonal pattern typical of elsewhere in the ecosystem. In the exploration area, however, they became more nocturnal. Neither the intensity nor the frequency of dynamite blasts affected the frequency of calling or the daily pattern of elephant activity. Nevertheless, the shift of activity to nocturnal hours became more pronounced as human activity neared each monitored area of forest. This change in activity pattern and its likely causes would not have been detected through standard monitoring methods, which are not sensitive to behavioral changes over short time scales (e.g., dung transects, point counts) or cover a limited area (e.g., camera traps). Simultaneous acoustic monitoring of animal communication, human, and environmental sounds allows the documentation of short-term behavioral changes in response to human disturbance. © 2010 Society for Conservation Biology.
A survey of atmospheric monitoring systems in U.S. underground coal mines
Rowland, J.H.; Harteis, S.P.; Yuan, L.
2018-01-01
In 1995 and 2003, the U.S. Mine Safety and Health Administration (MSHA) conducted surveys to determine the number of atmospheric monitoring systems (AMS) that were being used in underground coal mines in the United States. The survey reports gave data for the different AMS manufacturers, the different types of equipment monitored, and the different types of gas sensors and their locations. Since the last survey in 2003, MSHA has changed the regulation requirements for early fire detection along belt haulage entries. As of Dec. 31, 2009, point-type heat sensors are prohibited for use for an early fire detection system. Instead, carbon monoxide (CO) sensors are now required. This report presents results from a new survey and examines how the regulation changes have had an impact on the use of CO sensors in underground coal mines in the United States. The locations and parameters monitored by AMS and CO systems are also discussed. PMID:29674789
Non-intrusive appliance monitor apparatus
Hart, George W.; Kern, Jr., Edward C.; Schweppe, Fred C.
1989-08-15
A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each.
Mattfeldt, S.D.; Bailey, L.L.; Grant, E.H.C.
2009-01-01
Monitoring programs have the potential to identify population declines and differentiate among the possible cause(s) of these declines. Recent criticisms regarding the design of monitoring programs have highlighted a failure to clearly state objectives and to address detectability and spatial sampling issues. Here, we incorporate these criticisms to design an efficient monitoring program whose goals are to determine environmental factors which influence the current distribution and measure change in distributions over time for a suite of amphibians. In designing the study we (1) specified a priori factors that may relate to occupancy, extinction, and colonization probabilities and (2) used the data collected (incorporating detectability) to address our scientific questions and adjust our sampling protocols. Our results highlight the role of wetland hydroperiod and other local covariates in the probability of amphibian occupancy. There was a change in overall occupancy probabilities for most species over the first three years of monitoring. Most colonization and extinction estimates were constant over time (years) and space (among wetlands), with one notable exception: local extinction probabilities for Rana clamitans were lower for wetlands with longer hydroperiods. We used information from the target system to generate scenarios of population change and gauge the ability of the current sampling to meet monitoring goals. Our results highlight the limitations of the current sampling design, emphasizing the need for long-term efforts, with periodic re-evaluation of the program in a framework that can inform management decisions.
An open-population hierarchical distance sampling model
Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,
2015-01-01
Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
An open-population hierarchical distance sampling model.
Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott
2015-02-01
Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
Ares, William J; Grandhi, Ramesh M; Panczykowski, David M; Weiner, Gregory M; Thirumala, Parthasarathy; Habeych, Miguel E; Crammond, Donald J; Horowitz, Michael B; Jankowitz, Brian T; Jadhav, Ashutosh; Jovin, Tudor G; Ducruet, Andrew F; Balzer, Jeffrey
2018-02-01
Somatosensory evoked potential (SSEP) monitoring is used extensively for early detection and prevention of neurological complications in patients undergoing many different neurosurgical procedures. However, the predictive ability of SSEP monitoring during endovascular treatment of cerebral aneurysms is not well detailed. To evaluate the performance of intraoperative SSEP in the prediction postprocedural neurological deficits (PPNDs) after coil embolization of intracranial aneurysms. This population-based cohort study included patients ≥18 years of age undergoing intracranial aneurysm embolization with concurrent SSEP monitoring between January 2006 and August 2012. The ability of SSEP to predict PPNDs was analyzed by multiple regression analyses and assessed by the area under the receiver operating characteristic curve. In a population of 888 patients, SSEP changes occurred in 8.6% (n = 77). Twenty-eight patients (3.1%) suffered PPNDs. A 50% to 99% loss in SSEP waveform was associated with a 20-fold increase in risk of PPND; a total loss of SSEP waveform, regardless of permanence, was associated with a greater than 200-fold risk of PPND. SSEPs displayed very good predictive ability for PPND, with an area under the receiver operating characteristic curve of 0.84 (95% CI 0.76-0.92). This study supports the predictive ability of SSEPs for the detection of PPNDs. The magnitude and persistence of SSEP changes is clearly associated with the development of PPNDs. The utility of SSEP monitoring in detecting ischemia may provide an opportunity for neurointerventionalists to respond to changes intraoperatively to mitigate the potential for PPNDs. Copyright © 2017 by the Congress of Neurological Surgeons
Monitoring of Biodiversity Indicators in Boreal Forests: A Need for Improved Focus
Ian D. Thompson
2006-01-01
The general principles of scale and coarse and fine filters have been widely accepted, but management agencies and industry are still grappling with the question of what to monitor to detect changes in forest biodiversity after forest management. Part of this problem can be attributed to the lack of focused questions for monitoring associated with an absence of null...
NASA Astrophysics Data System (ADS)
Yakunin, A. G.; Hussein, H. M.
2018-01-01
The article shows how the known statistical methods, which are widely used in solving financial problems and a number of other fields of science and technology, can be effectively applied after minor modification for solving such problems in climate and environment monitoring systems, as the detection of anomalies in the form of abrupt changes in signal levels, the occurrence of positive and negative outliers and the violation of the cycle form in periodic processes.
Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery
NASA Technical Reports Server (NTRS)
Williams, D. L.; Stauffer, M. L.
1978-01-01
The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.
Schloesser, J.T.; Paukert, Craig P.; Doyle, W.J.; Hill, Tracy D.; Steffensen, K.D.; Travnichek, Vincent H.
2012-01-01
Occupancy modeling was used to determine (1) if detection probabilities (p) for 7 regionally imperiled Missouri River fishes (Scaphirhynchus albus, Scaphirhynchus platorynchus, Cycleptus elongatus, Sander canadensis, Macrhybopsis aestivalis, Macrhybopsis gelida, and Macrhybopsis meeki) differed among gear types (i.e. stationary gill nets, drifted trammel nets, and otter trawls), and (2) how detection probabilities were affected by habitat (i.e. pool, bar, and open water), longitudinal position (five 189 to 367 rkm long segments), sampling year (2003 to 2006), and season (July 1 to October 30 and October 31 to June 30). Adult, large-bodied fishes were best detected with gill nets (p: 0.02–0.74), but most juvenile large-bodied and all small-bodied species were best detected with otter trawls (p: 0.02–0.58). Trammel nets may be a redundant sampling gear for imperiled fishes in the lower Missouri River because most species had greater detection probabilities with gill nets or otter trawls. Detection probabilities varied with river segment for S. platorynchus, C. elongatus, and all small-bodied fishes, suggesting that changes in habitat influenced gear efficiency or abundance changes among river segments. Detection probabilities varied by habitat for adult S. albus and S. canadensis, year for juvenile S. albus, C. elongatus, and S. canadensis, and season for adult S. albus. Concentrating sampling effort on gears with the greatest detection probabilities may increase species detections to better monitor a population's response to environmental change and the effects of management actions on large-river fishes.
Sensor data monitoring and decision level fusion scheme for early fire detection
NASA Astrophysics Data System (ADS)
Rizogiannis, Constantinos; Thanos, Konstantinos Georgios; Astyakopoulos, Alkiviadis; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.
2017-05-01
The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.
Over-hydration detection in brain by magnetic induction spectroscopy
NASA Astrophysics Data System (ADS)
González, César A.; Pérez, María; Hevia, Nidiyare; Arámbula, Fernándo; Flores, Omar; Aguilar, Eliot; Hinojosa, Ivonne; Joskowicz, Leo; Rubinsky, Boris
2010-04-01
Detection and continuous monitoring of edema in the brain in early stages is useful for assessment of medical condition and treatment. We have proposed a solution in which the bulk measurements of the tissue electrical properties to detect edema or in general accumulation of fluids are made through measurement of the magnetic induction phase shift between applied and measured currents at different frequencies (Magnetic Induction Spectroscopy; MIS). Magnetic Resonant Imaging (MRI) has been characterized because its capability to detect different levels of brain tissue hydration by differences in diffusion-weighted (DW) sequences and it's involve apparent diffusion coefficient (ADC). The objective of this study was to explore the viability to use measurements of the bulk tissue electrical properties to detect edema or in general accumulation of fluids by MIS. We have induced a transitory and generalized tissue over-hydration condition in ten volunteers ingesting 1.5 to 2 liters of water in ten minutes. Basal and over-hydration conditions were monitored by MIS and MRI. Changes in the inductive phase shift at certain frequencies were consistent with changes in the brain tissue hydration level observed by DW-ADC. The results suggest that MIS has the potential to detect pathologies associated to changes in the content of fluids in brain tissue such as edema and hematomas.
NASA Astrophysics Data System (ADS)
Todoroki, Akira; Omagari, Kazuomi
Carbon Fiber Reinforced Plastic (CFRP) laminates are adopted for fuel tank structures of next generation space rockets or automobiles. Matrix cracks may cause fuel leak or trigger fatigue damage. A monitoring system of the matrix crack density is required. The authors have developed an electrical resistance change method for the monitoring of delamination cracks in CFRP laminates. Reinforcement fibers are used as a self-sensing system. In the present study, the electric potential method is adopted for matrix crack density monitoring. Finite element analysis (FEA) was performed to investigate the possibility of monitoring matrix crack density using multiple electrodes mounted on a single surface of a specimen. The FEA reveals the matrix crack density increases electrical resistance for a target segment between electrodes. Experimental confirmation was also performed using cross-ply laminates. Eight electrodes were mounted on a single surface of a specimen using silver paste after polishing of the specimen surface with sandpaper. The two outermost electrodes applied electrical current, and the inner electrodes measured electric voltage changes. The slope of electrical resistance during reloading is revealed to be an appropriate index for the detection of matrix crack density.
The United States Environmental Protection Agency (U.S. EPA) is working with its regional offices, states, tribes, and other entities to establish Regional Monitoring Networks (RMNs) at which biological, thermal, and hydrologic data will be collected from freshwater wadeable stre...
40 CFR 63.9631 - What are my monitoring requirements?
Code of Federal Regulations, 2010 CFR
2010-07-01
... maintain a bag leak detection system to monitor the relative change in particulate matter loadings... of ensuring the proper functioning of removal mechanisms. (3) Check the compressed air supply of... interior for air leaks. (8) Inspect fans for wear, material buildup, and corrosion through quarterly visual...
Detecting Damage in Ceramic Matrix Composites Using Electrical Resistance
NASA Technical Reports Server (NTRS)
Smith, Craig E.; Gyekenyesi, Andrew
2011-01-01
The majority of damage in SiC/SiC ceramic matrix composites subjected to monotonic tensile loads is in the form of distributed matrix cracks. These cracks initiate near stress concentrations, such as 90 deg fiber tows or large matrix pores and continue to accumulate with additional stress until matrix crack saturation is achieved. Such damage is difficult to detect with conventional nondestructive evaluation techniques (immersion ultrasonics, x-ray, etc.). Monitoring a specimen.s electrical resistance change provides an indirect approach for monitoring matrix crack density. Sylramic-iBN fiber- reinforced SiC composites with a melt infiltrated (MI) matrix were tensile tested at room temperature. Results showed an increase in resistance of more than 500% prior to fracture, which can be detected either in situ or post-damage. A relationship between resistance change and matrix crack density was also determined.
Detecting Cracks in Ceramic Matrix Composites by Electrical Resistance
NASA Technical Reports Server (NTRS)
Smith, Craig; Gyekenyesi, Andrew
2011-01-01
The majority of damage in SiC/SiC ceramic matrix composites subjected to monotonic tensile loads is in the form of distributed matrix cracks. These cracks initiate near stress concentrations, such as 90o fiber tows or large matrix pores and continue to accumulate with additional stress until matrix crack saturation is achieved. Such damage is difficult to detect with conventional nondestructive evaluation techniques (immersion ultrasonics, x-ray, etc.). Monitoring a specimen.s electrical resistance change provides an indirect approach for monitoring matrix crack density. Sylramic-iBN fiber- reinforced SiC composites with a melt infiltrated (MI) matrix were tensile tested at room temperature. Results showed an increase in resistance of more than 500% prior to fracture, which can be detected either in situ or post-damage. A relationship between resistance change and matrix crack density was also determined.
NASA Astrophysics Data System (ADS)
Holman, Hoi-Ying N.; Goth-Goldstein, Regine; Blakely, Elanor A.; Bjornstad, Kathy; Martin, Michael C.; McKinney, Wayne R.
2000-05-01
Vibrational spectroscopy, when combined with synchrotron radiation-based (SR) microscopy, is a powerful new analytical tool with high spatial resolution for detecting biochemical changes in the individual living cells. In contrast to other microscopy methods that require fixing, drying, staining or labeling, SR-FTIR microscopy probes intact living cells providing a composite view of all of the molecular response and the ability to monitor the response over time in the same cell. Observed spectral changes include all types of lesions induced in that cell as well as cellular responses to external and internal stresses. These spectral changes combined with other analytical tools may provide a fundamental understanding of the key molecular mechanisms induced in response to stresses created by low- doses of chemicals. In this study we used the high spatial - resolution SR-FTIR vibrational spectromicroscopy as a sensitive analytical tool to detect chemical- and radiation- induced changes in individual human cells. Our preliminary spectral measurements indicate that this technique is sensitive enough to detect changes in nucleic acids and proteins of cells treated with environmentally relevant concentrations of dioxin. This technique has the potential to distinguish changes from exogenous or endogenous oxidative processes. Future development of this technique will allow rapid monitoring of cellular processes such as drug metabolism, early detection of disease, bio- compatibility of implant materials, cellular repair mechanisms, self assembly of cellular apparatus, cell differentiation and fetal development.
Mitchell, Anthea L; Rosenqvist, Ake; Mora, Brice
2017-12-01
Forest degradation is a global phenomenon and while being an important indicator and precursor to further forest loss, carbon emissions due to degradation should also be accounted for in national reporting within the frame of UN REDD+. At regional to country scales, methods have been progressively developed to detect and map forest degradation, with these based on multi-resolution optical, synthetic aperture radar (SAR) and/or LiDAR data. However, there is no one single method that can be applied to monitor forest degradation, largely due to the specific nature of the degradation type or process and the timeframe over which it is observed. The review assesses two main approaches to monitoring forest degradation: first, where detection is indicated by a change in canopy cover or proxies, and second, the quantification of loss (or gain) in above ground biomass (AGB). The discussion only considers degradation that has a visible impact on the forest canopy and is thus detectable by remote sensing. The first approach encompasses methods that characterise the type of degradation and track disturbance, detect gaps in, and fragmentation of, the forest canopy, and proxies that provide evidence of forestry activity. Progress in these topics has seen the extension of methods to higher resolution (both spatial and temporal) data to better capture the disturbance signal, distinguish degraded and intact forest, and monitor regrowth. Improvements in the reliability of mapping methods are anticipated by SAR-optical data fusion and use of very high resolution data. The second approach exploits EO sensors with known sensitivity to forest structure and biomass and discusses monitoring efforts using repeat LiDAR and SAR data. There has been progress in the capacity to discriminate forest age and growth stage using data fusion methods and LiDAR height metrics. Interferometric SAR and LiDAR have found new application in linking forest structure change to degradation in tropical forests. Estimates of AGB change have been demonstrated at national level using SAR and LiDAR-assisted approaches. Future improvements are anticipated with the availability of next generation LiDAR sensors. Improved access to relevant satellite data and best available methods are key to operational forest degradation monitoring. Countries will need to prioritise their monitoring efforts depending on the significance of the degradation, balanced against available resources. A better understanding of the drivers and impacts of degradation will help guide monitoring and restoration efforts. Ultimately we want to restore ecosystem service and function in degraded forests before the change is irreversible.
Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo
2014-01-01
Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.
Automatic detection of unattended changes in room acoustics.
Frey, Johannes Daniel; Wendt, Mike; Jacobsen, Thomas
2015-01-01
Previous research has shown that the human auditory system continuously monitors its acoustic environment, detecting a variety of irregularities (e.g., deviance from prior stimulation regularity in pitch, loudness, duration, and (perceived) sound source location). Detection of irregularities can be inferred from a component of the event-related brain potential (ERP), referred to as the mismatch negativity (MMN), even in conditions in which participants are instructed to ignore the auditory stimulation. The current study extends previous findings by demonstrating that auditory irregularities brought about by a change in room acoustics elicit a MMN in a passive oddball protocol (acoustic stimuli with differing room acoustics, that were otherwise identical, were employed as standard and deviant stimuli), in which participants watched a fiction movie (silent with subtitles). While the majority of participants reported no awareness for any changes in the auditory stimulation, only one out of 14 participants reported to have become aware of changing room acoustics or sound source location. Together, these findings suggest automatic monitoring of room acoustics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Infrared imaging: a potential powerful tool for neuroimaging and neurodiagnostics
Khoshakhlagh, Arezou; Gunapala, Sarath D.
2017-01-01
Abstract. Infrared (IR) imaging is used to detect the subtle changes in temperature needed to accurately detect and monitor disease. Technological advances have made IR a highly sensitive and reliable detection tool with strong potential in medical and neurophotonics applications. An overview of IR imaging specifically investigating quantum well IR detectors developed at Jet Propulsion Laboratory for a noninvasive, nonradiating imaging tool is provided, which could be applied for neuroscience and neurosurgery where it involves sensitive cellular temperature change. PMID:28382311
Flexible surface acoustic wave respiration sensor for monitoring obstructive sleep apnea syndrome
NASA Astrophysics Data System (ADS)
Jin, Hao; Tao, Xiang; Dong, Shurong; Qin, Yiheng; Yu, Liyang; Luo, Jikui; Deen, M. Jamal
2017-11-01
Obstructive sleep apnea syndrome (OSAS) has received much attention in recent years due to its significant harm to human health and high morbidity rate. A respiration monitoring system is needed to detect OSAS, so that the patient can receive treatment in a timely manner. Wired and wireless OSAS monitoring systems have been developed, but they require a wire connection and batteries to operate, and they are bulky, heavy and not user-friendly. In this paper, we propose the use of a flexible surface acoustic wave (SAW) microsensor to detect and monitor OSAS by measuring the humidity change associated with the respiration of a person. SAW sensors on rigid 128° YX LiNbO3 substrate are also characterized for this application. Results show both types of SAW sensors are suitable for OSAS monitoring with good sensitivity, repeatability and reliability, and the response time and recovery time for the flexible SAW sensors are 1.125 and 0.75 s, respectively. Our work demonstrates the potential for an innovative flexible microsensor for the detection and monitoring of OSAS.
Inverse sequential procedures for the monitoring of time series
NASA Technical Reports Server (NTRS)
Radok, Uwe; Brown, Timothy
1993-01-01
Climate changes traditionally have been detected from long series of observations and long after they happened. The 'inverse sequential' monitoring procedure is designed to detect changes as soon as they occur. Frequency distribution parameters are estimated both from the most recent existing set of observations and from the same set augmented by 1,2,...j new observations. Individual-value probability products ('likelihoods') are then calculated which yield probabilities for erroneously accepting the existing parameter(s) as valid for the augmented data set and vice versa. A parameter change is signaled when these probabilities (or a more convenient and robust compound 'no change' probability) show a progressive decrease. New parameters are then estimated from the new observations alone to restart the procedure. The detailed algebra is developed and tested for Gaussian means and variances, Poisson and chi-square means, and linear or exponential trends; a comprehensive and interactive Fortran program is provided in the appendix.
Volatile organic compound sensing devices
Lancaster, G.D.; Moore, G.A.; Stone, M.L.; Reagen, W.K.
1995-08-29
Apparatus employing vapochromic materials in the form of inorganic double complex salts which change color reversibly when exposed to volatile organic compound (VOC) vapors is adapted for VOC vapor detection, VOC aqueous matrix detection, and selective VOC vapor detection. The basic VOC vapochromic sensor is incorporated in various devices such as a ground probe sensor, a wristband sensor, a periodic sampling monitor, a soil/water penetrometer, an evaporative purge sensor, and various vacuum-based sensors which are particularly adapted for reversible/reusable detection, remote detection, continuous monitoring, or rapid screening of environmental remediation and waste management sites. The vapochromic sensor is used in combination with various fiber optic arrangements to provide a calibrated qualitative and/or quantitative indication of the presence of VOCs. 15 figs.
Volatile organic compound sensing devices
Lancaster, Gregory D.; Moore, Glenn A.; Stone, Mark L.; Reagen, William K.
1995-01-01
Apparatus employing vapochromic materials in the form of inorganic double complex salts which change color reversibly when exposed to volatile organic compound (VOC) vapors is adapted for VOC vapor detection, VOC aqueous matrix detection, and selective VOC vapor detection. The basic VOC vapochromic sensor is incorporated in various devices such as a ground probe sensor, a wristband sensor, a periodic sampling monitor, a soil/water penetrometer, an evaporative purge sensor, and various vacuum-based sensors which are particularly adapted for reversible/reusable detection, remote detection, continuous monitoring, or rapid screening of environmental remediation and waste management sites. The vapochromic sensor is used in combination with various fiber optic arrangements to provide a calibrated qualitative and/or quantitative indication of the presence of VOCs.
Nordberg, Maj-Liz; Evertson, Joakim
2003-12-01
Vegetation cover-change analysis requires selection of an appropriate set of variables for measuring and characterizing change. Satellite sensors like Landsat TM offer the advantages of wide spatial coverage while providing land-cover information. This facilitates the monitoring of surface processes. This study discusses change detection in mountainous dry-heath communities in Jämtland County, Sweden, using satellite data. Landsat-5 TM and Landsat-7 ETM+ data from 1984, 1994 and 2000, respectively, were used. Different change detection methods were compared after the images had been radiometrically normalized, georeferenced and corrected for topographic effects. For detection of the classes change--no change the NDVI image differencing method was the most accurate with an overall accuracy of 94% (K = 0.87). Additional change information was extracted from an alternative method called NDVI regression analysis and vegetation change in 3 categories within mountainous dry-heath communities were detected. By applying a fuzzy set thresholding technique the overall accuracy was improved from of 65% (K = 0.45) to 74% (K = 0.59). The methods used generate a change product showing the location of changed areas in sensitive mountainous heath communities, and it also indicates the extent of the change (high, moderate and unchanged vegetation cover decrease). A total of 17% of the dry and extremely dry-heath vegetation within the study area has changed between 1984 and 2000. On average 4% of the studied heath communities have been classified as high change, i.e. have experienced "high vegetation cover decrease" during the period. The results show that the low alpine zone of the southern part of the study area shows the highest amount of "high vegetation cover decrease". The results also show that the main change occurred between 1994 and 2000.
Vegetation Monitoring of Mashhad Using AN Object-Oriented POST Classification Comparison Method
NASA Astrophysics Data System (ADS)
Khalili Moghadam, N.; Delavar, M. R.; Forati, A.
2017-09-01
By and large, todays mega cities are confronting considerable urban development in which many new buildings are being constructed in fringe areas of these cities. This remarkable urban development will probably end in vegetation reduction even though each mega city requires adequate areas of vegetation, which is considered to be crucial and helpful for these cities from a wide variety of perspectives such as air pollution reduction, soil erosion prevention, and eco system as well as environmental protection. One of the optimum methods for monitoring this vital component of each city is multi-temporal satellite images acquisition and using change detection techniques. In this research, the vegetation and urban changes of Mashhad, Iran, were monitored using an object-oriented (marker-based watershed algorithm) post classification comparison (PCC) method. A Bi-temporal multi-spectral Landsat satellite image was used from the study area to detect the changes of urban and vegetation areas and to find a relation between these changes. The results of this research demonstrate that during 1987-2017, Mashhad urban area has increased about 22525 hectares and the vegetation area has decreased approximately 4903 hectares. These statistics substantiate the close relationship between urban development and vegetation reduction. Moreover, the overall accuracies of 85.5% and 91.2% were achieved for the first and the second image classification, respectively. In addition, the overall accuracy and kappa coefficient of change detection were assessed 84.1% and 70.3%, respectively.
Laser Induced Fluorescence (LIF) as a Remote Sensing Tool: A Review
NASA Technical Reports Server (NTRS)
Chappelle, E. W.; Kim, M. S.; Mulchi, C. L.; Daughtry, C. S. T.; McMurtrey, J.; Corp, L.
1998-01-01
Vegetational changes are primary indicators of the present and future ecological status of the globe. These are changes which not only impact upon the primary productivity, but the total of the biogeochemical processes occurring on the planet. The impacts of global climatic and other environmental changes on vegetation must be monitored by some means in order to develop models which will allow us to predict long term effects. Large scale monitoring is now possible only with remote sensing systems, primarily passive reflectance, obtained by the use of satellite and aircraft platforms. However, passive reflectance techniques at this time are limited in their ability to detect subtle changes in the concentration and oxidation states of the many compounds involved in the light reactions of photosynthesis. Knowledge of these changes we consider to be fundamental in the remote assessment of both the rate and efficiency of photosynthesis and also the early detection of stress damage. The above factors pointed to the desirability of a sensing technique with the sensitivity and specificity necessary for detecting and quantifying those biological entities involved in photosynthesis. Another optical technique for vegetation monitoring is fluorescence. Previously, the lack of adequate excitation light sources and detector technologies have limited the use of fluorescence on intact plant leaves in the field. It is only recently with the advent of lasers with short pulse duration and advanced detector technologies that fluorescence measurements in the remote mode have become possible in the presence of ambient light.
O'Connell, Allan F.; Talancy, Neil W.; Bailey, Larissa L.; Sauer, John R.; Cook, Robert; Gilbert, Andrew T.
2006-01-01
Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant detectability when documenting species occurrence. This assumption is rarely met in practice because animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these influences, we estimated site occupancy rates using species-specific detection probabilities for meso- and large terrestrial mammal species on Cape Cod, Massachusetts, USA. We used model selection to assess the influence of different sampling methods and major environmental factors on our ability to detect individual species. Remote cameras detected the most species (9), followed by cubby boxes (7) and hair traps (4) over a 13-month period. Estimated site occupancy rates were similar among sampling methods for most species when detection probabilities exceeded 0.15, but we question estimates obtained from methods with detection probabilities between 0.05 and 0.15, and we consider methods with lower probabilities unacceptable for occupancy estimation and inference. Estimated detection probabilities can be used to accommodate variation in sampling methods, which allows for comparison of monitoring programs using different protocols. Vegetation and seasonality produced species-specific differences in detectability and occupancy, but differences were not consistent within or among species, which suggests that our results should be considered in the context of local habitat features and life history traits for the target species. We believe that site occupancy is a useful state variable and suggest that monitoring programs for mammals using occupancy data consider detectability prior to making inferences about species distributions or population change.
NASA Astrophysics Data System (ADS)
Jules, Kenol; Lin, Paul P.
2007-06-01
With the International Space Station currently operational, a significant amount of acceleration data is being down-linked, processed and analyzed daily on the ground on a continuous basis for the space station reduced gravity environment characterization, the vehicle design requirements verification and science data collection. To help understand the impact of the unique spacecraft environment on the science data, an artificial intelligence monitoring system was developed, which detects in near real time any change in the reduced gravity environment susceptible to affect the on-going experiments. Using a dynamic graphical display, the monitoring system allows science teams, at any time and any location, to see the active vibration disturbances, such as pumps, fans, compressor, crew exercise, re-boost and extra-vehicular activities that might impact the reduced gravity environment the experiments are exposed to. The monitoring system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many increments (an increment usually lasts 6 months) collected onboard the station for selected disturbances. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential systems failures. The monitoring system has two operating modes: online and offline. Both near real-time on-line vibratory disturbance detection and off-line detection and trend analysis are discussed in this paper.
Irvine, Gail V.
2010-01-01
Glacier Bay National Park and Preserve in southeastern Alaska includes extensive coastlines representing a major proportion of all coastlines held by the National Park Service. The marine plants and invertebrates that occupy intertidal shores form highly productive communities that are ecologically important to a number of vertebrate and invertebrate consumers and that are vulnerable to human disturbances. To better understand these communities and their sensitivity, it is important to obtain information on species abundances over space and time. During field studies from 1997 to 2001, I investigated probability-based rocky intertidal monitoring designs that allow inference of results to similar habitat within the bay and that reduce bias. Aerial surveys of a subset of intertidal habitat indicated that the original target habitat of bedrock-dominated sites with slope less than or equal to 30 degrees was rare. This finding illustrated the value of probability-based surveys and led to a shift in the target habitat type to more mixed rocky habitat with steeper slopes. Subsequently, I investigated different sampling methods and strategies for their relative power to detect changes in the abundances of the predominant sessile intertidal taxa: barnacles -Balanomorpha, the mussel Mytilus trossulus and the rockweed Fucus distichus subsp. evanescens. I found that lower-intensity sampling of 25 randomly selected sites (= coarse-grained sampling) provided a greater ability to detect changes in the abundances of these taxa than did more intensive sampling of 6 sites (= fine-grained sampling). Because of its greater power, the coarse-grained sampling scheme was adopted in subsequent years. This report provides detailed analyses of the 4 years of data and evaluates the relative effect of different sampling attributes and management-set parameters on the ability of the sampling to detect changes in the abundances of these taxa. The intent was to provide managers with information to guide design choices for intertidal monitoring. I found that the coarse-grained surveys, as conducted from 1998 to 2001, had power ranging from 0.68 to 1.0 to detect 10 percent annual changes in the abundances of these predominant sessile species. The information gained through intertidal monitoring would be useful in assessing changes due to climate (including ocean acidification), invasive species, trampling effects, and oil spills.
Feasibility of Active Monitoring for Plate Coupling Using ACROSS
NASA Astrophysics Data System (ADS)
Yamaoka, K.; Watanabe, T.; Ikuta, R.
2004-12-01
Detectability of temporal changes in reflected wave from the boundary of subducting plates in Tokai district with active sources are studied. Based on rock experiments the change in the intensity of reflection wave can be caused by change in coupling between subducting and overriding plates. ACROSS (Accurately-Controlled Rountine-Operated Signal System) consists of sinusoidal vibration sources and receivers is proved to provide a data of excellent signal resolution. The following technical issues should be overcome to monitor the returned signal from boundaries of subducting plates. (1) Long term operation of the source. (2) Detection of temporal change. (3) Accurate estimation of source functions and their temporal change. First two issues have already overcome. We have already succeeded a long-term operation experiment with the ACROSS system in Awaji, Japan. The operation was carried out for 15 months with only minor troubles. Continuous signal during the experiment are successfully obtained. In the experiment we developed a technique to monitor the temporal change of travel time with a resolution of several tens of microseconds. The third issue is one of the most difficult problem for practical monitoring using artificial sources. In the 15-month experiment we correct the source function using the record of seismometers that were deployed around the source We also estimate the efficiency of the reflected wave detection using ACROSS system. We use a data of seismic exploration experiment by blasts that carried out above subducting plate in Tokai district. Clear reflection from the surface of the Philippine Sea plate is observed in the waveform. Assuming that the ACROSS source is installed at the same place of the blast source, the detectability of temporal variation of reflection wave can be estimated. As we have measured the variation of signal amplitude that depends on the distance from an ACROSS source, ground noise at seismic stations (receivers) provide us the signal-to-noise ratio for the signal from ACROSS. The resolution can be estimated only by the signal-to-noise ratio. We surveyed the noise level at the place where reflection from the boundary of subducting Philippine Sea Plate can be detected. The results show that the resolution will be better than 1% in amplitude and 0.1milisecond in travel time for the stacking of one week using three-unit source and ten-elements receiver arrays.
Temporal variation in spectral detection thresholds of substrate and vegetation in AVIRIS images
NASA Technical Reports Server (NTRS)
Sabol, Donald E., Jr.; Roberts, Dar A.; Smith, Milton O.; Adams, John B.
1992-01-01
The ability to map changes over large surface areas over time is one of the advantages in using remote sensing as a monitoring tool. Temporal changes in the surface may be gradual, making them difficult to detect in the short-term, and because they commonly occur at the subpixel scale, they may be difficult to detect in the long-term as well. Also, subtle changes may be real or merely an artifact of image noise. It is, therefore, necessary to understand the factors that limit the detection of surface materials in evaluating temporal data. The spectral detectability of vegetation and soil in the 1990 July and October Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of Jasper Ridge, CA was evaluated and compared.
Unobtrusive measurement of daily computer use to detect mild cognitive impairment
Kaye, Jeffrey; Mattek, Nora; Dodge, Hiroko H; Campbell, Ian; Hayes, Tamara; Austin, Daniel; Hatt, William; Wild, Katherine; Jimison, Holly; Pavel, Michael
2013-01-01
Background Mild disturbances of higher order activities of daily living are present in people diagnosed with mild cognitive impairment (MCI). These deficits may be difficult to detect among those still living independently. Unobtrusive continuous assessment of a complex activity such as home computer use may detect mild functional changes and identify MCI. We sought to determine whether long-term changes in remotely monitored computer use differ in persons with MCI in comparison to cognitively intact volunteers. Methods Participants enrolled in a longitudinal cohort study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors were assessed for computer usage (number of days with use, mean daily usage and coefficient of variation of use) measured by remotely monitoring computer session start and end times. Results Over 230,000 computer sessions from 113 computer users (mean age, 85; 38 with MCI) were acquired during a mean of 36 months. In mixed effects models there was no difference in computer usage at baseline between MCI and intact participants controlling for age, sex, education, race and computer experience. However, over time, between MCI and intact participants, there was a significant decrease in number of days with use (p=0.01), mean daily usage (~1% greater decrease/month; p=0.009) and an increase in day-to-day use variability (p=0.002). Conclusions Computer use change can be unobtrusively monitored and indicate individuals with MCI. With 79% of those 55–64 years old now online, this may be an ecologically valid and efficient approach to track subtle clinically meaningful change with aging. PMID:23688576
Monitoring sediment transfer processes on the desert margin
NASA Technical Reports Server (NTRS)
Millington, Andrew C.; Arwyn, R. Jones; Quarmby, Neil; Townshend, John R. G.
1987-01-01
LANDSAT Thematic Mapper and Multispectral Scanner data have been used to construct change detection images for three playas in south-central Tunisia. Change detection images have been used to analyze changes in surface reflectance and absorption between wet and dry season (intra-annual change) and between different years (inter-annual change). Change detection imagery has been used to examine geomorphological changes on the playas. Changes in geomorphological phenomena are interpreted from changes in soil and foliar moisture levels, differences in reflectances between different salt and sediments and the spatial expression of geomorphological features. Intra-annual change phenomena that can be detected from multidate imagery are changes in surface moisture, texture and chemical composition, vegetation cover and the extent of aeolian activity. Inter-annual change phenomena are divisible into those restricted to marginal playa facies (sedimentation from sheetwash and alluvial fans, erosion from surface runoff and cliff retreat) and these are found in central playa facies which are related to the internal redistribution of water, salt and sediment.
Structural-change localization and monitoring through a perturbation-based inverse problem.
Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa
2014-11-01
Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.
Assessing background ground water chemistry beneath a new unsewered subdivision
Wilcox, J.D.; Bradbury, K.R.; Thomas, C.L.; Bahr, J.M.
2005-01-01
Previous site-specific studies designed to assess the impacts of unsewered subdivisions on ground water quality have relied on upgradient monitoring wells or very limited background data to characterize conditions prior to development. In this study, an extensive monitoring program was designed to document ground water conditions prior to construction of a rural subdivision in south-central Wisconsin. Previous agricultural land use has impacted ground water quality; concentrations of chloride, nitrate-nitrogen, and atrazine ranged from below the level of detection to 296 mg/L, 36 mg/L, and 0.8 ??g/L, respectively, and were highly variable from well to well and through time. Seasonal variations in recharge, surface topography, aquifer heterogeneities, surficial loading patterns, and well casing depth explain observed variations in ground water chemistry. This variability would not have been detected if background conditions were determined from only a few monitoring wells or inferred from wells located upgradient of the subdivision site. This project demonstrates the importance of characterizing both ground water quality and chemical variability prior to land-use change to detect any changes once homes are constructed. Copyright ?? 2005 National Ground Water Association.
Stuetz, R M
2004-01-01
An online monitoring system based on an array of non-specific sensors was used for the detection of chemical pollutants in wastewater and water. By superimposing sensor profiles for defined sampling window, the identification of data points outside these normal sensor response patterns was used to represent potential pollution episodes or other abnormalities within the process stream. Principle component analysis supported the detection of outliers or rapid changes in the sensor responses as an indicator of chemical pollutants. A model based on the comparison of sensor relative responses to a moving average for a defined sample window was tested for detecting and identifying sudden changes in the online data over a 6-month period. These results show the technical advantages of using a non-specific based monitoring system that can respond to a range of chemical species, due to broad selectivity of the sensor compositions. The findings demonstrate how this non-invasive technique could be further developed to provide early warning systems for application at the inlet of wastewater treatment plants.
An all fiber-optic multi-parameter structure health monitoring system
Hu, Chennan; Yu, Zhihao; Wang, Anbo
2016-08-24
In this article, we present an all fiber-optics based multi-parameter structure health monitoring system, which is able to monitor strain, temperature, crack and thickness of metal structures. This system is composed of two optical fibers, one for laser-acoustic excitation and the other for acoustic detection. A nano-second 1064 nm pulse laser was used for acoustic excitation and a 2 mm fiber Bragg grating was used to detect the acoustic vibration. The feasibility of this system was demonstrated on an aluminum test piece by the monitoring of the temperature, strain and thickness changes, as well as the appearance of an artificialmore » crack. The multiplexing capability of this system was also preliminarily demonstrated.« less
An all fiber-optic multi-parameter structure health monitoring system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Chennan; Yu, Zhihao; Wang, Anbo
In this article, we present an all fiber-optics based multi-parameter structure health monitoring system, which is able to monitor strain, temperature, crack and thickness of metal structures. This system is composed of two optical fibers, one for laser-acoustic excitation and the other for acoustic detection. A nano-second 1064 nm pulse laser was used for acoustic excitation and a 2 mm fiber Bragg grating was used to detect the acoustic vibration. The feasibility of this system was demonstrated on an aluminum test piece by the monitoring of the temperature, strain and thickness changes, as well as the appearance of an artificialmore » crack. The multiplexing capability of this system was also preliminarily demonstrated.« less
Non-intrusive appliance monitor apparatus
Hart, G.W.; Kern, E.C. Jr.; Schweppe, F.C.
1989-08-15
A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each. 9 figs.
Esslinger, George G.; Esler, Daniel N.; Howlin, S.; Starcevich, L.A.
2015-06-25
After many decades of absence from southeast Alaska, sea otters (Enhydra lutris) are recolonizing parts of their former range, including Glacier Bay, Alaska. Sea otters are well known for structuring nearshore ecosystems and causing community-level changes such as increases in kelp abundance and changes in the size and number of other consumers. Monitoring population status of sea otters in Glacier Bay will help park researchers and managers understand and interpret sea otter-induced ecosystem changes relative to other sources of variation, including potential human-induced impacts such as ocean acidification, vessel disturbance, and oil spills. This report was prepared for the National Park Service (NPS), Southeast Alaska Inventory and Monitoring Network following a request for evaluation of options for monitoring sea otter population status in Glacier Bay National Park and Preserve. To meet this request, we provide a detailed consideration of the primary method of assessment of abundance and distribution, aerial surveys, including analyses of power to detect interannual trends and designs to reduce variation around annual abundance estimates. We also describe two alternate techniques for evaluating sea otter population status—(1) quantifying sea otter diets and energy intake rates, and (2) detecting change in ages at death. In addition, we provide a brief section on directed research to identify studies that would further our understanding of sea otter population dynamics and effects on the Glacier Bay ecosystem, and provide context for interpreting results of monitoring activities.
A Comparison of Vibration and Oil Debris Gear Damage Detection Methods Applied to Pitting Damage
NASA Technical Reports Server (NTRS)
Dempsey, Paula J.
2000-01-01
Helicopter Health Usage Monitoring Systems (HUMS) must provide reliable, real-time performance monitoring of helicopter operating parameters to prevent damage of flight critical components. Helicopter transmission diagnostics are an important part of a helicopter HUMS. In order to improve the reliability of transmission diagnostics, many researchers propose combining two technologies, vibration and oil monitoring, using data fusion and intelligent systems. Some benefits of combining multiple sensors to make decisions include improved detection capabilities and increased probability the event is detected. However, if the sensors are inaccurate, or the features extracted from the sensors are poor predictors of transmission health, integration of these sensors will decrease the accuracy of damage prediction. For this reason, one must verify the individual integrity of vibration and oil analysis methods prior to integrating the two technologies. This research focuses on comparing the capability of two vibration algorithms, FM4 and NA4, and a commercially available on-line oil debris monitor to detect pitting damage on spur gears in the NASA Glenn Research Center Spur Gear Fatigue Test Rig. Results from this research indicate that the rate of change of debris mass measured by the oil debris monitor is comparable to the vibration algorithms in detecting gear pitting damage.
Biofouling detection monitoring devices: status assessment. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hillman, R.E.; Anson, D.; Corliss, J.M.
1985-03-01
An inventory of devices to detect and monitor biofouling in power plant condenser systems was prepared. The inventory was developed through a review of manufacturers' product information brochures, a general literature review, and limited personal contact with users and manufacturers. Two macrofouling and seventeen microfouling detection devices were reviewed. A summary analysis of the principal features of each device was prepared. Macrofouling devices are generally simple devices located at or near cooling water intakes. They monitor the growth of larger organisms such as mussels, barnacles, and large seaweeds. Microfouling detectors are usually located in or near the condenser tubes. Theymore » detect and monitor the growth of slime films on the tubes. Some of the devices measure changes in heat transfer or pressure drop in the condenser tubes. Other types include condenser simulators, biofilm samplers, or devices that measure the acoustic properties of the fouling films. Most devices are still in the development stage. Of the few available for general use, the type that measures heat transfer and/or pressure drop are developed to a greater degree than the other types. Recommendations for further research into development of a biofouling detection and monitoring devices include a side-by-side field comparison of selected devices, and the continued development of an effective acoustic device.« less
NASA Astrophysics Data System (ADS)
Thiel, Stephan
2017-09-01
Hydraulic fracking is a geoengineering application designed to enhance subsurface permeability to maximize fluid and gas flow. Fracking is commonly used in enhanced geothermal systems (EGS), tight shale gas, and coal seam gas (CSG) plays and in CO_2 storage scenarios. Common monitoring methods include microseismics and mapping small earthquakes with great resolution associated with fracture opening at reservoir depth. Recently, electromagnetic (EM) methods have been employed in the field to provide an alternative way of direct detection of fluids as they are pumped in the ground. Surface magnetotelluric (MT) measurements across EGS show subtle yet detectable changes during fracking derived from time-lapse MT deployments. Changes are directional and are predominantly aligned with current stress field, dictating preferential fracture orientation, supported by microseismic monitoring of frack-related earthquakes. Modeling studies prior to the injection are crucial for survey design and feasibility of monitoring fracks. In particular, knowledge of sediment thickness plays a fundamental role in resolving subtle changes. Numerical forward modeling studies clearly favor some form of downhole measurement to enhance sensitivity; however, these have yet to be conclusively demonstrated in the field. Nevertheless, real surface-based monitoring examples do not necessarily replicate the expected magnitude of change derived from forward modeling and are larger than expected in some cases from EGS and CSG systems. It appears the injected fluid volume alone cannot account for the surface change in resistivity, but connectedness of pore space is also significantly enhanced and nonlinear. Recent numerical studies emphasize the importance of percolation threshold of the fracture network on both electrical resistivity and permeability, which may play an important role in accounting for temporal changes in surface EM measurements during hydraulic fracking.
Change detection and classification in brain MR images using change vector analysis.
Simões, Rita; Slump, Cornelis
2011-01-01
The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases--such as Alzheimer's--focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on Change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.
Monitoring of environmental conditions in the Alaskan forests using ERS-1 SAR data
NASA Technical Reports Server (NTRS)
Rignot, Eric; Way, Jobea; Mcdonald, Kyle; Viereck, Leslie; Adams, Phyllis
1992-01-01
Preliminary results from an analysis of the multitemporal radar backscatter signatures of tree species acquired by European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data are presented. Significant changes in radar backscatter are detected. Correlation of these differences with ground truth observations indicate that these are due to changes in soil and liquid water content as a result of freeze/thaw events. C-band observations acquired by the NASA/Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) instrument demonstrate the potential of a C-band radar instrument to monitor drought/flood events. The potential of ERS-1 for monitoring phenologic changes in the forest and for classifying tree species is less promising.
40 CFR 63.7330 - What are my monitoring requirements?
Code of Federal Regulations, 2010 CFR
2010-07-01
... relative change in particulate matter loadings using a bag leak detection system according to the... integrity of the baghouse through quarterly visual inspections of the baghouse interior for air leaks; and... must at all times monitor the pressure drop and water flow rate using a CPMS according to the...
NASA Astrophysics Data System (ADS)
Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan
2018-03-01
High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.
Detection of Mouse Cough Based on Sound Monitoring and Respiratory Airflow Waveforms
Chen, Liyan; Lai, Kefang; Lomask, Joseph Mark; Jiang, Bert; Zhong, Nanshan
2013-01-01
Detection for cough in mice has never yielded clearly audible sounds, so there is still a great deal of debates as to whether mice can cough in response to tussive stimuli. Here we introduce an approach for detection of mouse cough based on sound monitoring and airflow signals. 40 Female BALB/c mice were pretreated with normal saline, codeine, capasazepine or desensitized with capsaicin. Single mouse was put in a plethysmograph, exposed to aerosolized 100 µmol/L capsaicin for 3 min, followed by continuous observation for 3 min. Airflow signals of total 6 min were recorded and analyzed to detect coughs. Simultaneously, mouse cough sounds were sensed by a mini-microphone, monitored manually by an operator. When manual and automatic detection coincided, the cough was positively identified. Sound and sound waveforms were also recorded and filtered for further analysis. Body movements were observed by operator. Manual versus automated counts were compared. Seven types of airflow signals were identified by integrating manual and automated monitoring. Observation of mouse movements and analysis of sound waveforms alone did not produce meaningful data. Mouse cough numbers decreased significantly after all above drugs treatment. The Bland-Altman and consistency analysis between automatic and manual counts was 0.968 and 0.956. The study suggests that the mouse is able to present with cough, which could be detected by sound monitoring and respiratory airflow waveform changes. PMID:23555643
Harris, Deborah L; Battin, Malcolm R; Williams, Chris E; Weston, Philip J; Harding, Jane E
2009-01-01
The optimal approach to detection and management of neonatal hypoglycaemia remains unclear. We sought to demonstrate whether electro-encephalography (EEG) changes could be detected on the amplitude-integrated EEG monitor during induced hypoglycaemia in newborn lambs, and also to determine the accuracy of continuously measured interstitial glucose in this situation. Needle electrodes were placed in the P3-P4, O1-O2 montages. The interstitial glucose sensor was placed subcutaneously. After 30 min baseline recordings, hypoglycaemia was induced by insulin infusion and blood glucose levels were monitored every 5 min. The infusion was adjusted to reduce blood glucose levels by 0.5 mmol/l every 15 min and then maintain a blood glucose level <1.0 mmol/l for 4 h. EEG parameters analysed included amplitude, continuity and spectral edge frequency. The interstitial and blood glucose levels were compared. All lambs (n = 15, aged 3-11 days) became hypoglycaemic, with median blood glucose levels falling from 6.5 to 1.0 mmol/l, p < 0.0001. There were no detectable changes in any of the measured EEG parameters related to hypoglycaemia, although seizures occurred in 2 lambs. There was moderate agreement between the intermittent blood glucose and continuous interstitial glucose measurements in the baseline, decline, and hypoglycaemia periods (mean difference -0.7 mmol/l, 95% confidence interval, CI, -2.8 to 1.4 mmol/l). However, agreement was poor during reversal of hypoglycaemia (mean difference 4.5 mmol/l, 95% CI -1.1 to 10.7 mmol/l). The cot-side EEG may not be a useful clinical tool in the detection of neurological changes induced by hypoglycaemia. However, continuous interstitial glucose monitoring may be useful in the management of babies at risk of hypoglycaemia. (c) 2008 S. Karger AG, Basel.
InSAR-Detected Tidal Flow in Louisiana's Coastal Wetlands
NASA Astrophysics Data System (ADS)
Oliver-Cabrera, T.; Wdowinski, S.
2014-12-01
The Louisiana coast is among the most productive coastal area in the US and home to the largest coastal wetland area in the nation. However, Louisiana coastal wetlands have been threatened by natural (sea-level rise) and human (infrastructure development) stresses; they constitute the major part of the wetland loss of the country. Monitoring Louisiana's coastal wetlands represent a large challenge for local and federal authorities due to the large amount of area and hostile environment. Insofar, optical remote sensing observations have been used to classify the wetlands, monitor land cover changes, and assess the wetland loss over time. However, optical data is insensitive to surface flow and, hence, unable to detect the width of the tidal zone and changes in this area over time. SAR interferometry can provide useful information and ease the monitoring task. Wetland InSAR is the only application of the InSAR technology that provides information of aquatic surface. It provides useful information on surface water level changes in both inland and coastal wetlands. In this study, we use InSAR and tide gauge observations to detect and compare surface water level changes in response to ocean tide propagation through the Louisiana coastal wetlands. Our data consist of ALOS PALSAR, Radarsat-1 and tide gauge information over the coast of Louisiana. In order to detect water level changes, we used mainly high coherence interferferograms with short temporal baselines (46-92 days for ALOS data and 24-48 days for Radarsat-1). Interferometric processing of the data provides details maps of water level changes in the coastal zone. Preliminary results indicate tidal changes of up 30 cm and that tidal flow is limited to 8-10 km from the open water. Our results also show that the tidal flow is disrupted by various man-made structures as, canals and roads. The high spatial resolution wetland InSAR observations can provide useful constraints for detailed coastal wetland flow models.
Semiselective Optoelectronic Sensors for Monitoring Microbes
NASA Technical Reports Server (NTRS)
Tabacco, Mary Beth; Chuang, Han; Taylor,Laura; Russo, Jaime
2003-01-01
Sensor systems are under development for use in real-time detection and quantitation of microbes in water without need for sampling. These systems include arrays of optical sensors; miniature, portable electronic data-acquisition circuits; and optoelectronic interfaces between the sensor arrays and data-acquisition circuits. These systems are intended for original use in long-term, inline monitoring of waterborne micro-organisms in water-reclamation systems aboard future spacecraft. They could also be adapted to similar terrestrial uses with respect to municipal water supplies, stored drinking water, and swimming water; for detecting low-level biological contamination in biotechnological, semiconductor, and pharmaceutical process streams; and in verifying the safety of foods and beverages. In addition, they could be adapted to monitoring of airborne microbes and of surfaces (e.g., to detect and/or quantitate biofilms). The designs of the sensors in these systems are based partly on those of sensors developed previously for monitoring airborne biological materials. The designs exploit molecular- recognition and fluorescence-spectroscopy techniques, such that in the presence of micro-organisms of interest, fluorescence signals change and the changes can be measured. These systems are characterized as semiselective because they respond to classes of micro-organisms and can be used to discriminate among the classes. This semiselectivity is a major aspect of the design: It is important to distinguish between (1) the principle of detection and quantitation of classes of micro-organisms by use of these sensors and (2) the principle of detection and quantitation of individual microbiological species by means of prior immuno-diagnostic and/or molecular-biology techniques. Detection of classes (in contradistinction to species) is particularly valuable when the exact nature of a contaminant is unknown.
Bergquist, J; Vona, M J; Stiller, C O; O'Connor, W T; Falkenberg, T; Ekman, R
1996-03-01
The use of capillary electrophoresis with laser-induced fluorescence detection (CE-LIF) for the analysis of microdialysate samples from the periaqueductal grey matter (PAG) of freely moving rats is described. By employing 3-(4-carboxybenzoyl)-2-quinoline-carboxaldehyde (CBQCA) as a derivatization agent, we simultaneously monitored the concentrations of 8 amino acids (arginine, glutamine, valine, gamma-amino-n-butyric acid (GABA), alanine, glycine, glutamate, and aspartate), with nanomolar and subnanomolar detection limits. Two of the amino acids (GABA and glutamate) were analysed in parallel by conventional high-performance liquid chromatography (HPLC) in order to directly compare the two analytical methods. Other CE methods for analysis of microdialysate have been previously described, and this improved method offers greater sensitivity, ease of use, and the possibility to monitor several amino acids simultaneously. By using this technique together with an optimised form of microdialysis technique, the tiny sample consumption and the improved detection limits permit the detection of fast and transient transmitter changes.
Intelligent transient transitions detection of LRE test bed
NASA Astrophysics Data System (ADS)
Zhu, Fengyu; Shen, Zhengguang; Wang, Qi
2013-01-01
Health Monitoring Systems is an implementation of monitoring strategies for complex systems whereby avoiding catastrophic failure, extending life and leading to improved asset management. A Health Monitoring Systems generally encompasses intelligence at many levels and sub-systems including sensors, actuators, devices, etc. In this paper, a smart sensor is studied, which is use to detect transient transitions of liquid-propellant rocket engines test bed. In consideration of dramatic changes of variable condition, wavelet decomposition is used to work real time in areas. Contrast to traditional Fourier transform method, the major advantage of adding wavelet analysis is the ability to detect transient transitions as well as obtaining the frequency content using a much smaller data set. Historically, transient transitions were only detected by offline analysis of the data. The methods proposed in this paper provide an opportunity to detect transient transitions automatically as well as many additional data anomalies, and provide improved data-correction and sensor health diagnostic abilities. The developed algorithms have been tested on actual rocket test data.
Integrating scales of seagrass monitoring to meet conservation needs
Neckles, Hilary A.; Kopp, Blaine S.; Peterson, Bradley J.; Pooler, Penelope S.
2012-01-01
We evaluated a hierarchical framework for seagrass monitoring in two estuaries in the northeastern USA: Little Pleasant Bay, Massachusetts, and Great South Bay/Moriches Bay, New York. This approach includes three tiers of monitoring that are integrated across spatial scales and sampling intensities. We identified monitoring attributes for determining attainment of conservation objectives to protect seagrass ecosystems from estuarine nutrient enrichment. Existing mapping programs provided large-scale information on seagrass distribution and bed sizes (tier 1 monitoring). We supplemented this with bay-wide, quadrat-based assessments of seagrass percent cover and canopy height at permanent sampling stations following a spatially distributed random design (tier 2 monitoring). Resampling simulations showed that four observations per station were sufficient to minimize bias in estimating mean percent cover on a bay-wide scale, and sample sizes of 55 stations in a 624-ha system and 198 stations in a 9,220-ha system were sufficient to detect absolute temporal increases in seagrass abundance from 25% to 49% cover and from 4% to 12% cover, respectively. We made high-resolution measurements of seagrass condition (percent cover, canopy height, total and reproductive shoot density, biomass, and seagrass depth limit) at a representative index site in each system (tier 3 monitoring). Tier 3 data helped explain system-wide changes. Our results suggest tiered monitoring as an efficient and feasible way to detect and predict changes in seagrass systems relative to multi-scale conservation objectives.
Effects of Stereoscopic Depth on Vigilance Performance and Cerebral Hemodynamics.
Greenlee, Eric T; Funke, Gregory J; Warm, Joel S; Finomore, Victor S; Patterson, Robert E; Barnes, Laura E; Funke, Matthew E; Vidulich, Michael A
2015-09-01
We tested the possibility that monitoring a display wherein critical signals for detection were defined by a stereoscopic three-dimensional (3-D) image might be more resistant to the vigilance decrement, and to temporal declines in cerebral blood flow velocity (CBFV), than monitoring a display featuring a customary two-dimensional (2-D) image. Hancock has asserted that vigilance studies typically employ stimuli for detection that do not exemplify those that occur in the natural world. As a result, human performance is suboptimal. From this perspective, tasks that better approximate perception in natural environments should enhance performance efficiency. To test that possibility, we made use of stereopsis, an important means by which observers interact with their everyday surroundings. Observers monitored a circular display in which a vertical line was embedded. Critical signals for detection in a 2-D condition were instances in which the line was rotated clockwise from vertical. In a 3-D condition, critical signals were cases in which the line appeared to move outward toward the observer. The overall level of signal detection and the stability of detection over time were greater when observers monitored for 3-D changes in target depth compared to 2-D changes in target orientation. However, the 3-D display did not retard the temporal decline in CBFV. These results provide the initial demonstration that 3-D displays can enhance performance in vigilance tasks. The use of 3-D displays may be productive in augmenting system reliability when operator vigilance is vital. © 2015, Human Factors and Ergonomics Society.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McCann, D.; White, D.
This paper reports on a smart alarm system installed on a number of offshore rigs and one land rig which can detect kicks more quickly than conventional systems. This rapid kick detection improves rig safety because the smaller the detected influx, the easier it is to control the well. The extensive computerized monitoring system helps drilling personnel detect fluid influxes and fluid losses before the changes in flow would normally be apparent.
The challenges of remote monitoring of wetlands
Gallant, Alisa L.
2015-01-01
Wetlands are highly productive and support a wide variety of ecosystem goods and services. Various forms of global change impose compelling needs for timely and reliable information on the status of wetlands worldwide, but several characteristics of wetlands make them challenging to monitor remotely: they lack a single, unifying land-cover feature; they tend to be highly dynamic and their energy signatures are constantly changing; and steep environmental gradients in and around wetlands produce narrow ecotones that often are below the resolving capacity of remote sensors. These challenges and needs set the context for a special issue focused on wetland remote sensing. Contributed papers responded to one of three overarching questions aimed at improving remote, large-area monitoring of wetlands: (1) What approaches and data products are being developed specifically to support regional to global long-term monitoring of wetland landscapes? (2) What are the promising new technologies and sensor/multisensor approaches for more accurate and consistent detection of wetlands? (3) Are there studies that demonstrate how remote long-term monitoring of wetland landscapes can reveal changes that correspond with changes in land cover and land use and/or changes in climate?
Physical habitat monitoring strategy (PHAMS) for reach-scale restoration effectiveness monitoring
Jones, Krista L.; O'Daniel, Scott J.; Beechie, Tim J.; Zakrajsek, John; Webster, John G.
2015-04-14
Habitat restoration efforts by the Confederated Tribes of the Umatilla Indian Reservation (CTUIR) have shifted from the site scale (1-10 meters) to the reach scale (100-1,000 meters). This shift was in response to the growing scientific emphasis on process-based restoration and to support from the 2007 Accords Agreement with the Bonneville Power Administration. With the increased size of restoration projects, the CTUIR and other agencies are in need of applicable monitoring methods for assessing large-scale changes in river and floodplain habitats following restoration. The goal of the Physical Habitat Monitoring Strategy is to outline methods that are useful for capturing reach-scale changes in surface and groundwater hydrology, geomorphology, hydrologic connectivity, and riparian vegetation at restoration projects. The Physical Habitat Monitoring Strategy aims to avoid duplication with existing regional effectiveness monitoring protocols by identifying complimentary reach-scale metrics and methods that may improve the ability of CTUIR and others to detect instream and riparian changes at large restoration projects.
Jeppesen, Jesper; Beniczky, Sándor; Johansen, Peter; Sidenius, Per; Fuglsang-Frederiksen, Anders
2015-03-01
Near infrared spectroscopy (NIRS) has proved useful in measuring significant hemodynamic changes in the brain during epileptic seizures. The advance of NIRS-technology into wireless and portable devices raises the possibility of using the NIRS-technology for portable seizure detection. This study used NIRS to measure changes in oxygenated (HbO), deoxygenated (HbR), and total hemoglobin (HbT) at left and right side of the frontal lobe in 33 patients with epilepsy undergoing long-term video-EEG monitoring. Fifteen patients had 34 focal seizures (20 temporal-, 11 frontal-, 2 parietal-lobe, one unspecific) recorded and analyzed with NIRS. Twelve parameters consisting of maximum increase and decrease changes of HbO, HbR and HbT during seizures (1 min before- to 3 min after seizure-onset) for left and right side, were compared with the patients' own non-seizure periods (a 2-h period and a 30-min exercise-period). In both non-seizure periods 4 min moving windows with maximum overlapping were applied to find non-seizure maxima of the 12 parameters. Detection was defined as positive when seizure maximum change exceeded non-seizure maximum change. When analyzing the 12 parameters separately the positive seizure detection was in the range of 6-24%. The increase in hemodynamics was in general better at detecting seizures (15-24%) than the decrease in hemodynamics (6-18%) (P=0.02). NIRS did not seem to be a suitable technology for generic seizure detection given the device, settings, and methods used in this study. There are still several challenges to overcome before the NIRS-technology can be used as a home-monitoring seizure detection device. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ye, Su; Chen, Dongmei; Yu, Jie
2016-04-01
In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.
Detecting and Quantifying Forest Change: The Potential of Existing C- and X-Band Radar Datasets.
Tanase, Mihai A; Ismail, Ismail; Lowell, Kim; Karyanto, Oka; Santoro, Maurizio
2015-01-01
This paper evaluates the opportunity provided by global interferometric radar datasets for monitoring deforestation, degradation and forest regrowth in tropical and semi-arid environments. The paper describes an easy to implement method for detecting forest spatial changes and estimating their magnitude. The datasets were acquired within space-borne high spatial resolutions radar missions at near-global scales thus being significant for monitoring systems developed under the United Framework Convention on Climate Change (UNFCCC). The approach presented in this paper was tested in two areas located in Indonesia and Australia. Forest change estimation was based on differences between a reference dataset acquired in February 2000 by the Shuttle Radar Topography Mission (SRTM) and TanDEM-X mission (TDM) datasets acquired in 2011 and 2013. The synergy between SRTM and TDM datasets allowed not only identifying changes in forest extent but also estimating their magnitude with respect to the reference through variations in forest height.
Transiently-Evoked Otoacoustic Emissions (teoaes) in Monitoring Adult Cis-Platin Patients.
NASA Astrophysics Data System (ADS)
Ribera, John Everett
1995-01-01
There is evidence to suggest that otoacoustic emissions (OAEs) reflect the integrity of cochlear outer hair cell (OHC) function. Cis-platin (CDDP) is a potent ototoxic chemotherapeutic agent that tends to destroy or disable OHCs. Therefore, this study was designed to answer the following questions: (1) Can TEOAEs be used in monitoring for ototoxicity in adult VA oncology patients receiving CDDP treatment? (2) If so, how sensitive are TEOAEs in detecting significant changes when compared to Audiometry in a VA population? and (3) Which of several TEOAE measures is the most sensitive to changes in hearing due to CDDP ototoxicity in a VA population?. In Experiment I, VA Medical Center patients were recruited (control group) and tested using a conventional audiometer and the ILO88 Otoacoustic Analyzer on three separate days. Data from this experiment were used to develop change criteria in each of four TEOAE measures (Reproducibility, Compare, 1 kHz Band Analysis, and OAE Response) for Experiment II. Experiment II was of similar design with the exception that the subjects (experimental group) were patients enrolled from the oncology ward and were administered CDDP after the first and second test sessions. Data from both groups and all test measures revealed (1) that there was no ear effect in any of the test conditions, (2) there was a group (drug) effect, and (3) there was a frequency effect at 2 kHz. Audiometry detected changes in 56% of the experimental subjects, while the number of changes varied among the TEOAE measures studied. Compare agreed with Audiometry more often and performed better than any other TEOAE measure in detecting change. Based on these findings, incorporation of Compare into an audiometric test battery to monitor for ototoxicity in the VA population is feasible. There is evidence to suggest that as measurement techniques are refined TEOAE analysis will become a valid test for monitoring of adult CDDP patients.
Rantz, Marilyn J; Skubic, Marjorie; Popescu, Mihail; Galambos, Colleen; Koopman, Richelle J; Alexander, Gregory L; Phillips, Lorraine J; Musterman, Katy; Back, Jessica; Miller, Steven J
2015-01-01
Environmentally embedded (nonwearable) sensor technology is in continuous use in elder housing to monitor a new set of ‘vital signs' that continuously measure the functional status of older adults, detect potential changes in health or functional status, and alert healthcare providers for early recognition and treatment of those changes. Older adult participants' respiration, pulse, and restlessness are monitored as they sleep. Gait speed, stride length, and stride time are calculated daily, and automatically assess for increasing fall risk. Activity levels are summarized and graphically displayed for easy interpretation. Falls are detected when they occur and alerts are sent immediately to healthcare providers, so time to rescue may be reduced. Automated health alerts are sent to healthcare staff, based on continuously running algorithms applied to the sensor data, days and weeks before typical signs or symptoms are detected by the person, family members, or healthcare providers. Discovering these new functional status ‘vital signs', developing automated methods for interpreting them, and alerting others when changes occur have the potential to transform chronic illness management and facilitate aging in place through the end of life. Key findings of research in progress at the University of Missouri are discussed in this viewpoint article, as well as obstacles to widespread adoption.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stone, Daithi A.; Hansen, Gerrit
Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the “confidence” language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies inmore » considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.« less
Moran, Seth C.; Freymueller, Jeff T.; LaHusen, Richard G.; McGee, Kenneth A.; Poland, Michael P.; Power, John A.; Schmidt, David A.; Schneider, David J.; Stephens, George; Werner, Cynthia A.; White, Randall A.
2008-01-01
As magma moves toward the surface, it interacts with anything in its path: hydrothermal systems, cooling magma bodies from previous eruptions, and (or) the surrounding 'country rock'. Magma also undergoes significant changes in its physical properties as pressure and temperature conditions change along its path. These interactions and changes lead to a range of geophysical and geochemical phenomena. The goal of volcano monitoring is to detect and correctly interpret such phenomena in order to provide early and accurate warnings of impending eruptions. Given the well-documented hazards posed by volcanoes to both ground-based populations (for example, Blong, 1984; Scott, 1989) and aviation (for example, Neal and others, 1997; Miller and Casadevall, 2000), volcano monitoring is critical for public safety and hazard mitigation. Only with adequate monitoring systems in place can volcano observatories provide accurate and timely forecasts and alerts of possible eruptive activity. At most U.S. volcanoes, observatories traditionally have employed a two-component approach to volcano monitoring: (1) install instrumentation sufficient to detect unrest at volcanic systems likely to erupt in the not-too-distant future; and (2) once unrest is detected, install any instrumentation needed for eruption prediction and monitoring. This reactive approach is problematic, however, for two reasons. 1. At many volcanoes, rapid installation of new ground-1. based instruments is difficult or impossible. Factors that complicate rapid response include (a) eruptions that are preceded by short (hours to days) precursory sequences of geophysical and (or) geochemical activity, as occurred at Mount Redoubt (Alaska) in 1989 (24 hours), Anatahan (Mariana Islands) in 2003 (6 hours), and Mount St. Helens (Washington) in 1980 and 2004 (7 and 8 days, respectively); (b) inclement weather conditions, which may prohibit installation of new equipment for days, weeks, or even months, particularly at midlatitude or high-latitude volcanoes; (c) safety factors during unrest, which can limit where new instrumentation can safely be installed (particularly at near-vent sites that can be critical for precursor detection and eruption forecasting); and (d) the remoteness of many U.S. volcanoes (particularly those in the Aleutians and the Marianas Islands), where access is difficult or impossible most of the year. Given these difficulties, it is reasonable to anticipate that ground-based monitoring of eruptions at U.S. volcanoes will likely be performed primarily with instruments installed before unrest begins. 2. Given a growing awareness of previously undetected 2. phenomena that may occur before an eruption begins, at present the types and (or) density of instruments in use at most U.S. volcanoes is insufficient to provide reliable early warning of volcanic eruptions. As shown by the gap analysis of Ewert and others (2005), a number of U.S. volcanoes lack even rudimentary monitoring. At those volcanic systems with monitoring instrumentation in place, only a few types of phenomena can be tracked in near-real time, principally changes in seismicity, deformation, and large-scale changes in thermal flux (through satellite-based remote sensing). Furthermore, researchers employing technologically advanced instrumentation at volcanoes around the world starting in the 1990s have shown that subtle and previously undetectable phenomena can precede or accompany eruptions. Detection of such phenomena would greatly improve the ability of U.S. volcano observatories to provide accurate early warnings of impending eruptions, and is a critical capability particularly at the very high-threat volcanoes identified by Ewert and others (2005). For these two reasons, change from a reactive to a proactive volcano-monitoring strategy is clearly needed at U.S. volcanoes. Monitoring capabilities need to be expanded at virtually every volcanic center, regardless of its current state of
Detecting insect pollinator declines on regional and global scales
Lubuhn, Gretchen; Droege, Sam; Connor, Edward F.; Gemmill-Herren, Barbara; Potts, Simon G.; Minckley, Robert L.; Griswold, Terry; Jean, Robert; Kula, Emanuel; Roubik, David W.; Cane, Jim; Wright, Karen W.; Frankie, Gordon; Parker, Frank
2013-01-01
Recently there has been considerable concern about declines in bee communities in agricultural and natural habitats. The value of pollination to agriculture, provided primarily by bees, is >$200 billion/year worldwide, and in natural ecosystems it is thought to be even greater. However, no monitoring program exists to accurately detect declines in abundance of insect pollinators; thus, it is difficult to quantify the status of bee communities or estimate the extent of declines. We used data from 11 multiyear studies of bee communities to devise a program to monitor pollinators at regional, national, or international scales. In these studies, 7 different methods for sampling bees were used and bees were sampled on 3 different continents. We estimated that a monitoring program with 200-250 sampling locations each sampled twice over 5 years would provide sufficient power to detect small (2-5%) annual declines in the number of species and in total abundance and would cost U.S.$2,000,000. To detect declines as small as 1% annually over the same period would require >300 sampling locations. Given the role of pollinators in food security and ecosystem function, we recommend establishment of integrated regional and international monitoring programs to detect changes in pollinator communities.
Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection
NASA Technical Reports Server (NTRS)
Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin
2010-01-01
Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.
New sensors and techniques for the structural health monitoring of propulsion systems.
Woike, Mark; Abdul-Aziz, Ali; Oza, Nikunj; Matthews, Bryan
2013-01-01
The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA), through the Aviation Safety Program (AVSP), has taken a lead role in the development of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. This paper presents a summary of key results and findings obtained from three different structural health monitoring approaches that have been investigated. This includes evaluating the performance of a novel microwave blade tip clearance sensor; a vibration based crack detection technique using an externally mounted capacitive blade tip clearance sensor; and lastly the results of using data driven anomaly detection algorithms for detecting cracks in a rotating disk.
New Sensors and Techniques for the Structural Health Monitoring of Propulsion Systems
2013-01-01
The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA), through the Aviation Safety Program (AVSP), has taken a lead role in the development of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. This paper presents a summary of key results and findings obtained from three different structural health monitoring approaches that have been investigated. This includes evaluating the performance of a novel microwave blade tip clearance sensor; a vibration based crack detection technique using an externally mounted capacitive blade tip clearance sensor; and lastly the results of using data driven anomaly detection algorithms for detecting cracks in a rotating disk. PMID:23935425
Quantifiable long-term monitoring on parks and nature preserves
Beck, Scott; Moorman, Christopher; DePerno, Christopher S.; Simons, Theodore R.
2013-01-01
Herpetofauna have declined globally, and monitoring is a useful approach to document local and long-term changes. However, monitoring efforts often fail to account for detectability or follow standardized protocols. We performed a case study at Hemlock Bluffs Nature Preserve in Cary, NC to model occupancy of focal species and demonstrate a replicable long-term protocol useful to parks and nature preserves. From March 2010 to 2011, we documented occupancy of Ambystoma opacum(Marbled Salamander), Plethodon cinereus (Red-backed Salamander), Carphophis amoenus (Eastern Worm Snake), and Diadophis punctatus (Ringneck Snake) at coverboard sites and estimated breeding female Ambystoma maculatum (Spotted Salamander) abundance via dependent double-observer egg-mass counts in ephemeral pools. Temperature influenced detection of both Marbled and Red-backed Salamanders. Based on egg-mass data, we estimated Spotted Salamander abundance to be between 21 and 44 breeding females. We detected 43 of 53 previously documented herpetofauna species. Our approach demonstrates a monitoring protocol that accounts for factors that influence species detection and is replicable by parks or nature preserves with limited resources.
A qualitative review for wireless health monitoring system
NASA Astrophysics Data System (ADS)
Arshad, Atika; Fadzil Ismail, Ahmad; Khan, Sheroz; Zahirul Alam, A. H. M.; Tasnim, Rumana; Samnan Haider, Syed; Shobaki, Mohammed M.; Shahid, Zeeshan
2013-12-01
A proliferating interest has been being observed over the past years in accurate wireless system development in order to monitor incessant human activities in health care centres. Furthermore because of the swelling number of elderly population and the inadequate number of competent staffs for nursing homes there is a big market petition for health care monitoring system. In order to detect human researchers developed different methods namely which include Field Identification technique, Visual Sensor Network, radar detection, e-mobile techniques and so on. An all-encompassing overview of the non-wired human detection application advancement is presented in this paper. Inductive links are used for human detection application while wiring an electronic system has become impractical in recent times. Keeping in mind the shortcomings, an Inductive Intelligent Sensor (IIS) has been proposed as a novel human monitoring system for future implementation. The proposed sensor works towards exploring the signature signals of human body movement and size. This proposed sensor is fundamentally based on inductive loop that senses the presence and a passing human resulting an inductive change.
Sprint, Gina; Cook, Diane; Weeks, Douglas; Dahmen, Jordana; La Fleur, Alyssa
2017-09-27
Time series data collected from sensors can be analyzed to monitor changes in physical activity as an individual makes a substantial lifestyle change, such as recovering from an injury or illness. In an inpatient rehabilitation setting, approaches to detect and explain changes in longitudinal physical activity data collected from wearable sensors can provide value as a monitoring, research, and motivating tool. We adapt and expand our Physical Activity Change Detection (PACD) approach to analyze changes in patient activity in such a setting. We use Fitbit Charge Heart Rate devices with two separate populations to continuously record data to evaluate PACD, nine participants in a hospitalized inpatient rehabilitation group and eight in a healthy control group. We apply PACD to minute-by-minute Fitbit data to quantify changes within and between the groups. The inpatient rehabilitation group exhibited greater variability in change throughout inpatient rehabilitation for both step count and heart rate, with the greatest change occurring at the end of the inpatient hospital stay, which exceeded day-to-day changes of the control group. Our additions to PACD support effective change analysis of wearable sensor data collected in an inpatient rehabilitation setting and provide insight to patients, clinicians, and researchers.
Lee, James S.; Shin, Keun-Young; Cheong, Oug Jae; Kim, Jae Hyun; Jang, Jyongsik
2015-01-01
We demonstrate an 80-μm-thick film (which is around 15% of the thickness of the human epidermis), which is a highly sensitive hybrid functional gauge sensor, and was fabricated from poly(vinylidene fluoride) (PVDF) and ZnO nanostructures with graphene electrodes. Using this film, we were able to simultaneously measure pressure and temperature in real time. The pressure was monitored from the change in the electrical resistance via the piezoresistance of the material, and the temperature was inferred based on the recovery time of the signal. Our thin film system enabled us to detect changes in pressure as small as 10 Pa which is pressure detection limit was 103-fold lower than the minimum level required for artificial skin, and to detect temperatures in the range 20–120°C. PMID:25601479
Lee, James S; Shin, Keun-Young; Cheong, Oug Jae; Kim, Jae Hyun; Jang, Jyongsik
2015-01-20
We demonstrate an 80-μm-thick film (which is around 15% of the thickness of the human epidermis), which is a highly sensitive hybrid functional gauge sensor, and was fabricated from poly(vinylidene fluoride) (PVDF) and ZnO nanostructures with graphene electrodes. Using this film, we were able to simultaneously measure pressure and temperature in real time. The pressure was monitored from the change in the electrical resistance via the piezoresistance of the material, and the temperature was inferred based on the recovery time of the signal. Our thin film system enabled us to detect changes in pressure as small as 10 Pa which is pressure detection limit was 10(3)-fold lower than the minimum level required for artificial skin, and to detect temperatures in the range 20-120 °C.
Zhang, Liwei; Anderson, Nicole; Dilmore, Robert; Soeder, Daniel J; Bromhal, Grant
2014-09-16
Potential natural gas leakage into shallow, overlying formations and aquifers from Marcellus Shale gas drilling operations is a public concern. However, before natural gas could reach underground sources of drinking water (USDW), it must pass through several geologic formations. Tracer and pressure monitoring in formations overlying the Marcellus could help detect natural gas leakage at hydraulic fracturing sites before it reaches USDW. In this study, a numerical simulation code (TOUGH 2) was used to investigate the potential for detecting leaking natural gas in such an overlying geologic formation. The modeled zone was based on a gas field in Greene County, Pennsylvania, undergoing production activities. The model assumed, hypothetically, that methane (CH4), the primary component of natural gas, with some tracer, was leaking around an existing well between the Marcellus Shale and the shallower and lower-pressure Bradford Formation. The leaky well was located 170 m away from a monitoring well, in the Bradford Formation. A simulation study was performed to determine how quickly the tracer monitoring could detect a leak of a known size. Using some typical parameters for the Bradford Formation, model results showed that a detectable tracer volume fraction of 2.0 × 10(-15) would be noted at the monitoring well in 9.8 years. The most rapid detection of tracer for the leak rates simulated was 81 days, but this scenario required that the leakage release point was at the same depth as the perforation zone of the monitoring well and the zones above and below the perforation zone had low permeability, which created a preferred tracer migration pathway along the perforation zone. Sensitivity analysis indicated that the time needed to detect CH4 leakage at the monitoring well was very sensitive to changes in the thickness of the high-permeability zone, CH4 leaking rate, and production rate of the monitoring well.
Monitoring trail conditions: New methodological considerations
Marion, Jeffrey L.; Leung, Yu-Fai; Nepal, Sanjay K.
2006-01-01
The U.S. National Park Service (NPS) accommodates nearly 300 million visitors per year, visitation that has the potential to produce negative effects on fragile natural and cultural resources. The policy guidance from the NPS Management Policies recognizes the legitimacy of providing opportunities for public enjoyment of parks while acknowledging the need for managers to “seek ways to avoid, or to minimize to the greatest degree practicable, adverse impacts on park resources and values” (NPS 2001). Thus, relative to visitor use, park managers must evaluate the types and extents of resource impacts associated with recreational activities, and determine to what extent they are unacceptable and constitute impairment. Visitor impact monitoring programs can assist managers in making objective evaluations of impact acceptability and impairment and in selecting effective impact management practices by providing quantitative documentation of the types and extent of recreationrelated impacts on natural resources. Monitoring programs are explicitly authorized in Section 4.1 of the Management Policies: Natural systems in the national park system, and the human influences upon them, will be monitored to detect change. The Service will use the results of monitoring and research to understand the detected change and to develop appropriate management actions.
Detection and monitoring of surface micro-cracks by PPP-BOTDA.
Meng, Dewei; Ansari, Farhad; Feng, Xin
2015-06-01
Appearance of micrometer size surface cracks is common in structural elements such as welded connections, beams, and gusset plates in bridges. Brillouin scattering-based sensors are capable of making distributed strain measurements. Pre-pump-pulse Brillouin optical time domain analysis (PPP-BOTDA) provides a centimeter-level spatial resolution, which facilitates detection and monitoring of the cracks. In the work described here, in addition to the shift in Brillouin frequency (distributed strains), change in the Brillouin gain spectrum (BGS) width is investigated for the detection and monitoring of surface micro-cracks. A theoretical analysis was undertaken in order to verify the rationality of the proposed method. The theoretical approach involved simulation of strain within a segment of the optical fiber traversing a crack and use of the simulated strain distribution in the opto-mechanical relations in order to numerically obtain the change in the BGS. Simulations revealed that the increase in crack opening displacements is associated with increase in BGS width and decrease in its peak power. Experimental results also indicated that the increases in crack opening displacements are accompanied with increases in BGS widths. However, it will be difficult to use the decrease in BGS power peak as another indicator due to practical difficulties in establishing generalized power amplitude in all the experiments. The study indicated that, in combination with the shift in Brillouin frequency, the increase in BGS width will provide a strong tool for detection and monitoring of surface micro-crack growths.
Towards Comprehensive Variation Models for Designing Vehicle Monitoring Systems
NASA Technical Reports Server (NTRS)
McAdams, Daniel A.; Tumer, Irem Y.; Clancy, Daniel (Technical Monitor)
2002-01-01
When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes in a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. This crucial roadblock makes their implementation in real vehicles (e.g., helicopter transmissions and aircraft engines) difficult, making their operation costly and unreliable. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. Using such models, we develop a methodology to account for design and manufacturing variations, and explore the changes in the vibration response to determine its stochastic nature. We explore the potential of the methodology using a nonlinear cam-follower model, where the spring stiffness values are assumed to follow a normal distribution. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle monitoring systems.
NASA Astrophysics Data System (ADS)
García, Alicia; Berrocoso, Manuel; Marrero, José M.; Fernández-Ros, Alberto; Prates, Gonçalo; De la Cruz-Reyna, Servando; Ortiz, Ramón
2014-06-01
The 2011 volcanic unrest at El Hierro Island illustrated the need for a Volcanic Alert System (VAS) specifically designed for the management of volcanic crises developing after long repose periods. The VAS comprises the monitoring network, the software tools for analysis of the monitoring parameters, the Volcanic Activity Level (VAL) management, and the assessment of hazard. The VAS presented here focuses on phenomena related to moderate eruptions, and on potentially destructive volcano-tectonic earthquakes and landslides. We introduce a set of new data analysis tools, aimed to detect data trend changes, as well as spurious signals related to instrumental failure. When data-trend changes and/or malfunctions are detected, a watchdog is triggered, issuing a watch-out warning (WOW) to the Monitoring Scientific Team (MST). The changes in data patterns are then translated by the MST into a VAL that is easy to use and understand by scientists, technicians, and decision-makers. Although the VAS was designed specifically for the unrest episodes at El Hierro, the methodologies may prove useful at other volcanic systems.
Okamura, Naomi; Kobayashi, Yo; Sugano, Shigeki; Fujie, Masakatsu G
2017-07-01
Static stretching is widely performed to decrease muscle tone as a part of rehabilitation protocols. Finding out the optimal duration of static stretching is important to minimize the time required for rehabilitation therapy and it would be helpful for maintaining the patient's motivation towards daily rehabilitation tasks. Several studies have been conducted for the evaluation of static stretching; however, the recommended duration of static stretching varies widely between 15-30 s in general, because the traditional methods for the assessment of muscle tone do not monitor the continuous change in the target muscle's state. We have developed a method to monitor the viscoelasticity of one muscle continuously during static stretching, using a wearable indentation tester. In this study, we investigated a suitable signal processing method to detect the time required to change the muscle tone, utilizing the data collected using a wearable indentation tester. By calculating a viscoelastic index with a certain time window, we confirmed that the stretching duration required to bring about a decrease in muscle tone could be obtained with an accuracy in the order of 1 s.
Robert E. Kennedy; Philip A. Townsend; John E. Gross; Warren B. Cohen; Paul Bolstad; Wang Y. Q.; Phyllis Adams
2009-01-01
Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis...
Detection, monitoring, and evaluation of spatio-temporal change in mosquito populations
USDA-ARS?s Scientific Manuscript database
USDA-ARS scientists seek to implement a sampling and global information technology based system that can be used for mosquito detection and trap deployment, to estimate mosquito species composition and distribution in space and time, and for targeting and evaluation of mosquito controls. Knowledge ...
Wireless and embedded carbon nanotube networks for damage detection in concrete structures
NASA Astrophysics Data System (ADS)
Saafi, Mohamed
2009-09-01
Concrete structures undergo an uncontrollable damage process manifesting in the form of cracks due to the coupling of fatigue loading and environmental effects. In order to achieve long-term durability and performance, continuous health monitoring systems are needed to make critical decisions regarding operation, maintenance and repairs. Recent advances in nanostructured materials such as carbon nanotubes have opened the door for new smart and advanced sensing materials that could effectively be used in health monitoring of structures where wireless and real time sensing could provide information on damage development. In this paper, carbon nanotube networks were embedded into a cement matrix to develop an in situ wireless and embedded sensor for damage detection in concrete structures. By wirelessly measuring the change in the electrical resistance of the carbon nanotube networks, the progress of damage can be detected and monitored. As a proof of concept, wireless cement-carbon nanotube sensors were embedded into concrete beams and subjected to monotonic and cyclic loading to evaluate the effect of damage on their response. Experimental results showed that the wireless response of the embedded nanotube sensors changes due to the formation of cracks during loading. In addition, the nanotube sensors were able to detect the initiation of damage at an early stage of loading.
NASA Astrophysics Data System (ADS)
Tang, Xiaojing
Fast and accurate monitoring of tropical forest disturbance is essential for understanding current patterns of deforestation as well as helping eliminate illegal logging. This dissertation explores the use of data from different satellites for near real-time monitoring of forest disturbance in tropical forests, including: development of new monitoring methods; development of new assessment methods; and assessment of the performance and operational readiness of existing methods. Current methods for accuracy assessment of remote sensing products do not address the priority of near real-time monitoring of detecting disturbance events as early as possible. I introduce a new assessment framework for near real-time products that focuses on the timing and the minimum detectable size of disturbance events. The new framework reveals the relationship between change detection accuracy and the time needed to identify events. In regions that are frequently cloudy, near real-time monitoring using data from a single sensor is difficult. This study extends the work by Xin et al. (2013) and develops a new time series method (Fusion2) based on fusion of Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) data. Results of three test sites in the Amazon Basin show that Fusion2 can detect 44.4% of the forest disturbance within 13 clear observations (82 days) after the initial disturbance. The smallest event detected by Fusion2 is 6.5 ha. Also, Fusion2 detects disturbance faster and has less commission error than more conventional methods. In a comparison of coarse resolution sensors, MODIS Terra and Aqua combined provides faster and more accurate detection of disturbance events than VIIRS (Visible Infrared Imaging Radiometer Suite) and MODIS single sensor data. The performance of near real-time monitoring using VIIRS is slightly worse than MODIS Terra but significantly better than MODIS Aqua. New monitoring methods developed in this dissertation provide forest protection organizations the capacity to monitor illegal logging events promptly. In the future, combining two Landsat and two Sentinel-2 satellites will provide global coverage at 30 m resolution every 4 days, and routine monitoring may be possible at high resolution. The methods and assessment framework developed in this dissertation are adaptable to newly available datasets.
NASA Astrophysics Data System (ADS)
Meyer, F. J.; McAlpin, D. B.; Gong, W.; Ajadi, O.; Arko, S.; Webley, P. W.; Dehn, J.
2015-02-01
Remote sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and its high performance in monitoring of change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to: (1) the high costs associated with radar data; (2) traditionally slow data processing and delivery procedures; and (3) the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of these limitations and allow for a meaningful integration of radar data into operational volcano monitoring decision support systems. Specifically, we present fast data access procedures as well as new approaches to multi-track processing that improve near real-time data access and temporal sampling of volcanic systems with SAR data. We introduce phase-based (coherent) and amplitude-based (incoherent) change detection procedures that are able to extract dense time series of hazard information from these data. For a demonstration, we present an integration of our processing system with an operational volcano monitoring system that was developed for use by the Alaska Volcano Observatory (AVO). Through an application to a historic eruption, we show that the integration of SAR into systems such as AVO can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.
Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Ken Brewer; Evan Brooks; Noel Gorelick; Mathew Gregory; Alexander Hernandez; Chengquan Huang; Joseph Hughes; Robert Kennedy; Thomas Loveland; Kevin Megown; Gretchen Moisen; Todd Schroeder; Brian Schwind; Stephen Stehman; Daniel Steinwand; James Vogelmann; Curtis Woodcock; Limin Yang; Zhe Zhu
2015-01-01
Forest change information is critical in forest planning, ecosystem modeling, and in updating forest condition maps. The Landsat satellite platform has provided consistent observations of the worldâs ecosystems since 1972. A number of innovative change detection algorithms have been developed to use the Landsat archive to identify and characterize forest change. The...
Monitoring crop and vegetation condition using the fused dense time-series landsat-like imagery
USDA-ARS?s Scientific Manuscript database
Since the launch of the first Landsat satellite in the early 1970s, Landsat has been widely used in many applications such as land cover and land use change monitoring, crop yield estimation, forest fire detection, and global ecosystem carbon cycle studies. Medium resolution sensors like Landsat hav...
Mary M. Conner; John J. Keane; Claire V. Gallagher; Thomas E. Munton; Paula A. Shaklee
2016-01-01
Monitoring studies often use marked animals to estimate population abundance at small spatial scales. However, at smaller scales, occupancy sampling, which uses detection/nondetection data, may be useful where sites are approximately territories, and occupancy dynamics should be strongly correlated with population dynamics. Occupancy monitoring has advantages...
Uav-Based 3d Urban Environment Monitoring
NASA Astrophysics Data System (ADS)
Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng
2018-04-01
Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.
Noninvasive valve monitor using constant magnetic and/or DC electromagnetic field
Casada, D.A.; Haynes, H.D.
1993-08-17
One or more sources of steady magnetic field are carefully located on the outside of a valve body. The constant magnetic field is transmitted into the valve body and valve internals. A magnetic field detector carefully located on the outside of the valve body detects the intensity of the magnetic field at its location. As the position of a valve internal part is changed, there is an alteration in the magnetic field in the valve, and a consequent change in the detected magnetic field. Changes in the detected signal provide an indication of the position and motion of the valve internals.
Noninvasive valve monitor using constant magnetic and/or DC electromagnetic field
Casada, Donald A.; Haynes, Howard D.
1993-01-01
One or more sources of steady magnetic field are carefully located on the outside of a valve body. The constant magnetic field is transmitted into the valve body and valve internals. A magnetic field detector carefully located on the outside of the valve body detects the intensity of the magnetic field at its location. As the position of a valve internal part is changed, there is an alteration in the magnetic field in the valve, and a consequent change in the detected magnetic field. Changes in the detected signal provide an indication of the position and motion of the valve internals.
16S rRNA beacons for bacterial monitoring during human space missions.
Larios-Sanz, Maia; Kourentzi, Katerina D; Warmflash, David; Jones, Jeffrey; Pierson, Duane L; Willson, Richard C; Fox, George E
2007-04-01
Microorganisms are unavoidable in space environments and their presence has, at times, been a source of problems. Concerns about disease during human space missions are particularly important considering the significant changes the immune system incurs during spaceflight and the history of microbial contamination aboard the Mir space station. Additionally, these contaminants may have adverse effects on instrumentation and life-support systems. A sensitive, highly specific system to detect, characterize, and monitor these microbial populations is essential. Herein we describe a monitoring approach that uses 16S rRNA targeted molecular beacons to successfully detect several specific bacterial groupings. This methodology will greatly simplify in-flight monitoring by minimizing sample handling and processing. We also address and provide solutions to target accessibility problems encountered in hybridizations that target 16S rRNA.
Bruce, Michael R [Austin, TX; Bruce, Victoria J [Austin, TX; Ring, Rosalinda M [Austin, TX; Cole, Edward Jr I [Albuquerque, NM; Hawkins, Charles F [Albuquerque, NM; Tangyungong, Paiboon [Albuquerque, NM
2006-06-13
According to an example embodiment of the present invention a semiconductor die having a resistive electrical connection is analyzed. Heat is directed to the die as the die is undergoing a state-changing operation to cause a failure due to suspect circuitry. The die is monitored, and a circuit path that electrically changes in response to the heat is detected and used to detect that a particular portion therein of the circuit is resistive. In this manner, the detection and localization of a semiconductor die defect that includes a resistive portion of a circuit path is enhanced.
Sentinel-1 Contribution to Monitoring Maritime Activity in the Arctic
NASA Astrophysics Data System (ADS)
Santamaria, Carlos; Greidanus, Harm; Fournier, Melanie; Eriksen, Torkild; Vespe, Michele; Alvarez, Marlene; Arguedas, Virginia Fernandez; Delaney, Conor; Argentieri, Pietro
2016-08-01
This paper presents results on the use of Sentinel-1 combined with satellite AIS to monitor maritime activity in the Arctic. Such activities are expected to increase, even if not uniformly across the Arctic, as the ice cover in the region retreats due to changes in climate. The objectives of monitoring efforts in the region can vary from country to country, but are generally related to increasing awareness on non- cooperative, small and cruise ships, fisheries, safety at sea, and Search and Rescue. A ship monitoring study has been conducted, involving more than 2,000 Sentinel-1 images acquired during one year in the central Arctic, where the ship densities are high. The main challenges to SAR-based monitoring in this area are described, solutions for some of them are proposed, and analyses of the results are shown. With the high detection thresholds needed to prevent false alarms from sea ice, 16% of the ships detected overall in the Sentinel-1 images have not been correlated to AIS- transmitting ships, and 48% of the AIS-transmitting ships are not correlated to ships detected in the images.
Supporting dynamic change detection: using the right tool for the task.
Vallières, Benoît R; Hodgetts, Helen M; Vachon, François; Tremblay, Sébastien
2016-01-01
Detecting task-relevant changes in a visual scene is necessary for successfully monitoring and managing dynamic command and control situations. Change blindness-the failure to notice visual changes-is an important source of human error. Change History EXplicit (CHEX) is a tool developed to aid change detection and maintain situation awareness; and in the current study we test the generality of its ability to facilitate the detection of changes when this subtask is embedded within a broader dynamic decision-making task. A multitasking air-warfare simulation required participants to perform radar-based subtasks, for which change detection was a necessary aspect of the higher-order goal of protecting one's own ship. In this task, however, CHEX rendered the operator even more vulnerable to attentional failures in change detection and increased perceived workload. Such support was only effective when participants performed a change detection task without concurrent subtasks. Results are interpreted in terms of the NSEEV model of attention behavior (Steelman, McCarley, & Wickens, Hum. Factors 53:142-153, 2011; J. Exp. Psychol. Appl. 19:403-419, 2013), and suggest that decision aids for use in multitasking contexts must be designed to fit within the available workload capacity of the user so that they may truly augment cognition.
Puschmann, Sebastian; Weerda, Riklef; Klump, Georg; Thiel, Christiane M
2013-05-01
Psychophysical experiments show that auditory change detection can be disturbed in situations in which listeners have to monitor complex auditory input. We made use of this change deafness effect to segregate the neural correlates of physical change in auditory input from brain responses related to conscious change perception in an fMRI experiment. Participants listened to two successively presented complex auditory scenes, which consisted of six auditory streams, and had to decide whether scenes were identical or whether the frequency of one stream was changed between presentations. Our results show that physical changes in auditory input, independent of successful change detection, are represented at the level of auditory cortex. Activations related to conscious change perception, independent of physical change, were found in the insula and the ACC. Moreover, our data provide evidence for significant effective connectivity between auditory cortex and the insula in the case of correctly detected auditory changes, but not for missed changes. This underlines the importance of the insula/anterior cingulate network for conscious change detection.
Oscillatory hydraulic testing as a strategy for NAPL source zone monitoring: Laboratory experiments
NASA Astrophysics Data System (ADS)
Zhou, YaoQuan; Cardiff, Michael
2017-05-01
Non-aqueous phase liquids (NAPLs) have a complex mode of transport in heterogeneous aquifers, which can result in pools and lenses of NAPLs (the "source zone") that are difficult to detect and can cause long-term contamination via slow dissolution into groundwater (the "dissolved plume"). Characterizing the extent and evolution of NAPL contamination within the source zone is a useful strategy for designing and adapting appropriate remedial actions at many contaminated sites. As a NAPL flows into a given aquifer volume, the effective hydraulic conductivity (K) and specific storage (Ss) of the volume changes associated with the viscosity and compressibility of the impinging fluid, meaning that NAPL movement may be detectable with hydraulic testing. Recently, the use of oscillatory pumping tests - in which sinusoidal pumping variations are implemented and oscillatory pressure changes are detected at monitoring locations - has been suggested as a low-impact hydraulic testing strategy for characterizing aquifer properties (Cardiff et al., 2013; Zhou et al., 2016). Here, we investigate this strategy in an experimental laboratory sandbox where dyed vegetable oil is injected and allowed to migrate as a NAPL. Initial qualitative analyses demonstrate that measurable changes in pressure signal amplitude and phase provide clear evidence for NAPL plume emplacement and migration. Using the approach developed in Zhou et al. (2016), we then apply tomographic analyses to estimate the location of effective K changes (representing fluid changes) and their movement throughout time. This approach provides a method for monitoring ongoing NAPL movement without net extraction or injection of fluid, making it advantageous in field remediation applications.
Quist, M.C.; Gerow, K.G.; Bower, M.R.; Hubert, W.A.
2006-01-01
Native fishes of the upper Colorado River basin (UCRB) have declined in distribution and abundance due to habitat degradation and interactions with normative fishes. Consequently, monitoring populations of both native and nonnative fishes is important for conservation of native species. We used data collected from Muddy Creek, Wyoming (2003-2004), to compare sample size estimates using a random and a fixed-site sampling design to monitor changes in catch per unit effort (CPUE) of native bluehead suckers Catostomus discobolus, flannelmouth suckers C. latipinnis, roundtail chub Gila robusta, and speckled dace Rhinichthys osculus, as well as nonnative creek chub Semotilus atromaculatus and white suckers C. commersonii. When one-pass backpack electrofishing was used, detection of 10% or 25% changes in CPUE (fish/100 m) at 60% statistical power required 50-1,000 randomly sampled reaches among species regardless of sampling design. However, use of a fixed-site sampling design with 25-50 reaches greatly enhanced the ability to detect changes in CPUE. The addition of seining did not appreciably reduce required effort. When detection of 25-50% changes in CPUE of native and nonnative fishes is acceptable, we recommend establishment of 25-50 fixed reaches sampled by one-pass electrofishing in Muddy Creek. Because Muddy Creek has habitat and fish assemblages characteristic of other headwater streams in the UCRB, our results are likely to apply to many other streams in the basin. ?? Copyright by the American Fisheries Society 2006.
Development of an Indicator to Monitor Mediterranean Wetlands
Sanchez, Antonio; Abdul Malak, Dania; Guelmami, Anis; Perennou, Christian
2015-01-01
Wetlands are sensitive ecosystems that are increasingly subjected to threats from anthropogenic factors. In the last decades, coastal Mediterranean wetlands have been suffering considerable pressures from land use change, intensification of urban growth, increasing tourism infrastructure and intensification of agricultural practices. Remote sensing (RS) and Geographic Information Systems (GIS) techniques are efficient tools that can support monitoring Mediterranean coastal wetlands on large scales and over long periods of time. The study aims at developing a wetland indicator to support monitoring Mediterranean coastal wetlands using these techniques. The indicator makes use of multi-temporal Landsat images, land use reference layers, a 50m numerical model of the territory (NMT) and Corine Land Cover (CLC) for the identification and mapping of wetlands. The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date. A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability. The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas. The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered. PMID:25826210
Development of an indicator to monitor mediterranean wetlands.
Sanchez, Antonio; Abdul Malak, Dania; Guelmami, Anis; Perennou, Christian
2015-01-01
Wetlands are sensitive ecosystems that are increasingly subjected to threats from anthropogenic factors. In the last decades, coastal Mediterranean wetlands have been suffering considerable pressures from land use change, intensification of urban growth, increasing tourism infrastructure and intensification of agricultural practices. Remote sensing (RS) and Geographic Information Systems (GIS) techniques are efficient tools that can support monitoring Mediterranean coastal wetlands on large scales and over long periods of time. The study aims at developing a wetland indicator to support monitoring Mediterranean coastal wetlands using these techniques. The indicator makes use of multi-temporal Landsat images, land use reference layers, a 50m numerical model of the territory (NMT) and Corine Land Cover (CLC) for the identification and mapping of wetlands. The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date. A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability. The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas. The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered.
Unobtrusive measurement of daily computer use to detect mild cognitive impairment.
Kaye, Jeffrey; Mattek, Nora; Dodge, Hiroko H; Campbell, Ian; Hayes, Tamara; Austin, Daniel; Hatt, William; Wild, Katherine; Jimison, Holly; Pavel, Michael
2014-01-01
Mild disturbances of higher order activities of daily living are present in people diagnosed with mild cognitive impairment (MCI). These deficits may be difficult to detect among those still living independently. Unobtrusive continuous assessment of a complex activity such as home computer use may detect mild functional changes and identify MCI. We sought to determine whether long-term changes in remotely monitored computer use differ in persons with MCI in comparison with cognitively intact volunteers. Participants enrolled in a longitudinal cohort study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors were assessed for computer use (number of days with use, mean daily use, and coefficient of variation of use) measured by remotely monitoring computer session start and end times. More than 230,000 computer sessions from 113 computer users (mean age, 85 years; 38 with MCI) were acquired during a mean of 36 months. In mixed-effects models, there was no difference in computer use at baseline between MCI and intact participants controlling for age, sex, education, race, and computer experience. However, over time, between MCI and intact participants, there was a significant decrease in number of days with use (P = .01), mean daily use (∼1% greater decrease/month; P = .009), and an increase in day-to-day use variability (P = .002). Computer use change can be monitored unobtrusively and indicates individuals with MCI. With 79% of those 55 to 64 years old now online, this may be an ecologically valid and efficient approach to track subtle, clinically meaningful change with aging. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Scott, R.; Entwistle, N. S.
2017-12-01
Gravel bed rivers and their associated wider systems present an ideal subject for development and improvement of rapid monitoring tools, with features dynamic enough to evolve within relatively short-term timescales. For detecting and quantifying topographical evolution, UAV based remote sensing has manifested as a reliable, low cost, and accurate means of topographic data collection. Here we present some validated methodologies for detection of geomorphic change at resolutions down to 0.05 m, building on the work of Wheaton et al. (2009) and Milan et al. (2007), to generate mesh based and pointcloud comparison data to produce a reliable picture of topographic evolution. Results are presented for the River Glen, Northumberland, UK. Recent channel avulsion and floodplain interaction, resulting in damage to flood defence structures make this site a particularly suitable case for application of geomorphic change detection methods, with the UAV platform at its centre. We compare multi-temporal, high-resolution point clouds derived from SfM processing, cross referenced with aerial LiDAR data, over a 1.5 km reach of the watercourse. Changes detected included bank erosion, bar and splay deposition, vegetation stripping and incipient channel avulsion. Utilisation of the topographic data for numerical modelling, carried out using CAESAR-Lisflood predicted the avulsion of the main channel, resulting in erosion of and potentially complete circumvention of original channel and flood levees. A subsequent UAV survey highlighted topographic change and reconfiguration of the local sedimentary conveyor as we predicted with preliminary modelling. The combined monitoring and modelling approach has allowed probable future geomorphic configurations to be predicted permitting more informed implementation of channel and floodplain management strategies.
Subsurface event detection and classification using Wireless Signal Networks.
Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T
2012-11-05
Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.
Subsurface Event Detection and Classification Using Wireless Signal Networks
Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.
2012-01-01
Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191
Vibration-based monitoring to detect mass changes in satellites
NASA Astrophysics Data System (ADS)
Maji, Arup; Vernon, Breck
2012-04-01
Vibration-based structural health monitoring could be a useful form of determining the health and safety of space structures. A particular concern is the possibility of a foreign object that attaches itself to a satellite in orbit for adverse reasons. A frequency response analysis was used to determine the changes in mass and moment of inertia of the space structure based on a change in the natural frequencies of the structure or components of the structure. Feasibility studies were first conducted on a 7 in x 19 in aluminum plate with various boundary conditions. Effect of environmental conditions on the frequency response was determined. The baseline frequency response for the plate was then used as the basis for detection of the addition, and possibly the location, of added masses on the plate. The test results were compared to both analytical solutions and finite element models created in SAP2000. The testing was subsequently expanded to aluminum alloy satellite panels and a mock satellite with dummy payloads. Statistical analysis was conducted on variations of frequency due to added mass and thermal changes to determine the threshold of added mass that can be detected.
Tracing Acetylene Dissolved in Transformer Oil by Tunable Diode Laser Absorption Spectrum.
Ma, Guo-Ming; Zhao, Shu-Jing; Jiang, Jun; Song, Hong-Tu; Li, Cheng-Rong; Luo, Ying-Ting; Wu, Hao
2017-11-02
Dissolved gas analysis (DGA) is widely used in monitoring and diagnosing of power transformer, since the insulation material in the power transformer decomposes gases under abnormal operation condition. Among the gases, acetylene, as a symbol of low energy spark discharge and high energy electrical faults (arc discharge) of power transformer, is an important monitoring parameter. The current gas detection method used by the online DGA equipment suffers from problems such as cross sensitivity, electromagnetic compatibility and reliability. In this paper, an optical gas detection system based on TDLAS technology is proposed to detect acetylene dissolved in transformer oil. We selected a 1530.370 nm laser in the near infrared wavelength range to correspond to the absorption peak of acetylene, while using the wavelength modulation strategy and Herriott cell to improve the detection precision. Results show that the limit of detection reaches 0.49 ppm. The detection system responds quickly to changes of gas concentration and is easily to maintenance while has no electromagnetic interference, cross-sensitivity, or carrier gas. In addition, a complete detection process of the system takes only 8 minutes, implying a practical prospect of online monitoring technology.
Nanoplasmonic molecular ruler for nuclease activity and DNA footprinting
Chen, Fanqing Frank; Liu, Gang L; Lee, Luke P
2013-10-29
This invention provides a nanoplasmonic molecular ruler, which can perform label-free and real-time monitoring of nucleic acid (e.g., DNA) length changes and perform nucleic acid footprinting. In various embodiments the ruler comprises a nucleic acid attached to a nanoparticle, such that changes in the nucleic acid length are detectable using surface plasmon resonance. The nanoplasmonic ruler provides a fast and convenient platform for mapping nucleic acid-protein interactions, for nuclease activity monitoring, and for other footprinting related methods.
Liu, David; Jenkins, Simon A; Sanderson, Penelope M; Watson, Marcus O; Leane, Terrence; Kruys, Amanda; Russell, W John
2009-10-01
Head-mounted displays (HMDs) can help anesthesiologists with intraoperative monitoring by keeping patients' vital signs within view at all times, even while the anesthesiologist is busy performing procedures or unable to see the monitor. The anesthesia literature suggests that there are advantages of HMD use, but research into head-up displays in the cockpit suggests that HMDs may exacerbate inattentional blindness (a tendency for users to miss unexpected but salient events in the field of view) and may introduce perceptual issues relating to focal depth. We investigated these issues in two simulator-based experiments. Experiment 1 investigated whether wearing a HMD would affect how quickly anesthesiologists detect events, and whether the focus setting of the HMD (near or far) makes any difference. Twelve anesthesiologists provided anesthesia in three naturalistic scenarios within a simulated operating theater environment. There were 24 different events that occurred either on the patient monitor or in the operating room. Experiment 2 investigated whether anesthesiologists physically constrained by performing a procedure would detect patient-related events faster with a HMD than without. Twelve anesthesiologists performed a complex simulated clinical task on a part-task endoscopic dexterity trainer while monitoring the simulated patient's vital signs. All participants experienced four different events within each of two scenarios. Experiment 1 showed that neither wearing the HMD nor adjusting the focus setting reduced participants' ability to detect events (the number of events detected and time to detect events). In general, participants spent more time looking toward the patient and less time toward the anesthesia machine when they wore the HMD than when they used standard monitoring alone. Participants reported that they preferred the near focus setting. Experiment 2 showed that participants detected two of four events faster with the HMD, but one event more slowly with the HMD. Participants turned to look toward the anesthesia machine significantly less often when using the HMD. When using the HMD, participants reported that they were less busy, monitoring was easier, and they believed they were faster at detecting abnormal changes. The HMD helped anesthesiologists detect events when physically constrained, but not when physically unconstrained. Although there was no conclusive evidence of worsened inattentional blindness, found in aviation, the perceptual properties of the HMD display appear to influence whether events are detected. Anesthesiologists wearing HMDs should self-adjust the focus to minimize eyestrain and should be aware that some changes may not attract their attention. Future areas of research include developing principles for the design of HMDs, evaluating other types of HMDs, and evaluating the HMD in clinical contexts.
Analysis and Implementation of Methodologies for the Monitoring of Changes in Eye Fundus Images
NASA Astrophysics Data System (ADS)
Gelroth, A.; Rodríguez, D.; Salvatelli, A.; Drozdowicz, B.; Bizai, G.
2011-12-01
We present a support system for changes detection in fundus images of the same patient taken at different time intervals. This process is useful for monitoring pathologies lasting for long periods of time, as are usually the ophthalmologic. We propose a flow of preprocessing, processing and postprocessing applied to a set of images selected from a public database, presenting pathological advances. A test interface was developed designed to select the images to be compared in order to apply the different methods developed and to display the results. We measure the system performance in terms of sensitivity, specificity and computation times. We have obtained good results, higher than 84% for the first two parameters and processing times lower than 3 seconds for 512x512 pixel images. For the specific case of detection of changes associated with bleeding, the system responds with sensitivity and specificity over 98%.
NASA Astrophysics Data System (ADS)
Neyer, F.; Nocerino, E.; Gruen, A.
2018-05-01
Creating 3-dimensional (3D) models of underwater scenes has become a common approach for monitoring coral reef changes and its structural complexity. Also in underwater archeology, 3D models are often created using underwater optical imagery. In this paper, we focus on the aspect of detecting small changes in the coral reef using a multi-temporal photogrammetric modelling approach, which requires a high quality control network. We show that the quality of a good geodetic network limits the direct change detection, i.e., without any further registration process. As the photogrammetric accuracy is expected to exceed the geodetic network accuracy by at least one order of magnitude, we suggest to do a fine registration based on a number of signalized points. This work is part of the Moorea Island Digital Ecosystem Avatar (IDEA) project that has been initiated in 2013 by a group of international researchers (https://mooreaidea.ethz.ch/).
NASA Astrophysics Data System (ADS)
Lee, Songhyun; Jeong, Hyeryun; Seong, Myeongsu; Kim, Jae Gwan
2017-12-01
Breast cancer is one of the most common cancers in females. To monitor chemotherapeutic efficacy for breast cancer, medical imaging systems such as x-ray mammography, computed tomography, magnetic resonance imaging, and ultrasound imaging have been used. Currently, it can take up to 3 to 6 weeks to see the tumor response from chemotherapy by monitoring tumor volume changes. We used near-infrared spectroscopy (NIRS) to predict breast cancer treatment efficacy earlier than tumor volume changes by monitoring tumor vascular reactivity during inhalational gas interventions. The results show that the amplitude of oxy-hemoglobin changes (vascular reactivity) during hyperoxic gas inhalation is well correlated with tumor growth and responded one day earlier than tumor volume changes after chemotherapy. These results may imply that NIRS with respiratory challenges can be useful in early detection of tumor and in the prediction of tumor response to chemotherapy.
NASA Astrophysics Data System (ADS)
Gao, Feng; Dong, Junyu; Li, Bo; Xu, Qizhi; Xie, Cui
2016-10-01
Change detection is of high practical value to hazard assessment, crop growth monitoring, and urban sprawl detection. A synthetic aperture radar (SAR) image is the ideal information source for performing change detection since it is independent of atmospheric and sunlight conditions. Existing SAR image change detection methods usually generate a difference image (DI) first and use clustering methods to classify the pixels of DI into changed class and unchanged class. Some useful information may get lost in the DI generation process. This paper proposed an SAR image change detection method based on neighborhood-based ratio (NR) and extreme learning machine (ELM). NR operator is utilized for obtaining some interested pixels that have high probability of being changed or unchanged. Then, image patches centered at these pixels are generated, and ELM is employed to train a model by using these patches. Finally, pixels in both original SAR images are classified by the pretrained ELM model. The preclassification result and the ELM classification result are combined to form the final change map. The experimental results obtained on three real SAR image datasets and one simulated dataset show that the proposed method is robust to speckle noise and is effective to detect change information among multitemporal SAR images.
Vogelmann, James; Gallant, Alisa L.; Shi, Hua; Zhu, Zhe
2016-01-01
There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all available clear Landsat 5–8 observations with the new Continuous Change Detection and Classification (CCDC) algorithm was very effective for illuminating vegetation trends. There are a number of potential challenges for assessing gradual changes, including atmospheric impacts, algorithm development and visualization of the changes. One of the biggest challenges for studying gradual change will be the lack of appropriate data for validating results and products.
Lomasney, Anna R; Yi, Lian; Roper, Michael G
2013-08-20
A method was developed that allowed simultaneous monitoring of the acute secretory dynamics of insulin and islet amyloid polypeptide (IAPP) from islets of Langerhans using a microfluidic system with two-color detection. A flow-switching feature enabled changes in the perfusion media within 5 s, allowing rapid exchange of the glucose concentrations delivered to groups of islets. The perfusate was continuously sampled by electroosmotic flow and mixed online with Cy5-labeled insulin, fluorescein isothiocyanate (FITC)-labeled IAPP, anti-insulin, and anti-IAPP antibodies in an 8.15 cm mixing channel maintained at 37 °C. The immunoassay mixture was injected for 0.3 s onto a 1.5 cm separation channel at 11.75 s intervals and immunoassay reagents detected using 488 and 635 nm lasers with two independent photomultiplier tubes for detection of the FITC and Cy5 signal. RSD of the bound-to-free immunoassay ratios ranged from 2 to 7% with LODs of 20 nM for insulin and 1 nM for IAPP. Simultaneous secretion profiles of the two peptides were monitored from groups of 4-10 islets during multiple step changes in glucose concentration. Insulin and IAPP were secreted in an approximately 10:1 ratio and displayed similar responses to step changes from 3 to 11 or 20 mM glucose. The ability to monitor the secretory dynamics of multiple peptides from islets of Langerhans in a highly automated fashion is expected to be a useful tool for investigating hormonal regulation of glucose homeostasis.
Geographic applications of ERTS-1 data to landscape change
NASA Technical Reports Server (NTRS)
Rehder, J. B.
1973-01-01
The analysis of landscape change requires large area coverage on a periodic basis in order to analyze aggregate changes over an extended period of time. To date, only the ERTS program can provide this capability. Three avenues of experimentation and analysis are being used in the investigation: (1) a multi-scale sampling procedure utilizing aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures, comparisons and ultimately for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions.
The use of UAVs for monitoring land degradation
NASA Astrophysics Data System (ADS)
Themistocleous, Kyriacos
2017-10-01
Land degradation is one of the causes of desertification of drylands in the Mediterranean. UAVs can be used to monitor and document the various variables that cause desertification in drylands, including overgrazing, aridity, vegetation loss, etc. This paper examines the use of UAVs and accompanying sensors to monitor overgrazing, vegetation stress and aridity in the study area. UAV images can be used to generate digital elevation models (DEMs) to examine the changes in microtopography as well as ortho-photos were used to detect changes in vegetation patterns. The combined data of the digital elevation models and the orthophotos can be used to identify the mechanisms for desertification in the study area.
NASA Astrophysics Data System (ADS)
Martin, Michael C.; Holman, Hoi-Ying N.; Blakely, Eleanor A.; Goth-Goldstein, Regine; McKinney, Wayne R.
2000-03-01
Vibrational spectroscopy, when combined with synchrotron radiation-based (SR) microscopy, is a powerful new analytical tool with high spatial resolution for detecting biochemical changes in individual living cells. In contrast to other microscopy methods that require fixing, drying, staining or labeling, SR FTIR microscopy probes intact living cells providing a composite view of all of the molecular responses and the ability to monitor the responses over time in the same cell. Observed spectral changes include all types of lesions induced in that cell as well as cellular responses to external and internal stresses. These spectral changes combined with other analytical tools may provide a fundamental understanding of the key molecular mechanisms induced in response to stresses created by low-doses of radiation and chemicals. In this study we used high spatial-resolution SR FTIR vibrational spectromicroscopy at ALS Beamline 1.4.3 as a sensitive analytical tool to detect chemical- and radiation-induced changes in individual human cells. Our preliminary spectral measurements indicate that this technique is sensitive enough to detect changes in nucleic acids and proteins of cells treated with environmentally relevant concentrations of oxidative stresses: bleomycin, hydrogen peroxide, and X-rays. We observe spectral changes that are unique to each exogenous stressor. This technique has the potential to distinguish changes from exogenous or endogenous oxidative processes. Future development of this technique will allow rapid monitoring of cellular processes such as drug metabolism, early detection of disease, bio-compatibility of implant materials, cellular repair mechanisms, self assembly of cellular apparatus, cell differentiation and fetal development.
Li, Xuejian; Wang, Youqing
2016-12-01
Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.
NASA Astrophysics Data System (ADS)
Archer, Reginald S.
This research focuses on measuring and monitoring long term recovery progress from the impacts of Hurricane Katrina on New Orleans, LA. Remote sensing has frequently been used for emergency response and damage assessment after natural disasters. However, techniques for analysis of long term disaster recovery using remote sensing have not been widely explored. With increased availability and lower costs, remote sensing offers an objective perspective, systematic and repeatable analysis, and provides a substitute to multiple site visits. In addition, remote sensing allows access to large geographical areas and areas where ground access may be disrupted, restricted or denied. This dissertation addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators. Maximum likelihood classification and post-classification change detection were applied to multi-temporal high resolution aerial images to quantitatively measure the progress of recovery. Images were classified to automatically identify disaster recovery indicators and exploit the indicators that are visible within each image. The spectral analysis demonstrated that employing maximum likelihood classification to high resolution true color aerial images performed adequately and provided a good indication of spectral pattern recognition, despite the limited spectral information. Applying the change detection to the classified images was effective for determining the temporal trajectory of indicators categorized as blue tarps, FEMA trailers, houses, vegetation, bare earth and pavement. The results of the post classification change detection revealed a dominant change trajectory from bluetarp to house, as damaged houses became permanently repaired. Specifically, the level of activity of blue tarps, housing, vegetation, FEMA trailers (temporary housing) pavement and bare earth were derived from aerial image processing to measure and monitor the progress of recovery. Trajectories of recovery for each individual indicator were examined to provide a better understanding of activity during reconstruction. A collection of spatial metrics was explored in order to identify spatial patterns and characterize classes in terms of patches of pixels. One of the key findings of the spatial analysis is that patch shapes were more complex in the presence of debris and damaged or destroyed buildings. The combination of spectral, temporal, and spatial analysis provided a satisfactory, though limited, solution to the question of whether remote sensing alone, can be used to quantitatively assess and monitor the progress of long term recovery following a major disaster. The research described in this dissertation provided a detailed illustration of the level of activity experienced by different recovery indicators during the long term recovery process. It also addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators identified from classified high resolution true color aerial imagery. The results produced in this research demonstrate that the observed trajectories for actual indicators of recovery indicate different levels of recovery activity even within the same community. The level of activity of the long term reconstruction phase observed in the Kates model is not consistent with the level of activity of key recovery indicators in the Lower 9th Ward during the same period. Used in the proper context, these methods and results provide decision making information for determining resources. KEYWORDS: Change detection, classification, Katrina, New Orleans, remote sensing, disaster recovery, spatial metrics
Klimstra, J.D.; O'Connell, A.F.; Pistrang, M.J.; Lewis, L.M.; Herrig, J.A.; Sauer, J.R.
2007-01-01
Science-based monitoring of biological resources is important for a greater understanding of ecological systems and for assessment of the target population using theoretic-based management approaches. When selecting variables to monitor, managers first need to carefully consider their objectives, the geographic and temporal scale at which they will operate, and the effort needed to implement the program. Generally, monitoring can be divided into two categories: index and inferential. Although index monitoring is usually easier to implement, analysis of index data requires strong assumptions about consistency in detection rates over time and space, and parameters are often biasednot accounting for detectability and spatial variation. In most cases, individuals are not always available for detection during sampling periods, and the entire area of interest cannot be sampled. Conversely, inferential monitoring is more rigorous because it is based on nearly unbiased estimators of spatial distribution. Thus, we recommend that detectability and spatial variation be considered for all monitoring programs that intend to make inferences about the target population or the area of interest. Application of these techniques is especially important for the monitoring of Threatened and Endangered (T&E) species because it is critical to determine if population size is increasing or decreasing with some level of certainty. Use of estimation-based methods and probability sampling will reduce many of the biases inherently associated with index data and provide meaningful information with respect to changes that occur in target populations. We incorporated inferential monitoring into protocols for T&E species spanning a wide range of taxa on the Cherokee National Forest in the Southern Appalachian Mountains. We review the various approaches employed for different taxa and discuss design issues, sampling strategies, data analysis, and the details of estimating detectability using site occupancy. These techniques provide a science-based approach for monitoring and can be of value to all resource managers responsible for management of T&E species.
[Schistosomiasis monitoring and its cost in population in Danyang City, 2010-2014].
Zhu, Tao; Jiang, Tao; Shi, Yu-kun; Wang, Juan
2015-12-01
To explore the monitoring method of the infection source of schistosomiasis in the population of the schistosomiasis transmission-interrupted area with Oncomelania hupensis snails. The changes of schistosomiasis among the population were investigated by using the active and passive monitoring methods in Danyang City from 2010 to 2014, and the cost-effectiveness of the two monitoring methods was evaluated. Totally 49,277 persons were detected for schistosomiasis by dipstick dye immunoassay (DDIA) from 2010 to 2014 and 608 cases were positive, and the positive rate was 1.23%. There were no positive persons by etiology detections. The positive rates of active and passive monitoring methods were 1.61% and 1.13%, respectively and there was a significant difference between them (χ² = 15.982, P < 0.05). The average cost per positive case of the active monitoring was higher than that of the passive monitoring without considering the costs of the mobilization and labor. In the schistosomiasis transmission-interrupted area with snails, the active and passive monitoring methods need to be combined in the future.
Detection and monitoring of anaerobic rumen fungi using an ARISA method.
Denman, S E; Nicholson, M J; Brookman, J L; Theodorou, M K; McSweeney, C S
2008-12-01
To develop an automated ribosomal intergenic spacer region analysis (ARISA) method for the detection of anaerobic rumen fungi and also to demonstrate utility of the technique to monitor colonization and persistence of fungi, and diet-induced changes in community structure. The method could discriminate between three genera of anaerobic rumen fungal isolates, representing Orpinomyces, Piromyces and Neocallimastix species. Changes in anaerobic fungal composition were observed between animals fed a high-fibre diet compared with a grain-based diet. ARISA analysis of rumen samples from animals on grain showed a decrease in fungal diversity with a dominance of Orpinomyces and Piromyces spp. Clustering analysis of ARISA profile patterns grouped animals based on diet. A single strain of Orpinomyces was dosed into a cow and was detectable within the rumen fungal population for several weeks afterwards. The ARISA technique was capable of discriminating between pure cultures at the genus level. Diet composition has a significant influence on the diversity of anaerobic fungi in the rumen and the method can be used to monitor introduced strains. Through the use of ARISA analysis, a better understanding of the effect of diets on rumen anaerobic fungi populations is provided.
Modeling Patterns of Activities using Activity Curves
Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen
2016-01-01
Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve, which represents an abstraction of an individual’s normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics. PMID:27346990
Modeling Patterns of Activities using Activity Curves.
Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen
2016-06-01
Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.
Early warning by near-real time disturbance monitoring (Invited)
NASA Astrophysics Data System (ADS)
Verbesselt, J.; Zeileis, A.; Herold, M.
2013-12-01
Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a multi-purpose time-series-based disturbance detection approach that identifies and models stable historical variation to enable change detection within newly acquired data. Satellite image time series of vegetation greenness provide a global record of terrestrial vegetation productivity over the past decades. Here, we assess and demonstrate the method by applying it to (1) real-world satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought-related vegetation disturbances (2) landsat image time series to detect forest disturbances. First, results illustrate that disturbances are successfully detected in near real-time while being robust to seasonality and noise. Second, major drought-related disturbance corresponding with most drought-stressed regions in Somalia are detected from mid-2010 onwards. Third, the method can be applied to landsat image time series having a lower temporal data density. Furthermore the method can analyze in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds and does not require time series gap filling. While the data and methods used are appropriate for proof-of-concept development of global scale disturbance monitoring, specific applications (e.g., drought or deforestation monitoring) mandates integration within an operational monitoring framework. Furthermore, the real-time monitoring method is implemented in open-source environment and is freely available in the BFAST package for R software. Information illustrating how to apply the method on satellite image time series are available at http://bfast.R-Forge.R-project.org/ and the example section of the bfastmonitor() function within the BFAST package.
NASA Astrophysics Data System (ADS)
Gill, M.; Svoboda, M.
2012-12-01
Arctic ecosystems and the biodiversity they support are experiencing growing pressure from various stressors (e.g. development, climate change, contaminants, etc.) while established research and monitoring programs remain largely uncoordinated, lacking the ability to effectively monitor, understand and report on biodiversity trends at the circumpolar scale. The maintenance of healthy arctic ecosystems is a global imperative as the Arctic plays a critical role in the Earth's physical, chemical and biological balance. A coordinated and comprehensive effort for monitoring arctic ecosystems is needed to facilitate effective and timely conservation and adaptation actions. The Arctic's size and complexity represents a significant challenge towards detecting and attributing important biodiversity trends. This demands a scaled, pan-arctic, ecosystem-based approach that not only identifies trends in biodiversity, but also identifies underlying causes. It is critical that this information be made available to generate effective strategies for adapting to changes now taking place in the Arctic—a process that ultimately depends on rigorous, integrated, and efficient monitoring programs that have the power to detect change within a "management" time frame. To meet these challenges and in response to the Arctic Climate Impact Assessment's recommendation to expand and enhance arctic biodiversity monitoring, the Conservation of Arctic Flora and Fauna (CAFF) Working Group of the Arctic Council launched the Circumpolar Biodiversity Monitoring Program (CBMP). The CBMP is led by Environment Canada on behalf of Canada and the Arctic Council. The CBMP is working with over 60 global partners to expand, integrate and enhance existing arctic biodiversity research and monitoring efforts to facilitate more rapid detection, communication and response to significant trends and pressures. Towards this end, the CBMP has established three Expert Monitoring Groups representing major Arctic themes (Marine, Freshwater, and Terrestrial). Each group, representing a diversity of disciplines, is tasked with developing and implementing pan-arctic integrated biodiversity monitoring plans for the Arctic's ecosystems. To facilitate effective reporting and data management, the CBMP is developing a suite of indices and indicators and a web-based data portal that will be used to report on the current state of arctic biodiversity at various scales and levels of detail to suit a wide range of audiences (e.g. local Arctic communities, regional and national governments and the Convention on Biological Diversity). The current and planned CBMP biodiversity monitoring underpins these indicators and indices. The presentation will highlight the CBMP approach and provide some examples of how integrated monitoring, data management and reporting are leading to more informed decision-making.
Alien liquid detector and control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Potter, B.M.
An alien liquid detector employs a monitoring element and an energizing circuit for maintaining the temperature of the monitoring element substantially above ambient temperature. For this purpose an electronic circit controls a flow of heating current to the monitoring element. The presence of an alien liquid is detected by sensing a predetermined change in heating current flow to the monitoring element, e.g., to distinguish between water and oil. In preferred embodiments the monitoring element is a thermistor whose resistance is compared with a reference resistance and heating current through the thermistor is controlled in accordance with the difference. In onemore » embodiment a bridge circuit senses the resistance difference; the difference may be sensed by an operational amplifier arrangement. Features of the invention include positioning the monitoring element at the surface of water, slightly immersed, so that the power required to maintain the thermistor temperature substantially above ambient temperature serves to detect presence of oil pollution at the surface.« less
Design and analysis for detection monitoring of forest health
F. A. Roesch
1995-01-01
An analysis procedure is proposed for the sample design of the Forest Health Monitoring Program (FHM) in the United States. The procedure is intended to provide increased sensitivity to localized but potentially important changes in forest health by explicitly accounting for the spatial relationships between plots in the FHM design. After a series of median sweeps...
Risk analysis and detection of thrombosis by measurement of electrical resistivity of blood.
Sapkota, Achyut; Asakura, Yuta; Maruyama, Osamu; Kosaka, Ryo; Yamane, Takashi; Takei, Masahiro
2013-01-01
Monitoring of thrombogenic process is very important in ventricular assistance devices (VADs) used as temporary or permanent measures in patients with advanced heart failure. Currently, there is a lack of a system which can perform a real-time monitoring of thrombogenic activity. Electrical signals vary according to the change in concentration of coagulation factors as well as the distribution of blood cells, and thus have potential to detect the thrombogenic process in an early stage. In the present work, we have made an assessment of an instrumentation system exploiting the electrical properties of blood. The experiments were conducted using bovine blood. Electrical resistance tomography with eight-electrode sensor was used to monitor the spatio-temporal change in electrical resistivity of blood in thrombogenic and non-thrombogenic condition. Under non-thrombogenic condition, the resistivity was uniform across the cross-section and average resistivity monotonically decreased with time before remaining almost flat. In contrary, under thrombogenic condition, there was non-uniform distribution across the cross-section, and average resistivity fluctuated with time.
Non-invasive Continuous Monitoring of Cerebral Edema Using Portable Microwave Based System
NASA Astrophysics Data System (ADS)
Jiang, Yuhao; Zhao, Minji; Wang, Huiqian; Li, Guoquan
2018-01-01
A portable non-invasive head detecting system based on microwave technology was developed for evaluation of cerebral edema change inside human brain. Real-time monitoring of cerebral edema in the brain helps the clinician to assess medical condition and treatment. In this work, a microwave signal was transmitted and coupled into an open-end circular waveguide sensor, incident on a 3D printed head phantom, and reflected back to receiver. Theoretically, the operation of this instrument depends on the conductivity contrast between cerebral edema and healthy brain tissues. The efficacy of the proposed detecting system is verified using 3D printed anatomically and dielectrically realistic human head phantoms with simulated cerebral edema targets with different size. Changes in the amplitude of time domain result were shown to be induced by the expansion or decrease of the edema volume. The eventual goal of this proposed head evaluating system is use in the hospital as an effective real-time monitoring tool.
Helble, Tyler A; D'Spain, Gerald L; Campbell, Greg S; Hildebrand, John A
2013-11-01
This paper demonstrates the importance of accounting for environmental effects on passive underwater acoustic monitoring results. The situation considered is the reduction in shipping off the California coast between 2008-2010 due to the recession and environmental legislation. The resulting variations in ocean noise change the probability of detecting marine mammal vocalizations. An acoustic model was used to calculate the time-varying probability of detecting humpback whale vocalizations under best-guess environmental conditions and varying noise. The uncorrected call counts suggest a diel pattern and an increase in calling over a two-year period; the corrected call counts show minimal evidence of these features.
Harmsen, Bart J; Foster, Rebecca J; Sanchez, Emma; Gutierrez-González, Carmina E; Silver, Scott C; Ostro, Linde E T; Kelly, Marcella J; Kay, Elma; Quigley, Howard
2017-01-01
In this study, we estimate life history parameters and abundance for a protected jaguar population using camera-trap data from a 14-year monitoring program (2002-2015) in Belize, Central America. We investigated the dynamics of this jaguar population using 3,075 detection events of 105 individual adult jaguars. Using robust design open population models, we estimated apparent survival and temporary emigration and investigated individual heterogeneity in detection rates across years. Survival probability was high and constant among the years for both sexes (φ = 0.78), and the maximum (conservative) age recorded was 14 years. Temporary emigration rate for the population was random, but constant through time at 0.20 per year. Detection probability varied between sexes, and among years and individuals. Heterogeneity in detection took the form of a dichotomy for males: those with consistently high detection rates, and those with low, sporadic detection rates, suggesting a relatively stable population of 'residents' consistently present and a fluctuating layer of 'transients'. Female detection was always low and sporadic. On average, twice as many males than females were detected per survey, and individual detection rates were significantly higher for males. We attribute sex-based differences in detection to biases resulting from social variation in trail-walking behaviour. The number of individual females detected increased when the survey period was extended from 3 months to a full year. Due to the low detection rates of females and the variable 'transient' male subpopulation, annual abundance estimates based on 3-month surveys had low precision. To estimate survival and monitor population changes in elusive, wide-ranging, low-density species, we recommend repeated surveys over multiple years; and suggest that continuous monitoring over multiple years yields even further insight into population dynamics of elusive predator populations.
Monitoring of Progressive Damage in Buildings Using Laser Scan Data
NASA Astrophysics Data System (ADS)
Puente, I.; Lindenbergh, R.; Van Natijne, A.; Esposito, R.; Schipper, R.
2018-05-01
Vulnerability of buildings to natural and man-induced hazards has become a main concern for our society. Ensuring their serviceability, safety and sustainability is of vital importance and the main reason for setting up monitoring systems to detect damages at an early stage. In this work, a method is presented for detecting changes from laser scan data, where no registration between different epochs is needed. To show the potential of the method, a case study of a laboratory test carried out at the Stevin laboratory of Delft University of Technology was selected. The case study was a quasi-static cyclic pushover test on a two-story high unreinforced masonry structure designed to simulate damage evolution caused by cyclic loading. During the various phases, we analysed the behaviour of the masonry walls by monitoring the deformation of each masonry unit. First a plane is fitted to the selected wall point cloud, consisting of one single terrestrial laser scan, using Principal Component Analysis (PCA). Second, the segmentation of individual elements is performed. Then deformations with respect to this plane model, for each epoch and specific element, are determined by computing their corresponding rotation and cloud-to-plane distances. The validation of the changes detected within this approach is done by comparison with traditional deformation analysis based on co-registered TLS point clouds between two or more epochs of building measurements. Initial results show that the sketched methodology is indeed able to detect changes at the mm level while avoiding 3D point cloud registration, which is a main issue in computer vision and remote sensing.
Seong-Jin Kim; Euisik Yoon
2012-06-01
We present a label-free CMOS field-effect transistor sensing array to detect the surface potential change affected by the negative charge in DNA molecules for real-time monitoring and quantification. The proposed CMOS bio sensor includes a new sensing pixel architecture implemented with correlated double sampling for reducing offset fixed pattern noise and 1/f noise of the sensing devices. We incorporated non-surface binding detection which allows real-time continuous monitoring of DNA concentrations without immobilizing them on the sensing surface. Various concentrations of 19-bp oligonucleotides solution can be discriminated using the prototype device fabricated in 1- μm double-poly double-metal standard CMOS process. The detection limit was measured as 1.1 ng/μl with a dynamic range of 40 dB and the transient response time was measured less than 20 seconds.
Self-learning health monitoring algorithm in composite structures
NASA Astrophysics Data System (ADS)
Grassia, Luigi; Iannone, Michele; Califano, America; D'Amore, Alberto
2018-02-01
The paper describes a system that it is able of monitoring the health state of a composite structure in real time. The hardware of the system consists of a wire of strain sensors connected to a control unit. The software of the system elaborates the strain data and in real time is able to detect the presence of an eventual damage of the structures monitored with the strain sensors. The algorithm requires as input only the strains of the monitored structured measured on real time, i.e. those strains coming from the deformations of the composite structure due to the working loads. The health monitoring system does not require any additional device to interrogate the structure as often used in the literature, instead it is based on a self-learning procedure. The strain data acquired when the structure is healthy are used to set up the correlations between the strain in different positions of structure by means of neural network. Once the correlations between the strains in different position have been set up, these correlations act as a fingerprint of the healthy structure. In case of damage the correlation between the strains in the position of the structure near the damage will change due to the change of the stiffness of the structure caused by the damage. The developed software is able to recognize the change of the transfer function between the strains and consequently is able to detect the damage.
Continuous electroencephalogram monitoring in the intensive care unit.
Friedman, Daniel; Claassen, Jan; Hirsch, Lawrence J
2009-08-01
Because of recent technical advances, it is now possible to record and monitor the continuous digital electroencephalogram (EEG) of many critically ill patients simultaneously. Continuous EEG monitoring (cEEG) provides dynamic information about brain function that permits early detection of changes in neurologic status, which is especially useful when the clinical examination is limited. Nonconvulsive seizures are common in comatose critically ill patients and can have multiple negative effects on the injured brain. The majority of seizures in these patients cannot be detected without cEEG. cEEG monitoring is most commonly used to detect and guide treatment of nonconvulsive seizures, including after convulsive status epilepticus. In addition, cEEG is used to guide management of pharmacological coma for treatment of increased intracranial pressure. An emerging application for cEEG is to detect new or worsening brain ischemia in patients at high risk, especially those with subarachnoid hemorrhage. Improving quantitative EEG software is helping to make it feasible for cEEG (using full scalp coverage) to provide continuous information about changes in brain function in real time at the bedside and to alert clinicians to any acute brain event, including seizures, ischemia, increasing intracranial pressure, hemorrhage, and even systemic abnormalities affecting the brain, such as hypoxia, hypotension, acidosis, and others. Monitoring using only a few electrodes or using full scalp coverage, but without expert review of the raw EEG, must be done with extreme caution as false positives and false negatives are common. Intracranial EEG recording is being performed in a few centers to better detect seizures, ischemia, and peri-injury depolarizations, all of which may contribute to secondary injury. When cEEG is combined with individualized, physiologically driven decision making via multimodality brain monitoring, intensivists can identify when the brain is at risk for injury or when neuronal injury is already occurring and intervene before there is permanent damage. The exact role and cost-effectiveness of cEEG at the current time remains unclear, but we believe it has significant potential to improve neurologic outcomes in a variety of settings.
Volumetric Security Alarm Based on a Spherical Ultrasonic Transducer Array
NASA Astrophysics Data System (ADS)
Sayin, Umut; Scaini, Davide; Arteaga, Daniel
Most of the existent alarm systems depend on physical or visual contact. The detection area is often limited depending on the type of the transducer, creating blind spots. Our proposition is a truly volumetric alarm system that can detect any movement in the intrusion area, based on monitoring the change over time of the impulse response of the room, which acts as an acoustic footprint. The device depends on an omnidirectional ultrasonic transducer array emitting sweep signals to calculate the impulse response in short intervals. Any change in the room conditions is monitored through a correlation function. The sensitivity of the alarm to different objects and different environments depends on the sweep duration, sweep bandwidth, and sweep interval. Successful detection of intrusions also depends on the size of the monitoring area and requires an adjustment of emitted ultrasound power. Strong air flow affects the performance of the alarm. A method for separating moving objects from strong air flow is devised using an adaptive thresholding on the correlation function involving a series of impulse response measurements. The alarm system can be also used for fire detection since air flow sourced from heating objects differ from random nature of the present air flow. Several measurements are made to test the integrity of the alarm in rooms sizing from 834-2080m3 with irregular geometries and various objects. The proposed system can efficiently detect intrusion whilst adequate emitting power is provided.
Jiang, Nan; Zhu, Wenquan; Zheng, Zhoutao; ...
2013-08-12
The long-term Normalized Difference Vegetation Index (NDVI) time-series data set generated from the Advanced Very High Resolution Radiometers (AVHRR) has been widely used to monitor vegetation activity change. The third version of NDVI (NDVI3g) produced by the Global Inventory Modeling and Mapping Studies (GIMMS) group was released recently. The comparisons between the new and old versions should be conducted for linking existing studies with future applications of NDVI3g in monitoring vegetation activity change. Based on simple and piecewise linear regression methods, this research made a comparative analysis between NDVIg and NDVI3g for monitoring vegetation activity change and its responses tomore » climate change in the middle and high latitudes of the Northern Hemisphere during 1982–2008. Our results indicated that there were large differences between NDVIg and NDVI3g in the spatial patterns for both the overall changing trends and the timing of Turning Points (TP) in NDVI time series, which spread over almost the entire study region. The average NDVI trend from NDVI3g was almost twice as great as that from NDVIg and the detected average timing of TP from NDVI3g was about one year later. Although the general spatial patterns were consistent between two data sets for detecting the responses of growing-season NDVI to temperature and precipitation changes, there were large differences in the response magnitude, with a higher response magnitude to temperature in NDVI3g and an opposite response to precipitation change for the two data sets. Finally, these results demonstrated that the NDVIg data set may underestimate the vegetation activity change trend and its response to climate change in the middle and high latitudes of the Northern Hemisphere during the past three decades.« less
NASA Technical Reports Server (NTRS)
1988-01-01
The charters of Freedom Monitoring System will periodically assess the physical condition of the U.S. Constitution, Declaration of Independence and Bill of Rights. Although protected in helium filled glass cases, the documents are subject to damage from light vibration and humidity. The photometer is a CCD detector used as the electronic film for the camera system's scanning camera which mechanically scans the document line by line and acquires a series of images, each representing a one square inch portion of the document. Perkin-Elmer Corporation's photometer is capable of detecting changes in contrast, shape or other indicators of degradation with 5 to 10 times the sensitivity of the human eye. A Vicom image processing computer receives the data from the photometer stores it and manipulates it, allowing comparison of electronic images over time to detect changes.
Weir, L.A.; Royle, J. Andrew; Nanjappa, P.; Jung, R.E.
2005-01-01
One of the most fundamental problems in monitoring animal populations is that of imperfect detection. Although imperfect detection can be modeled, studies examining patterns in occurrence often ignore detection and thus fail to properly partition variation in detection from that of occurrence. In this study, we used anuran calling survey data collected on North American Amphibian Monitoring Program routes in eastern Maryland to investigate factors that influence detection probability and site occupancy for 10 anuran species. In 2002, 17 calling survey routes in eastern Maryland were surveyed to collect environmental and species data nine or more times. To analyze these data, we developed models incorporating detection probability and site occupancy. The results suggest that, for more than half of the 10 species, detection probabilities vary most with season (i.e., day-of-year), air temperature, time, and moon illumination, whereas site occupancy may vary by the amount of palustrine forested wetland habitat. Our results suggest anuran calling surveys should document air temperature, time of night, moon illumination, observer skill, and habitat change over time, as these factors can be important to model-adjusted estimates of site occupancy. Our study represents the first formal modeling effort aimed at developing an analytic assessment framework for NAAMP calling survey data.
Karl, Jason W.; Gillan, Jeffrey K.; Barger, Nichole N.; Herrick, Jeffrey E.; Duniway, Michael C.
2014-01-01
The use of very high resolution (VHR; ground sampling distances < ∼5 cm) aerial imagery to estimate site vegetation cover and to detect changes from management has been well documented. However, as the purpose of monitoring is to document change over time, the ability to detect changes from imagery at the same or better level of accuracy and precision as those measured in situ must be assessed for image-based techniques to become reliable tools for ecosystem monitoring. Our objective with this study was to quantify the relationship between field-measured and image-interpreted changes in vegetation and ground cover measured one year apart in a Piñon and Juniper (P–J) woodland in southern Utah, USA. The study area was subject to a variety of fuel removal treatments between 2009 and 2010. We measured changes in plant community composition and ground cover along transects in a control area and three different treatments prior to and following P–J removal. We compared these measurements to vegetation composition and change based on photo-interpretation of ∼4 cm ground sampling distance imagery along similar transects. Estimates of cover were similar between field-based and image-interpreted methods in 2009 and 2010 for woody vegetation, no vegetation, herbaceous vegetation, and litter (including woody litter). Image-interpretation slightly overestimated cover for woody vegetation and no-vegetation classes (average difference between methods of 1.34% and 5.85%) and tended to underestimate cover for herbaceous vegetation and litter (average difference of −5.18% and 0.27%), but the differences were significant only for litter cover in 2009. Level of agreement between the field-measurements and image-interpretation was good for woody vegetation and no-vegetation classes (r between 0.47 and 0.89), but generally poorer for herbaceous vegetation and litter (r between 0.18 and 0.81) likely due to differences in image quality by year and the difficulty in discriminating fine vegetation and litter in imagery. Our results show that image interpretation to detect vegetation changes has utility for monitoring fuels reduction treatments in terms of woody vegetation and no-vegetation classes. The benefits of this technique are that it provides objective and repeatable measurements of site conditions that could be implemented relatively inexpensively and easily without the need for highly specialized software or technical expertise. Perhaps the biggest limitations of image interpretation to monitoring fuels treatments are challenges in estimating litter and herbaceous vegetation cover and the sensitivity of herbaceous cover estimates to image quality and shadowing.
Kelly, Brian P.
2011-01-01
The City of Independence, Missouri, operates a well field in the Missouri River alluvial aquifer. Contributing recharge areas (CRA) were last determined for the well field in 1996. Since that time, eight supply wells have been installed in the area north of the Missouri River and well pumpage has changed for the older supply wells. The change in pumping has altered groundwater flow and substantially changed the character of the CRA and groundwater travel times to the supply wells. The U.S Geological Survey, in a cooperative study with the City of Independence, Missouri, simulated steady-state groundwater flow for 2007 well pumpage, average annual river stage, and average annual recharge. Particle-tracking analysis was used to determine the CRA for supply wells and monitoring wells, and the travel time from recharge areas to supply wells, recharge areas to monitoring wells, and monitoring wells to supply wells. The simulated CRA for the well field is elongated in the upstream direction and extends to both sides of the Missouri River. Groundwater flow paths and recharge areas estimated for monitoring wells indicate the origin of water to each monitoring well, the travel time of that water from the recharge area, the flow path from the vicinity of each monitoring well to a supply well, and the travel time from the monitoring well to the supply well. Monitoring wells 14a and 14b have the shortest groundwater travel time from their contributing recharge area of 0.30 years and monitoring well 29a has the longest maximum groundwater travel time from its contributing recharge area of 1,701 years. Monitoring well 22a has the shortest groundwater travel time of 0.5 day to supply well 44 and monitoring well 3b has the longest maximum travel time of 31.91 years to supply well 10. Water-quality samples from the Independence groundwater monitoring well network were collected from 1997 to 2008 by USGS personnel during ongoing annual sampling within the 10-year contributing recharge area (CRA) of the Independence well field. Statistical summaries and the spatial and temporal variability of water quality in the Missouri River alluvial aquifer near the Independence well field were characterized from analyses of 598 water samples. Water-quality constituent groups include dissolved oxygen and physical properties, nutrients, major ions and trace elements, wastewater indicator compounds, fuel compounds, and total benzene, toluene, ethylbenzene, and xylene (BTEX), alachlor, and atrazine. The Missouri Secondary Maximum Contaminant Level (SMCL) for iron was exceeded in almost all monitoring wells. The Missouri Maximum Contaminant Level (MCL) for arsenic was exceeded 32 times in samples from monitoring wells. The MCL for barium was exceeded five times in samples from one monitoring well. The SMCL for manganese was exceeded 160 times in samples from all monitoring wells and the combined well-field sample. The most frequently detected wastewater indicator compounds were N,N-diethyl-meta-toluamide (DEET), phenol, caffeine, and metolachlor. The most frequently detected fuel compounds were toluene and benzene. Alachlor was detected in 22 samples and atrazine was detected in 37 samples and the combined well-field sample. The MCL for atrazine was exceeded in one sample from one monitoring well. Samples from monitoring wells with median concentrations of total inorganic nitrogen larger than 1 milligram per liter (mg/L) are located near agricultural land and may indicate that agricultural land practices are the source of nitrogen to groundwater. Largest median values of specific conductance; total inorganic nitrogen; dissolved calcium, magnesium, sodium, iron, arsenic, manganese, bicarbonate, and sulfate and detections of wastewater indicator compounds generally were in water samples from monitoring wells with CRAs that intersect the south bank of the Missouri River. Zones of higher specific conductance were located just upstream from the Independen
Comprehensive methods for earlier detection and monitoring of forest decline
Jennifer Pontius; Richard Hallett
2014-01-01
Forested ecosystems are threatened by invasive pests, pathogens, and unusual climatic events brought about by climate change. Earlier detection of incipient forest health problems and a quantitatively rigorous assessment method is increasingly important. Here, we describe a method that is adaptable across tree species and stress agents and practical for use in the...
Study on environment detection and appraisement of mining area with RS
NASA Astrophysics Data System (ADS)
Yang, Fengjie; Hou, Peng; Zhou, Guangzhu; Li, Qingting; Wang, Jie; Cheng, Jianguang
2006-12-01
In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.
A remotely interrogatable sensor for chemical monitoring
NASA Technical Reports Server (NTRS)
Stoyanov, P. G.; Doherty, S. A.; Grimes, C. A.; Seitz, W. R.
1998-01-01
A new type of continuously operating, in-situ, remotely monitored sensor is presented. The sensor is comprised of a thin film array of magnetostatically coupled, magnetically soft ferromagnetic thin film structures, adhered to or encased within a thin polymer layer. The polymer is made so that it swells or shrinks in response to the chemical analyte of interest, which in this case is pH. As the polymer swells or shrinks, the magnetostatic coupling between the magnetic elements changes, resulting in changes in the magnetic switching characteristics of the sensor. Placed within a sinusoidal magnetic field the magnetization vector of the coupled sensor elements periodically reverses directions, generating magnetic flux that can be remotely detected as a series of voltage spikes in appropriately placed pickup coils. one preliminary sensor design consists of four triangles, initially spaced approximately 50 micrometers apart, arranged to form a 12 mm x 12 mm square with the triangle tips centered at a common origin. Our preliminary work has focused on monitoring of pH using a lightly crosslinked pH sensitive polymer layer of hydroxyethylmethacrylate and 2-(dimethylamino) ethylmethacrylate. As the polymer swells or shrinks the magnetostatic coupling between the triangles changes, resulting in measurable changes in the amplitude of the detected voltage spirits.
NASA Astrophysics Data System (ADS)
Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi
2009-08-01
Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.
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.
Capacitively readout multi-element sensor array with common-mode cancellation
Britton, Jr., Charles L.; Warmack, Robert J.; Bryan, William L.; Jones, Robert L.; Oden, Patrick Ian; Thundat, Thomas
2001-01-01
An improved multi-element apparatus for detecting the presence of at least one chemical, biological or physical component in a monitored area comprising an array or single set of the following elements: a capacitive transducer having at least one cantilever spring element secured thereto, the cantilever element having an area thereof coated with a chemical having an affinity for the component to be detected; a pick-up plate positioned adjacent to the cantilever element at a distance such that a capacitance between the cantilever element and the pick-up plate changes as the distance between the cantilever element and the pick-up plate varies, the change in capacitance being a measurable variation; a detection means for measuring the measurable variation in the capacitance between the cantilever element and the pick-up plate that forms a measurement channel signal; and at least one feedback cantilever spring element positioned apart from the coated cantilever element, the cantilever element substantially unaffected by the component being monitored and providing a reference channel signal to the detection means that achieves a common mode cancellation between the measurement channel signal and reference channel signal.
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.
Kubisch, Rebekka; Bohrn, Ulrich; Fleischer, Maximilian; Stütz, Evamaria
2012-01-01
Pollution of drinking water sources represents a continuously emerging problem in global environmental protection. Novel techniques for real-time monitoring of water quality, capable of the detection of unanticipated toxic and bioactive substances, are urgently needed. In this study, the applicability of a cell-based sensor system using selected eukaryotic cell lines for the detection of aquatic pollutants is shown. Readout parameters of the cells were the acidification (metabolism), oxygen consumption (respiration) and impedance (morphology) of the cells. A variety of potential cytotoxic classes of substances (heavy metals, pharmaceuticals, neurotoxins, waste water) was tested with monolayers of L6 cells (rat myoblasts). The cytotoxicity or cellular effects induced by inorganic ions (Ni2+ and Cu2+) can be detected with the metabolic parameters acidification and respiration down to 0.5 mg/L, whereas the detection limit for other substances like nicotine and acetaminophen are rather high, in the range of 0.1 mg/L and 100 mg/L. In a close to application model a real waste water sample shows detectable signals, indicating the existence of cytotoxic substances. The results support the paradigm change from single substance detection to the monitoring of overall toxicity. PMID:22737014
Kubisch, Rebekka; Bohrn, Ulrich; Fleischer, Maximilian; Stütz, Evamaria
2012-01-01
Pollution of drinking water sources represents a continuously emerging problem in global environmental protection. Novel techniques for real-time monitoring of water quality, capable of the detection of unanticipated toxic and bioactive substances, are urgently needed. In this study, the applicability of a cell-based sensor system using selected eukaryotic cell lines for the detection of aquatic pollutants is shown. Readout parameters of the cells were the acidification (metabolism), oxygen consumption (respiration) and impedance (morphology) of the cells. A variety of potential cytotoxic classes of substances (heavy metals, pharmaceuticals, neurotoxins, waste water) was tested with monolayers of L6 cells (rat myoblasts). The cytotoxicity or cellular effects induced by inorganic ions (Ni(2+) and Cu(2+)) can be detected with the metabolic parameters acidification and respiration down to 0.5 mg/L, whereas the detection limit for other substances like nicotine and acetaminophen are rather high, in the range of 0.1 mg/L and 100 mg/L. In a close to application model a real waste water sample shows detectable signals, indicating the existence of cytotoxic substances. The results support the paradigm change from single substance detection to the monitoring of overall toxicity.
Local Leak Detection and Health Monitoring of Pressurized Tanks
NASA Technical Reports Server (NTRS)
Polzin, Kurt; Witherow, William; Korman, Valentin; Sinko, John; Hendrickson, Adam
2011-01-01
An optical gas-detection sensor safely monitors pressurized systems (such as cryogenic tanks) and distribution systems for leaks. This sensor system is a fiber-coupled, solid optical body interferometer that allows for the miniaturized sensing element of the device to be placed in the smallest of recesses, and measures a wide range of gas species and densities (leaks). The deflection of the fringe pattern is detected and recorded to yield the time-varying gas density in the gap. This technology can be used by manufacturers or storage facilities with toxic, hazardous, or explosive gases. The approach is to monitor the change in the index of refraction associated with low-level gas leaks into a vacuum environment. The completion of this work will provide NASA with an enabling capability to detect gas system leaks in space, and to verify that pressurized systems are in a safe (i.e. non-leaking) condition during manned docking and transit operations. By recording the output of the sensor, a time-history of the leak can be constructed to indicate its severity. Project risk is mitigated by having several interferometric geometries and detection techniques available, each potentially leveraging hardware and lessons learned to enhance detectability.
NASA Astrophysics Data System (ADS)
Koschuch, Richard; Brauner, Michael; Hu, Kaiheng; Hübl, Johannes
2016-04-01
Automatic monitoring of alpine mass movement is a major challenge in dealing with natural hazards. The presented research project shows a new approach in measurment and alarming technology for water level changes an debris flow by using a high-frequency Pulse Doppler RADAR. The detection system was implemented on 3 places (2 in Tirol/Austria within the monitoring systems of the IAN/BOKU; 1 in Dongchuan/China within the monitoring systems of the IMHE/Chinese Academy of Science) in order to prove the applicability of the RADAR in monitoring torrential activities (e.g. debris-flows, mudflows, flash floods, etc.). The main objective is to illustrate the principles and the potential of an innovative RADAR system and its versatility as an automatic detection system for fast (> 1 km/h - 300 km/h) alpine mass movements of any kind. The high frequency RADAR device was already successfully tested for snow avalanches in Sedrun/Switzerland (Lussi et al., 2012), in Ischgl/Austria (Kogelnig et al., 2012). The experience and the data of the five year showed the enormous potential of the presented RADAR technology in use as an independent warning and monitoring system in the field of natural hazard. We have been able to measure water level changes, surface velocities and several debris flows and can compare this data with the other installed systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Merchant, Bion J
2015-12-22
NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The version 2.0 of the software supports the simulation of seismic, hydroacoustic, and infrasonic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria. NetMOD will be distributed with a project file defining the basic performance characteristics of the International Monitoring System (IMS), a network of sensors operated by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Network modeling is needed to be able to assess and explainmore » the potential effect of changes to the IMS, to prioritize station deployment and repair, and to assess the overall CTBTO monitoring capability currently and in the future. Currently the CTBTO uses version 1.0 of NetMOD, provided to them in early 2014. NetMOD will provide a modern tool that will cover all the simulations currently available and allow for the development of additional simulation capabilities of the IMS in the future. NetMOD simulates the performance of monitoring networks by estimating the relative amplitudes of the signal and noise measured at each of the stations within the network based upon known geophysical principles. From these signal and noise estimates, a probability of detection may be determined for each of the stations. The detection probabilities at each of the stations may then be combined to produce an estimate of the detection probability for the entire monitoring network.« less
Simultaneous Detection of Static and Dynamic Signals by a Flexible Sensor Based on 3D Graphene.
Xu, Rongqing; Wang, Di; Zhang, Hongchao; Xie, Na; Lu, Shan; Qu, Ke
2017-05-08
A flexible acoustic pressure sensor was developed based on the change in electrical resistance of three-dimensional (3D) graphene change under the acoustic waves action. The sensor was constructed by 3D graphene foam (GF) wrapped in flexible polydimethylsiloxane (PDMS). Tuning forks and human physiological tests indicated that the acoustic pressure sensor can sensitively detect the deformation and the acoustic pressure in real time. The results are of significance to the development of graphene-based applications in the field of health monitoring, in vitro diagnostics, advanced therapies, and transient pressure detection.
NASA Astrophysics Data System (ADS)
Jin, Chenhao; Li, Jingcheng; Jang, Shinae; Sun, Xiaorong; Christenson, Richard
2015-03-01
Structural health monitoring has drawn significant attention in the past decades with numerous methodologies and applications for civil structural systems. Although many researchers have developed analytical and experimental damage detection algorithms through vibration-based methods, these methods are not widely accepted for practical structural systems because of their sensitivity to uncertain environmental and operational conditions. The primary environmental factor that influences the structural modal properties is temperature. The goal of this article is to analyze the natural frequency-temperature relationships and detect structural damage in the presence of operational and environmental variations using modal-based method. For this purpose, correlations between natural frequency and temperature are analyzed to select proper independent variables and inputs for the multiple linear regression model and neural network model. In order to capture the changes of natural frequency, confidence intervals to detect the damages for both models are generated. A long-term structural health monitoring system was installed on an in-service highway bridge located in Meriden, Connecticut to obtain vibration and environmental data. Experimental testing results show that the variability of measured natural frequencies due to temperature is captured, and the temperature-induced changes in natural frequencies have been considered prior to the establishment of the threshold in the damage warning system. This novel approach is applicable for structural health monitoring system and helpful to assess the performance of the structure for bridge management and maintenance.
Middle infrared optoelectronic absorption systems for monitoring physiological glucose solutions
NASA Astrophysics Data System (ADS)
Martin, W. Blake
Tight monitoring of the glucose levels for diabetic individuals is essential to control long-term complications. A definitive diabetes management system has yet to be developed for the diabetic. This research investigates the application of middle infrared absorption frequencies for monitoring glucose levels in biological solutions. Three frequencies were identified using a Fourier transform infrared spectrometer and correlated to changes in glucose concentrations. The 1035 +/- 1 cm-1 frequency was determined to be the best representative frequency. Other biological molecules contributed no significant interference to monitoring glucose absorption. A second frequency at 1193 cm-1 was suggested as a representative background absorption frequency, which could be used for more accurate glucose absorption values. Next, a quantum cascade laser optoelectronic absorption system was designed and developed to monitor glucose. After careful alignment and design, the system was used to monitor physiological glucose concentrations. Correlation at 1036 cm-1 with glucose changes was comparable to the previous results. The use of the background absorption frequency was verified. This frequency essentially acts as a calibrating frequency to adjust in real-time to any changes in the background absorption that may alter the accuracy of the predicted glucose value. An evanescent wave cavity ring-down spectroscopy technique was explored to monitor molecules in a biological solution. Visible light at 425 nm was used to monitor hemoglobin in control urine samples. An adsorption isotherm for hemoglobin was detectable to limit of 5.8 nM. Evanescent wave cavity ring-down spectroscopy would be useful for a glucose solution. Given an equivalent system designed for the middle infrared, the molar extinction coefficient of glucose allows for a detectable limit of 45 mg/dl for a free-floating glucose solution, which is below normal physiological concentrations. The future use of a hydrophobic coating could limit the adsorption of glucose to the surface but still allow physiological monitoring. Three middle infrared optoelectronic absorption systems have been designed for monitoring glucose in a physiological solution. The systems are applicable for the monitoring of glucose. These systems may lead to a useful monitoring device for the diabetic so that the universal complications associated with the disease may be limited.
NASA Astrophysics Data System (ADS)
Tallman, T.; Semperlotti, F.; Wang, K. W.
2012-04-01
The high strength to weight ratio of fibrous composites such as glass-fiber reinforced polymers (GFRP) makes them prominent structural materials. However, their laminar nature is susceptible to delamination failure the onset of which traditional structural health monitoring (SHM) techniques cannot reliably and accurately detect. Carbon nano-tubes (CNT) have been recently used to tailor the electrical conductivity of polymer based materials that otherwise behave as insulators. The occurrence of damage in the polymer matrix produces localized changes in conductivity which can be tracked using electrical impedance tomography (EIT). This paper explores combining advances in composite manufacturing with EIT to develop a SHM technique that exploits anisotropic conductance monitoring for enhanced delamination and matrix crack detection.
The nursing perspective on monitoring hemodynamics and oxygen transport.
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.
Mottram, T
2016-10-01
Dairy cows are high value farm animals requiring careful management to achieve the best results. Since the advent of robotic and high throughput milking, the traditional few minutes available for individual human attention daily has disappeared and new automated technologies have been applied to improve monitoring of dairy cow production, nutrition, fertility, health and welfare. Cows milked by robots must meet legal requirements to detect healthy milk. This review focuses on emerging technical approaches in those areas of high cost to the farmer (fertility, metabolic disorders, mastitis, lameness and calving). The availability of low cost tri-axial accelerometers and wireless telemetry has allowed accurate models of behaviour to be developed and sometimes combined with rumination activity detected by acoustic sensors to detect oestrus; other measures (milk and skin temperature, electronic noses, milk yield) have been abandoned. In-line biosensors have been developed to detect markers for ovulation, pregnancy, lactose, mastitis and metabolic changes. Wireless telemetry has been applied to develop boluses for monitoring the rumen pH and temperature to detect metabolic disorders. Udder health requires a multisensing approach due to the varying inflammatory responses collectively described as mastitis. Lameness can be detected by walk over weigh cells, but also by various types of video image analysis and speed measurement. Prediction and detection of calving time is an area of active research mostly focused on behavioural change.
An Approach to V&V of Embedded Adaptive Systems
NASA Technical Reports Server (NTRS)
Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth
2004-01-01
Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,
Mugnai, Sergio; Monetti, Emanuela; Voigt, Boris; Volkmann, Dieter; Mancuso, Stefano
2014-01-01
Oxygen influx showed an asymmetry in the transition zone of the root apex when roots were placed horizontally on ground. The influx increased only in the upper side, while no changes were detected in the division and in the elongation zone. Nitric oxide (NO) was also monitored after gravistimulation, revealing a sudden burst only in the transition zone. In order to confirm these results in real microgravity conditions, experiments have been set up by using parabolic flights and drop tower. The production of reactive oxygen species (ROS) was also monitored. Oxygen, NO, and ROS were continuously monitored during normal and hyper- and microgravity conditions in roots of maize seedlings. A distinct signal in oxygen and NO fluxes was clearly detected only in the apex zone during microgravity, with no significant changes in normal and in hypergravity conditions. The same results were obtained by ROS measurement. The detrimental effect of D'orenone, disrupting the polarised auxin transport, on the onset of the oxygen peaks during the microgravity period was also evaluated. Results indicates an active role of NO and ROS as messengers during the gravitropic response, with probable implications in the auxin redistribution. PMID:25197662
NASA Astrophysics Data System (ADS)
Tian, Fenghua; Ding, Haishu; Cai, Zhigang; Wang, Guangzhi; Zhao, Fuyun
2002-04-01
In recent studies, near-infrared spectroscopy (NIRS) has been considered as a potentially ideal noninvasive technique for the postoperative monitoring of plastic surgery. In this study, free flaps were raised on rhesus monkeys' forearms and oxygen delivery to these flaps was monitored following vascular occlusions and inhalation of pure oxygen. Optical fibers were adopted in the probe of the oximeter so that the detection could be performed in reflectance mode. The distance between emitter and detector can be adjusted easily to achieve the best efficacy. Different and repeatable patterns of changes were measured following vascular occlusions (arterial occlusion, venous occlusion and total occlusion) on flaps. It is clear that the near-infrared spectroscopy is capable of postoperatively monitoring vascular problems in flaps. NIRS showed high sensitivity to detect the dynamic changes in flaps induced by inhalation of pure oxygen in this study. The experimental results indicated that it was potential to assess tissue viability utilizing the dynamic changes induced by a noninvasive stimulation. It may be a new assessing method that is rapid, little influenced by other factors and brings less discomfort to patients.
Optical monitoring of thermal effects in RPE during heating
NASA Astrophysics Data System (ADS)
Schuele, G.; Huie, Ph.; Yellachich, D.; Molnar, F. E.; O'Conell-Rodwell, C.; Vitkin, E.; Perelman, L. T.; Palanker, D.
2005-04-01
Fast and non-invasive detection of cellular stress is useful for fundamental research and practical applications in medicine and biology. Using Light Scattering Spectroscopy we extract information about changes in refractive index and size of the cellular organelles. Particle sizes down to 50nm in diameter can be detected using light within the spectral range of 450-850 nm. We monitor the heat-induced sub-cellular structural changes in human RPE cells and, for comparison, in transfected NIH-3T3 cells which express luciferase linked to the heat shock protein (HSP). Using inverse light scattering fitting algorithm, we reconstruct the size distribution of the sub-micron organelles from the light scattering spectrum. The most significant (up to 70%) and rapid (20sec) temperature-related changes can be linked to an increase of refractive index of the 160nm sized mitochondria. The start of this effect coincides with the onset of HSP expression. This technique provides an insight into metabolic processes within organelles larger than 50nm without exogenous staining and opens doors for non-invasive real-time assessment of cellular stress, which can be used for monitoring of retinal laser treatments like transpupillary thermo therapy or PDT.
NASA Astrophysics Data System (ADS)
Gance, J.; Sailhac, P.; Malet, J.; Supper, R.; Jochum, B.; Ottowitz, D.; Grandjean, G.
2013-12-01
Movements of water in the topsoil (infiltration, run-off and evaporation) influence changes in slope stability which is the main controlling factor of landslide triggering (e.g. van Asch et al., 1999). Among the petrophysical parameters that can provide time-lapse sections of the topsoil, we consider the electrical conductivity for its sensitivity to soil water contents. Based on recent works which showed the possibility of monitoring the hydrological response of a clay-shale slope to a controlled rainfall experiment (Travelletti et al., 2012), we installed a permanent electrical monitoring experiment at the Super-Sauze landslide for long-term monitoring (one year) of natural meteorological events. We used the GEOMON4D resistivimeter, developed by the Austrian Geological Survey (Vienna, Austria) for experiments needing high rate of data acquisition, records of full signal samples for noise detection, remote controlled management and automatic data transfer (Supper et al., 2002, 2003 & 2004). The electrode positions varying with time, we installed two terrestrial optical cameras to characterize the changes in dipole geometry. Several hydrological sensors were installed along the profile to measure soil temperature, water temperature and conductivity, ground water level and soil humidity in the vadose zone. The main challenge is the processing of ca. 4.2 million of electrical resistivity data. In this difficult context, the potential factors influencing electrical resistivity with time without modification of soil saturation are the relative changes in the dipole geometry (linked to the displacement of the electrodes), changes in soil and water temperature, change in material porosity due to compaction/dilatation caused by the landslide movement. Therefore, before any inversion of data, we verify the presence of possible 3D effects, and assess the measurement accuracy and uncertainty. An apparent resistivity variation threshold, from which a modification of the saturation can be attributed, is determined. From those first results, we first investigate changes in the apparent resistivity. Responses to different hydrological processes (such as soil freezing/thawing, snow melting, high intensity rainfall, debris flow events) occurring during the monitoring period are detectable on the inversed resistivities over short periods. For example The results of the study highlight the difficulty to monitor hydrological changes on a clay-shale landslide, and will permit to improve such future device. Although a quantitative interpretation of the apparent resistivity is impossible, typical responses are clearly detectable and allows a first qualitative interpretation of hydrological changes in the landslide
Global change and terrestrial plant community dynamics
Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...
2016-02-29
Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less
Global change and terrestrial plant community dynamics
Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.
2016-01-01
Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338
NASA Astrophysics Data System (ADS)
Faouzi, B.; Washaya, P.
2017-09-01
This paper is based on using DMSP-OLS data from satellites nighttime light observations to detect both sources of light emissions in Algeria from human settlement areas and gas flaring from oil-extraction and natural gas production. We used the time series of data from DMSP-OLS images to examine the spatial and temporal characteristics of urban development in 48 Algerian provinces from 1993 to 2012. A systematic nighttime light calibration method was used to improve the consistency and comparability of the DSMPOSL images and then a separation is made between light detected from human settlements and light detected from gas flaring in order to allow us to study human settlements without other light emissions and then assess the suitability of using DMSP data in southern Algeria and its ability to monitor gas flaring. Linear regression methods were developed to identify the dynamic change of nighttime light and estimated its growth directions at pixel level. This work is the first to use nighttime light observations to detect and monitor the growth of human settlements in North Africa. In this study, we made use of DMSP-OLS data as a return ticket to the years of crises and we found the most affected provinces during that period. The DMSP-OLS data proved to be an index of growth in the economy during the period of stability in Algeria expressed by positive dynamic changes in the lighted area in all Algerian provinces. We used NTL data as an alternative to annual growth indexes for each province, which are unavailable, and its help as a monitoring system for socioeconomic parameters to fill the gap of data availability. We also proposed nighttime light remote sensing data as a useful tool to control and reduce CO2 emissions in Algeria's petroleum sector.
NASA Technical Reports Server (NTRS)
Riggs, George A.; Hall, Dorothy K.; Foster, James L.
2009-01-01
Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.
Charlton, R A; Schiavone, F; Barrick, T R; Morris, R G; Markus, H S
2010-01-01
Diffusion tensor imaging (DTI) is a sensitive method for detecting white matter damage, and in cross sectional studies DTI measures correlate with age related cognitive decline. However, there are few data on whether DTI can detect age related changes over short time periods and whether such change correlates with cognitive function. In a community sample of 84 middle-aged and elderly adults, MRI and cognitive testing were performed at baseline and after 2 years. Changes in DTI white matter histograms, white matter hyperintensity (WMH) volume and brain volume were determined. Change over time in performance on tests of executive function, working memory and information processing speed were also assessed. Significant change in all MRI measures was detected. For cognition, change was detected for working memory and this correlated with change in DTI only. In a stepwise regression, with change in working memory as the dependent variable, a DTI histogram measure explained 10.8% of the variance in working memory. Change in WMH or brain volume did not contribute to the model. DTI is sensitive to age related change in white matter ultrastructure and appears useful for monitoring age related white matter change even over short time periods.
Tracking the health of trees over time on forest health monitoring plots
Jim Steinman
2000-01-01
The Forest Health Monitoring (FHM) Program was initiated in 1990 as a cooperative effort between the USDA Forest Service and the National Association of State Foresters. Program efforts include detecting changes in tree health from a national grid of one-sixth acre permanent sample plots. Tree data have been collected in various states since 1991, and include species,...
Geneva Chong; David Barnett; Benjamin Chemel; Roy Renkin; Pamela Sikkink
2011-01-01
A 2002 National Research Council (NRC) evaluation of ungulate management practices in Yellowstone specifically concluded that previous (1957 to present) vegetation monitoring efforts were insufficient to determine whether climate or ungulates were more influential on shrub/steppe dynamics on the northern ungulate winter range. The NRC further recommended that the...
Marc C. Coles-Ritchie; Richard C. Henderson; Eric K. Archer; Caroline Kennedy; Jeffrey L. Kershner
2004-01-01
Tests were conducted to evaluate variability among observers for riparian vegetation data collection methods and data reduction techniques. The methods are used as part of a largescale monitoring program designed to detect changes in riparian resource conditions on Federal lands. Methods were evaluated using agreement matrices, the Bray-Curtis dissimilarity metric, the...
Tracking the health of trees over time on Forest Health Monitoring plots
Jim Steinman
2000-01-01
The Forest Health Monitoring (FHM) Program was initiated in 1990 as a cooperative effort between the USDA Forest Service and the National Association of State Foresters. Program efforts include detecting changes in tree health from a national grid of one-sixth acre permanent sample plots. Tree data have been collected in various States since 1991, and include species...
PCA feature extraction for change detection in multidimensional unlabeled data.
Kuncheva, Ludmila I; Faithfull, William J
2014-01-01
When classifiers are deployed in real-world applications, it is assumed that the distribution of the incoming data matches the distribution of the data used to train the classifier. This assumption is often incorrect, which necessitates some form of change detection or adaptive classification. While there has been a lot of work on change detection based on the classification error monitored over the course of the operation of the classifier, finding changes in multidimensional unlabeled data is still a challenge. Here, we propose to apply principal component analysis (PCA) for feature extraction prior to the change detection. Supported by a theoretical example, we argue that the components with the lowest variance should be retained as the extracted features because they are more likely to be affected by a change. We chose a recently proposed semiparametric log-likelihood change detection criterion that is sensitive to changes in both mean and variance of the multidimensional distribution. An experiment with 35 datasets and an illustration with a simple video segmentation demonstrate the advantage of using extracted features compared to raw data. Further analysis shows that feature extraction through PCA is beneficial, specifically for data with multiple balanced classes.
Diffuse ultrasound monitoring of stress and damage development on a 15-ton concrete beam.
Zhang, Yuxiang; Planès, Thomas; Larose, Eric; Obermann, Anne; Rospars, Claude; Moreau, Gautier
2016-04-01
This paper describes the use of an ultrasonic imaging technique (Locadiff) for the Non-Destructive Testing & Evaluation of a concrete structure. By combining coda wave interferometry and a sensitivity kernel for diffuse waves, Locadiff can monitor the elastic and structural properties of a heterogeneous material with a high sensitivity, and can map changes of these properties over time when a perturbation occurs in the bulk of the material. The applicability of the technique to life-size concrete structures is demonstrated through the monitoring of a 15-ton reinforced concrete beam subject to a four-point bending test causing cracking. The experimental results show that Locadiff achieved to (1) detect and locate the cracking zones in the core of the concrete beam at an early stage by mapping the changes in the concrete's micro-structure; (2) monitor the internal stress level in both temporal and spatial domains by mapping the variation in velocity caused by the acousto-elastic effect. The mechanical behavior of the concrete structure is also studied using conventional techniques such as acoustic emission, vibrating wire extensometers, and digital image correlation. The performances of the Locadiff technique in the detection of early stage cracking are assessed and discussed.
Series quartz crystal sensor for remote bacteria population monitoring in raw milk via the Internet.
Chang, Ku-Shang; Jang, Hung-Der; Lee, Ching-Fu; Lee, Yuan-Guey; Yuan, Chiun-Jye; Lee, Sheng-Hsien
2006-02-15
A remote monitoring system based on a piezoelectric quartz crystal (SPQC) sensor was developed for the determination of the bacteria population in raw milk. The system employs the Windows XP server operating system, and its programs for data acquisition, display and transmission were developed using the LabVIEW 7.1 programming language. The circuit design consists of a circuit with a piezoelectric quartz crystal (SPQC) and a pair of electrodes. This system can provide dynamic data monitoring on a web-page via the Internet. Immersion of the electrodes in a cell culture with bacteria inoculums resulted in a change of frequency caused by the impedance change due to microbial metabolism and the adherence of bacteria on the surface of the electrodes. The calibration curve of detection times against density of bacteria showed a linear correlation coefficient (R(2) = 0.9165) over the range of 70-10(6) CFU ml(-1). The sensor could acquire sufficient data rapidly (within 4 h) and thus enabled real-time monitoring of bacteria growth via the Internet. This system has potential application in the detection of bacteria concentration of milk at dairy farms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.
Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less
NASA Astrophysics Data System (ADS)
Lasaponara, R.; Lanorte, A.; Coluzzi, R.; Masini, N.
2009-04-01
The systematic monitoring of cultural and natural heritage is a basic step for its conservation. Monitoring strategies should constitute an integral component of policies relating to land use, development, and planning. To this aim remote sensing technologies can be used profitably. This paper deals with the use of multitemporal, multisensors, and multiscale satellite data for assessing and monitoring changes affecting cultural landscapes and archaeological sites. The discussion is focused on some significant test cases selected in Peru (South America) and Southern Italy . Artifacts, unearthed sites, and marks of buried remains have been investigated by using multitemporal aerial and satellite data, such as Quickbird, ASTER, Landsat MSS and TM.
Gear-box fault detection using time-frequency based methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Odgaard, Peter Fogh; Stoustrup, Jakob
2015-01-01
Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected.more » Two different time-frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen-Loeve basis. Both of them detects the gear-box fault with an acceptable detection delay.« less
Monitoring of bedridden patients: development of a fall detection tool.
Vilas-Boas, M; Silva, P; Cunha, S R; Correia, M V
2013-01-01
Falls of patients are an important issue in hospitals nowadays; it causes severe injuries, increases hospitalization time and treatment costs. The detection of a fall, in time, provides faster rescue to the patient, preventing more serious injuries, as well as saving nursing time. The MovinSense® is an electronic device designed for monitoring patients to prevent pressure sores, and the main goal of this work was to develop a new tool for this device, with the purpose of detecting if the patient has fallen from the hospital bed, without changing any of the device's original features. Experiments for gathering data samples of inertial signals of falling from the bed were obtained using the device. For fall detection a sensitivity of 72% and specificity of 100% were reached. Another algorithm was developed to detect if the patient got out of his/her bed.
Conformational Change of Bacteriorhodopsin Quantitatively Monitored by Microcantilever Sensors
Braun, Thomas; Backmann, Natalija; Vögtli, Manuel; Bietsch, Alexander; Engel, Andreas; Lang, Hans-Peter; Gerber, Christoph; Hegner, Martin
2006-01-01
Bacteriorhodopsin proteoliposomes were used as a model system to explore the applicability of micromechanical cantilever arrays to detect conformational changes in membrane protein patches. The three main results of our study concern: 1), reliable functionalization of micromechanical cantilever arrays with proteoliposomes using ink jet spotting; 2), successful detection of the prosthetic retinal removal (bleaching) from the bacteriorhodopsin protein by measuring the induced nanomechanical surface stress change; and 3), the quantitative response thereof, which depends linearly on the amount of removed retinal. Our results show this technique to be a potential tool to measure membrane protein-based receptor-ligand interactions and conformational changes. PMID:16443650
Accessing long-term memory representations during visual change detection.
Beck, Melissa R; van Lamsweerde, Amanda E
2011-04-01
In visual change detection tasks, providing a cue to the change location concurrent with the test image (post-cue) can improve performance, suggesting that, without a cue, not all encoded representations are automatically accessed. Our studies examined the possibility that post-cues can encourage the retrieval of representations stored in long-term memory (LTM). Participants detected changes in images composed of familiar objects. Performance was better when the cue directed attention to the post-change object. Supporting the role of LTM in the cue effect, the effect was similar regardless of whether the cue was presented during the inter-stimulus interval, concurrent with the onset of the test image, or after the onset of the test image. Furthermore, the post-cue effect and LTM performance were similarly influenced by encoding time. These findings demonstrate that monitoring the visual world for changes does not automatically engage LTM retrieval.
Hocking, Kyle M; Sileshi, Ban; Baudenbacher, Franz J; Boyer, Richard B; Kohorst, Kelly L; Brophy, Colleen M; Eagle, Susan S
2016-10-01
Unrecognized hemorrhage and unguided resuscitation is associated with increased perioperative morbidity and mortality. The authors investigated peripheral venous waveform analysis (PIVA) as a method for quantitating hemorrhage as well as iatrogenic fluid overload during resuscitation. The authors conducted a prospective study on Yorkshire Pigs (n = 8) undergoing hemorrhage, autologous blood return, and administration of balanced crystalloid solution beyond euvolemia. Intra-arterial blood pressure, electrocardiogram, and pulse oximetry were applied to each subject. Peripheral venous pressure was measured continuously through an upper extremity standard peripheral IV catheter and analyzed with LabChart. The primary outcome was comparison of change in the first fundamental frequency (f1) of PIVA with standard and invasive monitoring and shock index (SI). Hemorrhage, return to euvolemia, and iatrogenic fluid overload resulted in significantly non-zero slopes of f1 amplitude. There were no significant differences in heart rate or mean arterial pressure, and a late change in SI. For the detection of hypovolemia the PIVA f1 amplitude change generated an receiver operator curves (ROC) curve with an area under the curve (AUC) of 0.93; heart rate AUC = 0.61; mean arterial pressure AUC = 0.48, and SI AUC = 0.72. For hypervolemia the f1 amplitude generated an ROC curve with an AUC of 0.85, heart rate AUC = 0.62, mean arterial pressure AUC = 0.63, and SI AUC = 0.65. In this study, PIVA demonstrated a greater sensitivity for detecting acute hemorrhage, return to euvolemia, and iatrogenic fluid overload compared with standard monitoring and SI. PIVA may provide a low-cost, minimally invasive monitoring solution for monitoring and resuscitating patients with perioperative hemorrhage.
The detection of brain ischaemia in rats by inductive phase shift spectroscopy.
González, C A; Villanueva, C; Vera, C; Flores, O; Reyes, R D; Rubinsky, B
2009-08-01
Ischaemia in the brain is an important clinical problem that is often monitored and studied with expensive devices such as MRI and PET, which are not readily available in low economical resource parts of the world. We have developed a new less expensive tool for non-invasive monitoring of ischaemia in the brain. This is a first feasibility study describing the concept. The system is based on the hypothesis that electromagnetic properties of the tissue change during ischaemia and that measuring the electromagnetic properties of the bulk of the brain with non-contact means can detect these changes. The apparatus we have built and whose design we describe here consists of two electromagnetic coils placed around the head. The system measures the bulk change in time of the phase difference between the electromagnetic signal on the two coils in a range of frequencies. A mathematical model simulating the device and the measurement is also introduced. Ischaemia was induced in the brain of rats by occlusion of the right cerebral and carotid arteries. Experimental subjects were monitored for 24 h. Inductive phase shift measurements were made at five frequencies in the range of 0.1-50 MHz eight times during the observation period. An ex vivo estimation of the percentage of necrosis in the ischemic subjects at t = 24 h was done. The mathematical model was also applied to the experimental tested situation. The results of both experiments and theory show significant phase shifts increase as a function of frequency and ischaemia time. The theoretical and experimental results suggest that the tested technique has the potential to detect the processes and level of ischaemia in the brain by non-invasive, continuous, bulk volumetric monitoring with a simple and inexpensive apparatus.
Monitoring strip mining and reclamation with LANDSAT data in Belmont County, Ohio
NASA Technical Reports Server (NTRS)
Witt, R. G.; Schaal, G. M.; Bly, B. G.
1983-01-01
The utility of LANDSAT digital data for mapping and monitoring surface mines in Belmont County, Ohio was investigated. Two data sets from 1976 and 1979 were processed to classify level 1 land covers and three strip mine categories in order to examine change over time and assess reclamation efforts. The two classifications were compared with aerial photographs. Results of the accuracy assessment show that both classifications are approximately 86 per cent correct, and that surface mine change detection (date-to-date comparison) is facilitated by the digital format of LANDSAT data.
Integrating Remote and Social Sensing Data for a Scenario on Secure Societies in Big Data Platform
NASA Astrophysics Data System (ADS)
Albani, Sergio; Lazzarini, Michele; Koubarakis, Manolis; Taniskidou, Efi Karra; Papadakis, George; Karkaletsis, Vangelis; Giannakopoulos, George
2016-08-01
In the framework of the Horizon 2020 project BigDataEurope (Integrating Big Data, Software & Communities for Addressing Europe's Societal Challenges), a pilot for the Secure Societies Societal Challenge was designed considering the requirements coming from relevant stakeholders. The pilot is focusing on the integration in a Big Data platform of data coming from remote and social sensing.The information on land changes coming from the Copernicus Sentinel 1A sensor (Change Detection workflow) is integrated with information coming from selected Twitter and news agencies accounts (Event Detection workflow) in order to provide the user with multiple sources of information.The Change Detection workflow implements a processing chain in a distributed parallel manner, exploiting the Big Data capabilities in place; the Event Detection workflow implements parallel and distributed social media and news agencies monitoring as well as suitable mechanisms to detect and geo-annotate the related events.
Effective detection of CO 2 leakage: a comparison of groundwater sampling and pressure monitoring
Keating, Elizabeth; Dai, Zhenxue; Dempsey, David; ...
2014-12-31
Shallow aquifer monitoring is likely to be a required aspect to any geologic CO 2 sequestration operation. Collecting groundwater samples and analyzing for geochemical parameters such as pH, alkalinity, total dissolved carbon, and trace metals has been suggested by a number of authors as a possible strategy to detect CO 2 leakage. The effectiveness of this approach, however, will depend on the hydrodynamics of the leak-induced CO 2 plume and the spatial distribution of the monitoring wells relative to the origin of the leak. To our knowledge, the expected effectiveness of groundwater sampling to detect CO 2 leakage has notmore » yet been quantitatively assessed. In this study we query hundreds of simulations developed for the National Risk Assessment Project (US DOE) to estimate risks to drinking water resources associated with CO 2 leaks. The ensemble of simulations represent transient, 3-D multi-phase reactive transport of CO 2 and brine leaked from a sequestration reservoir, via a leaky wellbore, into an unconfined aquifer. Key characteristics of the aquifer, including thickness, mean permeability, background hydraulic gradient, and geostatistical measures of aquifer heterogeneity, were all considered uncertain parameters. Complex temporally-varying CO 2 and brine leak rate scenarios were simulated using a heuristic scheme with ten uncertain parameters. The simulations collectively predict the spatial and temporal evolution of CO 2 and brine plumes over 200 years in a shallow aquifer under a wide range of leakage scenarios and aquifer characteristics. Using spatial data from an existing network of shallow drinking water wells in the Edwards Aquifer, TX, as one illustrative example, we calculated the likelihood of leakage detection by groundwater sampling. In this monitoring example, there are 128 wells available for sampling, with a density of about 2.6 wells per square kilometer. If the location of the leak is unknown a priori, a reasonable assumption in many cases, we found that the leak would be detected in at least one of the monitoring wells in less than 10% of the scenarios considered. This is because plume sizes are relatively small, and so the probability of detection decreases rapidly with distance from the leakage point. For example, 400m away from the leakage point there is less than 20% chance of detection. We then compared the effectiveness of groundwater quality sampling to shallow aquifer and/or reservoir pressure monitoring. For the Edwards Aquifer example, pressure monitoring in the same monitoring well network was found to be even less effective that groundwater quality monitoring. This is presumably due to the unconfined conditions and relatively high permeability, so pressure perturbations quickly dissipate. Although specific results may differ from site to site, this type of analysis should be useful to site operators and regulators when selecting leak detection strategies. Given the spatial characteristics of a proposed monitoring well network, probabilities of leakage detection can be rapidly calculated using this methodology. Although conditions such as these may not be favorable for leakage detection in shallow aquifers, leakage detection could be much more successful in the injection reservoir. We demonstrate proof-of-concept for this hypothesis, presenting a simulation where there is measurable pressure change at the injection well due to overpressurization, fault rupture, and consequent leakage up the fault into intermediate and shallow aquifers. The size of the detectible pressure change footprint is much larger in the reservoir than in either of the overlying aquifers. Further exploration of the range of conditions for which this technique would be successful is the topic of current study.« less
Early effects of climate change: do they include changes in vector-borne disease?
Kovats, R S; Campbell-Lendrum, D H; McMichael, A J; Woodward, A; Cox, J S
2001-01-01
The world's climate appears now to be changing at an unprecedented rate. Shifts in the distribution and behaviour of insect and bird species indicate that biological systems are already responding to this change. It is well established that climate is an important determinant of the spatial and temporal distribution of vectors and pathogens. In theory, a change in climate would be expected to cause changes in the geographical range, seasonality (intra-annual variability), and in the incidence rate (with or without changes in geographical or seasonal patterns). The detection and then attribution of such changes to climate change is an emerging task for scientists. We discuss the evidence required to attribute changes in disease and vectors to the early effects of anthropogenic climate change. The literature to date indicates that there is a lack of strong evidence of the impact of climate change on vector-borne diseases (i.e. malaria, dengue, leishmaniasis, tick-borne diseases). New approaches to monitoring, such as frequent and long-term sampling along transects to monitor the full latitudinal and altitudinal range of specific vector species, are necessary in order to provide convincing direct evidence of climate change effects. There is a need to reassess the appropriate levels of evidence, including dealing with the uncertainties attached to detecting the health impacts of global change. PMID:11516383
Voltage Sensors Monitor Harmful Static
NASA Technical Reports Server (NTRS)
2009-01-01
A tiny sensor, small enough to be worn on clothing, now monitors voltage changes near sensitive instruments after being created to alert Agency workers to dangerous static buildup near fuel operations and avionics. San Diego s Quasar Federal Systems received a Small Business Innovation Research (SBIR) contract from Kennedy Space Center to develop its remote voltage sensor (RVS), a dime-sized electrometer designed to measure triboelectric changes in the environment. One of the unique qualities of the RVS is that it can detect static at greater distances than previous devices, measuring voltage changes from a few centimeters to a few meters away, due to its much-improved sensitivity.
Potential of plant genetic systems for monitoring and screening mutagens
Nilan, R. A.
1978-01-01
Plants have too long been ignored as useful screening and monitoring systems of environmental mutagens. However, there are about a dozen reliable, some even unique, plant genetic systems that can increase the scope and effectiveness of chemical and physical mutagen screening and monitoring procedures. Some of these should be included in the Tier II tests. Moreover, plants are the only systems now in use as monitors of genetic effects caused by polluted atmosphere and water and by pesticides. There are several major advantages of the plant test systems which relate to their reproductive nature, easy culture and growth habits that should be considered in mutagen screening and monitoring. In addition to these advantages, the major plant test systems exhibit numerous genetic and chromosome changes for determining the effects of mutagens. Some of these have not yet been detected in other nonmammalian and mammalian test systems, but probably occur in the human organism. Plants have played major roles in various aspects of mutagenesis research, primarily in mutagen screening (detection and verification of mutagenic activity), mutagen monitoring, and determining mutagen effects and mechanisms of mutagen action. They have played lesser roles in quantification of mutagenic activity and understanding the nature of induced mutations. Mutagen monitoring with plants, especially in situ on land or in water, will help determine potential genetic hazards of air and water pollutants and protect the genetic purity of crop plants and the purity of the food supply. The Tradescantia stamen-hair system is used in a mobile laboratory for determining the genetic effects of industrial and automobile pollution in a number of sites in the U.S.A. The fern is employed for monitoring genetic effects of water pollution in the Eastern states. The maize pollen system and certain weeds have monitored genetic effects of pesticides. Several other systems that have considerable value and should be developed and more widely used in mutagen monitoring and screening, especially for in situ monitoring, are discussed. Emphasis is placed on pollen systems in which changes in pollen structure, chemistry, and chromosomes can be scored for monitoring; and screening systems which can record low levels of genetic effects as well as provide information on the nature of induced mutations. The value of plant systems for monitoring and screening mutagens can be improved by: greater knowledge of plant cell processes at the molecular and ultrastructural levels; relating these processes to mutagen effects and plant cell responses; improving current systems for increased sensitivity, ease of detecting genetic and chromosome changes, recording of data (including automation), and for extending the range of genetic and chromosome end points; and designing and developing new systems with the aid of previous and current botanical and genetic knowledge. PMID:367768
A statistical power analysis of woody carbon flux from forest inventory data
James A. Westfall; Christopher W. Woodall; Mark A. Hatfield
2013-01-01
At a national scale, the carbon (C) balance of numerous forest ecosystem C pools can be monitored using a stock change approach based on national forest inventory data. Given the potential influence of disturbance events and/or climate change processes, the statistical detection of changes in forest C stocks is paramount to maintaining the net sequestration status of...
The Hungarian congenital malformation monitoring system.
Czeizel, A
1978-01-01
The Hungarian Congenital Malformation Monitor has been operating since 1973 in order to detect the temporal and regional clusters of 12 indicator congenital malformations as early as possible. This Monitor takes part in the International Clearinghouse for Birth Defects Monitoring System. Three continuously increasing trends were detected in 1973--1976. They may be connected with the more complete notifications, although the increase of limb reduction deformities are only partly explained by this factor. Transitional (quarterly) significant clusters were observed in the case of anencephaly (1974, IV), spina bifida (1974, II; and 1975, III; 1976, III), cleft lip +/- cleft palate (1974, III). The possibility of three technical biases (changes in diagnosis, notification and evaluation of the given congenital malformation) has to be excluded before accepting the fact of a real epidemic. Subsequently, a case-control epidemiological study by personal interviews and with matched controls has to be performed.
Fang, Mingxi; Adhikari, Rashmi; Bi, Jianheng; Mazi, Wafa; Dorh, Nethaniah; Wang, Jianbo; Conner, Nathan; Ainsley, Jon; Karabencheva-Christova, Tatyana G; Luo, Fen-Tair; Tiwari, Ashutosh; Liu, Haiying
2017-12-28
We report five fluorescent probes based on coumarin-hybridized fluorescent dyes with spirolactam ring structures (A-E) to detect pH changes in live cell by monitoring visible and near-infrared fluorescence changes. Under physiological or basic conditions, the fluorescent probes A, B, C, D and E preserve their spirolactam ring-closed forms and only display fluorescent peaks in the visible region corresponding to coumarin moieties at 497, 483, 498, 497 and 482 nm, respectively. However, at acidic pH, the rings of the spirolactam forms of the fluorescent probes A, B, C, D and E open up, generating new near-infrared fluorescence peaks at 711, 696, 707, 715, and 697 nm, respectively, through significantly extended π-conjugation to coumarin moieties of the fluorophores. The fluorescent probes B and E can be applied to visualize pH changes by monitoring visible as well as near-infrared fluorescence changes. This helps avoid fluorescence imaging blind spots at neutral or basic pH, which typical pH fluorescent probes encounter. The probes exhibit high sensitivity to pH changes, excellent photostability, low auto-fluorescence background and good cell membrane permeability.
NASA Technical Reports Server (NTRS)
Rehder, J. B. (Principal Investigator)
1973-01-01
The author has identified the following significant results. ERTS-1 has proven to be an effective earth-orbiting monitor of landscape change. Its regional coverage for large areal monitoring has been effective for the detection and mapping of agricultural plowing regions, for general forest cover mapping, for flood mapping, for strip mine mapping, and for short-lived precipitation mapping patterns. Paramount to the entire study has been the temporal coverage provided by ERTS. Without the cyclic coverage on an 18 day basis, temporal coverage would have been inadequate for the detection and mapping of strip mining landscape change, the analysis of agricultural landscape change based on plowing patterns, the analysis of urban-suburban growth changes, and the mapping of the Mississippi River floods. Cost benefits from ERTS are unquestionably superior to aircraft systems in regard to large regional coverage and cyclic temporal parameters. For the analysis of landscape change in large regions such as statewide areas or even areas of 10,000 square miles, ERTS is of cost benefit consideration. Not only does the cost of imagery favor ERTS but the reduction of man-hours using ERTS has been in the magnitude of 1:10.
Hargreaves, Sarah; Hawley, Mark S; Haywood, Annette; Enderby, Pamela M
2017-06-28
Health technologies are being developed to help people living at home manage long-term conditions. One such technology is "lifestyle monitoring" (LM), a telecare technology based on the idea that home activities may be monitored unobtrusively via sensors to give an indication of changes in health-state. However, questions remain about LM technology: how home activities change when participants experience differing health-states; and how sensors might capture clinically important changes to inform timely interventions. The objective of this paper was to report the findings of a study aimed at identifying changes in activity indicative of important changes in health in people with long-term conditions, particularly changes indicative of exacerbation, by exploring the relationship between home activities and health among people with heart failure (HF). We aimed to add to the knowledge base informing the development of home monitoring technologies designed to detect health deterioration in order to facilitate early intervention and avoid hospital admissions. This qualitative study utilized semistructured interviews to explore everyday activities undertaken during the three health-states of HF: normal days, bad days, and exacerbations. Potential recruits were identified by specialist nurses and attendees at an HF support group. The sample was purposively selected to include a range of experience of living with HF. The sample comprised a total of 20 people with HF aged 50 years and above, and 11 spouses or partners of the individuals with HF. All resided in Northern England. Participant accounts revealed that home activities are in part shaped by the degree of intrusion from HF symptoms. During an exacerbation, participants undertook activities specifically to ease symptoms, and detailed activity changes were identified. Everyday activity was also influenced by a range of factors other than health. The study highlights the importance of careful development of LM technology to identify changes in activities that occur during clinically important changes in health. These detailed activity changes need to be considered by developers of LM sensors, platforms, and algorithms intended to detect early signs of deterioration. Results suggest that for LM to move forward, sensor set-up should be personalized to individual circumstances and targeted at individual health conditions. LM needs to take account of the uncertainties that arise from placing technology within the home, in order to inform sensor set-up and data interpretation. This targeted approach is likely to yield more clinically meaningful data and address some of the ethical issues of remote monitoring. ©Sarah Hargreaves, Mark S Hawley, Annette Haywood, Pamela M Enderby. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.06.2017.
Centre of Gravity Plethysmography--A Means of Detecting Mass Transfer of Fluid within the Body.
ERIC Educational Resources Information Center
Buck, Michael
1988-01-01
Describes the monitoring of the redistribution of blood by using a technique which detects changes in the center of gravity of the body. Provides information about the principles and application, construction of apparatus, operating routines, and use of the computer as a recorder. Includes suggested investigations, demonstrations, and diagrams.…
An aquatic macroinvertebrate monitoring program is suggested for 'early warning' detection of toxic discharges to streams in oil shale development areas. Changes in stream biota are used to signal need for increasing levels of chemical analyses to identify and quantify toxic poll...
Lu, Ji-Yun; Liang, Da-Kai; Zhang, Xiao-Li; Zhu, Zhu
2009-12-01
Spectrum of fiber bragg grating (FBG) sensor modulated by double long period grating (LPFG) is proposed in the paper. Double LPFG consists of two LPFGS whose center wavelengths are the same and reflection spectrum of FBG sensor is located in linear range of double LPFG transmission spectrum. Based on spectral analysis of FBG and double LPFG, reflection spectrum of FBG modulated by double LPFG is obtained and studied by use of band-hider filter characteristics for double LPFG. An FBG sensor is attached on the surface of thin steel beam, which is strained by bending, and the center wavelength of FBG sensor will shift. The spectral peak of FBG sensor modulated by double LPFG is changed correspondingly, and the spectral change will lead to variation in exit light intensity from double LPFG. Experiment demonstrates that the relation of filtering light intensity from double LPFG monitored by optical power meter to center wavelength change of FBG sensor is linear and the minimum strain of material (steel beam) detected by the modulation and demodulation system is 1.05 microepsilon. This solution is used in impact monitoring of optical fibre smart structure, and FBG sensor is applied for impulse response signal monitoring induced by low-velocity impact, when impact pendulum is loaded to carbon fiber-reinforced plastics (CFP). The acquired impact response signal and fast Fourier transform of the signal detected by FBG sensor agree with the measurement results of eddy current displacement meter attached to the FBG sensor. From the results, the present method using FBG sensor is found to be effective for monitoring the impact. The research provides a practical reference in dynamic monitoring of optical fiber smart structure field.
Design of intelligent composites with life-cycle health management capabilities
NASA Astrophysics Data System (ADS)
Rosania, Colleen L.; Larrosa, Cecilia C.; Chang, Fu-Kuo
2015-03-01
Use of carbon fiber reinforced polymers (CFRPs) presents challenges because of their complex manufacturing processes and different damage mechanics in relation to legacy metal materials. New monitoring methods for manufacturing, quality verification, damage estimation, and prognosis are needed to use CFRPs safely and efficiently. This work evaluates the development of intelligent composite materials using integrated piezoelectric sensors to monitor the material during cure and throughout service life. These sensors are used to propagate ultrasonic waves through the structure for health monitoring. During manufacturing, data is collected at different stages during the cure cycle, detecting the changing material properties during cure and verifying quality and degree of cure. The same sensors can then be used with previously developed techniques to perform damage detection, such as impact detection and matrix crack density estimation. Real-time damage estimation can be combined with prognostic models to predict future propagation of damage in the material. In this work experimental results will be presented from composite coupons with embedded piezoelectric sensors. Cure monitoring and damage detection results derived from analysis of the ultrasonic sensor signal will be shown. Sensitive signal parameters to the different stimuli in both the time and frequency domains will be explored for this analysis. From these results, use of the same sensor networks from manufacturing throughout the life of the composite material will demonstrate the full life-cycle monitoring capability of these intelligent materials.
Lopez-Meyer, Paulo; Patil, Yogendra; Tiffany, Tiffany; Sazonov, Edward
2013-01-01
Common methods for monitoring of cigarette smoking, such as portable puff-topography instruments or self-report questionnaires, tend to be biased due to conscious or unconscious underreporting. Additionally, these methods may change the natural smoking behavior of individuals. Our long term objective is the development of a wearable non-invasive monitoring system (Personal Automatic Cigarette Tracker - PACT) to reliably monitor cigarette smoking behavior under free living conditions. PACT monitors smoking by observing characteristic breathing patterns of smoke inhalations that follow a cigarette-to-mouth hand gesture. As envisioned, PACT does not rely on self-report or require any conscious effort from the user. A major element of the PACT is a proximity sensor that detects typical cigarette-to-mouth gesture during cigarette smoking. This study describes the design and validation of a prototype RF proximity sensor that captures hand-to-mouth gestures with a high sensitivity (0.90), and a methodology that can reject up to 68% of artifacts gestures originating from activities other than cigarette smoking.
A scalable architecture for online anomaly detection of WLCG batch jobs
NASA Astrophysics Data System (ADS)
Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.
2016-10-01
For data centres it is increasingly important to monitor the network usage, and learn from network usage patterns. Especially configuration issues or misbehaving batch jobs preventing a smooth operation need to be detected as early as possible. At the GridKa data and computing centre we therefore operate a tool BPNetMon for monitoring traffic data and characteristics of WLCG batch jobs and pilots locally on different worker nodes. On the one hand local information itself are not sufficient to detect anomalies for several reasons, e.g. the underlying job distribution on a single worker node might change or there might be a local misconfiguration. On the other hand a centralised anomaly detection approach does not scale regarding network communication as well as computational costs. We therefore propose a scalable architecture based on concepts of a super-peer network.
Detecting insider activity using enhanced directory virtualization.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shin, Dongwan; Claycomb, William R.
2010-07-01
Insider threats often target authentication and access control systems, which are frequently based on directory services. Detecting these threats is challenging, because malicious users with the technical ability to modify these structures often have sufficient knowledge and expertise to conceal unauthorized activity. The use of directory virtualization to monitor various systems across an enterprise can be a valuable tool for detecting insider activity. The addition of a policy engine to directory virtualization services enhances monitoring capabilities by allowing greater flexibility in analyzing changes for malicious intent. The resulting architecture is a system-based approach, where the relationships and dependencies between datamore » sources and directory services are used to detect an insider threat, rather than simply relying on point solutions. This paper presents such an architecture in detail, including a description of implementation results.« less
NASA Technical Reports Server (NTRS)
Baxter, W. J., Jr.; Frant, M. S.; West, S. J.
1978-01-01
Solid-state sensing unit developed for use with NASA's Water-Quality Monitoring System can detect small velocity changes in slow moving fluid. Nonprotruding sensor is applicable to numerous other uses requiring sensitive measurement of slow flows.
The Future of Asthma Monitoring | NIH MedlinePlus the Magazine
... Institute of Biomedical Imaging and Bioengineering (NIBIB) uses biosensors to gather data about environmental and other factors involved in childhood asthma. Biosensors are devices that detect and measure biochemical changes ...
Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991
NASA Technical Reports Server (NTRS)
Mcelroy, James L. (Editor); Mcneal, Robert J. (Editor)
1991-01-01
The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.
Planetary-scale surface water detection from space
NASA Astrophysics Data System (ADS)
Donchyts, G.; Baart, F.; Winsemius, H.; Gorelick, N.
2017-12-01
Accurate, efficient and high-resolution methods of surface water detection are needed for a better water management. Datasets on surface water extent and dynamics are crucial for a better understanding of natural and human-made processes, and as an input data for hydrological and hydraulic models. In spite of considerable progress in the harmonization of freely available satellite data, producing accurate and efficient higher-level surface water data products remains very challenging. This presentation will provide an overview of existing methods for surface water extent and change detection from multitemporal and multi-sensor satellite imagery. An algorithm to detect surface water changes from multi-temporal satellite imagery will be demonstrated as well as its open-source implementation (http://aqua-monitor.deltares.nl). This algorithm was used to estimate global surface water changes at high spatial resolution. These changes include climate change, land reclamation, reservoir construction/decommissioning, erosion/accretion, and many other. This presentation will demonstrate how open satellite data and open platforms such as Google Earth Engine have helped with this research.
Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing
NASA Astrophysics Data System (ADS)
Ya'acob, Norsuzila; Mohd Azize, Aziean Binti; Anis Mahmon, Nur; Laily Yusof, Azita; Farhana Azmi, Nor; Mustafa, Norfazira
2014-03-01
This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.
Impact of ERTS-1 images on management of New Jersey's coastal zone
NASA Technical Reports Server (NTRS)
Feinberg, E. B.; Yunghans, R. S.; Stitt, J. A.; Mairs, R. L.
1974-01-01
The thrust of New Jersey's ERTS investigation is development of procedures for operational use of ERTS-1 data by the Department of Environmental Protection in the management of the State's coastal zone. Four major areas of concern were investigated: detection of land use changes in the coastal zone; monitoring of offshore waste disposal; siting of ocean outfalls; and allocation of funds for shore protection. ERTS imagery was not useful for shore protection purposes; it was of limited practical value in the evaluation of offshore waste disposal and ocean outfall siting. However, ERTS imagery shows great promise for operational detection of land use changes in the coastal zone. Some constraints for practical change detection have been identified.
NASA Astrophysics Data System (ADS)
Zhang, Xin; Lee, Songyi; Liu, Yifan; Lee, Minji; Yin, Jun; Sessler, Jonathan L.; Yoon, Juyoung
2014-04-01
Carbon dioxide (CO2) is an important green house gas. This is providing an incentive to develop new strategies to detect and capture CO2. Achieving both functions within a single molecular system represents an unmet challenge in terms of molecular design and could translate into enhanced ease of use. Here, we report an anion-activated chemosensor system, NAP-chol 1, that permits dissolved CO2 to be detected in organic media via simple color changes or through ratiometric differences in fluorescence intensity. NAP-chol 1 also acts as a super gelator for DMSO. The resulting gel is transformed into a homogeneous solution upon exposure to fluoride anions. Bubbling with CO2 regenerates the gel. Subsequent flushing with N2 or heating serves to release the CO2 and reform the sol form. This series of transformations is reversible and can be followed by easy-to-discern color changes. Thus, NAP-chol 1 allows for the capture and release of CO2 gas while acting as a three mode sensing system. In particular, it permits CO2 to be detected through reversible sol-gel transitions, simple changes in color, or ratiometric monitoring of the differences in the fluorescence features.
Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Apostolakis, Iason-Zacharias; Konofagou, Elisa E.
2015-01-01
Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed High-Intensity Focused Ultrasound (HIFU) treatment monitoring method that utilizes an amplitude-modulated therapeutic ultrasound beam to induce an oscillatory radiation force at the HIFU focus and estimates the focal tissue displacement to monitor the HIFU thermal treatment. In this study, the performance of HMIFU under acoustic, thermal and mechanical effects were investigated. The performance of HMIFU was assessed in ex vivo canine liver specimens (n=13) under slow denaturation or boiling regimes. Passive Cavitation Detector (PCD) was used to assess the acoustic cavitation activity while a bare-wire thermocouple was used to monitor the focal temperature change. During lesioning with slow denaturation, high quality displacements (correlation coefficient above 0.97) were observed under minimum cavitation noise, indicating tissue the initial-softening-then-stiffening property change. During HIFU with boiling, HMIFU monitored a consistent change in lesion-to-background displacement contrast (0.46±0.37) despite the presence of strong cavitation noise due to boiling during lesion formation. Therefore, HMIFU effectively monitored softening-then-stiffening during lesioning under slow denaturation, and detected lesioning under boiling with a distinct change in displacement contrast under boiling in the presence of cavitation. In conclusion, HMIFU was shown effective in HIFU monitoring and lesioning identification without being significantly affected by cavitation noise. PMID:26168177
Malinova, Vesna; von Eckardstein, Kajetan; Rohde, Veit; Mielke, Dorothee
2015-10-01
The intraoperative microvascular Doppler sonography (iMDS) is a well-established tool in vascular surgery for blood flow velocity (BFV) monitoring, capable of detecting vessel occlusion. However, identification of subtotal vessel compromise is more difficult, since the measured BFV may substantially vary with changing insonation angles and insonated vessel segments. To keep these parameters constant we combined neuronavigation with iMDS (niMDS). The question was if niMDS allows the detection of subtotal vessel compromise in aneurysm surgery. During surgery, the 3-dimensional reconstruction of the CT-angiography, which was obtained routinely prior to surgery, was displayed by the neuronavigational system. Prior to clipping, neuronavigation was used to define target point and trajectory, which, by coupling the neuronavigational pointer with the Doppler probe, correspond to the insonated vessel segment and the insonation angle. After clipping, for each vessel segment, the same trajectory was used for all consecutive measurements. The mean BFVs pre- and post-clipping were documented. We performed 82 BFV-measurements in 39 aneurysm surgeries. Mean deviation between pre- and post-clipping BFV values was 2.12cm/s. There was a significant correlation between the mean BFV values before and after clipping (r=0.45 [95% CI 17-66%]; p=0.002). One patient experienced new neurological deficits due to occlusion of a perforating vessel that was not insonated. The study could not answer the question if niMDS can detect BFV changes after clipping indicating vessel compromise, as no subtotal vessel occlusion occurred in the 39 operations. However, we proofed that niMDS-measured BFVs only varied minimally in uncompromised vessels pre- and post-clipping, suggesting that vessel compromises might be easily detected during aneurysm surgery. Copyright © 2015 Elsevier B.V. All rights reserved.
Yoshida, Satoshi; Zhang, Qin-Zeng; Sakuyama, Shu; Matsushima, Satoshi
2009-07-24
The metabolism of dietary fatty acids in human has been measured so far using human blood cells and stable-isotope labeled fatty acids, however, no direct data was available for human peripheral tissues and other major organs. To realize the role of dietary fatty acids in human health and diseases, it would be eager to develop convenient and suitable method to monitor fatty acid metabolism in human. We have developed the measurement system in situ for human lip surface lipids using the Fourier transform infrared spectroscopy (FTIR) - attenuated total reflection (ATR) detection system with special adaptor to monitor metabolic changes of lipids in human body. As human lip surface lipids may not be much affected by skin sebum constituents and may be affected directly by the lipid constituents of diet, we could detect changes of FTIR-ATR spectra, especially at 3005 to approximately 3015 cm(-1), of lip surface polyunsaturated fatty acids in a duration time-dependent manner after intake of the docosahexaenoic acid (DHA)-containing triglyceride diet. The ingested DHA appeared on the lip surface and was detected by FTIR-ATR directly and non-invasively. It was found that the metabolic rates of DHA for male volunteer subjects with age 60s were much lower than those with age 20s. Lipid hydroperoxides were found in lip lipids which were extracted from the lip surface using a mixture of ethanol/ethylpropionate/iso-octane solvents, and were the highest in the content just before noon. The changes of lipid hydroperoxides were detected also in situ with FTIR-ATR at 968 cm(-1). The measurements of lip surface lipids with FTIR-ATR technique may advance the investigation of human lipid metabolism in situ non-invasively.
Immune monitoring of clinical trials with biotherapies.
Whiteside, Theresa L
2008-01-01
Immune monitoring of biotherapy clinical trials has undergone a considerable change in recent years. Technical advances together with new insights into molecular immunology have ushered a new genre of assays into immune monitoring. Single-cell assays, multiplex profiling, and signaling molecule detection have replaced formerly used bulk assays, such as proliferation or cytotoxicity. The emphasis on immune cell functions and quantitation of antigen-specific T cells has been playing a major role in attempts to establish correlations between therapy-induced alterations in immune responses and clinical endpoints. However, this has been an elusive goal to achieve, and there is a special need for improving the quality of serial monitoring to ensure that it adequately and reliably measures changes induced by administered biotherapy. In this respect, monitoring performed in specialized reference laboratories operating as good laboratory practice (GLP) facilities and strengthening of interactions between the clinical investigator, the clinical immunologist, and the biostatistician are crucial for successful use of immune monitoring in clinical studies.
NASA Astrophysics Data System (ADS)
Ortiz, Ramon; Berrocoso, Manuel; Marrero, Jose Manuel; Fernandez-Ros, Alberto; Prates, Gonçalo; De la Cruz-Reyna, Servando; Garcia, Alicia
2014-05-01
In volcanic areas with long repose periods (as El Hierro), recently installed monitoring networks offer no instrumental record of past eruptions nor experience in handling a volcanic crisis. Both conditions, uncertainty and inexperience, contribute to make the communication of hazard more difficult. In fact, in the initial phases of the unrest at El Hierro, the perception of volcanic risk was somewhat distorted, as even relatively low volcanic hazards caused a high political impact. The need of a Volcanic Alert System became then evident. In general, the Volcanic Alert System is comprised of the monitoring network, the software tools for the analysis of the observables, the management of the Volcanic Activity Level, and the assessment of the threat. The Volcanic Alert System presented here places special emphasis on phenomena associated to moderate eruptions, as well as on volcano-tectonic earthquakes and landslides, which in some cases, as in El Hierro, may be more destructive than an eruption itself. As part of the Volcanic Alert System, we introduce here the Volcanic Activity Level which continuously applies a routine analysis of monitoring data (particularly seismic and deformation data) to detect data trend changes or monitoring network failures. The data trend changes are quantified according to the Failure Forecast Method (FFM). When data changes and/or malfunctions are detected, by an automated watchdog, warnings are automatically issued to the Monitoring Scientific Team. Changes in the data patterns are then translated by the Monitoring Scientific Team into a simple Volcanic Activity Level, that is easy to use and understand by the scientists and technicians in charge for the technical management of the unrest. The main feature of the Volcanic Activity Level is its objectivity, as it does not depend on expert opinions, which are left to the Scientific Committee, and its capabilities for early detection of precursors. As a consequence of the El Hierro experience we consider the objectivity of the Volcanic Activity Level a powerful tool to focus the discussions in a Scientific Committee on the activity forecast and on the expected scenarios, rather than on the multiple explanations of the data fluctuations, which is one of the main sources of conflict in the Scientific Committee discussions. Although the Volcanic Alert System was designed specifically for the unrest episodes at El Hierro, the involved methodologies may be applied to other situations of unrest.
Parr, T W; Sier, A R J; Battarbee, R W; Mackay, A; Burgess, J
2003-07-01
Widespread concern over the state of the environment and the impacts of anthropogenic activities on ecosystem services and functions has highlighted the need for high-quality, long-term datasets for detecting and understanding environmental change. In July 2001, an international conference reviewed progress in the field of long-term ecosystem research and monitoring (LTERM). Examples are given which demonstrate the need for long-term environmental monitoring and research, for palaeoecological reconstructions of past environments and for applied use of historical records that inform us of past environmental conditions. LTERM approaches are needed to provide measures of baseline conditions and for informing decisions on ecosystem management and environmental policy formulation. They are also valuable in aiding the understanding of the processes of environmental change, including the integrated effects of natural and anthropogenic drivers and pressures, recovery from stress and resilience of species, populations, communities and ecosystems. The authors argue that, in order to realise the full potential of LTERM approaches, progress must be made in four key areas: (i) increase the number, variety and scope of LTERM activities to help define the operational range of ecosystems; (ii) greater integration of research, monitoring, modelling, palaeoecological reconstruction and remote sensing to create a broad-scale early warning system of environmental change; (iii) development of inter-disciplinary approaches which draw upon social and environmental science expertise to understand the factors determining the vulnerability and resilience of the nature-society system to change; and (iv) more and better use of LTERM data and information to inform the public and policymakers and to provide guidance on sustainable development.
Kranzfelder, Michael; Zywitza, Dorit; Jell, Thomas; Schneider, Armin; Gillen, Sonja; Friess, Helmut; Feussner, Hubertus
2012-06-15
Technical progress in the surgical operating room (OR) increases constantly, facilitating the development of intelligent OR systems functioning as "safety backup" in the background of surgery. Precondition is comprehensive data retrieval to identify imminent risky situations and inaugurate adequate security mechanisms. Radio-frequency-identification (RFID) technology may have the potential to meet these demands. We set up a pilot study investigating feasibility and appliance reliability of a stationary RFID system for real-time surgical sponge monitoring (passive tagged sponges, position monitoring: mayo-stand/abdominal situs/waste bucket) and OR team tracking (active transponders, position monitoring: right/left side of OR table). In vitro: 20/20 sponges (100%) were detected on the mayo-stand and within the OR-phantom, however, real-time detection accuracy declined to 7/20 (33%) when the tags were moved simultaneously. All retained sponges were detected correctly. In vivo (animal): 7-10/10 sterilized sponges (70%-100%) were detected correctly within the abdominal cavity. OR-team: detection accuracy within the OR (surveillance antenna) and on both sides of the OR table (sector antenna) was 100%. Mean detection time for position change (left to right side and contrariwise) was 30-60 s. No transponder failure was noted. This is the first combined RFID system that has been developed for stationary use in the surgical OR. Preclinical evaluation revealed a reliable sponge tracking and correct detection of retained textiles (passive RFID) but also demonstrated feasibility of comprehensive data acquisition of team motion (active RFID). However, detection accuracy needs to be further improved before implementation into the surgical OR. Copyright © 2012 Elsevier Inc. All rights reserved.
Multivariate analysis of gamma spectra to characterize used nuclear fuel
Coble, Jamie; Orton, Christopher; Schwantes, Jon
2017-01-17
The Multi-Isotope Process (MIP) Monitor provides an efficient means to monitor the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of key stages in the reprocessing stream in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor; PWR and BWR, respectively), initial enrichment, burn up, and cooling time. Simulated gammamore » spectra were used in this paper to develop and test three fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type for the three PWR and three BWR reactor designs studied. Locally weighted PLS models were fitted on-the-fly to estimate the remaining fuel characteristics. For the simulated gamma spectra considered, burn up was predicted with 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment with approximately 2% RMSPE. Finally, this approach to automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and to inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters that may indicate issues with operational control or malicious activities.« less
Multivariate analysis of gamma spectra to characterize used nuclear fuel
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coble, Jamie; Orton, Christopher; Schwantes, Jon
The Multi-Isotope Process (MIP) Monitor provides an efficient means to monitor the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of key stages in the reprocessing stream in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor; PWR and BWR, respectively), initial enrichment, burn up, and cooling time. Simulated gammamore » spectra were used in this paper to develop and test three fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type for the three PWR and three BWR reactor designs studied. Locally weighted PLS models were fitted on-the-fly to estimate the remaining fuel characteristics. For the simulated gamma spectra considered, burn up was predicted with 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment with approximately 2% RMSPE. Finally, this approach to automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and to inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters that may indicate issues with operational control or malicious activities.« less
Optical monitoring of kidney oxygenation and hemodynamics using a miniaturized near-infrared sensor
NASA Astrophysics Data System (ADS)
Shadgan, Babak; Macnab, Andrew; Nigro, Mark; Nguan, Christopher
2017-02-01
Background: Following human renal allograft transplant primary graft dysfunction can occur early in the postoperative period as a result of acute tubular necrosis, acute rejection, drug toxicity, and vascular complications. Successful treatment of graft dysfunction requires early detection and accurate diagnosis so that disease-specific medical and/or surgical intervention can be provided promptly. However, current diagnostic methods are not sensitive or specific enough, so that identifying the cause of graft dysfunction is problematic and often delayed. Near-infrared spectroscopy (NIRS) is an established optical method that monitors changes in tissue hemodynamics and oxygenation in real time. We report the feasibility of directly monitoring kidney the kidney in an animal model using NIRS to detect renal ischemia and hypoxia. Methods: In an anesthetized pig, a customized continuous wave spatially resolved (SR) NIRS sensor was fixed directly to the surface of the surgically exposed kidney. Changes in the concentration of oxygenated (O2Hb) deoxygenated (HHb) and total hemoglobin (THb) were monitored before, during and after renal artery clamping and reperfusion, and the resulting fluctuations in chromophore concentration from baseline used to measure variations in renal perfusion and oxygenation. Results: On clamping the renal artery THb and O2Hb concentrations declined progressively while HHb rose. With reperfusion after releasing the artery clamp O2Hb and THb rose while HHb fell with all parameters returning to its baseline. This pattern was similar in all three trials. Conclusion: This pilot study indicates that a miniaturized NIRS sensor applied directly to the surface of a kidney in an animal model can detect the onset of renal ischemia and tissue hypoxia. With modification, our NIRS-based method may contribute to early detection of renal vascular complications and graft dysfunction following renal transplant.
Krajewski, Stefanie; Krauss, Sabrina; Kurz, Julia; Neumann, Bernd; Schlensak, Christian; Wendel, Hans P
2014-03-01
In patients undergoing cardiac surgery with heart-lung machine support, adequate anticoagulation to mitigate blood clotting caused by the artificial surfaces of the extracorporeal circulation (ECC) system is essential. These patients routinely receive heparin, whose effectiveness is monitored by measurements of the activated clotting time (ACT). However, ACT values only poorly correlate with the actual hemostatic status. The aim of our study was to evaluate the detection of free thrombin in heparinized human blood as a monitor of anticoagulation during ECC. Human whole blood was anticoagulated with different concentrations of heparin (0.75, 1, 2 or 3 IU/ml) and circulated in the Chandler-loop model for up to 240 min at 37 °C. Next to ACT, ECC-mediated changes in free active thrombin, prothrombin fragment 1+2 (F1+2) and thrombin-antithrombin-III (TAT) levels were measured before and during circulation. Platelet activation and cell count parameters were further investigated. Our study shows that detection of ECC-mediated changes in free thrombin is possible in blood anticoagulated with 0.75 or 1 IU/ml heparin, whereas no thrombin was detectable at higher heparin concentrations. Thrombin generation during 240 min of ECC is comparable to F 1+2 and TAT plasma levels during ECC. Thrombin is the key enzyme in the coagulation cascade and hence represents a promising marker for monitoring the coagulation status of patients. Although detection of free thrombin was not feasible at high heparin concentrations, the employed test represents an additional test to current laboratory methods investigating blood coagulation at low heparin concentrations. Copyright © 2013 Elsevier Ltd. All rights reserved.
Toward Failure Modeling In Complex Dynamic Systems: Impact of Design and Manufacturing Variations
NASA Technical Reports Server (NTRS)
Tumer, Irem Y.; McAdams, Daniel A.; Clancy, Daniel (Technical Monitor)
2001-01-01
When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes during a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the. modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle vibration monitoring systems.
NASA Technical Reports Server (NTRS)
Bozeman, Richard J., Jr. (Inventor)
1990-01-01
The invention relates to monitoring circuitry for the real time detection of vibrations of a predetermined frequency and which are greater than a predetermined magnitude. The circuitry produces an instability signal in response to such detection. The circuitry is particularly adapted for detecting instabilities in rocket thrusters, but may find application with other machines such as expensive rotating machinery, or turbines. The monitoring circuitry identifies when vibration signals are present having a predetermined frequency of a multi-frequency vibration signal which has an RMS energy level greater than a predetermined magnitude. It generates an instability signal only if such a vibration signal is identified. The circuitry includes a delay circuit which responds with an alarm signal only if the instability signal continues for a predetermined time period. When used with a rocket thruster, the alarm signal may be used to cut off the thruster if such thruster is being used in flight. If the circuitry is monitoring tests of the thruster, it generates signals to change the thruster operation, for example, from pulse mode to continuous firing to determine if the instability of the thruster is sustained once it is detected.
Optical fiber extrinsic Fabry-Perot interferometric (EFPI)-based biosensors
NASA Astrophysics Data System (ADS)
Elster, Jennifer L.; Jones, Mark E.; Evans, Mishell K.; Lenahan, Shannon M.; Boyce, Christopher A.; Velander, William H.; VanTassell, Roger
2000-05-01
A novel system incorporating optical fiber extrinsic Fabry- Perot interferometric (EFPI)-based sensors for rapid detection of biological targets is presented. With the appropriate configuration, the EFPI senor is able to measure key environmental parameters by monitoring the interferometric fringes resulting from an optical path differences of reflected signals. The optical fiber EFPI sensor has been demonstrated for strain, pressure, and temperature measurements and can be readily modified for refractive index measurements by allowing solutions to flow into an open cavity. The sensor allows for highly sensitive, real-time, refractive index measurements and by applying affinity coatings containing ligands within this cavity, specific binding of target molecules can be accomplished. As target molecules bind to the coating, there is an increased density within the film, causing a measurable refractive index change that correlates to the concentration of detected target molecules. This sensor platform offers enhanced sensing capabilities for clinical diagnostics, pharmaceutical screening, environmental monitoring, food pathogen detection, biological warfare agent detection, and industrial bioprocessing. Promising applications also exist for process monitoring within the food/beverage, petroleum, and chemical industry.
A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring
NASA Astrophysics Data System (ADS)
Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang
2017-07-01
Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.
Smith, L.L.; Barichivich, W.J.; Staiger, J.S.; Smith, Kimberly G.; Dodd, C.K.
2006-01-01
We conducted an amphibian inventory at Okefenokee National Wildlife Refuge from August 2000 to June 2002 as part of the U.S. Department of the Interior's national Amphibian Research and Monitoring Initiative. Nineteen species of amphibians (15 anurans and 4 caudates) were documented within the Refuge, including one protected species, the Gopher Frog Rana capito. We also collected 1 y of monitoring data for amphibian populations and incorporated the results into the inventory. Detection probabilities and site occupancy estimates for four species, the Pinewoods Treefrog (Hyla femoralis), Pig Frog (Rana grylio), Southern Leopard Frog (R. sphenocephala) and Carpenter Frog (R. virgatipes) are presented here. Detection probabilities observed in this study indicate that spring and summer surveys offer the best opportunity to detect these species in the Refuge. Results of the inventory suggest that substantial changes may have occurred in the amphibian fauna within and adjacent to the swamp. However, monitoring the amphibian community of Okefenokee Swamp will prove difficult because of the logistical challenges associated with a rigorous statistical assessment of status and trends.
Early warning of changing drinking water quality by trend analysis.
Tomperi, Jani; Juuso, Esko; Leiviskä, Kauko
2016-06-01
Monitoring and control of water treatment plants play an essential role in ensuring high quality drinking water and avoiding health-related problems or economic losses. The most common quality variables, which can be used also for assessing the efficiency of the water treatment process, are turbidity and residual levels of coagulation and disinfection chemicals. In the present study, the trend indices are developed from scaled measurements to detect warning signs of changes in the quality variables of drinking water and some operating condition variables that strongly affect water quality. The scaling is based on monotonically increasing nonlinear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. Deviation indices are used to assess the severity of situations. The study shows the potential of the described trend analysis as a predictive monitoring tool, as it provides an advantage over the traditional manual inspection of variables by detecting changes in water quality and giving early warnings.
Wang, Dan; Singhasemanon, Nan; Goh, Kean S
2016-11-15
Pesticides are routinely monitored in surface waters and resultant data are analyzed to assess whether their uses will damage aquatic eco-systems. However, the utility of the monitoring data is limited because of the insufficiency in the temporal and spatial sampling coverage and the inability to detect and quantify trace concentrations. This study developed a novel assessment procedure that addresses those limitations by combining 1) statistical methods capable of extracting information from concentrations below changing detection limits, 2) statistical resampling techniques that account for uncertainties rooted in the non-detects and insufficient/irregular sampling coverage, and 3) multiple lines of evidence that improve confidence in the final conclusion. This procedure was demonstrated by an assessment on chlorpyrifos monitoring data in surface waters of California's Central Valley (2005-2013). We detected a significant downward trend in the concentrations, which cannot be observed by commonly-used statistical approaches. We assessed that the aquatic risk was low using a probabilistic method that works with non-detects and has the ability to differentiate indicator groups with varying sensitivity. In addition, we showed that the frequency of exceedance over ambient aquatic life water quality criteria was affected by pesticide use, precipitation and irrigation demand in certain periods anteceding the water sampling events. Copyright © 2016 Elsevier B.V. All rights reserved.
Algorithm-based arterial blood sampling recognition increasing safety in point-of-care diagnostics.
Peter, Jörg; Klingert, Wilfried; Klingert, Kathrin; Thiel, Karolin; Wulff, Daniel; Königsrainer, Alfred; Rosenstiel, Wolfgang; Schenk, Martin
2017-08-04
To detect blood withdrawal for patients with arterial blood pressure monitoring to increase patient safety and provide better sample dating. Blood pressure information obtained from a patient monitor was fed as a real-time data stream to an experimental medical framework. This framework was connected to an analytical application which observes changes in systolic, diastolic and mean pressure to determine anomalies in the continuous data stream. Detection was based on an increased mean blood pressure caused by the closing of the withdrawal three-way tap and an absence of systolic and diastolic measurements during this manipulation. For evaluation of the proposed algorithm, measured data from animal studies in healthy pigs were used. Using this novel approach for processing real-time measurement data of arterial pressure monitoring, the exact time of blood withdrawal could be successfully detected retrospectively and in real-time. The algorithm was able to detect 422 of 434 (97%) blood withdrawals for blood gas analysis in the retrospective analysis of 7 study trials. Additionally, 64 sampling events for other procedures like laboratory and activated clotting time analyses were detected. The proposed algorithm achieved a sensitivity of 0.97, a precision of 0.96 and an F1 score of 0.97. Arterial blood pressure monitoring data can be used to perform an accurate identification of individual blood samplings in order to reduce sample mix-ups and thereby increase patient safety.
Numerical modeling of time-lapse monitoring of CO2 sequestration in a layered basalt reservoir
Khatiwada, M.; Van Wijk, K.; Clement, W.P.; Haney, M.
2008-01-01
As part of preparations in plans by The Big Sky Carbon Sequestration Partnership (BSCSP) to inject CO2 in layered basalt, we numerically investigate seismic methods as a noninvasive monitoring technique. Basalt seems to have geochemical advantages as a reservoir for CO2 storage (CO2 mineralizes quite rapidly while exposed to basalt), but poses a considerable challenge in term of seismic monitoring: strong scattering from the layering of the basalt complicates surface seismic imaging. We perform numerical tests using the Spectral Element Method (SEM) to identify possibilities and limitations of seismic monitoring of CO2 sequestration in a basalt reservoir. While surface seismic is unlikely to detect small physical changes in the reservoir due to the injection of CO2, the results from Vertical Seismic Profiling (VSP) simulations are encouraging. As a perturbation, we make a 5%; change in wave velocity, which produces significant changes in VSP images of pre-injection and post-injection conditions. Finally, we perform an analysis using Coda Wave Interferometry (CWI), to quantify these changes in the reservoir properties due to CO2 injection.
NASA Technical Reports Server (NTRS)
Kessel, C.; Wickens, C. D.
1978-01-01
The development of the internal model as it pertains to the detection of step changes in the order of control dynamics is investigated for two modes of participation: whether the subjects are actively controlling those dynamics or are monitoring an autopilot controlling them. A transfer of training design was used to evaluate the relative contribution of proprioception and visual information to the overall accuracy of the internal model. Sixteen subjects either tracked or monitored the system dynamics as a 2-dimensional pursuit display under single task conditions and concurrently with a sub-critical tracking task at two difficulty levels. Detection performance was faster and more accurate in the manual as opposed to the autopilot mode. The concurrent tracking task produced a decrement in detection performance for all conditions though this was more marked for the manual mode. The development of an internal model in the manual mode transferred positively to the automatic mode producing enhanced detection performance. There was no transfer from the internal model developed in the automatic mode to the manual mode.
Optical monitoring of spinal cord hemodynamics, a feasibility study
NASA Astrophysics Data System (ADS)
Shadgan, Babak; Kwon, Brian K.; Streijger, Femke; Manouchehri, Neda; So, Kitty; Shortt, Katelyn; Cripton, Peter A.; Macnab, Andrew
2017-02-01
Background: After an acute traumatic spinal cord injury (SCI), the spinal cord is subjected to ischemia, hypoxia, and increased hydrostatic pressure which exacerbate further secondary damage and neuronal deficit. The purpose of this pilot study was to explore the use of near infrared spectroscopy (NIRS) for non-invasive and real-time monitoring of these changes within the injured spinal cord in an animal model. NIRS is a non-invasive optical technique that utilizes light in the near infrared spectrum to monitor changes in the concentration of tissue chromophores from which alterations in tissues oxygenation and perfusion can be inferred in real time. Methods: A custom-made miniaturized NIRS sensor was developed to monitor spinal cord hemodynamics and oxygenation noninvasively and in real time simultaneously with invasive, intraparenchymal monitoring in a pig model of SCI. The spinal cord around the T10 injury site was instrumented with intraparenchymal probes inserted directly into the spinal cord to measure oxygen pressure, blood flow, and hydrostatic pressure, and the same region of the spinal cord was monitored with the custom-designed extradural NIRS probe. We investigated how well the extradural NIRS probe detected intraparenchymal changes adjacent to the injury site after alterations in systemic blood pressure, global hypoxia, and traumatic injury generated by a weight-drop contusion. Results: The NIRS sensor successfully identified periods of systemic hypoxia, re-ventilation and changes in spinal cord perfusion and oxygenation during alterations of mean arterial pressure and following spinal cord injury. Conclusion: This pilot study indicates that extradural NIRS monitoring of the spinal cord is feasible as a non-invasive optical method to identify changes in spinal cord hemodynamics and oxygenation in real time. Further development of this technique would allow clinicians to monitor real-time physiologic changes within the injured spinal cord during the acute post-injury period.
Lane, John W.; Day-Lewis, Frederick D.; Johnson, Carole D.; Joesten, Peter K.; Kochiss, Christopher S.
2007-01-01
Based on the geophysical data, conceptual models of the distributions of emulsified vegetable oil and ground water with altered chemistry were developed. The field data indicate that, in several cases, the plume of ground water with altered chemistry would not be detected by direct chemical sampling given the construction of monitoring wells; hence the geophysical data provide valuable site-specific insights for the interpretation of water samples and monitoring of biostimulation projects. Application of geophysical methods to data from the ACP demonstrated the utility of radar for monitoring biostimulation injections.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Nan; Zhu, Wenquan; Zheng, Zhoutao
The long-term Normalized Difference Vegetation Index (NDVI) time-series data set generated from the Advanced Very High Resolution Radiometers (AVHRR) has been widely used to monitor vegetation activity change. The third version of NDVI (NDVI3g) produced by the Global Inventory Modeling and Mapping Studies (GIMMS) group was released recently. The comparisons between the new and old versions should be conducted for linking existing studies with future applications of NDVI3g in monitoring vegetation activity change. Based on simple and piecewise linear regression methods, this research made a comparative analysis between NDVIg and NDVI3g for monitoring vegetation activity change and its responses tomore » climate change in the middle and high latitudes of the Northern Hemisphere during 1982–2008. Our results indicated that there were large differences between NDVIg and NDVI3g in the spatial patterns for both the overall changing trends and the timing of Turning Points (TP) in NDVI time series, which spread over almost the entire study region. The average NDVI trend from NDVI3g was almost twice as great as that from NDVIg and the detected average timing of TP from NDVI3g was about one year later. Although the general spatial patterns were consistent between two data sets for detecting the responses of growing-season NDVI to temperature and precipitation changes, there were large differences in the response magnitude, with a higher response magnitude to temperature in NDVI3g and an opposite response to precipitation change for the two data sets. Finally, these results demonstrated that the NDVIg data set may underestimate the vegetation activity change trend and its response to climate change in the middle and high latitudes of the Northern Hemisphere during the past three decades.« less
Vanishing tattoo multi-sensor for biomedical diagnostics
NASA Astrophysics Data System (ADS)
Moczko, E.; Meglinski, I.; Piletsky, S.
2008-04-01
Currently, precise non-invasive diagnostics systems for the real-time multi detection and monitoring of physiological parameters and chemical analytes in the human body are urgently required by clinicians, physiologists and bio-medical researchers. We have developed a novel cost effective smart 'vanishing tattoo' (similar to temporary child's tattoos) consisting of environmental-sensitive dyes. Painlessly impregnated into the skin the smart tattoo is capable of generating optical/fluorescence changes (absorbance, transmission, reflectance, emission and/or luminescence within UV, VIS or NIR regions) in response to physical or chemical changes. These changes allow the identification of colour pattern changes similar to bar-code scanning. Such a system allows an easy, cheap and robust comprehensive detection of various parameters and analytes in a small volume of sample (e.g. variations in pH, temperature, ionic strength, solvent polarity, presence of redox species, surfactants, oxygen). These smart tattoos have possible applications in monitoring the progress of disease and transcutaneous drug delivery. The potential of this highly innovative diagnostic tool is wide and diverse and can impact on routine clinical diagnostics, general therapeutic management, skin care and cosmetic products testing as well as fundamental physiological investigations.
Vanishing "tattoo" multisensor for biomedical diagnostics
NASA Astrophysics Data System (ADS)
Moczko, E.; Meglinski, I.; Piletsky, S.
2008-02-01
Currently, precise non-invasive diagnostics systems for the real-time multi detection and monitoring of physiological parameters and chemical analytes in the human body are urgently required by clinicians, physiologists and bio-medical researchers. We have developed a novel cost effective smart 'vanishing tattoo' (similar to temporary child's tattoos) consisting of environmental-sensitive dyes. Painlessly impregnated into the skin the smart tattoo is capable of generating optical/fluorescence changes (absorbance, transmission, reflectance, emission and/or luminescence within UV, VIS or NIR regions) in response to physical or chemical changes. These changes allow the identification of colour pattern changes similar to bar-code scanning. Such a system allows an easy, cheap and robust comprehensive detection of various parameters and analytes in a small volume of sample (e.g. variations in pH, temperature, ionic strength, solvent polarity, presence of redox species, surfactants, oxygen). These smart tattoos have possible applications in monitoring the progress of disease and transcutaneous drug delivery. The potential of this highly innovative diagnostic tool is wide and diverse and can impact on routine clinical diagnostics, general therapeutic management, skin care and cosmetic products testing as well as fundamental physiological investigations.
4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR
NASA Astrophysics Data System (ADS)
Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas
2016-04-01
The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten, Austria) and an agricultural maize crop stand (Heidelberg, Germany). This research demonstrates the potential and also limitations of fully automated, near real-time 4D LiDAR monitoring in geosciences.
A multi-modal approach for activity classification and fall detection
NASA Astrophysics Data System (ADS)
Castillo, José Carlos; Carneiro, Davide; Serrano-Cuerda, Juan; Novais, Paulo; Fernández-Caballero, Antonio; Neves, José
2014-04-01
The society is changing towards a new paradigm in which an increasing number of old adults live alone. In parallel, the incidence of conditions that affect mobility and independence is also rising as a consequence of a longer life expectancy. In this paper, the specific problem of falls of old adults is addressed by devising a technological solution for monitoring these users. Video cameras, accelerometers and GPS sensors are combined in a multi-modal approach to monitor humans inside and outside the domestic environment. Machine learning techniques are used to detect falls and classify activities from accelerometer data. Video feeds and GPS are used to provide location inside and outside the domestic environment. It results in a monitoring solution that does not imply the confinement of the users to a closed environment.
Power of sign surveys to monitor population trend
Kendall, Katherine C.; Metzgar, Lee H.; Patterson, David A.; Steele, Brian M.
1992-01-01
The urgent need for an effective monitoring scheme for grizzly bear (Ursus arctos) populations led us to investigate the effort required to detect changes in populations of low—density dispersed animals, using sign (mainly scats and tracks) they leave on trails. We surveyed trails in Glacier National Park for bear tracks and scats during five consecutive years. Using these data, we modeled the occurrence of bear sign on trails, then estimated the power of various sampling schemes. Specifically, we explored the power of bear sign surveys to detect a 20% decline in sign occurrence. Realistic sampling schemes appear feasible if the density of sign is high enough, and we provide guidelines for designs with adequate replication to monitor long—term trends of dispersed populations using sign occurrences on trails.
Thirumala, Parthasarathy D; Crammond, Donald J; Loke, Yoon K; Cheng, Hannah L; Huang, Jessie; Balzer, Jeffrey R
2017-03-01
OBJECTIVE The goal of this study was to evaluate the efficacy of intraoperative transcranial motor evoked potential (TcMEP) monitoring in predicting an impending neurological deficit during corrective spinal surgery for patients with idiopathic scoliosis (IS). METHODS The authors searched the PubMed and Web of Science database for relevant lists of retrieved reports and/or experiments published from January 1950 through October 2014 for studies on TcMEP monitoring use during IS surgery. The primary analysis of this review fit the operating characteristic into a hierarchical summary receiver operating characteristic curve model to determine the efficacy of intraoperative TcMEP-predicted change. RESULTS Twelve studies, with a total of 2102 patients with IS were included. Analysis found an observed incidence of neurological deficits of 1.38% (29/2102) in the sample population. Of the patients who sustained a neurological deficit, 82.8% (24/29) also had irreversible TcMEP change, whereas 17.2% (5/29) did not. The pooled analysis using the bivariate model showed TcMEP change with sensitivity (mean 91% [95% CI 34%-100%]) and specificity (mean 96% [95% CI 92-98%]). The diagnostic odds ratio indicated that it is 250 times more likely to observe significant TcMEP changes in patients who experience a new-onset motor deficit immediately after IS correction surgery (95% CI 11-5767). TcMEP monitoring showed high discriminant ability with an area under the curve of 0.98. CONCLUSIONS A patient with a new neurological deficit resulting from IS surgery was 250 times more likely to have changes in TcMEPs than a patient without new deficit. The authors' findings from 2102 operations in patients with IS show that TcMEP monitoring is a highly sensitive and specific test for detecting new spinal cord injuries in patients undergoing corrective spinal surgery for IS. They could not assess the value of TcMEP monitoring as a therapeutic adjunct owing to the limited data available and their study design.
a Landsat Time-Series Stacks Model for Detection of Cropland Change
NASA Astrophysics Data System (ADS)
Chen, J.; Chen, J.; Zhang, J.
2017-09-01
Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.
A novel framework for the use of remote sensing for monitoring catchments at continental scales.
Bugnot, A B; Lyons, M B; Scanes, P; Clark, G F; Fyfe, S K; Lewis, A; Johnston, E L
2018-07-01
Historical ecology can teach us valuable lessons on the processes and drivers of environmental change that can inform future monitoring priorities and management strategies. Environmental data to study environmental history, however, is often absent or of low quality. Even when studying changes occurring during the last few decades, monitoring efforts are scarce due to logistical and cost limitations, leaving large areas unassessed. The aim of this study is to evaluate the use of estuarine water colour as an indicator of historical environmental change in catchments. Water colour change was assessed in estuaries in Australia from 1987 to 2015 using satellite remote sensing. Random points were selected for each estuary and applied to the Australian Geoscience Data Cube (based on Landsat images) to obtain reflectance data through time. We propose a framework where (i) water colour is used to detect historical changes in catchments using generalised additive models, (ii) possible stressors and pressures driving those changes are evaluated using other available historical data, and (iii) lessons learned inform appropriate monitoring and management actions. This framework represents a novel approach to generate historical data for large-scale assessments of environmental change at catchment level, even in poorly studied areas. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
A service relation model for web-based land cover change detection
NASA Astrophysics Data System (ADS)
Xing, Huaqiao; Chen, Jun; Wu, Hao; Zhang, Jun; Li, Songnian; Liu, Boyu
2017-10-01
Change detection with remotely sensed imagery is a critical step in land cover monitoring and updating. Although a variety of algorithms or models have been developed, none of them can be universal for all cases. The selection of appropriate algorithms and construction of processing workflows depend largely on the expertise of experts about the "algorithm-data" relations among change detection algorithms and the imagery data used. This paper presents a service relation model for land cover change detection by integrating the experts' knowledge about the "algorithm-data" relations into the web-based geo-processing. The "algorithm-data" relations are mapped into a set of web service relations with the analysis of functional and non-functional service semantics. These service relations are further classified into three different levels, i.e., interface, behavior and execution levels. A service relation model is then established using the Object and Relation Diagram (ORD) approach to represent the multi-granularity services and their relations for change detection. A set of semantic matching rules are built and used for deriving on-demand change detection service chains from the service relation model. A web-based prototype system is developed in .NET development environment, which encapsulates nine change detection and pre-processing algorithms and represents their service relations as an ORD. Three test areas from Shandong and Hebei provinces, China with different imagery conditions are selected for online change detection experiments, and the results indicate that on-demand service chains can be generated according to different users' demands.
Spatial and Temporal Monitoring Resolutions for CO2 Leakage Detection at Carbon Storage Sites
NASA Astrophysics Data System (ADS)
Yang, Y. M.; Dilmore, R. M.; Daley, T. M.; Carroll, S.; Mansoor, K.; Gasperikova, E.; Harbert, W.; Wang, Z.; Bromhal, G. S.; Small, M.
2016-12-01
Different leakage monitoring techniques offer different strengths in detection sensitivity, coverage, feedback time, cost, and technology availability, such that they may complement each other when applied together. This research focuses on quantifying the spatial coverage and temporal resolution of detection response for several geophysical remote monitoring and direct groundwater monitoring techniques for an optimal monitoring plan for CO2 leakage detection. Various monitoring techniques with different monitoring depths are selected: 3D time-lapse seismic survey, wellbore pressure, groundwater chemistry and soil gas. The spatial resolution in terms of leakage detectability is quantified through the effective detection distance between two adjacent monitors, given the magnitude of leakage and specified detection probability. The effective detection distances are obtained either from leakage simulations with various monitoring densities or from information garnered from field test data. These spatial leakage detection resolutions are affected by physically feasible monitoring design and detection limits. Similarly, the temporal resolution, in terms of leakage detectability, is quantified through the effective time to positive detection of a given size of leak and a specified detection probability, again obtained either from representative leakage simulations with various monitoring densities or from field test data. The effective time to positive detection is also affected by operational feedback time (associated with sampling, sample analysis and data interpretation), with values obtained mainly through expert interviews and literature review. In additional to the spatial and temporal resolutions of these monitoring techniques, the impact of CO2 plume migration speed and leakage detection sensitivity of each monitoring technique are also discussed with consideration of how much monitoring is necessary for effective leakage detection and how these monitoring techniques can be better combined in a time-space framework. The results of the spatial and temporal leakage detection resolutions for several geophysical monitoring techniques and groundwater monitoring are summarized to inform future monitoring designs at carbon storage sites.
Ellingsen, Kari E; Yoccoz, Nigel G; Tveraa, Torkild; Hewitt, Judi E; Thrush, Simon F
2017-10-30
The importance of long-term environmental monitoring and research for detecting and understanding changes in ecosystems and human impacts on natural systems is widely acknowledged. Over the last decades, a number of critical components for successful long-term monitoring have been identified. One basic component is quality assurance/quality control protocols to ensure consistency and comparability of data. In Norway, the authorities require environmental monitoring of the impacts of the offshore petroleum industry on the Norwegian continental shelf, and in 1996, a large-scale regional environmental monitoring program was established. As a case study, we used a sub-set of data from this monitoring to explore concepts regarding best practices for long-term environmental monitoring. Specifically, we examined data from physical and chemical sediment samples and benthic macroinvertebrate assemblages from 11 stations from six sampling occasions during the period 1996-2011. Despite the established quality assessment and quality control protocols for this monitoring program, we identified several data challenges, such as missing values and outliers, discrepancies in variable and station names, changes in procedures without calibration, and different taxonomic resolution. Furthermore, we show that the use of different laboratories over time makes it difficult to draw conclusions with regard to some of the observed changes. We offer recommendations to facilitate comparison of data over time. We also present a new procedure to handle different taxonomic resolution, so valuable historical data is not discarded. These topics have a broader relevance and application than for our case study.
NASA Astrophysics Data System (ADS)
Jo, Janggun; Yang, Xinmai
2011-09-01
Photoacoustic microscopy (PAM) was used to detect small animal brain activation in response to drug abuse. Cocaine hydrochloride in saline solution was injected into the blood stream of Sprague Dawley rats through tail veins. The rat brain functional change in response to the injection of drug was then monitored by the PAM technique. Images in the coronal view of the rat brain at the locations of 1.2 and 3.4 mm posterior to bregma were obtained. The resulted photoacoustic (PA) images showed the regional changes in the blood volume. Additionally, the regional changes in blood oxygenation were also presented. The results demonstrated that PA imaging is capable of monitoring regional hemodynamic changes induced by drug abuse.
Practicability of monitoring soil Cd, Hg, and Pb pollution based on a geochemical survey in China.
Xia, Xueqi; Yang, Zhongfang; Li, Guocheng; Yu, Tao; Hou, Qingye; Mutelo, Admire Muchimamui
2017-04-01
Repeated visiting, i.e., sampling and analysis at two or more temporal points, is one of the important ways of monitoring soil heavy metal contamination. However, with the concern about the cost, determination of the number of samples and the temporal interval, and their capability to detect a certain change is a key technical problem to be solved. This depends on the spatial variation of the parameters in the monitoring units. The "National Multi-Purpose Regional Geochemical Survey" (NMPRGS) project in China, acquired the spatial distribution of heavy metals using a high density sampling method in the most arable regions in China. Based on soil Cd, Hg, and Pb data and taking administrative regions as the monitoring units, the number of samples and temporal intervals that may be used for monitoring soil heavy metal contamination were determined. It was found that there is a large variety of spatial variation of the elements in each NMPRGS region. This results in the difficulty in the determination of the minimum detectable changes (MDC), the number of samples, and temporal intervals for revisiting. This paper recommends a suitable set of the number of samples (n r ) for each region under the balance of cost, practicability, and monitoring precision. Under n r , MDC values are acceptable for all the regions, and the minimum temporal intervals are practical with the range of 3.3-13.3 years. Copyright © 2017 Elsevier Ltd. All rights reserved.
Experimental damage detection of wind turbine blade using thin film sensor array
NASA Astrophysics Data System (ADS)
Downey, Austin; Laflamme, Simon; Ubertini, Filippo; Sarkar, Partha
2017-04-01
Damage detection of wind turbine blades is difficult due to their large sizes and complex geometries. Additionally, economic restraints limit the viability of high-cost monitoring methods. While it is possible to monitor certain global signatures through modal analysis, obtaining useful measurements over a blade's surface using off-the-shelf sensing technologies is difficult and typically not economical. A solution is to deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel large-area electronic sensor measuring strain over very large surfaces. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a hybrid dense sensor network of soft elastomeric capacitors to detect, localize, and quantify damage, and resistive strain gauges to augment such dense sensor network with high accuracy data at key locations. The proposed hybrid dense sensor network is installed inside a wind turbine blade model and tested in a wind tunnel to simulate an operational environment. Damage in the form of changing boundary conditions is introduced into the monitored section of the blade. Results demonstrate the ability of the hybrid dense sensor network, and associated algorithms, to detect, localize, and quantify damage.
Leem, Seong Kyu; Khan, Faheem; Cho, Sung Ho
2017-05-30
In order to avoid car crashes, active safety systems are becoming more and more important. Many crashes are caused due to driver drowsiness or mobile phone usage. Detecting the drowsiness of the driver is very important for the safety of a car. Monitoring of vital signs such as respiration rate and heart rate is important to determine the occurrence of driver drowsiness. In this paper, robust vital signs monitoring through impulse radio ultra-wideband (IR-UWB) radar is discussed. We propose a new algorithm that can estimate the vital signs even if there is motion caused by the driving activities. We analyzed the whole fast time vital detection region and found the signals at those fast time locations that have useful information related to the vital signals. We segmented those signals into sub-signals and then constructed the desired vital signal using the correlation method. In this way, the vital signs of the driver can be monitored noninvasively, which can be used by researchers to detect the drowsiness of the driver which is related to the vital signs i.e., respiration and heart rate. In addition, texting on a mobile phone during driving may cause visual, manual or cognitive distraction of the driver. In order to reduce accidents caused by a distracted driver, we proposed an algorithm that can detect perfectly a driver's mobile phone usage even if there are various motions of the driver in the car or changes in background objects. These novel techniques, which monitor vital signs associated with drowsiness and detect phone usage before a driver makes a mistake, may be very helpful in developing techniques for preventing a car crash.
Leem, Seong Kyu; Khan, Faheem; Cho, Sung Ho
2017-01-01
In order to avoid car crashes, active safety systems are becoming more and more important. Many crashes are caused due to driver drowsiness or mobile phone usage. Detecting the drowsiness of the driver is very important for the safety of a car. Monitoring of vital signs such as respiration rate and heart rate is important to determine the occurrence of driver drowsiness. In this paper, robust vital signs monitoring through impulse radio ultra-wideband (IR-UWB) radar is discussed. We propose a new algorithm that can estimate the vital signs even if there is motion caused by the driving activities. We analyzed the whole fast time vital detection region and found the signals at those fast time locations that have useful information related to the vital signals. We segmented those signals into sub-signals and then constructed the desired vital signal using the correlation method. In this way, the vital signs of the driver can be monitored noninvasively, which can be used by researchers to detect the drowsiness of the driver which is related to the vital signs i.e., respiration and heart rate. In addition, texting on a mobile phone during driving may cause visual, manual or cognitive distraction of the driver. In order to reduce accidents caused by a distracted driver, we proposed an algorithm that can detect perfectly a driver's mobile phone usage even if there are various motions of the driver in the car or changes in background objects. These novel techniques, which monitor vital signs associated with drowsiness and detect phone usage before a driver makes a mistake, may be very helpful in developing techniques for preventing a car crash. PMID:28556818
Levee Monitoring with Radar Remote Sensing
NASA Technical Reports Server (NTRS)
Jones, Cathleen E.
2012-01-01
Topics in this presentation are: 1. Overview of radar remote sensing 2. Surface change detection with Differential Interferometric Radar Processing 3. Study of the Sacramento - San Joaquin levees 4. Mississippi River Levees during the Spring 2011 floods.
Kraemer, Thomas F.; Brabets, Timothy P.
2012-01-01
The ability to detect hydrologic variation in large arctic river systems is of major importance in understanding and predicting effects of climate change in high-latitude environments. Monitoring uranium isotopes (234U and 238U) in river water of the Yukon River Basin of Alaska and northwestern Canada (2001–2005) has enhanced the ability to identify water sources to rivers, as well as detect flow changes that have occurred over the 5-year study. Uranium isotopic data for the Yukon River and major tributaries (the Porcupine and Tanana rivers) identify several sources that contribute to river flow, including: deep groundwater, seasonally frozen river-valley alluvium groundwater, and high-elevation glacial melt water. The main-stem Yukon River exhibits patterns of uranium isotopic variation at several locations that reflect input from ice melt and shallow groundwater in the spring, as well as a multi-year pattern of increased variability in timing and relative amount of water supplied from higher elevations within the basin. Results of this study demonstrate both the utility of uranium isotopes in revealing sources of water in large river systems and of incorporating uranium isotope analysis in long-term monitoring of arctic river systems that attempt to assess the effects of climate change.
Synchronous monitoring of muscle dynamics and electromyogram
NASA Astrophysics Data System (ADS)
Zakir Hossain, M.; Grill, Wolfgang
2011-04-01
A non-intrusive novel detection scheme has been implemented to detect the lateral muscle extension, force of the skeletal muscle and the motor action potential (EMG) synchronously. This allows the comparison of muscle dynamics and EMG signals as a basis for modeling and further studies to determine which architectural parameters are most sensitive to changes in muscle activity. For this purpose the transmission time for ultrasonic chirp signal in the frequency range of 100 kHz to 2.5 MHz passing through the muscle under observation and respective motor action potentials are recorded synchronously to monitor and quantify biomechanical parameters related to muscle performance. Additionally an ultrasonic force sensor has been employed for monitoring. Ultrasonic traducers are placed on the skin to monitor muscle expansion. Surface electrodes are placed suitably to pick up the potential for activation of the monitored muscle. Isometric contraction of the monitored muscle is ensured by restricting the joint motion with the ultrasonic force sensor. Synchronous monitoring was initiated by a software activated audio beep starting at zero time of the subsequent data acquisition interval. Computer controlled electronics are used to generate and detect the ultrasonic signals and monitor the EMG signals. Custom developed software and data analysis is employed to analyze and quantify the monitored data. Reaction time, nerve conduction speed, latent period between the on-set of EMG signals and muscle response, degree of muscle activation and muscle fatigue development, rate of energy expenditure and motor neuron recruitment rate in isometric contraction, and other relevant parameters relating to muscle performance have been quantified with high spatial and temporal resolution.
Long-term microfluidic glucose and lactate monitoring in hepatic cell culture
Prill, Sebastian; Jaeger, Magnus S.; Duschl, Claus
2014-01-01
Monitoring cellular bioenergetic pathways provides the basis for a detailed understanding of the physiological state of a cell culture. Therefore, it is widely used as a tool amongst others in the field of in vitro toxicology. The resulting metabolic information allows for performing in vitro toxicology assays for assessing drug-induced toxicity. In this study, we demonstrate the value of a microsystem for the fully automated detection of drug-induced changes in cellular viability by continuous monitoring of the metabolic activity over several days. To this end, glucose consumption and lactate secretion of a hepatic tumor cell line were continuously measured using microfluidically addressed electrochemical sensors. Adapting enzyme-based electrochemical flat-plate sensors, originally designed for human whole-blood samples, to their use with cell culture medium supersedes the common manual and laborious colorimetric assays and off-line operated external measurement systems. The cells were exposed to different concentrations of the mitochondrial inhibitor rotenone and the cellular response was analyzed by detecting changes in the rates of the glucose and lactate metabolism. Thus, the system provides real-time information on drug-induced liver injury in vitro. PMID:24926387
Electrical Resistance Technique to Monitor SiC Composite Detection
NASA Technical Reports Server (NTRS)
Smith, Craig; Morscher, Gregory; Xia, Zhenhai
2008-01-01
Ceramic matrix composites are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems. The employment of these materials in such applications is limited by the ability to process components reliable and to accurately monitor and predict damage evolution that leads to failure under stressed-oxidation conditions. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. Electrical resistance of SiC/SiC composites is one technique that shows special promise towards this end. Since both the matrix and the fibers are conductive, changes in matrix or fiber properties should relate to changes in electrical conductivity along the length of a specimen or part. The effect of matrix cracking on electrical resistivity for several composite systems will be presented and some initial measurements performed at elevated temperatures under stress-rupture conditions. The implications towards electrical resistance as a technique applied to composite processing, damage detection (health monitoring), and life-modeling will be discussed.
Evaluating the efficiency of environmental monitoring programs
Levine, Carrie R.; Yanai, Ruth D.; Lampman, Gregory G.; Burns, Douglas A.; Driscoll, Charles T.; Lawrence, Gregory B.; Lynch, Jason; Schoch, Nina
2014-01-01
Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.
Weiqi Zhou; Austin Troy; Morgan Grove
2008-01-01
Accurate and timely information about land cover pattern and change in urban areas is crucial for urban land management decision-making, ecosystem monitoring and urban planning. This paper presents the methods and results of an object-based classification and post-classification change detection of multitemporal high-spatial resolution Emerge aerial imagery in the...
Real-time monitoring of enzyme-free strand displacement cascades by colorimetric assays
NASA Astrophysics Data System (ADS)
Duan, Ruixue; Wang, Boya; Hong, Fan; Zhang, Tianchi; Jia, Yongmei; Huang, Jiayu; Hakeem, Abdul; Liu, Nannan; Lou, Xiaoding; Xia, Fan
2015-03-01
The enzyme-free toehold-mediated strand displacement reaction has shown potential for building programmable DNA circuits, biosensors, molecular machines and chemical reaction networks. Here we report a simple colorimetric method using gold nanoparticles as signal generators for the real-time detection of the product of the strand displacement cascade. During the process the assembled gold nanoparticles can be separated, resulting in a color change of the solution. This assay can also be applied in complex mixtures, fetal bovine serum, and to detect single-base mismatches. These results suggest that this method could be of general utility to monitor more complex enzyme-free strand displacement reaction-based programmable systems or for further low-cost diagnostic applications.The enzyme-free toehold-mediated strand displacement reaction has shown potential for building programmable DNA circuits, biosensors, molecular machines and chemical reaction networks. Here we report a simple colorimetric method using gold nanoparticles as signal generators for the real-time detection of the product of the strand displacement cascade. During the process the assembled gold nanoparticles can be separated, resulting in a color change of the solution. This assay can also be applied in complex mixtures, fetal bovine serum, and to detect single-base mismatches. These results suggest that this method could be of general utility to monitor more complex enzyme-free strand displacement reaction-based programmable systems or for further low-cost diagnostic applications. Electronic supplementary information (ESI) available: Experimental procedures and analytical data are provided. See DOI: 10.1039/c5nr00697j
Use of large-scale acoustic monitoring to assess anthropogenic pressures on Orthoptera communities.
Penone, Caterina; Le Viol, Isabelle; Pellissier, Vincent; Julien, Jean-François; Bas, Yves; Kerbiriou, Christian
2013-10-01
Biodiversity monitoring at large spatial and temporal scales is greatly needed in the context of global changes. Although insects are a species-rich group and are important for ecosystem functioning, they have been largely neglected in conservation studies and policies, mainly due to technical and methodological constraints. Sound detection, a nondestructive method, is easily applied within a citizen-science framework and could be an interesting solution for insect monitoring. However, it has not yet been tested at a large scale. We assessed the value of a citizen-science program in which Orthoptera species (Tettigoniidae) were monitored acoustically along roads. We used Bayesian model-averaging analyses to test whether we could detect widely known patterns of anthropogenic effects on insects, such as the negative effects of urbanization or intensive agriculture on Orthoptera populations and communities. We also examined site-abundance correlations between years and estimated the biases in species detection to evaluate and improve the protocol. Urbanization and intensive agricultural landscapes negatively affected Orthoptera species richness, diversity, and abundance. This finding is consistent with results of previous studies of Orthoptera, vertebrates, carabids, and butterflies. The average mass of communities decreased as urbanization increased. The dispersal ability of communities increased as the percentage of agricultural land and, to a lesser extent, urban area increased. Despite changes in abundances over time, we found significant correlations between yearly abundances. We identified biases linked to the protocol (e.g., car speed or temperature) that can be accounted for ease in analyses. We argue that acoustic monitoring of Orthoptera along roads offers several advantages for assessing Orthoptera biodiversity at large spatial and temporal extents, particularly in a citizen science framework. © 2013 Society for Conservation Biology.
a New Process-Oriented and Spatiotemporal Data Model for GIS Data
NASA Astrophysics Data System (ADS)
Shen, Y.
2018-04-01
With the rapid development of wireless sensor and information technology, there is a trend of transition from "digital monitoring" to "intelligence monitoring" advancing process. The traditional model cannot completely match the dynamic data to accurately describe changes of geographical and environmental changes. In this paper, we try to build a process-oriented and real-time spatiotemporal data model to meet the demands. With various types of monitoring devices, detection methods and the utilization of new technologies, the model can simulate the possible waterlog area in a specific year by analyzing the given data. By testing and modifying the spatiotemporal model, we can come to a rational conclusion that our model can forecast the actual situation in certain extent.
Bernstein, Richard A; Kamel, Hooman; Granger, Christopher B; Kowal, Robert C; Ziegler, Paul D; Schwamm, Lee H
2017-08-01
Approximately 20% of ischemic strokes are associated with clinically apparent atrial fibrillation (AF). Regardless of stroke etiology, detection of AF in patients with ischemic strokes often changes antithrombotic treatment from anti-platelet to oral anticoagulation therapy. The role and the optimum duration of cardiac monitoring to detect AF in patients with strokes presumed due to large vessel atherosclerosis or small vessel disease is unknown. This manuscript describes the design and rationale of the STROKE-AF trial. STROKE-AF is a randomized, controlled, open-label, post-market clinical trial. Detection of AF will be evaluated using continuous arrhythmia monitoring with an insertable cardiac monitor (ICM) compared with standard of care follow-up in patients with stroke (within the prior 10 days) that is presumed due to large vessel cervical or intracranial atherosclerosis, or to small vessel disease. Approximately 500 patients will be enrolled at approximately 40 centers in the United States. Patients will be randomized 1:1 to arrhythmia monitoring with an ICM (continuous monitoring arm) or standard of care follow-up (control arm). Subjects will be followed for ≥12 months and up to 3 years. The primary objective is to compare the incidence rate of detected AF through 12 months of follow-up between the two arms. This trial will provide information on the value of ICMs to detect subclinical AF in patients with stroke presumed due to large vessel atherosclerosis or small vessel disease, which will have implications for guiding treatment with oral anticoagulation for secondary stroke prevention. Copyright © 2017 Elsevier Inc. All rights reserved.
Cockings, Jerome G L; Cook, David A; Iqbal, Rehana K
2006-02-01
A health care system is a complex adaptive system. The effect of a single intervention, incorporated into a complex clinical environment, may be different from that expected. A national database such as the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme in the UK represents a centralised monitoring, surveillance and reporting system for retrospective quality and comparative audit. This can be supplemented with real-time process monitoring at a local level for continuous process improvement, allowing early detection of the impact of both unplanned and deliberately imposed changes in the clinical environment. Demographic and UK Acute Physiology and Chronic Health Evaluation II (APACHE II) data were prospectively collected on all patients admitted to a UK regional hospital between 1 January 2003 and 30 June 2004 in accordance with the ICNARC Case Mix Programme. We present a cumulative expected minus observed (E-O) plot and the risk-adjusted p chart as methods of continuous process monitoring. We describe the construction and interpretation of these charts and show how they can be used to detect planned or unplanned organisational process changes affecting mortality outcomes. Five hundred and eighty-nine adult patients were included. The overall death rate was 0.78 of predicted. Calibration showed excess survival in ranges above 30% risk of death. The E-O plot confirmed a survival above that predicted. Small transient variations were seen in the slope that could represent random effects, or real but transient changes in the quality of care. The risk-adjusted p chart showed several observations below the 2 SD control limits of the expected mortality rate. These plots provide rapid analysis of risk-adjusted performance suitable for local application and interpretation. The E-O chart provided rapid easily visible feedback of changes in risk-adjusted mortality, while the risk-adjusted p chart allowed statistical evaluation. Local analysis of risk-adjusted mortality data with an E-O plot and a risk-adjusted p chart is feasible and allows the rapid detection of changes in risk-adjusted outcome of intensive care patients. This complements the centralised national database, which is more archival and comparative in nature.
Hayatsu, Yukihiro; Kawamoto, Shunsuke; Matsunaga, Tadao; Haga, Yoichi; Saiki, Yoshikatsu
2014-10-01
The aim of our study was to develop a novel monitoring system for spinal cord blood flow (SCBF) to test the efficacy of the SCBF sensor in an animal model. The sensor system consisted of 2 optical fibers, a pedestal for fiber fixation, and a mirror for the laser reflection and was incorporated into a cerebrospinal fluid drainage catheter. In vivo studies were performed in a swine model (n=10) to measure SCBF during spinal cord ischemia induced by clamping the descending thoracic aorta and supra-aortic neck vessels, when necessary. A temporary low cardiac output model was also created by inflow clamping of the inferior vena cava to analyze the quantitative changes in SCBF during this maneuver. The developed SCBF monitoring catheter placed intrathecally could detect SCBF in all the swine. The SCBF after aortic crossclamping at the fourth intercostal level exhibited diverse changes reproducibly among the swine, with a >25% reduction in SCBF in 5 pigs, an increase in 3, and no significant changes in 2. Consistent reductions were recorded during inferior vena cava occlusion. The mean SCBF decreased by 32% after inferior vena cava occlusion when the cardiac output had decreased by 27%. We have developed a novel SCBF sensor that could detect real-time changes in spinal cord perfusion in a swine model. The device holds promise to detect imminent ischemia or ensure acceptable blood perfusion in the spinal cord and could further enhance our understanding of spinal cord circulation. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.
Tene, A; Tobin, B; Dyckmans, J; Ray, D; Black, K; Nieuwenhuis, M
2011-03-01
A thinning experiment stand at Avoca, Ballinvalley, on the east coast of the Republic of Ireland was used to test a developed methodology aimed at monitoring drought stress, based on the analysis of growth rings obtained by coring. The stand incorporated six plots representing three thinning regimes (light, moderate and heavy) and was planted in the spring of 1943 on a brown earth soil. Radial growth (early- and latewood) was measured for the purpose of this study. A multidisciplinary approach was used to assess historic tree response to climate: specifically, the application of statistical tools such as principal component and canonical correlation analysis to dendrochronology, stable isotopes, ring density proxy, blue reflectance and forest biometrics. Results showed that radial growth was a good proxy for monitoring changes to moisture deficit, while maximum density and blue reflectance were appropriate for assessing changes in accumulated temperature for the growing season. Rainfall also influenced radial growth changes but not significantly, and was a major factor in stable carbon and oxygen discrimination, mostly in the latewood formation phase. Stable oxygen isotope analysis was more accurate than radial growth analysis in drought detection, as it helped detect drought signals in both early- and latewood while radial growth analysis only detected the drought signal in earlywood. Many studies have shown that tree rings provide vital information for marking past climatic events. This work provides a methodology to better identify and understand how commonly measured tree proxies relate to environmental parameters, and can best be used to characterize and pinpoint drought events (variously described using parameters such as like moisture deficit, accumulated temperature, rainfall and potential evaporation).
Track-monitoring from the dynamic response of an operational train
NASA Astrophysics Data System (ADS)
Lederman, George; Chen, Siheng; Garrett, James; Kovačević, Jelena; Noh, Hae Young; Bielak, Jacobo
2017-03-01
We explore a data-driven approach for monitoring rail infrastructure from the dynamic response of a train in revenue-service. Presently, track inspection is performed either visually or with dedicated track geometry cars. In this study, we examine a more economical approach where track inspection is performed by analyzing vibration data collected from an operational passenger train. The high frequency with which passenger trains travel each section of track means that faults can be detected sooner than with dedicated inspection vehicles, and the large number of passes over each section of track makes a data-driven approach statistically feasible. We have deployed a test-system on a light-rail vehicle and have been collecting data for the past two years. The collected data underscores two of the main challenges that arise in train-based track monitoring: the speed of the train at a given location varies from pass to pass and the position of the train is not known precisely. In this study, we explore which feature representations of the data best characterize the state of the tracks despite these sources of uncertainty (i.e., in the spatial domain or frequency domain), and we examine how consistently change detection approaches can identify track changes from the data. We show the accuracy of these different representations, or features, and different change detection approaches on two types of track changes, track replacement and tamping (a maintenance procedure to improve track geometry), and two types of data, simulated data and operational data from our test-system. The sensing, signal processing, and data analysis we propose in the study could facilitate safer trains and more cost-efficient maintenance in the future. Moreover, the proposed approach is quite general and could be extended to other parts of the infrastructure, including bridges.
Bayesian analyses of time-interval data for environmental radiation monitoring.
Luo, Peng; Sharp, Julia L; DeVol, Timothy A
2013-01-01
Time-interval (time difference between two consecutive pulses) analysis based on the principles of Bayesian inference was investigated for online radiation monitoring. Using experimental and simulated data, Bayesian analysis of time-interval data [Bayesian (ti)] was compared with Bayesian and a conventional frequentist analysis of counts in a fixed count time [Bayesian (cnt) and single interval test (SIT), respectively]. The performances of the three methods were compared in terms of average run length (ARL) and detection probability for several simulated detection scenarios. Experimental data were acquired with a DGF-4C system in list mode. Simulated data were obtained using Monte Carlo techniques to obtain a random sampling of the Poisson distribution. All statistical algorithms were developed using the R Project for statistical computing. Bayesian analysis of time-interval information provided a similar detection probability as Bayesian analysis of count information, but the authors were able to make a decision with fewer pulses at relatively higher radiation levels. In addition, for the cases with very short presence of the source (< count time), time-interval information is more sensitive to detect a change than count information since the source data is averaged by the background data over the entire count time. The relationships of the source time, change points, and modifications to the Bayesian approach for increasing detection probability are presented.
The power of FIA Phase 3 Crown-Indicator variables to detect change
William Bechtold; KaDonna Randolph; Stanley Zarnoch
2009-01-01
The goal of Phase 3 Detection Monitoring as implemented by the Forest Inventory and Analysis Program is to identify forest ecosystems where conditions might be deteriorating in subtle ways over large areas. At the relatively sparse sampling intensity of the Phase 3 plot network, a rough measure of success for the forest health indicators developed for this purpose is...
Resolution-improved in situ DNA hybridization detection based on microwave photonic interrogation.
Cao, Yuan; Guo, Tuan; Wang, Xudong; Sun, Dandan; Ran, Yang; Feng, Xinhuan; Guan, Bai-ou
2015-10-19
In situ bio-sensing system based on microwave photonics filter (MPF) interrogation method with improved resolution is proposed and experimentally demonstrated. A microfiber Bragg grating (mFBG) is used as sensing probe for DNA hybridization detection. Different from the traditional wavelength monitoring technique, we use the frequency interrogation scheme for resolution-improved bio-sensing detection. Experimental results show that the frequency shift of MPF notch presents a linear response to the surrounding refractive index (SRI) change over the range of 1.33 to 1.38, with a SRI resolution up to 2.6 × 10(-5) RIU, which has been increased for almost two orders of magnitude compared with the traditional fundamental mode monitoring technique (~3.6 × 10(-3) RIU). Due to the high Q value (about 27), the whole process of DNA hybridization can be in situ monitored. The proposed MPF-based bio-sensing system provides a new interrogation method over the frequency domain with improved sensing resolution and rapid interrogation rate for biochemical and environmental measurement.
Mobile nocturnal long-term monitoring of wheezing and cough.
Gross, Volker; Reinke, Christian; Dette, Frank; Koch, Roland; Vasilescu, Dragos; Penzel, Thomas; Koehler, Ulrich
2007-02-01
Changes in normal lung sounds are an important sign of pathophysiological processes in the bronchial system and lung tissue. For the diagnosis of bronchial asthma, coughing and wheezing are important symptoms that indicate the existence of obstruction. In particular, nocturnal long-term acoustic monitoring and assessment make sense for qualitative and quantitative detection and documentation. Previous methods used for lung function diagnosis require active patient cooperation that is not possible during sleep. We developed a mobile device based on the CORSA standard that allows the recording of respiratory sounds throughout the night. To date, we have recorded 133 patients with different diagnoses (80 male, 53 female), of whom 38 were children. In 68 of the patients we could detect cough events and in 87 we detected wheezing. The recording method was tolerated by all participating adults and children. Our mobile system allows non-invasive and cooperation-independent nocturnal monitoring of acoustic symptoms in the domestic environment, especially at night, when most ailments occur.
Airborne Detection and Tracking of Geologic Leakage Sites
NASA Astrophysics Data System (ADS)
Jacob, Jamey; Allamraju, Rakshit; Axelrod, Allan; Brown, Calvin; Chowdhary, Girish; Mitchell, Taylor
2014-11-01
Safe storage of CO2 to reduce greenhouse gas emissions without adversely affecting energy use or hindering economic growth requires development of monitoring technology that is capable of validating storage permanence while ensuring the integrity of sequestration operations. Soil gas monitoring has difficulty accurately distinguishing gas flux signals related to leakage from those associated with meteorologically driven changes of soil moisture and temperature. Integrated ground and airborne monitoring systems are being deployed capable of directly detecting CO2 concentration in storage sites. Two complimentary approaches to detecting leaks in the carbon sequestration fields are presented. The first approach focuses on reducing the requisite network communication for fusing individual Gaussian Process (GP) CO2 sensing models into a global GP CO2 model. The GP fusion approach learns how to optimally allocate the static and mobile sensors. The second approach leverages a hierarchical GP-Sigmoidal Gaussian Cox Process for airborne predictive mission planning to optimally reducing the entropy of the global CO2 model. Results from the approaches will be presented.
A wire-based dual-analyte sensor for glucose and lactate: in vitro and in vivo evaluation.
Ward, W Kenneth; House, Jody L; Birck, Jonathan; Anderson, Ellen M; Jansen, Lawrence B
2004-06-01
Continuous measurement of lactate is potentially useful for detecting physical exhaustion and for monitoring critical care conditions characterized by hypoperfusion, such as heart failure. In some conditions, it may be desirable to monitor more than one metabolic parameter concurrently. For this reason, we designed and fabricated twisted wire-based microelectrodes that can measure both lactate and glucose. These dual-analyte sensors were characterized in vitro by measuring their response to the analyte of interest and to assess whether they were susceptible to interference from the other analyte. When measured in stirred aqueous buffer, lactate sensors detected a very small amount of crosstalk from glucose in vitro, although this signal was less than 3% of the response to lactate. Glucose sensors did not detect crosstalk from lactate. Sensors were implanted subcutaneously in rats and tested during infusions of lactate and glucose. Each sensing electrode responded rapidly to changes in its analyte concentration, and there was no evidence of in vivo crosstalk. This study constitutes proof of the concept that oxidase-based, amperometric wire microsensors can detect changes in glucose and lactate during subcutaneous implantation in rats.
NASA Technical Reports Server (NTRS)
Spruce, Joseph; Hargrove, William; Gasser, Gerald
2013-01-01
This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.
Applications of ERTS-1 data to landscape change in eastern Tennessee
NASA Technical Reports Server (NTRS)
Rehder, J. B. (Principal Investigator)
1973-01-01
The author has identified the following significant results. The analysis of landscape change in eastern Tennessee from ERTS-1 data is being derived from three avenues of experimentation and analysis: (1) a multi-stage sampling procedure utilizing ground and aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures and comparisons for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions. Significant results include: maps of strip mining changes and forest inventory, watershed identification and delimitation, and agricultural regions derived from spring plowing patterns appearing on the ERTS-1 imagery.
Angel, S.M.
1987-02-27
Particular gases or liquids are detected with a fiber optic element having a cladding or coating of a material which absorbs the fluid or fluids and which exhibits a change of an optical property, such as index of refraction, light transmissiveness or fluoresence emission, for example, in response to absorption of the fluid. The fluid is sensed by directing light into the fiber optic element and detecting changes in the light, such as exit angle changes for example, that result from the changed optical property of the coating material. The fluid detector may be used for such purposes as sensing toxic or explosive gases in the atmosphere, measuring ground water contamination or monitoring fluid flows in industrial processes, among other uses. 10 figs.
Mustonen, Tero
2015-12-01
This article explores the pioneering potential of communal visual-optic histories which are recorded, painted, documented, or otherwise expressed. These materials provide collective meanings of an image or visual material within a specific cultural group. They potentially provide a new method for monitoring and documenting changes to ecosystem health and species distribution, which can effectively inform society and decision makers of Arctic change. These visual histories can be positioned in a continuum that extends from rock art to digital photography. They find their expressions in forms ranging from images to the oral recording of knowledge and operate on a given cultural context. For monitoring efforts in the changing boreal zone and Arctic, a respectful engagement with visual histories can reveal emerging aspects of change. The examples from North America and case studies from Eurasia in this article include Inuit sea ice observations, Yu'pik visual traditions of masks, fish die-offs in a sub-boreal catchment area, permafrost melt in the Siberian tundra and early, first detection of a scarabaeid beetle outbreak, a Southern species in the Skolt Sámi area. The pros and cons of using these histories and their reliability are reviewed.
Lee, Adrian J; Jacobson, Sheldon H
2012-02-01
A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information-based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions. © 2012 Society for Risk Analysis. All rights reserved.
Kim, Nam-Hoon; Hwang, Jin Hwan; Cho, Jaegab; Kim, Jae Seong
2018-06-04
The characteristics of an estuary are determined by various factors as like as tide, wave, river discharge, etc. which also control the water quality of the estuary. Therefore, detecting the changes of characteristics is critical in managing the environmental qualities and pollution and so the locations of monitoring should be selected carefully. The present study proposes a framework to deploy the monitoring systems based on a graphical method of the spatial and temporal optimizations. With the well-validated numerical simulation results, the monitoring locations are determined to capture the changes of water qualities and pollutants depending on the variations of tide, current and freshwater discharge. The deployment strategy to find the appropriate monitoring locations is designed with the constrained optimization method, which finds solutions by constraining the objective function into the feasible regions. The objective and constrained functions are constructed with the interpolation technique such as objective analysis. Even with the smaller number of the monitoring locations, the present method performs well equivalently to the arbitrarily and evenly deployed monitoring system. Copyright © 2018 Elsevier Ltd. All rights reserved.
Harmsen, Bart J.; Foster, Rebecca J.; Sanchez, Emma; Gutierrez-González, Carmina E.; Silver, Scott C.; Ostro, Linde E. T.; Kelly, Marcella J.; Kay, Elma; Quigley, Howard
2017-01-01
In this study, we estimate life history parameters and abundance for a protected jaguar population using camera-trap data from a 14-year monitoring program (2002–2015) in Belize, Central America. We investigated the dynamics of this jaguar population using 3,075 detection events of 105 individual adult jaguars. Using robust design open population models, we estimated apparent survival and temporary emigration and investigated individual heterogeneity in detection rates across years. Survival probability was high and constant among the years for both sexes (φ = 0.78), and the maximum (conservative) age recorded was 14 years. Temporary emigration rate for the population was random, but constant through time at 0.20 per year. Detection probability varied between sexes, and among years and individuals. Heterogeneity in detection took the form of a dichotomy for males: those with consistently high detection rates, and those with low, sporadic detection rates, suggesting a relatively stable population of ‘residents’ consistently present and a fluctuating layer of ‘transients’. Female detection was always low and sporadic. On average, twice as many males than females were detected per survey, and individual detection rates were significantly higher for males. We attribute sex-based differences in detection to biases resulting from social variation in trail-walking behaviour. The number of individual females detected increased when the survey period was extended from 3 months to a full year. Due to the low detection rates of females and the variable ‘transient’ male subpopulation, annual abundance estimates based on 3-month surveys had low precision. To estimate survival and monitor population changes in elusive, wide-ranging, low-density species, we recommend repeated surveys over multiple years; and suggest that continuous monitoring over multiple years yields even further insight into population dynamics of elusive predator populations. PMID:28658274
Lee, Jung-Min; Levy, Doron
2016-01-01
High-grade serous ovarian cancer (HGSOC) represents the majority of ovarian cancers and accounts for the largest proportion of deaths from the disease. A timely detection of low volume HGSOC should be the goal of any screening studies. However, numerous transvaginal ultrasound (TVU) detection-based population studies aimed at detecting low-volume disease have not yielded reduced mortality rates. A quantitative invalidation of TVU as an effective HGSOC screening strategy is a necessary next step. Herein, we propose a mathematical model for a quantitative explanation on the reported failure of TVU-based screening to improve HGSOC low-volume detectability and overall survival.We develop a novel in silico mathematical assessment of the efficacy of a unimodal TVU monitoring regimen as a strategy aimed at detecting low-volume HGSOC in cancer-positive cases, defined as cases for which the inception of the first malignant cell has already occurred. Our findings show that the median window of opportunity interval length for TVU monitoring and HGSOC detection is approximately 1.76 years. This does not translate into reduced mortality levels or improved detection accuracy in an in silico cohort across multiple TVU monitoring frequencies or detection sensitivities. We demonstrate that even a semiannual, unimodal TVU monitoring protocol is expected to miss detectable HGSOC. Lastly, we find that circa 50% of the simulated HGSOC growth curves never reach the baseline detectability threshold, and that on average, 5–7 infrequent, rate-limiting stochastic changes in the growth parameters are associated with reaching HGSOC detectability and mortality thresholds respectively. Focusing on a malignancy poorly studied in the mathematical oncology community, our model captures the dynamic, temporal evolution of HGSOC progression. Our mathematical model is consistent with recent case reports and prospective TVU screening population studies, and provides support to the empirical recommendation against frequent HGSOC screening. PMID:27257824
Desaules, André
2012-11-01
It is crucial for environmental monitoring to fully control temporal bias, which is the distortion of real data evolution by varying bias through time. Temporal bias cannot be fully controlled by statistics alone but requires appropriate and sufficient metadata, which should be under rigorous and continuous quality assurance and control (QA/QC) to reliably document the degree of consistency of the monitoring system. All presented strategies to detect and control temporal data bias (QA/QC, harmonisation/homogenisation/standardisation, mass balance approach, use of tracers and analogues and control of changing boundary conditions) rely on metadata. The Will Rogers phenomenon, due to subsequent reclassification, is a particular source of temporal data bias introduced to environmental monitoring here. Sources and effects of temporal data bias are illustrated by examples from the Swiss soil monitoring network. The attempt to make a comprehensive compilation and assessment of required metadata for soil contamination monitoring reveals that most metadata are still far from being reliable. This leads to the conclusion that progress in environmental monitoring means further development of the concept of environmental metadata for the sake of temporal data bias control as a prerequisite for reliable interpretations and decisions.
Lundgren, Robert F.; Lopes, Thomas J.
1999-01-01
The Ohio River is a source of drinking water for more than 3 million people. Thus, it is important to monitor the water quality of this river to determine if contaminants are present, their concentrations, and if water quality is changing with time. This report presents an analysis of the occurrence, distribution, and trends of 21 volatile organic compounds (VOCs) along the main stem of the Ohio River and its major tributaries from 1987 through 1996. The data were collected by the Ohio River Valley Water Sanitation Commission's Organics Detection System, which monitors daily for VOCs at 15 stations. Various statistical methods were applied to basinwide data from all monitoring stations and to data from individual monitoring stations. For the basinwide data, one or more VOCs were detected in 45 percent of the 44,837 river-water samples. Trichloromethane, detected in 26 percent of the samples, was the most frequently detected VOC followed by benzene (11 percent), methylbenzene (6.4 percent), and the other 18 VOCs, which were detected in less than 4 percent of the samples. In samples from 8 of the 15 monitoring stations, trichloromethane was also the most frequently detected VOC. These stations were generally near large cities along the Ohio River. The median trichloromethane concentration was 0.3 microgram per liter (μg/L), and concentrations ranged from less than 0.1 to 125.3 μg/L. Most of the VOCs had median detected concentrations that ranged from 0.1 to 0.4 μg/L for the basinwide data and for samples from individual stations. Samples from stations in the upstream part of the basin and from the Kanawha River had the highest median concentrations. Ninety-nine percent of the detected VOC concentrations were within U.S. Environmental Protection Agency drinking-water regulations. Of the 268 exceedances of drinking-water regulations, 188 were due to the detection of 1,2-dichloroethane prior to 1993 in samples from the monitoring station near Paducah, Ky. Time trend analyses indicated that most VOCs had no trend in samples at most monitoring stations because they were detected infrequently. At one or more stations, 14 VOCs had decreasing trends in monthly mean concentrations that ranged from -0.01 to -0.42 μ/L per year. Nine VOCs had significant decreasing trends in percentage detection that ranged from -1.08 to -12.90 percent per year. These trends suggest that source-control efforts are working and that water quality is improving.
Optimization of Sensor Monitoring Strategies for Emissions
NASA Astrophysics Data System (ADS)
Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.
2016-12-01
Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Niwa, O; Horiuchi, T; Torimitsu, K
1997-01-01
A small volume L-glutamate online sensor was developed in order to monitor changes in the local concentration of L-glutamate released from cultured nerve cells. Syringe pump in the suction mode is used to sample extracellular fluid continuously from a glass micro-capillary and the concentration of L-glutamate can be determined by using a glassy carbon (GC) electrode modified with an Os-polyvinylpyridine mediator bottom film containing horseradish peroxidase and a bovine serum albumin top layer containing L-glutamate oxidase. The overall efficiency of L-glutamate detection with a sensor is 71% under optimum conditions due to an efficient enzymatic reaction at the modified electrode in the thin layer radial flow cell. As a result, we achieved a detection limit of 7-15 nM and a linear range of 50 nM to 10 microM. In an in vitro experiment, the extracellular fluid near a particular nerve cell can be sampled with this micro-pipet and continuously introduced into the modified GC electrode in the radial flow cell via suction provided by a syringe pump. The nerve cells are stimulated by the KCl in a glass capillary and the L-glutamate concentration change can be monitored by changing the distance between the sampling pipet and the nerve cells.
Enhanced data validation strategy of air quality monitoring network.
Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem
2018-01-01
Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.
Replaceable Sensor System for Bioreactor Monitoring
NASA Technical Reports Server (NTRS)
Mayo, Mike; Savoy, Steve; Bruno, John
2006-01-01
A sensor system was proposed that would monitor spaceflight bioreactor parameters. Not only will this technology be invaluable in the space program for which it was developed, it will find applications in medical science and industrial laboratories as well. Using frequency-domain-based fluorescence lifetime technology, the sensor system will be able to detect changes in fluorescence lifetime quenching that results from displacement of fluorophorelabeled receptors bound to target ligands. This device will be used to monitor and regulate bioreactor parameters including glucose, pH, oxygen pressure (pO2), and carbon dioxide pressure (pCO2). Moreover, these biosensor fluorophore receptor-quenching complexes can be designed to further detect and monitor for potential biohazards, bioproducts, or bioimpurities. Biosensors used to detect biological fluid constituents have already been developed that employ a number of strategies, including invasive microelectrodes (e.g., dark electrodes), optical techniques including fluorescence, and membrane permeable systems based on osmotic pressure. Yet the longevity of any of these sensors does not meet the demands of extended use in spacecraft habitat or bioreactor monitoring. It was therefore necessary to develop a sensor platform that could determine not only fluid variables such as glucose concentration, pO2, pCO2, and pH but can also regulate these fluid variables with controlled feedback loop.
Insulin aggregation tracked by its intrinsic TRES
NASA Astrophysics Data System (ADS)
Chung, Li Hung C.; Birch, David J. S.; Vyshemirsky, Vladislav; Ryadnov, Maxim G.; Rolinski, Olaf J.
2017-12-01
Time-resolved emission spectra (TRES) have been used to detect conformational changes of intrinsic tyrosines within bovine insulin at a physiological pH. The approach offers the ability to detect the initial stages of insulin aggregation at the molecular level. The data analysis has revealed the existence of at least three fluorescent species undergoing dielectric relaxation and significant spectral changes due to insulin aggregation. The results indicate the suitability of the intrinsic TRES approach for insulin studies and for monitoring its stability during storage and aggregation in insulin delivery devices.
Cournane, S; Sheehy, N; Cooke, J
2014-06-01
Benford's law is an empirical observation which predicts the expected frequency of digits in naturally occurring datasets spanning multiple orders of magnitude, with the law having been most successfully applied as an audit tool in accountancy. This study investigated the sensitivity of the technique in identifying system output changes using simulated changes in interventional radiology Dose-Area-Product (DAP) data, with any deviations from Benford's distribution identified using z-statistics. The radiation output for interventional radiology X-ray equipment is monitored annually during quality control testing; however, for a considerable portion of the year an increased output of the system, potentially caused by engineering adjustments or spontaneous system faults may go unnoticed, leading to a potential increase in the radiation dose to patients. In normal operation recorded examination radiation outputs vary over multiple orders of magnitude rendering the application of normal statistics ineffective for detecting systematic changes in the output. In this work, the annual DAP datasets complied with Benford's first order law for first, second and combinations of the first and second digits. Further, a continuous 'rolling' second order technique was devised for trending simulated changes over shorter timescales. This distribution analysis, the first employment of the method for radiation output trending, detected significant changes simulated on the original data, proving the technique useful in this case. The potential is demonstrated for implementation of this novel analysis for monitoring and identifying change in suitable datasets for the purpose of system process control. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina
2015-01-01
Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.
Miller, Michael J; Walsh, Michael R; Shrake, Jerry L; Dukes, Randall E; Hill, Daniel B
2009-01-01
This paper describes the use of the BioVigilant IMD-A, a real-time and continuous monitoring technology based on optical spectroscopy, to simultaneously and instantaneously detect, size, and enumerate both viable and nonviable particles in a variety of filling and transfer isolator environments during an aseptic fill, transfer of sterilized components, and filling interventions. Continuous monitoring of three separate isolators for more than 16 h and representing more than 28 m3 of air per isolator (under static conditions) yielded a mean viable particle count of zero (0) per cubic meter. Although the mean count per cubic meter was zero, the detection of very low levels of single viable particles was randomly observed in each of these sampling runs. No viable particles were detected during the manual transfer of sterilized components from transfer isolators into a filling isolator, and similar results were observed during an aseptic fill, a filling needle change-out procedure, and during disassembly, movement, and reassembly of a vibrating stopper bowl. During the continuous monitoring of a sample transfer port and a simulated mousehole, no viable particles were detected; however, when the sampling probe was inserted beyond the isolator-room interface, the IMD-A instantaneously detected and enumerated both viable and nonviable particles originating from the surrounding room. Data from glove pinhole studies showed no viable particles being observed, although significant viable particles were immediately detected when the gloves were removed and a bare hand was allowed to introduce microorganisms into the isolator. The IMD-A technology offers the industry an unprecedented advantage over growth-based bioaerosol samplers for monitoring the state of microbiological control in pharmaceutical manufacturing environments, and represents significant progress toward the acceptance of microbiology process analytical technology solutions for the industry.
Diagnostic Yield of Extended Cardiac Patch Monitoring in Patients with Stroke or TIA.
Tung, Christie E; Su, Derek; Turakhia, Mintu P; Lansberg, Maarten G
2014-01-01
It is important to evaluate patients with transient ischemic attack (TIA) or stroke for atrial fibrillation (AF) because the detection of AF changes the recommended anti-thrombotic regimen from treatment with an antiplatelet agent to oral anticoagulation. This study describes the diagnostic yield of a patch-based, single-use, and water-resistant 14-day continuous cardiac rhythm monitor (ZIO Patch) in patients with stroke or TIA. We obtained data from the manufacturer and servicer of the ZIO Patch (iRhythm Technologies). Patients who were monitored between January 2012 and June 2013 and whose indication for monitoring was TIA or stroke were included. The duration of monitoring, the number and type of arrhythmias, and the time to first arrhythmia were documented. One thousand one hundred seventy-one monitoring reports were analyzed. The mean monitor wear time was 10.9 days and the median wear time was 13.0 days (interquartile range 7.2-14.0). The median analyzable time relative to the total wear time was 98.7% (IQR 96.0-99.5%). AF was present in 5.0% of all reports. The mean duration before the first episode of paroxysmal AF (PAF) was 1.5 days and the median duration was 0.4 days. 14.3% of first PAF episodes occurred after 48 h. The mean PAF burden was 12.7% of the total monitoring duration. Excellent quality of the recordings and very good patient compliance coupled with a substantial proportion of AF detection beyond the first 48 h of monitoring suggest that the cardiac patch is superior to conventional 48-h Holter monitors for AF detection in patients with stroke or TIA.
NASA Astrophysics Data System (ADS)
Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.
2014-03-01
Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.
Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.
2014-01-01
Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase-shift during high energy HIFU treatment with tissue boiling. Forty three (n=43) thermal lesions were formed in ex vivo canine liver specimens (n=28). Two dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10-s, 20-s and 30-s HIFU durations at three different acoustic powers of 8, 10, and 11W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and Passive Cavitation Detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δφ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite unpredictable changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property change throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes. PMID:24556974
Hou, Gary Y; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E
2014-03-07
Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.
Ghanbari, Sarah; Ravikumar, Anusha; Seubert, John; Figueira, Silvia
2013-01-01
Contaminated water is a serious concern in many developing countries with severe health consequences particularly for children. Current methods for monitoring waterborne pathogens are often time consuming, expensive, and labor intensive, making them not suitable for these regions. Electrochemical detection in a microfluidic platform offers many advantages such as portability, minimal use of instrumentation, and easy integration with electronics. In many parts of the world, however, the required equipment for pathogen detection through electrochemical sensors is either not available or insufficiently portable, and operators may not be trained to use these sensors and interpret results, ultimately preventing its wide adoption. Counterintuitively, these same regions often have an extensive mobile phone infrastructure, suggesting the possibility of integrating electrochemical detection of bacterial pathogens with a mobile platform. Toward a solution to water quality interventions, we demonstrate a microfluidic electrochemical sensor combined with a mobile interface that detects the sequences from bacterial pathogens, suitable for rapid, affordable, and point-of-care water monitoring. We employ the transduction of DNA hybridization into a readily detectable electric signal by means of a conformational change of DNA stem-loop structure. Using this platform, we successfully demonstrate the detection of as low as 100 nM E. coli sequences and the automatic interpretation and mapping of the detection results via a mobile application. PMID:27170858
Electrical response of culture media during bacterial growth on a paper-based device
NASA Astrophysics Data System (ADS)
Srimongkon, Tithimanan; Buerkle, Marius; Nakamura, Akira; Enomae, Toshiharu; Ushijima, Hirobumi; Fukuda, Nobuko
2017-05-01
In this work, we evaluated the feasibility of a paper-based bacterial detection system. The paper served as a substrate for the measurement electrodes and the culture medium. Using a printing technique, we patterned gold electrodes onto the paper substrate and applied Luria broth (LB) agar gel as a culture medium on top of the electrodes. As the first step towards the development of a bacterial detection system, we determined changes in the surface potential during bacterial growth and monitored these changes over 24 h. This allowed us to correlate changes in the surface potential with the different growth phases of the bacteria.
Yessotoxin detection in bivalve molluscs: A case study from coastal mussel farms (Sardinia, Italy)
Mudadu, Alessandro Graziano; Lorenzoni, Giuseppa; Bazzoni, Anna Maria; Bazzardi, Riccardo; Tedde, Giuseppe; Arras, Igor; Sanna, Giovanna; Santucciu, Cinzia; Marongiu, Edoardo; Virgilio, Sebastiano
2018-01-01
This work reports the first communication relating to the presence of yessotoxins in Mytilus galloprovincialis from coastal mussel farms (Sardinia, western Mediterranean) detected during 2008 and 2013 through a monitoring programme. The paper emphasizes how the changes both in yessotoxin permitted limits and used methods, established by legislation, have influenced the interpretation of the obtained results. Consequently, the samples that resulted negative during 2008 would have been positive until August 2013 and negative from September 2013 up to now, and the samples that were positive in 2013 would have been positive in 2008 and negative nowadays, according to Regulation currently in force. Regular monitoring of biotoxins demonstrated that, although yessotoxins have been rarely present in the past in Sardinia, they may cause toxicity in shellfish. So, it’s important to keep up on legislation’s changing and laboratory methods. PMID:29564241
Satellites monitor Atlanta regional development
Todd, William J.; Blackmon, C.C.; Rudasill, R.G.
1979-01-01
Since the adoption of a Regional Development Plan in 1975, the Atlanta Regional Commission has investigated methods for monitoring regional development patterns in a periodic, efficient manner. A promising approach appears to be the use of Landsat satellite data. In cooperation with the Earth Resources Observation Systems (EROS) Data Center, the commission used machine processing of digital temporal overlays of Landsat data collected in 1972, 1974 and 1976 to detect land use and land cover changes in the Atlanta metropolitan area. Results of the analysis revealed the conversion of forested and open space areas to residential, commercial and industrial land use in the urban-rural fringe zone from 1972 to 1974 and from 1974 to 1976. The study indicated that a land use and land cover change-detection program may be used to revise small-area forecasts of land use, population and employment made by planning models.
Using Knowledge Base for Event-Driven Scheduling of Web Monitoring Systems
NASA Astrophysics Data System (ADS)
Kim, Yang Sok; Kang, Sung Won; Kang, Byeong Ho; Compton, Paul
Web monitoring systems report any changes to their target web pages by revisiting them frequently. As they operate under significant resource constraints, it is essential to minimize revisits while ensuring minimal delay and maximum coverage. Various statistical scheduling methods have been proposed to resolve this problem; however, they are static and cannot easily cope with events in the real world. This paper proposes a new scheduling method that manages unpredictable events. An MCRDR (Multiple Classification Ripple-Down Rules) document classification knowledge base was reused to detect events and to initiate a prompt web monitoring process independent of a static monitoring schedule. Our experiment demonstrates that the approach improves monitoring efficiency significantly.
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.
Forest health monitoring in the Ngangao Forest, Taita Tills, Kenya: A five year assessment of change
Paul C. Rogers; Barbara O' Connell; James Mwang' ombe; Seif Madoffe; Gerard Hertel
2008-01-01
Forest Health Monitoring (FHM) provides a standardized detection-level survey of forest and tree characteristics for large forested areas. We have adopted FHM methods from this temperate-based program to tropical forests in the Eastern Arc Mountains (EAM) of Kenya and Tanzania. This paper reports the first assessment of trend data in the EAM over a period from 2001 to...
NASA Technical Reports Server (NTRS)
Frederick, J. E.; Heath, D. F.; Cebula, R. P.
1986-01-01
The scientific objective of unambiguously detecting subtle global trends in upper stratospheric ozone requires that one maintains a thorough understanding of the satellite-based remote sensors intended for this task. The instrument now in use for long term ozone monitoring is the SBUV/2 being flown on NOAA operational satellites. A critical activity in the data interpretation involves separating small changes in measurement sensitivity from true atmospheric variability. By defining the specific issues that must be addressed and presenting results derived early in the mission of the first SBUV/2 flight model, this work serves as a guide to the instrument investigations that are essential in the attempt to detect long-term changes in the ozone layer.
NASA Astrophysics Data System (ADS)
Liu, W.; Du, M. H.; Chan, Francis H. Y.; Lam, F. K.; Luk, D. K.; Hu, Y.; Fung, Kan S. M.; Qiu, W.
1998-09-01
Recently there has been a considerable interest in the use of a somatosensory evoked potential (SEP) for monitoring the functional integrity of the spinal cord during surgery such as spinal scoliosis. This paper describes a monitoring system and signal processing algorithms, which consists of 50 Hz mains filtering and a wavelet signal analyzer. Our system allows fast detection of changes in SEP peak latency, amplitude and signal waveform, which are the main parameters of interest during intra-operative procedures.
Temperature Climatology with Rayleigh Lidar Above Observatory of Haute-Provence: Dynamical Feedback
NASA Astrophysics Data System (ADS)
Keckhut, Philippe; Hauchecorne, Alain; Funatsu, Beatriz; Khaykin, Serguey; Mze, Nahouda; Claud, Chantal; Angot, Guillaume
2016-06-01
Rayleigh lidar in synergy with satellite observations (SSU and AMSU) allow insuring an efficient monitoring and showing that cooling has continued. New approach for trend detection has been developed allowing a better estimate of changes due to radiative forcing. Stratospheric Warmings and gravity waves contribute to insure a dynamical feedback of the long-term changes.
Kryshtal, R G; Medved, A V
2014-02-01
Application of surface acoustic wave resonators with a phase format of an output signal as the thermometric "magnifying glass" is suggested. Possibilities of monitoring and measuring of small changes of temperature from 0.001 K to 0.3 K of objects having thermal contact with the resonator's substrate are shown experimentally.
USDA-ARS?s Scientific Manuscript database
Arid rangelands within the southwestern United States have been severely degraded over the past century due to intensive land-use practices (e.g., livestock overgrazing, recreation) and the increasing effects of drought and climate change. Consequently, there is a critical need to develop monitoring...
The affection of boreal forest changes on imbalance of Nature (Invited)
NASA Astrophysics Data System (ADS)
Tana, G.; Tateishi, R.
2013-12-01
Abstract: The balance of nature does not exist, and, perhaps, never has existed [1]. In other words, the Mother Nature is imbalanced at all. The Mother Nature is changing every moment and never returns to previous condition. Because of the imbalance of nature, global climate has been changing gradually. To reveal the imbalance of nature, there is a need to monitor the dynamic changes of the Earth surface. Forest cover and forest cover change have been grown in importance as basic variables for modelling of global biogeochemical cycles as well as climate [2]. The boreal area contains 1/3 of the earth's trees. These trees play a large part in limiting harmful greenhouse gases by aborbing much of the earth's carbon dioxide (CO2) [3]. The boreal area mainly consists of needleleaf evergreen forest and needleleaf deciduous forest. Both of the needleleaf evergreen forest and needleleaf deciduous forest play the important roles on the uptake of CO2. However, because of the dormant period of needleleaf evergreen forest are shorter than that of needleleaf deciduous forest, needleleaf evergreen forest makes a greater contribution to the absorbtion of CO2. Satellite sensor because of its ability to observe the Earth continuously, can provide the opportunity to monitor the dynamic changes of the Earth. In this study, we used the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data to monitor the dynamic change of boreal forest area which are mainly consist from needleleaf evergreen forest and needleleaf deciduous forest during 2003-2012. Three years MODIS data from the year 2003, 2008 and 2012 were used to detect the forest changed area. A hybrid change detection method which combines the threshold method and unsupervised classification method was used to detect the changes of forest area. In the first step, the difference of Normalized Difference Vegetation Index (NDVI) of the three years were calculated and were used to extract the changed areas by the threshold method. In the second step, the unsupervised classification method was used to classify and analyze detected change areas derived from the first step. Finally, the changed area were validated using the traning data collected for the three years. The validation result revealed that the forest in the study area has undergone the area and type changes during 2003-2012. The detailed procedure will be presented in the meeting. References: [1] Elton, C.S. (1930). Animal Ecology and Evolution. New York, Oxford University Press. [2] Potapov, P., Hansen, M. C., Stehman, S. V., Loveland, T. R., Pittman, K. (2008). Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss, Remote Sensing of Environment, 112, 3708-3719. [3] Houghton, R. A. (2003). Why are estimates of the terrestrial carbon balance so different? Global Change Biology, 9, 500-509.
Sonoelasticity to monitor mechanical changes during rigor and ageing.
Ayadi, A; Culioli, J; Abouelkaram, S
2007-06-01
We propose the use of sonoelasticity as a non-destructive method to monitor changes in the resistance of muscle fibres, unaffected by connective tissue. Vibrations were applied at low frequency to induce oscillations in soft tissues and an ultrasound transducer was used to detect the motions. The experiments were carried out on the M. biceps femoris muscles of three beef cattle. In addition to the sonoelasticity measurements, the changes in meat during rigor and ageing were followed by measurements of both the mechanical resistance of myofibres and pH. The variations of mechanical resistance and pH were compared to those of the sonoelastic variables (velocity and attenuation) at two frequencies. The relationships between pH and velocity or attenuation and between the velocity or attenuation and the stress at 20% deformation were highly correlated. We concluded that sonoelasticity is a non-destructive method that can be used to monitor mechanical changes in muscle fibers during rigor-mortis and ageing.
Devising a Coral Reef Ocean Acidification Monitoring Portfolio
NASA Astrophysics Data System (ADS)
Gledhill, D. K.; Jewett, L.
2012-12-01
Coral reef monitoring has frequently been based only on descriptive science with limited capacity to assign specific attribution to agents of change. There is a requirement to engineer a diagnostic monitoring approach that can test predictions regarding the response of coral reef ecosystems to ocean acidification, and to identify potential areas of refugia or areas of particular concern. The approach should provide the means to detect not only changes in water chemistry but also changes in coral reef community structure and function which can be anticipated based upon our current understanding of paleo-OA events, experimental findings, process investigations, and modeling projections In August, 2012 a Coral Reef Ocean Acidification Monitoring Portfolio Workshop was hosted by the NOAA Ocean Acidification Program and the National Coral Reef Institute at the Nova Southeastern University Oceanographic Center. The workshop convened researchers and project managers from around the world engaged in coral reef ecosystems ocean acidification monitoring and research. The workshop sought to define a suite of metrics to include as part of long-term coral reef monitoring efforts that can contribute to discerning specific attribution of changes in coral reef ecosystems in response to ocean acidification. This portfolio of observations should leverage existing and proposed monitoring initiatives and would be derived from a suite of chemical, biogeochemical and ecological measurements. This talk will report out on the key findings from the workshop which should include identifying the most valuable that should be integrated into long-term coral reef ecosystem monitoring that will aid in discerning changes in coral reef ecosystems in response to ocean acidification. The outcomes should provide: recommendations of the most efficient and robust ways to monitor these metrics; identified augmentations that would be required to current ocean acidification monitoring necessary to achieve these metrics; identify opportunities for immediate collaborations using existing resources that can serve to reduce the identified gaps; and help to clarify expectations for ocean acidification monitoring.
NASA Technical Reports Server (NTRS)
2000-01-01
The BioScan System was developed by OmniCorder Technologies, Inc. at the Jet Propulsion Laboratory. The system is able to locate cancerous lesions by detecting the cancer's ability to recruit a new blood supply. A digital sensor detects infrared energy emitted from the body and identifies the minute differences accompanying the blood flow changes associated with cancerous cells. It also has potential use as a monitoring device during cancer treatment. This technology will reduce the time taken to detect cancerous cells and allow for earlier intervention, therefore increasing the overall survival rates of breast cancer patients.
The INTELSAT VI SSTDMA network diagnostic system
NASA Astrophysics Data System (ADS)
Tamboli, Satish P.; Zhu, Xiaobo; Wilkins, Kim N.; Gupta, Ramesh K.
The system-level design of an expert-system-based, near-real-time diagnostic system for INTELSAT VI satellite-switched time-division multiple access (SSTDMA) network is described. The challenges of INTELSAT VI diagnostics are discussed, along with alternative approaches for network diagnostics and the rationale for choosing a method based on burst unique-word detection. The focal point of the diagnostic system is the diagnostic processor, which resides in the central control and monitoring facility known as the INTELSAT Operations Center TDMA Facility (IOCTF). As real-time information such as burst unique-word detection data, reference terminal status data, and satellite telemetry alarm data are received at the IOCTF, the diagnostic processor continuously monitors the data streams. When a burst status change is detected, a 'snapshot' of the real-time data is forwarded to the expert system. Receipt of the change causes a set of rules to be invoked which associate the traffic pattern with a set of probable causes. A user-friendly interface allows a graphical view of the burst time plan and provides the ability to browse through the knowledge bases.
A pH-based biosensor for detection of arsenic in drinking water.
de Mora, K; Joshi, N; Balint, B L; Ward, F B; Elfick, A; French, C E
2011-05-01
Arsenic contaminated groundwater is estimated to affect over 100 million people worldwide, with Bangladesh and West Bengal being among the worst affected regions. A simple, cheap, accurate and disposable device is required for arsenic field testing. We have previously described a novel biosensor for arsenic in which the output is a change in pH, which can be detected visually as a colour change by the use of a pH indicator. Here, we present an improved formulation allowing sensitive and accurate detection of less than 10 ppb arsenate with static overnight incubation. Furthermore, we describe a cheap and simple high-throughput system for simultaneous monitoring of pH in multiple assays over time. Up to 50 samples can be monitored continuously over the desired time period. Cells can be stored and distributed in either air-dried or freeze-dried form. This system was successfully tested on arsenic-contaminated groundwater samples from the South East region of Hungary. We hope to continue to develop this sensor to produce a device suitable for field trials.
Swann, Don E.; Bucci, Melanie; Kuenzi, Amy J.; Alberti, Barbara N.; Schwalbe, Cecil R.; Halvorson, William L.; van Riper, Charles; Schwalbe, Cecil R.
2010-01-01
Long-term monitoring in national parks is essential to meet National Park Service and other important public goals. Terrestrial mammals are often proposed for monitoring because large mammals are of interest to visitors and small mammals are important as prey. However, traditional monitoring strategies for mammals are often too expensive and complex to sustain for long periods, particularly in small parks. To evaluate potential strategies for long-term monitoring in small parks, we conducted an intensive one-year inventory of terrestrial mammals at Coronado National Memorial, located in Arizona on the U.S.-Mexico international border, then continued less-intensive monitoring at the site for 7 additional years. During 1996-2003 we confirmed 44 species of terrestrial mammals. Most species (40) were detected in the intensive first year of the study, but we continued to detect new species in later years. Mark-recapture data on small mammals indicated large inter-annual fluctuations in population size, but no significant trend over the 7-year period. Issues associated with the international border affected monitoring efforts and increased sampling costs. Our study confirms that sustained annual monitoring of mammals is probably not feasible in small park units like Coronado. However, comparisons of our data with past studies provide insight into important changes in the mammal community since the 1970s, including an increase in abundance and diversity of grassland rodents. Our results suggest that intensive inventories every 10-20 years may be a valuable and cost-effective approach for detecting long-term trends in terrestrial mammal communities in small natural areas.
da Silva, Thiago Ferreira; Xavier, Guilherme B; Temporão, Guilherme P; von der Weid, Jean Pierre
2012-08-13
By employing real-time monitoring of single-photon avalanche photodiodes we demonstrate how two types of practical eavesdropping strategies, the after-gate and time-shift attacks, may be detected. Both attacks are identified with the detectors operating without any special modifications, making this proposal well suited for real-world applications. The monitoring system is based on accumulating statistics of the times between consecutive detection events, and extracting the afterpulse and overall efficiency of the detectors in real-time using mathematical models fit to the measured data. We are able to directly observe changes in the afterpulse probabilities generated from the after-gate and faint after-gate attacks, as well as different timing signatures in the time-shift attack. We also discuss the applicability of our scheme to other general blinding attacks.
NASA Astrophysics Data System (ADS)
Camacho-Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Moreno-Beltrán, Gustavo; Quiroga, Jabid
2017-05-01
Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross-correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in the structural response when damages occur. Two types of damage cases are studied: crack and leak for each structure, respectively. Experimental results show that the methodology is promising in the continuous monitoring of real structures.
Tracking signal test to monitor an intelligent time series forecasting model
NASA Astrophysics Data System (ADS)
Deng, Yan; Jaraiedi, Majid; Iskander, Wafik H.
2004-03-01
Extensive research has been conducted on the subject of Intelligent Time Series forecasting, including many variations on the use of neural networks. However, investigation of model adequacy over time, after the training processes is completed, remains to be fully explored. In this paper we demonstrate a how a smoothed error tracking signals test can be incorporated into a neuro-fuzzy model to monitor the forecasting process and as a statistical measure for keeping the forecasting model up-to-date. The proposed monitoring procedure is effective in the detection of nonrandom changes, due to model inadequacy or lack of unbiasedness in the estimation of model parameters and deviations from the existing patterns. This powerful detection device will result in improved forecast accuracy in the long run. An example data set has been used to demonstrate the application of the proposed method.
Monitoring tissue metabolism via time-resolved laser fluorescence
NASA Astrophysics Data System (ADS)
Maerz, Holger K.; Buchholz, Rainer; Emmrich, Frank; Fink, Frank; Geddes, Clive L.; Pfeifer, Lutz; Raabe, Ferdinand; Marx, Uwe
1999-05-01
Most assays for drug screening are monitoring the metabolism of cells by detecting the NADH content, which symbolize its metabolic activity, indirectly. Nowadays, the performance of a LASER enables us to monitor the metabolic state of mammalian cells directly and on-line by using time-resolved autofluorescence detection. Therefore, we developed in combination with tissue engineering, an assay for monitoring minor toxic effects of volatile organic compounds (VOC), which are accused of inducing Sick Building Syndrome (SBS). Furthermore, we used the Laserfluoroscope (LF) for pharmacological studies on human bone marrow in vitro with special interest in chemotherapy simulation. In cancer research and therapy, the effect of chemostatica in vitro in the so-called oncobiogram is being tested; up to now without great success. However, it showed among other things that tissue structure plays a vital role. Consequently, we succeeded in simulating a chemotherapy in vitro on human bone marrow. Furthermore, after tumor ektomy we were able to distinguish between tumoric and its surrounding healthy tissue by using the LF. With its sensitive detection of metabolic changes in tissues the LF enables a wide range of applications in biotechnology, e.g. for quality control in artificial organ engineering or biocompatability testing.
Neutronic analysis of the 1D and 1E banks reflux detection system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blanchard, A.
1999-12-21
Two H Canyon neutron monitoring systems for early detection of postulated abnormal reflux conditions in the Second Uranium Cycle 1E and 1D Mixer-Settle Banks have been designed and built. Monte Carlo neutron transport simulations using the general purpose, general geometry, n-particle MCNP code have been performed to model expected response of the monitoring systems to varying conditions.The confirmatory studies documented herein conclude that the 1E and 1D neutron monitoring systems are able to achieve adequate neutron count rates for various neutron source and detector configurations, thereby eliminating excessive integration count time. Neutron count rate sensitivity studies are also performed. Conversely,more » the transport studies concluded that the neutron count rates are statistically insensitive to nitric acid content in the aqueous region and to the transition region length. These studies conclude that the 1E and 1D neutron monitoring systems are able to predict the postulated reflux conditions for all examined perturbations in the neutron source and detector configurations. In the cases examined, the relative change in the neutron count rates due to postulated transitions from normal {sup 235}U concentration levels to reflux levels remain satisfactory detectable.« less
Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring
NASA Technical Reports Server (NTRS)
Williams, Martha K.; Lewis, Mark; Szafran, J.; Shelton, C.; Ludwig, L.; Gibson, T.; Lane, J.; Trautwein, T.
2015-01-01
Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.
Vaccarono, Mattia; Bechini, Renzo; Chandrasekar, Chandra V.; ...
2016-11-08
The stability of weather radar calibration is a mandatory aspect for quantitative applications, such as rainfall estimation, short-term weather prediction and initialization of numerical atmospheric and hydrological models. Over the years, calibration monitoring techniques based on external sources have been developed, specifically calibration using the Sun and calibration based on ground clutter returns. In this paper, these two techniques are integrated and complemented with a self-consistency procedure and an intercalibration technique. The aim of the integrated approach is to implement a robust method for online monitoring, able to detect significant changes in the radar calibration. The physical consistency of polarimetricmore » radar observables is exploited using the self-consistency approach, based on the expected correspondence between dual-polarization power and phase measurements in rain. This technique allows a reference absolute value to be provided for the radar calibration, from which eventual deviations may be detected using the other procedures. In particular, the ground clutter calibration is implemented on both polarization channels (horizontal and vertical) for each radar scan, allowing the polarimetric variables to be monitored and hardware failures to promptly be recognized. The Sun calibration allows monitoring the calibration and sensitivity of the radar receiver, in addition to the antenna pointing accuracy. It is applied using observations collected during the standard operational scans but requires long integration times (several days) in order to accumulate a sufficient amount of useful data. Finally, an intercalibration technique is developed and performed to compare colocated measurements collected in rain by two radars in overlapping regions. The integrated approach is performed on the C-band weather radar network in northwestern Italy, during July–October 2014. The set of methods considered appears suitable to establish an online tool to monitor the stability of the radar calibration with an accuracy of about 2 dB. In conclusion, this is considered adequate to automatically detect any unexpected change in the radar system requiring further data analysis or on-site measurements.« less