Relationships between full-day arm movement characteristics and developmental status in infants with typical development as they learn to reach: An observational study

PubMed Central

Shida-Tokeshi, Joanne; Lane, Christianne J.; Trujillo-Priego, Ivan A.; Deng, Weiyang; Vanderbilt, Douglas L.; Loeb, Gerald E.; Smith, Beth A.

2018-01-01

Background: Advances in wearable sensor technology now allow us to quantify the number, type and kinematic characteristics of bouts of infant arm movement made across a full day in the natural environment. Our aim here was to determine whether the amount and kinematic characteristics of arm movements made across the day in the natural environment were related to developmental status in infants with typical development as they learned to reach for objects using their arms. Methods: We used wearable sensors to measure arm movement across days and months as infants developed arm reaching skills. In total, 22 infants with typical development participated, aged between 38 and 203 days. Of the participants, 2 infants were measured once and the other 20 infants were measured once per month for 3 to 6 visits. The Bayley Scales of Infant Development was used to measure developmental level. Results: Our main findings were: 1) infant arm movement characteristics as measured by full-day wearable sensor data were related to Bayley motor, cognitive and language scores, indicating a relationship between daily movement characteristics and developmental status; 2) infants who moved more had larger increases in language and cognitive scores across visits; and 3) larger changes in movement characteristics across visits were related to higher motor scores. Conclusions: This was a preliminary, exploratory, small study of the potential importance of infant arm movement characteristics as measured by full-day wearable sensor data. Our results support full-day arm movement activity as an area of interest for future study as a biomarker of neurodevelopmental status and as a target for early intervention. PMID:29708221

The Performance and Usability of a Factory-Calibrated Flash Glucose Monitoring System

PubMed Central

Bailey, Timothy; Bode, Bruce W.; Christiansen, Mark P.; Klaff, Leslie J.

2015-01-01

Abstract Introduction: The purpose of the study was to evaluate the performance and usability of the FreeStyle® Libre™ Flash glucose monitoring system (Abbott Diabetes Care, Alameda, CA) for interstitial glucose results compared with capillary blood glucose results. Materials and Methods: Seventy-two study participants with type 1 or type 2 diabetes were enrolled by four U.S. clinical sites. A sensor was inserted on the back of each upper arm for up to 14 days. Three factory-only calibrated sensor lots were used in the study. Sensor glucose measurements were compared with capillary blood glucose (BG) results (approximately eight per day) obtained using the BG meter built into the reader (BG reference) and with the YSI analyzer (Yellow Springs Instrument, Yellow Springs, OH) reference tests at three clinic visits (32 samples per visit). Sensor readings were masked to the participants. Results: The accuracy of the results was demonstrated against capillary BG reference values, with 86.7% of sensor results within Consensus Error Grid Zone A. The percentage of readings within Consensus Error Grid Zone A on Days 2, 7, and 14 was 88.4%, 89.2%, and 85.2%, respectively. The overall mean absolute relative difference was 11.4%. The mean lag time between sensor and YSI reference values was 4.5±4.8 min. Sensor accuracy was not affected by factors such as body mass index, age, type of diabetes, clinical site, insulin administration, or hemoglobin A1c. Conclusions: Interstitial glucose measurements with the FreeStyle Libre system were found to be accurate compared with capillary BG reference values, with accuracy remaining stable over 14 days of wear and unaffected by patient characteristics. PMID:26171659

The Performance and Usability of a Factory-Calibrated Flash Glucose Monitoring System.

PubMed

Bailey, Timothy; Bode, Bruce W; Christiansen, Mark P; Klaff, Leslie J; Alva, Shridhara

2015-11-01

The purpose of the study was to evaluate the performance and usability of the FreeStyle(®) Libre™ Flash glucose monitoring system (Abbott Diabetes Care, Alameda, CA) for interstitial glucose results compared with capillary blood glucose results. Seventy-two study participants with type 1 or type 2 diabetes were enrolled by four U.S. clinical sites. A sensor was inserted on the back of each upper arm for up to 14 days. Three factory-only calibrated sensor lots were used in the study. Sensor glucose measurements were compared with capillary blood glucose (BG) results (approximately eight per day) obtained using the BG meter built into the reader (BG reference) and with the YSI analyzer (Yellow Springs Instrument, Yellow Springs, OH) reference tests at three clinic visits (32 samples per visit). Sensor readings were masked to the participants. The accuracy of the results was demonstrated against capillary BG reference values, with 86.7% of sensor results within Consensus Error Grid Zone A. The percentage of readings within Consensus Error Grid Zone A on Days 2, 7, and 14 was 88.4%, 89.2%, and 85.2%, respectively. The overall mean absolute relative difference was 11.4%. The mean lag time between sensor and YSI reference values was 4.5±4.8 min. Sensor accuracy was not affected by factors such as body mass index, age, type of diabetes, clinical site, insulin administration, or hemoglobin A1c. Interstitial glucose measurements with the FreeStyle Libre system were found to be accurate compared with capillary BG reference values, with accuracy remaining stable over 14 days of wear and unaffected by patient characteristics.

The Granite Mountain Atmospheric Sciences Testbed (GMAST): A Facility for Long Term Complex Terrain Airflow Studies

NASA Astrophysics Data System (ADS)

Zajic, D.; Pace, J. C.; Whiteman, C. D.; Hoch, S.

2011-12-01

This presentation describes a new facility at Dugway Proving Ground (DPG), Utah that can be used to study airflow over complex terrain, and to evaluate how airflow over a mountain barrier affects wind patterns over adjacent flatter terrain. DPG's primary mission is to conduct testing, training, and operational assessments of chemical and biological weapon systems. These operations require very precise weather forecasts. Most test operations at DPG are conducted on fairly flat test ranges having uniform surface cover, where airflow patterns are generally well-understood. However, the DPG test ranges are located alongside large, isolated mountains, most notably Granite Mountain, Camelback Mountain, and the Cedar Mountains. Airflows generated over, or influenced by, these mountains can affect wind patterns on the test ranges. The new facility, the Granite Mountain Atmospheric Sciences Testbed, or GMAST, is designed to facilitate studies of airflow interactions with topography. This facility will benefit DPG by improving understanding of how mountain airflows interact with the test range conditions. A core infrastructure of weather sensors around and on Granite Mountain has been developed including instrumented towers and remote sensors, along with automated data collection and archival systems. GMAST is expected to be in operation for a number of years and will provide a reference domain for mountain meteorology studies, with data useful for analysts, modelers and theoreticians. Visiting scientists are encouraged to collaborate with DPG personnel to utilize this valuable scientific resource and to add further equipment and scientific designs for both short-term and long-term atmospheric studies. Several of the upcoming MATERHORN (MountAin TERrain atmospHeric mOdeling and obseRvatioNs) project field tests will be conducted at DPG, giving an example of GMAST utilization and collaboration between DPG and visiting scientists.

Fault detection and isolation in motion monitoring system.

PubMed

Kim, Duk-Jin; Suk, Myoung Hoon; Prabhakaran, B

2012-01-01

Pervasive computing becomes very active research field these days. A watch that can trace human movement to record motion boundary as well as to study of finding social life pattern by one's localized visiting area. Pervasive computing also helps patient monitoring. A daily monitoring system helps longitudinal study of patient monitoring such as Alzheimer's and Parkinson's or obesity monitoring. Due to the nature of monitoring sensor (on-body wireless sensor), however, signal noise or faulty sensors errors can be present at any time. Many research works have addressed these problems any with a large amount of sensor deployment. In this paper, we present the faulty sensor detection and isolation using only two on-body sensors. We have been investigating three different types of sensor errors: the SHORT error, the CONSTANT error, and the NOISY SENSOR error (see more details on section V). Our experimental results show that the success rate of isolating faulty signals are an average of over 91.5% on fault type 1, over 92% on fault type 2, and over 99% on fault type 3 with the fault prior of 30% sensor errors.

Augmented awareness

USDA-ARS?s Scientific Manuscript database

The sounds insects make as they move and feed can be amplified 100–1000x by vibration sensor systems, which makes them easily detectable with headphones. In 2008, I visited Mackay and Bundaberg in Queensland to search for greyback canegrub (Dermolepida albohirtum) and other insect pests in sugarcane...

Effectiveness and Safety of an Extended ICU Visitation Model for Delirium Prevention: A Before and After Study.

PubMed

Rosa, Regis Goulart; Tonietto, Tulio Frederico; da Silva, Daiana Barbosa; Gutierres, Franciele Aparecida; Ascoli, Aline Maria; Madeira, Laura Cordeiro; Rutzen, William; Falavigna, Maicon; Robinson, Caroline Cabral; Salluh, Jorge Ibrain; Cavalcanti, Alexandre Biasi; Azevedo, Luciano Cesar; Cremonese, Rafael Viegas; Haack, Tarissa Ribeiro; Eugênio, Cláudia Severgnini; Dornelles, Aline; Bessel, Marina; Teles, José Mario Meira; Skrobik, Yoanna; Teixeira, Cassiano

2017-10-01

To evaluate the effect of an extended visitation model compared with a restricted visitation model on the occurrence of delirium among ICU patients. Prospective single-center before and after study. Thirty-one-bed medical-surgical ICU. All patients greater than or equal to 18 years old with expected length of stay greater than or equal to 24 hours consecutively admitted to the ICU from May 2015 to November 2015. Change of visitation policy from a restricted visitation model (4.5 hr/d) to an extended visitation model (12 hr/d). Two hundred eighty-six patients were enrolled (141 restricted visitation model, 145 extended visitation model). The primary outcome was the cumulative incidence of delirium, assessed bid using the confusion assessment method for the ICU. Predefined secondary outcomes included duration of delirium/coma; any ICU-acquired infection; ICU-acquired bloodstream infection, pneumonia, and urinary tract infection; all-cause ICU mortality; and length of ICU stay. The median duration of visits increased from 133 minutes (interquartile range, 97.7-162.0) in restricted visitation model to 245 minutes (interquartile range, 175.0-272.0) in extended visitation model (p < 0.001). Fourteen patients (9.6%) developed delirium in extended visitation model compared with 29 (20.5%) in restricted visitation model (adjusted relative risk, 0.50; 95% CI, 0.26-0.95). In comparison with restricted visitation model patients, extended visitation model patients had shorter length of delirium/coma (1.5 d [interquartile range, 1.0-3.0] vs 3.0 d [interquartile range, 2.5-5.0]; p = 0.03) and ICU stay (3.0 d [interquartile range, 2.0-4.0] vs 4.0 d [interquartile range, 2.0-6.0]; p = 0.04). The rate of ICU-acquired infections and all-cause ICU mortality did not differ significantly between the two study groups. In this medical-surgical ICU, an extended visitation model was associated with reduced occurrence of delirium and shorter length of delirium/coma and ICU stay.

Equipment Management for Sensor Networks: Linking Physical Infrastructure and Actions to Observational Data

NASA Astrophysics Data System (ADS)

Jones, A. S.; Horsburgh, J. S.; Matos, M.; Caraballo, J.

2015-12-01

Networks conducting long term monitoring using in situ sensors need the functionality to track physical equipment as well as deployments, calibrations, and other actions related to site and equipment maintenance. The observational data being generated by sensors are enhanced if direct linkages to equipment details and actions can be made. This type of information is typically recorded in field notebooks or in static files, which are rarely linked to observations in a way that could be used to interpret results. However, the record of field activities is often relevant to analysis or post-processing of the observational data. We have developed an underlying database schema and deployed a web interface for recording and retrieving information on physical infrastructure and related actions for observational networks. The database schema for equipment was designed as an extension to the Observations Data Model 2 (ODM2), a community-developed information model for spatially discrete, feature based earth observations. The core entities of ODM2 describe location, observed variable, and timing of observations, and the equipment extension contains entities to provide additional metadata specific to the inventory of physical infrastructure and associated actions. The schema is implemented in a relational database system for storage and management with an associated web interface. We designed the web-based tools for technicians to enter and query information on the physical equipment and actions such as site visits, equipment deployments, maintenance, and calibrations. These tools were implemented for the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) ecohydrologic observatory, and we anticipate that they will be useful for similar large-scale monitoring networks desiring to link observing infrastructure to observational data to increase the quality of sensor-based data products.

Usability of a novel digital medicine system in adults with schizophrenia treated with sensor-embedded tablets of aripiprazole.

PubMed

Peters-Strickland, Timothy; Pestreich, Linda; Hatch, Ainslie; Rohatagi, Shashank; Baker, Ross A; Docherty, John P; Markovtsova, Lada; Raja, Praveen; Weiden, Peter J; Walling, David P

2016-01-01

Digital medicine system (DMS) is a novel drug-device combination that objectively measures and reports medication ingestion. The DMS consists of medication embedded with an ingestible sensor (digital medicine), a wearable sensor, and software applications. This study evaluated usability of the DMS in adults with schizophrenia rated by both patients and their health care providers (HCPs) during 8-week treatment with prescribed doses of digital aripiprazole. Six US sites enrolled outpatients into this Phase IIa, open-label study (NCT02219009). The study comprised a screening phase, a training phase (three weekly site visits), and a 5-week independent phase. Patients and HCPs independently rated usability of and satisfaction with the DMS. Sixty-seven patients were enrolled, and 49 (73.1%) patients completed the study. The mean age (SD) of the patients was 46.6 years (9.7 years); the majority of them were male (74.6%), black (76.1%), and rated mildly ill on the Clinical Global Impression - Severity scale (70.1%). By the end of week 8 or early termination, 82.1% (55/67) of patients had replaced the wearable sensor independently or with minimal assistance, based on HCP rating. The patients used the wearable sensor for a mean (SD) of 70.7% (24.7%) and a median of 77.8% of their time in the trial. The patients contacted a call center most frequently at week 1. At the last visit, 78% (47/60) of patients were somewhat satisfied/satisfied/extremely satisfied with the DMS. A high proportion of patients with schizophrenia were able to use the DMS and reported satisfaction with the DMS. These data support the potential utility of the DMS in clinical practice.

Design and implementation of a bluetooth-based band-aid pulse rate sensor

NASA Astrophysics Data System (ADS)

Kumar, Prashanth S.; Oh, Sechang; Rai, Pratyush; Kwon, Hyeokjun; Banerjee, Nilanjan; Varadan, Vijay K.

2011-04-01

Remote patient monitoring systems capable of collecting vital patient data such as blood pressure readings, Electrocardiograph (ECG) waveforms, and heart rate can obviate the need for repeated visits to the hospital. Moreover, such systems that continuously monitor the human physiology can provide valuable data to prognosticate the onset of critical health problems. The key to such remote health diagnostics is the design of minimally intrusive, low cost sensors that do not impede a patient's quotidian life but at the same time collect reliable noise free data. To this end, in this paper, we design and implement a Bluetooth-based wireless sensor system with a disposable sensor element and a reusable wireless component that can be worn as a "band-aid". The sensor is a piezoelectric polymer film placed on the wrist in proximity to the radial artery. The band-aid sized sensor allows non-intrusive monitoring of the pulsatile flow of blood in the artery. The sensor, using the Bluetooth module, can communicate with any Bluetooth enabled computer, mobile phone, or PDA. The data collected from the patient can be remotely viewed and analyzed by a physician.

The State of Sensor Technology and Air Quality Monitoring

EPA Science Inventory

Produces data of known value and highly reliableStationary- cannot be easily relocatedInstruments are often large and require a building to support their operationExpensive to purchase and operate (typically > $20K each)Requires frequent visits by highly trained staff to check on...

Transmission Line Security Monitor

ScienceCinema

None

2017-12-09

The Transmission Line Security Monitor is a multi-sensor monitor that mounts directly on high-voltage transmission lines to detect, characterize and communicate terrorist activity, human tampering and threatening conditions around support towers. For more information about INL's critical infrastructure protection research, visit http://www.facebook.com/idahonationallaboratory.

Reduction of Energy Intake using Just-In-Time Feedback from a Wearable Sensor System

PubMed Central

Farooq, Muhammad; McCrory, Megan A.; Sazonov, Edward

2017-01-01

Objective This work explored the potential use of a wearable sensor system for providing just-in-time (JIT) feedback on the progression of a meal and tested its ability to reduce the total food mass intake. Methods Eighteen participants each consumed three meals in a lab while monitored by a wearable sensor system capable of accurately tracking chew counts. The baseline visit was used to establish the self-determined ingested mass and the associated chew counts. Real-time feedback on chew counts was provided in the next two visits during which the target chew counts was either the same as that at baseline or the baseline chew counts reduced by 25%, in randomized order. The target was concealed from the participant and from the experimenter. Nonparametric repeated-measures ANOVA were performed to compare mass of intake, meal duration, and ratings of hunger, appetite, and thirst across 3 meals. Results JIT feedback targeting a 25% reduction in chew counts resulted in a reduction in mass and energy intake without affecting perceived hunger or fullness. Conclusion JIT feedback on chewing behavior may reduce intake within a meal. This system can be further used to help develop individualized strategies to provide just-in-time adaptive interventions for reducing energy intake. PMID:28233942

Reduction of energy intake using just-in-time feedback from a wearable sensor system.

PubMed

Farooq, Muhammad; McCrory, Megan A; Sazonov, Edward

2017-04-01

This work explored the potential use of a wearable sensor system for providing just-in-time (JIT) feedback on the progression of a meal and tested its ability to reduce the total food mass intake. Eighteen participants consumed three meals each in a lab while monitored by a wearable sensor system capable of accurately tracking chew counts. The baseline visit was used to establish the self-determined ingested mass and the associated chew counts. Real-time feedback on chew counts was provided in the next two visits, during which the target chew count was either the same as that at baseline or the baseline chew count reduced by 25% (in randomized order). The target was concealed from the participant and from the experimenter. Nonparametric repeated-measures ANOVAs were performed to compare mass of intake, meal duration, and ratings of hunger, appetite, and thirst across three meals. JIT feedback targeting a 25% reduction in chew counts resulted in a reduction in mass and energy intake without affecting perceived hunger or fullness. JIT feedback on chewing behavior may reduce intake within a meal. This system can be further used to help develop individualized strategies to provide JIT adaptive interventions for reducing energy intake. © 2017 The Obesity Society.

Preliminary evaluation of the airborne imaging spectrometer for vegetation analysis

NASA Technical Reports Server (NTRS)

Strahler, A. H.; Woodcock, C. E.

1984-01-01

The primary goal of the project was to provide ground truth and manual interpretation of data from an experimental flight of the Airborne Infrared Spectrometer (AIS) for a naturally vegetated test site. Two field visits were made; one trip to note snow conditions and temporally related vegetation states at the time of the sensor overpass, and a second trip following acquisition of prints of the AIS images for field interpretation. Unfortunately, the ability to interpret the imagery was limited by the quality of the imagery due to the experimental nature of the sensor.

Do diabetes group visits lead to lower medical care charges?

PubMed

Clancy, Dawn E; Dismuke, Clara E; Magruder, Kathryn Marley; Simpson, Kit N; Bradford, David

2008-01-01

To evaluate whether attending diabetes group visits (GVs) leads to lower medical care charges for inadequately insured patients with type 2 diabetes mellitus (DM). Randomized controlled clinical trial. Data were abstracted from financial records for 186 patients with uncontrolled type 2 DM randomized to receive care in GVs or usual care for 12 months. Mann-Whitney tests for differences of means for outpatient visits (primary and specialty care), emergency department (ED) visits, and inpatient stays were performed. Separate charge models were developed for primary and specialty outpatient visits. Because GV adherence is potentially dependent on unobserved patient characteristics, treatment effect models of outpatient charges and specialty care visits were estimated using maximum likelihood methods. Mann-Whitney test results indicated that GV patients had reduced ED and total charges but more outpatient charges than usual care patients. Ordinary least squares estimations confirmed that GVs increased outpatient visit charges; however, controlling for endogeneity by estimating a treatment effect model of outpatient visit charges showed that GVs statistically significantly reduced outpatient charges (P <.001). Estimation of a separate treatment effect model of specialty care visits confirmed that GV effects on outpatient visit charges occurred via a reduction in specialty care visits. After controlling for endogeneity via estimation of a treatment effect model, GVs statistically significantly reduced outpatient visit charges. Estimation of a separate treatment effect model of specialty care visits indicated that GVs likely substitute for more expensive specialty care visits.

Wavelet PCA for automatic identification of walking with and without an exoskeleton on a treadmill using pressure and accelerometer sensors.

PubMed

Naik, Ganesh R; Pendharkar, Gita; Nguyen, Hung T

2016-08-01

Nowadays portable devices with more number of sensors are used for gait assessment and monitoring for elderly and disabled. However, the problem with using multiple sensors is that if they are placed on the same platform or base, there could be cross talk between them, which could change the signal amplitude or add noise to the signal. Hence, this study uses wavelet PCA as a signal processing technique to separate the original sensor signal from the signal obtained from the sensors through the integrated unit to compare the two types of walking (with and without an exoskeleton). This comparison using wavelet PCA will enable the researchers to obtain accurate sensor data and compare and analyze the data in order to further improve the design of compact portable devices used to monitor and assess the gait in stroke or paralyzed subjects. The advantage of designing such systems is that they can also be used to assess and monitor the gait of the stroke subjects at home, which will save them time and efforts to visit the laboratory or clinic.

The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System.

PubMed

Caduff, Andreas; Zanon, Mattia; Mueller, Martin; Zakharov, Pavel; Feldman, Yuri; De Feo, Oscar; Donath, Marc; Stahel, Werner A; Talary, Mark S

2015-07-01

We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate. Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived. We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals. We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches. © 2015 Diabetes Technology Society.

The value of redundant measurements - highlights from AmeriFlux site visits using a portable eddy covariance system

NASA Astrophysics Data System (ADS)

Chan, S.; Billesbach, D. P.; Hanson, C. V.; Dengel, S.; Polonik, P.; Biraud, S.

2016-12-01

The AmeriFlux network conducts independent site visits using a portable eddy covariance system (PECS). Short-term (<2 weeks), side-by-side comparisons enable the network to evaluate inter-comparability between sites, improve data quality, and assess measurement uncertainty across the network. The PECS includes commonly used sensors for turbulent flux, radiation, and meteorological measurements which are maintained and calibrated using established best practices at levels at or above the manufacturer's recommendations. The importance of site visits was realized at the inception of the AmeriFlux network with the first site visit in 1997. Since that time, more than 180 site visits at over 120 different sites have been conducted. Site visit reports over the years have led to many key findings and important advances within the flux community which are highlighted in the presentation. Furthermore, we summarize and synthesize results from recent site comparisons that were conducted with the latest generation of the PECS (2013-present). The presentation quantifies observed differences between the PECS and network sites for key flux, radiation, and meteorological metrics. The aggregated comparisons provide insight into comparability amongst network sites as well as areas for improvement. We identify common errors and issues and discuss some best practices.

Factors affecting yearly and monthly visits to Taipei Zoo

NASA Astrophysics Data System (ADS)

Su, Ai-Tsen; Lin, Yann-Jou

2018-02-01

This study investigated factors affecting yearly and monthly numbers of visits to Taipei Zoo. Both linear and nonlinear regression models were used to estimate yearly visits. The results of both models showed that the "opening effect" and "animal star effect" had a significantly positive effect on yearly visits, while a SARS outbreak had a negative effect. The number of years had a significant influence on yearly visits. Results showed that the nonlinear model had better explanatory power and fitted the variations of visits better. Results of monthly model showed that monthly visits were significantly influenced by time fluctuations, weather conditions, and the animal star effect. Chinese New Year, summer vacation, numbers of holidays, and animal star exhibitions increased the number of monthly visits, while the number of days with temperatures at or below 15 °C, the number of days with temperatures at or above 30 °C, and the number of rainy days had significantly negative effects. Furthermore, the model of monthly visits showed that the animal star effect could last for over two quarters. The results of this study clarify the factors affecting visits to an outdoor recreation site and confirm the importance of meteorological factors to recreation use.

Time series modeling for syndromic surveillance.

PubMed

Reis, Ben Y; Mandl, Kenneth D

2003-01-23

Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization.

Monitoring Quality Across Home Visiting Models: A Field Test of Michigan's Home Visiting Quality Assurance System.

PubMed

Heany, Julia; Torres, Jennifer; Zagar, Cynthia; Kostelec, Tiffany

2018-06-05

Introduction In order to achieve the positive outcomes with parents and children demonstrated by many home visiting models, home visiting services must be well implemented. The Michigan Home Visiting Initiative developed a tool and procedure for monitoring implementation quality across models referred to as Michigan's Home Visiting Quality Assurance System (MHVQAS). This study field tested the MHVQAS. This article focuses on one of the study's evaluation questions: Can the MHVQAS be applied across models? Methods Eight local implementing agencies (LIAs) from four home visiting models (Healthy Families America, Early Head Start-Home Based, Parents as Teachers, Maternal Infant Health Program) and five reviewers participated in the study by completing site visits, tracking their time and costs, and completing surveys about the process. LIAs also submitted their most recent review by their model developer. The researchers conducted participant observation of the review process. Results Ratings on the MHVQAS were not significantly different between models. There were some differences in interrater reliability and perceived reliability between models. There were no significant differences between models in perceived validity, satisfaction with the review process, or cost to participate. Observational data suggested that cross-model applicability could be improved by assisting sites in relating the requirements of the tool to the specifics of their model. Discussion The MHVQAS shows promise as a tool and process to monitor implementation quality of home visiting services across models. The results of the study will be used to make improvements before the MHVQAS is used in practice.

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

NASA Technical Reports Server (NTRS)

Strube, Matthew; Henry, Ross; Skeleton, Eugene; Eepoel, John Van; Gill, Nat; McKenna, Reed

2015-01-01

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

PubMed

Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

2017-07-10

Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

CULTURAL ADAPTATIONS OF EVIDENCE-BASED HOME-VISITATION MODELS IN TRIBAL COMMUNITIES.

PubMed

Hiratsuka, Vanessa Y; Parker, Myra E; Sanchez, Jenae; Riley, Rebecca; Heath, Debra; Chomo, Julianna C; Beltangady, Moushumi; Sarche, Michelle

2018-05-01

The Tribal Maternal, Infant, and Early Childhood Home Visiting (Tribal MIECHV) Program provides federal grants to tribes, tribal consortia, tribal organizations, and urban Indian organizations to implement evidence-based home-visiting services for American Indian and Alaska Native (AI/AN) families. To date, only one evidence-based home-visiting program has been developed for use in AI/AN communities. The purpose of this article is to describe the steps that four Tribal MIECHV Programs took to assess community needs, select a home-visiting model, and culturally adapt the model for use in AI/AN communities. In these four unique Tribal MIECHV Program settings, each program employed a rigorous needs-assessment process and developed cultural modifications in accordance with community strengths and needs. Adaptations occurred in consultation with model developers, with consideration of the conceptual rationale for the program, while grounding new content in indigenous cultures. Research is needed to improve measurement of home-visiting outcomes in tribal and urban AI/AN settings, develop culturally grounded home-visiting interventions, and assess the effectiveness of home visiting in AI/AN communities. © 2018 Michigan Association for Infant Mental Health.

Fires in Philippines

NASA Technical Reports Server (NTRS)

2002-01-01

Roughly a dozen fires (red pixels) dotted the landscape on the main Philippine island of Luzon on April 1, 2002. This true-color image was acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard NASA's Terra spacecraft. Please note that the high-resolution scene provided here is 500 meters per pixel. For a copy of this scene at the sensor's fullest resolution, visit the MODIS Rapidfire site.

ACD16-0001-018

NASA Image and Video Library

2016-01-06

This Nissan LEAF vehicle being tested on the Ames campus is equipped with cameras, sensors and cellular data networking, and uses robotics software originally developed for Ames’ K-10 and K-REX planetary rovers to operate autonomously. Shown here are Kathy Sun and Liam Pedersen, Nissan who are awaiting the arrival of the visiting group from Renault-Nissan Alliance for a demo ride across Ames.

Feasibility of an Orthogonal Redundant Sensor incorporating Optical plus Redundant Electrochemical Glucose Sensing.

PubMed

McAuley, Sybil A; Dang, Tri T; Horsburgh, Jodie C; Bansal, Anubhuti; Ward, Glenn M; Aroyan, Sarkis; Jenkins, Alicia J; MacIsaac, Richard J; Shah, Rajiv V; O'Neal, David N

2016-05-01

Orthogonal redundancy for glucose sensing (multiple sensing elements utilizing distinct methodologies) may enhance performance compared to nonredundant sensors, and to sensors with multiple elements utilizing the same technology (simple redundancy). We compared the performance of a prototype orthogonal redundant sensor (ORS) combining optical fluorescence and redundant electrochemical sensing via a single insertion platform to an electrochemical simple redundant sensor (SRS). Twenty-one adults with type 1 diabetes wore an ORS and an SRS concurrently for 7 days. Following sensor insertion, and on Day 4 with a standardized meal, frequent venous samples were collected for reference glucose measurement (laboratory [YSI] and meter) over 3 and 4 hours, respectively. Between study visits reference capillary blood glucose testing was undertaken. Sensor data were processed prospectively. ORS mean absolute relative difference (MARD) was (mean ± SD) 10.5 ± 13.2% versus SRS 11.0 ± 10.4% (P = .34). ORS values in Clarke error grid zones A and A+B were 88.1% and 97.6%, respectively, versus SRS 86.4% and 97.8%, respectively (P = .23 and P = .84). ORS Day 1 MARD (10.7 ± 10.7%) was superior to SRS (16.5 ± 13.4%; P < .0001), and comparable to ORS MARD for the week. ORS sensor survival (time-averaged mean) was 92.1% versus SRS 74.4% (P = .10). ORS display time (96.0 ± 5.8%) was equivalent to SRS (95.6 ± 8.9%; P = .87). Combining simple and orthogonal sensor redundancy via a single insertion is feasible, with accuracy comparing favorably to current generation nonredundant sensors. Addition of an optical component potentially improves sensor reliability compared to electrochemical sensing alone. Further improvement in optical sensing performance is required prior to clinical application. © 2016 Diabetes Technology Society.

Motion perception: behavior and neural substrate.

PubMed

Mather, George

2011-05-01

Visual motion perception is vital for survival. Single-unit recordings in primate primary visual cortex (V1) have revealed the existence of specialized motion sensing neurons; perceptual effects such as the motion after-effect demonstrate their importance for motion perception. Human psychophysical data on motion detection can be explained by a computational model of cortical motion sensors. Both psychophysical and physiological data reveal at least two classes of motion sensor capable of sensing motion in luminance-defined and texture-defined patterns, respectively. Psychophysical experiments also reveal that motion can be seen independently of motion sensor output, based on attentive tracking of visual features. Sensor outputs are inherently ambiguous, due to the problem of univariance in neural responses. In order to compute stimulus direction and speed, the visual system must compare the responses of many different sensors sensitive to different directions and speeds. Physiological data show that this computation occurs in the visual middle temporal (MT) area. Recent psychophysical studies indicate that information about spatial form may also play a role in motion computations. Adaptation studies show that the human visual system is selectively sensitive to large-scale optic flow patterns, and physiological studies indicate that cells in the middle superior temporal (MST) area derive this sensitivity from the combined responses of many MT cells. Extraretinal signals used to control eye movements are an important source of signals to cancel out the retinal motion responses generated by eye movements, though visual information also plays a role. A number of issues remain to be resolved at all levels of the motion-processing hierarchy. WIREs Cogni Sci 2011 2 305-314 DOI: 10.1002/wcs.110 For further resources related to this article, please visit the WIREs website Additional Supporting Information may be found in http://www.lifesci.sussex.ac.uk/home/George_Mather/Motion/index.html. Copyright © 2010 John Wiley & Sons, Ltd.

Smart home in a box: usability study for a large scale self-installation of smart home technologies.

PubMed

Hu, Yang; Tilke, Dominique; Adams, Taylor; Crandall, Aaron S; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-07-01

This study evaluates the ability of users to self-install a smart home in a box (SHiB) intended for use by a senior population. SHiB is a ubiquitous system, developed by the Washington State University Center for Advanced Studies in Adaptive Systems (CASAS). Participants involved in this study are from the greater Palouse region of Washington State, and there are 13 participants in the study with an average age of 69.23. The SHiB package, which included several different types of components to collect and transmit sensor data, was given to participants to self-install. After installation of the SHiB, the participants were visited by researchers for a check of the installation. The researchers evaluated how well the sensors were installed and asked the resident questions about the installation process to help improve the SHiB design. The results indicate strengths and weaknesses of the SHiB design. Indoor motion tracking sensors are installed with high success rate, low installation success rate was found for door sensors and setting up the Internet server.

Smart home in a box: usability study for a large scale self-installation of smart home technologies

PubMed Central

Hu, Yang; Tilke, Dominique; Adams, Taylor; Crandall, Aaron S.; Schmitter-Edgecombe, Maureen

2017-01-01

This study evaluates the ability of users to self-install a smart home in a box (SHiB) intended for use by a senior population. SHiB is a ubiquitous system, developed by the Washington State University Center for Advanced Studies in Adaptive Systems (CASAS). Participants involved in this study are from the greater Palouse region of Washington State, and there are 13 participants in the study with an average age of 69.23. The SHiB package, which included several different types of components to collect and transmit sensor data, was given to participants to self-install. After installation of the SHiB, the participants were visited by researchers for a check of the installation. The researchers evaluated how well the sensors were installed and asked the resident questions about the installation process to help improve the SHiB design. The results indicate strengths and weaknesses of the SHiB design. Indoor motion tracking sensors are installed with high success rate, low installation success rate was found for door sensors and setting up the Internet server. PMID:28936390

KSC-2011-7542

NASA Image and Video Library

2011-10-26

VANDENBERG AIR FORCE BASE, Calif. -- A model of the NASA’s National Polar-orbiting Operational Environmental Satellite System Preparatory Project (NPP) spacecraft is displayed during the prelaunch news conference at Vandenberg Air Force Base, Calif. NPP represents a critical first step in building the next-generation of Earth-observing satellites. NPP will carry the first of the new sensors developed for this satellite fleet, now known as the Joint Polar Satellite System (JPSS), to be launched in 2016. NPP is the bridge between NASA's Earth Observing System (EOS) satellites and the forthcoming series of JPSS satellites. The mission will test key technologies and instruments for the JPSS missions. NPP is targeted to launch Oct. 28 from Space Launch Complex-2 aboard a United Launch Alliance Delta II rocket. For more information, visit http://www.nasa.gov/NPP. Photo credit: NASA/VAFB

Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model

NASA Astrophysics Data System (ADS)

Novikov, Ilya; Kalter-Leibovici, Ofra; Chetrit, Angela; Stav, Nir; Epstein, Yoram

2012-01-01

Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April-October, 2001-2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate ( r 2 = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits ( P < 0.001). An increase in electrical power consumption significantly attenuated the effect of weather conditions on ER visits by 4% per 1,000 MWh ( P < 0.001). Higher daily mean SO2 concentrations were associated with a greater number of ER visits (1% per 1 ppb increment; P = 0.017). Calendar data were the main predictors of ER visits ( r 2 = 0.794). The predictive model was highly accurate in forecasting the number of visits to ERs 2 days ahead. The marginal effect of temperature on the number of ER visits can be attributed to behavioral adaptations, including the use of air-conditioning.

Modeling Health Care Expenditures and Use.

PubMed

Deb, Partha; Norton, Edward C

2018-04-01

Health care expenditures and use are challenging to model because these dependent variables typically have distributions that are skewed with a large mass at zero. In this article, we describe estimation and interpretation of the effects of a natural experiment using two classes of nonlinear statistical models: one for health care expenditures and the other for counts of health care use. We extend prior analyses to test the effect of the ACA's young adult expansion on three different outcomes: total health care expenditures, office-based visits, and emergency department visits. Modeling the outcomes with a two-part or hurdle model, instead of a single-equation model, reveals that the ACA policy increased the number of office-based visits but decreased emergency department visits and overall spending.

Air Pollution Exposure Modeling for Health Studies | Science ...

EPA Pesticide Factsheets

Dr. Michael Breen is leading the development of air pollution exposure models, integrated with novel personal sensor technologies, to improve exposure and risk assessments for individuals in health studies. He is co-investigator for multiple health studies assessing the exposure and effects of air pollutants. These health studies include participants with asthma, diabetes, and coronary artery disease living in various U.S. cities. He has developed, evaluated, and applied novel exposure modeling and time-activity tools, which includes the Exposure Model for Individuals (EMI), GPS-based Microenvironment Tracker (MicroTrac) and Exposure Tracker models. At this seminar, Dr. Breen will present the development and application of these models to predict individual-level personal exposures to particulate matter (PM) for two health studies in central North Carolina. These health studies examine the association between PM and adverse health outcomes for susceptible individuals. During Dr. Breen’s visit, he will also have the opportunity to establish additional collaborations with researchers at Harvard University that may benefit from the use of exposure models for cohort health studies. These research projects that link air pollution exposure with adverse health outcomes benefit EPA by developing model-predicted exposure-dose metrics for individuals in health studies to improve the understanding of exposure-response behavior of air pollutants, and to reduce participant

Fixture For Mounting A Pressure Sensor

NASA Technical Reports Server (NTRS)

Cagle, Christopher M.

1995-01-01

Fixture for mounting pressure sensor in aerodynamic model simplifies task of removal and replacement of sensor in event sensor becomes damaged. Makes it unnecessary to dismantle model. Also minimizes any change in aerodynamic characteristics of model in event of replacement. Removable pressure sensor installed in fixture in wall of model. Wires from sensor pass through channel under surface.

Interacting coastal based ecosystem services: recreation and water quality in Puget Sound, WA

USGS Publications Warehouse

Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William

2013-01-01

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments.

Interacting Coastal Based Ecosystem Services: Recreation and Water Quality in Puget Sound, WA

PubMed Central

Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William

2013-01-01

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments. PMID:23451067

Collaborative Monitoring and Hazard Mitigation at Fuego Volcano, Guatemala

NASA Astrophysics Data System (ADS)

Lyons, J. J.; Bluth, G. J.; Rose, W. I.; Patrick, M.; Johnson, J. B.; Stix, J.

2007-05-01

A portable, digital sensor network has been installed to closely monitor changing activity at Fuego volcano, which takes advantage of an international collaborative effort among Guatemala, U.S. and Canadian universities, and the Peace Corps. The goal of this effort is to improve the understanding shallow internal processes, and consequently to more effectively mitigate volcanic hazards. Fuego volcano has had more than 60 historical eruptions and nearly-continuous activity make it an ideal laboratory to study volcanic processes. Close monitoring is needed to identify base-line activity, and rapidly identify and disseminate changes in the activity which might threaten nearby communities. The sensor network is comprised of a miniature DOAS ultraviolet spectrometer fitted with a system for automated plume scans, a digital video camera, and two seismo-acoustic stations and portable dataloggers. These sensors are on loan from scientists who visited Fuego during short field seasons and donated use of their sensors to a resident Peace Corps Masters International student from Michigan Technological University for extended data collection. The sensor network is based around the local volcano observatory maintained by Instituto National de Sismologia, Vulcanologia, Metrologia e Hidrologia (INSIVUMEH). INSIVUMEH provides local support and historical knowledge of Fuego activity as well as a secure location for storage of scientific equipment, data processing, and charging of the batteries that power the sensors. The complete sensor network came online in mid-February 2007 and here we present preliminary results from concurrent gas, seismic, and acoustic monitoring of activity from Fuego volcano.

Optical modeling toward optimizing monitoring of intestinal perfusion in trauma patients

NASA Astrophysics Data System (ADS)

Akl, Tony J.; Wilson, Mark A.; Ericson, M. N.; Coté, Gerard L.

2013-02-01

Trauma is the number one cause of death for people between the ages 1 and 44 years in the United States. In addition, according to the Centers of Disease Control and Prevention, injury results in over 31 million emergency department visits annually. Minimizing the resuscitation period in major abdominal injuries increases survival rates by correcting impaired tissue oxygen delivery. Optimization of resuscitation requires a monitoring method to determine sufficient tissue oxygenation. Oxygenation can be assessed by determining the adequacy of tissue perfusion. In this work, we present the design of a wireless perfusion and oxygenation sensor based on photoplethysmography. Through optical modeling, the benefit of using the visible wavelengths 470, 525 and 590nm (around the 525nm hemoglobin isobestic point) for intestinal perfusion monitoring is compared to the typical near infrared (NIR) wavelengths (805nm isobestic point) used in such sensors. Specifically, NIR wavelengths penetrate through the thin intestinal wall ( 4mm) leading to high background signals. However, these visible wavelengths have two times shorter penetration depth that the NIR wavelengths. Monte-Carlo simulations show that the transmittance of the three selected wavelengths is lower by 5 orders of magnitude depending on the perfusion state. Due to the high absorbance of hemoglobin in the visible range, the perfusion signal carried by diffusely reflected light is also enhanced by an order of magnitude while oxygenation signal levels are maintained. In addition, short source-detector separations proved to be beneficial for limiting the probing depth to the thickness of the intestinal wall.

Should Supervisors Intervene during Classroom Visits?

ERIC Educational Resources Information Center

Marshall, Kim

2015-01-01

Real-time coaching has become the go-to supervisory model in some schools (especially charters), with supervisors routinely jumping in during teacher observations and sometimes taking over the class to model a more effective approach. The author sets out goals and guidelines for impromptu classroom visits that include visiting each classroom at…

Automated Water Quality Survey and Evaluation Using an IoT Platform with Mobile Sensor Nodes.

PubMed

Li, Teng; Xia, Min; Chen, Jiahong; Zhao, Yuanjie; de Silva, Clarence

2017-07-28

An Internet of Things (IoT) platform with capabilities of sensing, data processing, and wireless communication has been deployed to support remote aquatic environmental monitoring. In this paper, the design and development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the spatiotemporal quality evaluation of surface water is presented. A survey planner is proposed to distribute the Sampling Locations of Interest (SLoIs) over the study area and generate paths for MSNs to visit the SLoIs, given the limited energy and time budgets. The SLoIs are chosen based on a cellular decomposition that is composed of uniform hexagonal cells. They are visited by the MSNs along a path ring generated by a planning approach that uses a spanning tree. For quality evaluation, an Online Water Quality Index (OLWQI) is developed to interpret the large quantities of online measurements. The index formulations are modified by a state-of-the-art index, the CCME WQI, which has been developed by the Canadian Council of Ministers of Environment (CCME) for off-line indexing. The proposed index has demonstrated effective and reliable performance in online indexing a large volume of measurements of water quality parameters. The IoT platform is deployed in the field, and its performance is demonstrated and discussed in this paper.

Wired enzyme electrodes--a retroperspective story about an exciting time at University of Texas at Austin and its impact on my scientific career.

PubMed

Lindquist, Sten-Eric

2013-07-22

The present paper features an exciting time in the late 1980s when I, as a visiting scientist, had the privilege to participate in the early and very exciting development of the in vivo redox-polymer-wired glucose sensor in Professor Adam Heller's laboratory at the Department of Chemical Engineering at University of Texas at Austin. This story is followed by an overview of the research my visit initiated at Uppsala University. In collaboration with Swedish colleagues, we explored a few of the many possibilities to form new biosensors by utilizing Prof. Heller's concept of cross-linked redox-polymer/redox-enzyme electrodes. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Close To You? How Parent–Adult Child Contact Is Influenced by Family Patterns

PubMed Central

Spitze, Glenna; Ward, Russell A.; Zhuo, Yue (Angela)

2016-01-01

Objectives. Intergenerational contacts occur in the context of other family relationships. We examine how in-person contacts among parents and all adult children affect each other, focusing on proximity and other predictors to assess whether and how visiting is correlated across adult children. Methods. We use a modeling approach derived from an adaptation of multilevel models to provide a convenient mechanism by which to write child-specific equations, each with its own set of predictors, and wherein one child’s attribute values can be attached to other children’s records. Results. We find that parent–adult child visiting is positively correlated across siblings, but the frequency of visiting within families is not directly reciprocated. Rather, visiting responds to common family factors. Visiting declines with distance, but there are strong discontinuities in the effect. Distance between parents and a focal child is positively associated with visiting with other children. Discussion. The empirical patterns we report can be framed within enhancement and compensation models. Positive correlations and cross-sibling interactions that juxtapose levels of visiting against not seeing a child in last 12 months are consistent with the enhancement model. The cross-sibling interaction for distance, whereby one child’s farther distance leads to more visits reported with others, provides evidence of a countervailing, though, weaker, pattern of compensation for proximity. PMID:26024669

Weather and Prey Predict Mammals' Visitation to Water.

PubMed

Harris, Grant; Sanderson, James G; Erz, Jon; Lehnen, Sarah E; Butler, Matthew J

2015-01-01

Throughout many arid lands of Africa, Australia and the United States, wildlife agencies provide water year-round for increasing game populations and enhancing biodiversity, despite concerns that water provisioning may favor species more dependent on water, increase predation, and reduce biodiversity. In part, understanding the effects of water provisioning requires identifying why and when animals visit water. Employing this information, by matching water provisioning with use by target species, could assist wildlife management objectives while mitigating unintended consequences of year-round watering regimes. Therefore, we examined if weather variables (maximum temperature, relative humidity [RH], vapor pressure deficit [VPD], long and short-term precipitation) and predator-prey relationships (i.e., prey presence) predicted water visitation by 9 mammals. We modeled visitation as recorded by trail cameras at Sevilleta National Wildlife Refuge, New Mexico, USA (June 2009 to September 2014) using generalized linear modeling. For 3 native ungulates, elk (Cervus Canadensis), mule deer (Odocoileus hemionus), and pronghorn (Antilocapra americana), less long-term precipitation and higher maximum temperatures increased visitation, including RH for mule deer. Less long-term precipitation and higher VPD increased oryx (Oryx gazella) and desert cottontail rabbits (Sylvilagus audubonii) visitation. Long-term precipitation, with RH or VPD, predicted visitation for black-tailed jackrabbits (Lepus californicus). Standardized model coefficients demonstrated that the amount of long-term precipitation influenced herbivore visitation most. Weather (especially maximum temperature) and prey (cottontails and jackrabbits) predicted bobcat (Lynx rufus) visitation. Mule deer visitation had the largest influence on coyote (Canis latrans) visitation. Puma (Puma concolor) visitation was solely predicted by prey visitation (elk, mule deer, oryx). Most ungulate visitation peaked during May and June. Coyote, elk and puma visitation was relatively consistent throughout the year. Within the diel-period, activity patterns for predators corresponded with prey. Year-round water management may favor species with consistent use throughout the year, and facilitate predation. Providing water only during periods of high use by target species may moderate unwanted biological costs.

Weather and Prey Predict Mammals’ Visitation to Water

PubMed Central

Harris, Grant; Sanderson, James G.; Erz, Jon; Lehnen, Sarah E.; Butler, Matthew J.

2015-01-01

Throughout many arid lands of Africa, Australia and the United States, wildlife agencies provide water year-round for increasing game populations and enhancing biodiversity, despite concerns that water provisioning may favor species more dependent on water, increase predation, and reduce biodiversity. In part, understanding the effects of water provisioning requires identifying why and when animals visit water. Employing this information, by matching water provisioning with use by target species, could assist wildlife management objectives while mitigating unintended consequences of year-round watering regimes. Therefore, we examined if weather variables (maximum temperature, relative humidity [RH], vapor pressure deficit [VPD], long and short-term precipitation) and predator-prey relationships (i.e., prey presence) predicted water visitation by 9 mammals. We modeled visitation as recorded by trail cameras at Sevilleta National Wildlife Refuge, New Mexico, USA (June 2009 to September 2014) using generalized linear modeling. For 3 native ungulates, elk (Cervus Canadensis), mule deer (Odocoileus hemionus), and pronghorn (Antilocapra americana), less long-term precipitation and higher maximum temperatures increased visitation, including RH for mule deer. Less long-term precipitation and higher VPD increased oryx (Oryx gazella) and desert cottontail rabbits (Sylvilagus audubonii) visitation. Long-term precipitation, with RH or VPD, predicted visitation for black-tailed jackrabbits (Lepus californicus). Standardized model coefficients demonstrated that the amount of long-term precipitation influenced herbivore visitation most. Weather (especially maximum temperature) and prey (cottontails and jackrabbits) predicted bobcat (Lynx rufus) visitation. Mule deer visitation had the largest influence on coyote (Canis latrans) visitation. Puma (Puma concolor) visitation was solely predicted by prey visitation (elk, mule deer, oryx). Most ungulate visitation peaked during May and June. Coyote, elk and puma visitation was relatively consistent throughout the year. Within the diel-period, activity patterns for predators corresponded with prey. Year-round water management may favor species with consistent use throughout the year, and facilitate predation. Providing water only during periods of high use by target species may moderate unwanted biological costs. PMID:26560518

The Visiting Specialist Model of Rural Health Care Delivery: A Survey in Massachusetts

ERIC Educational Resources Information Center

Drew, Jacob; Cashman, Suzanne B.; Savageau, Judith A.; Stenger, Joseph

2006-01-01

Context: Hospitals in rural communities may seek to increase specialty care access by establishing clinics staffed by visiting specialists. Purpose: To examine the visiting specialist care delivery model in Massachusetts, including reasons specialists develop secondary rural practices and distances they travel, as well as their degree of…

Mathematical models and photogrammetric exploitation of image sensing

NASA Astrophysics Data System (ADS)

Puatanachokchai, Chokchai

Mathematical models of image sensing are generally categorized into physical/geometrical sensor models and replacement sensor models. While the former is determined from image sensing geometry, the latter is based on knowledge of the physical/geometric sensor models and on using such models for its implementation. The main thrust of this research is in replacement sensor models which have three important characteristics: (1) Highly accurate ground-to-image functions; (2) Rigorous error propagation that is essentially of the same accuracy as the physical model; and, (3) Adjustability, or the ability to upgrade the replacement sensor model parameters when additional control information becomes available after the replacement sensor model has replaced the physical model. In this research, such replacement sensor models are considered as True Replacement Models or TRMs. TRMs provide a significant advantage of universality, particularly for image exploitation functions. There have been several writings about replacement sensor models, and except for the so called RSM (Replacement Sensor Model as a product described in the Manual of Photogrammetry), almost all of them pay very little or no attention to errors and their propagation. This is because, it is suspected, the few physical sensor parameters are usually replaced by many more parameters, thus presenting a potential error estimation difficulty. The third characteristic, adjustability, is perhaps the most demanding. It provides an equivalent flexibility to that of triangulation using the physical model. Primary contributions of this thesis include not only "the eigen-approach", a novel means of replacing the original sensor parameter covariance matrices at the time of estimating the TRM, but also the implementation of the hybrid approach that combines the eigen-approach with the added parameters approach used in the RSM. Using either the eigen-approach or the hybrid approach, rigorous error propagation can be performed during image exploitation. Further, adjustability can be performed when additional control information becomes available after the TRM has been implemented. The TRM is shown to apply to imagery from sensors having different geometries, including an aerial frame camera, a spaceborne linear array sensor, an airborne pushbroom sensor, and an airborne whiskbroom sensor. TRM results show essentially negligible differences as compared to those from rigorous physical sensor models, both for geopositioning from single and overlapping images. Simulated as well as real image data are used to address all three characteristics of the TRM.

Fires in Idaho and Montana

NASA Technical Reports Server (NTRS)

2002-01-01

2000 continues to be the worst fire season in the United States in decades. By August 8, 2000, fires in Montana and Idaho had burned more than 250,000 acres. Resources were stretched so thin that Army and Marine soldiers were recruited to help fight the fires. President Clinton visited Payette National Forest to lend moral support to the firefighters. Dense smoke from Idaho and western Montana is visible stretching all the way to North and South Dakota in this image from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The image was taken on August 7, 2000. Although the primary mission of SeaWiFS is to measure the biology of the ocean, it also provides stunning color imagery of the Earth's surface. For more information about fires in the U.S., visit the National Interagency Fire Center. To learn more about using satellites to monitor fires, visit Global Fire Monitoring and New Technology for Monitoring Fires from Space in the Earth Observatory. Provided by the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE

Network exploitation using WAMI tracks

NASA Astrophysics Data System (ADS)

Rimey, Ray; Record, Jim; Keefe, Dan; Kennedy, Levi; Cramer, Chris

2011-06-01

Creating and exploiting network models from wide area motion imagery (WAMI) is an important task for intelligence analysis. Tracks of entities observed moving in the WAMI sensor data are extracted, then large numbers of tracks are studied over long time intervals to determine specific locations that are visited (e.g., buildings in an urban environment), what locations are related to other locations, and the function of each location. This paper describes several parts of the network detection/exploitation problem, and summarizes a solution technique for each: (a) Detecting nodes; (b) Detecting links between known nodes; (c) Node attributes to characterize a node; (d) Link attributes to characterize each link; (e) Link structure inferred from node attributes and vice versa; and (f) Decomposing a detected network into smaller networks. Experimental results are presented for each solution technique, and those are used to discuss issues for each problem part and its solution technique.

KSC-2011-7543

NASA Image and Video Library

2011-10-26

VANDENBERG AIR FORCE BASE, Calif. -- A model of the NASA’s National Polar-orbiting Operational Environmental Satellite System Preparatory Project (NPP) spacecraft and the United Launch Alliance Delta II rocket are displayed during the prelaunch news conference at Vandenberg Air Force Base, Calif. NPP represents a critical first step in building the next-generation of Earth-observing satellites. NPP will carry the first of the new sensors developed for this satellite fleet, now known as the Joint Polar Satellite System (JPSS), to be launched in 2016. NPP is the bridge between NASA's Earth Observing System (EOS) satellites and the forthcoming series of JPSS satellites. The mission will test key technologies and instruments for the JPSS missions. NPP is targeted to launch Oct. 28 from Space Launch Complex-2 aboard a United Launch Alliance Delta II rocket. For more information, visit http://www.nasa.gov/NPP. Photo credit: NASA/VAFB

Deep-brain stimulator and control of Parkinson's disease

NASA Astrophysics Data System (ADS)

Varadan, Vijay K.; Harbaugh, Robert; Abraham, Jose K.

2004-07-01

The design of a novel feedback sensor system with wireless implantable polymer MEMS sensors for detecting and wirelessly transmitting physiological data that can be used for the diagnosis and treatment of various neurological disorders, such as Parkinson's disease, epilepsy, head injury, stroke, hydrocephalus, changes in pressure, patient movements, and tremors is presented in this paper. The sensor system includes MEMS gyroscopes, accelerometers, and pressure sensors. This feedback sensor system focuses on the development and integration of implantable systems with various wireless sensors for medical applications, particularly for the Parkinson's disease. It is easy to integrate and modify the sensor network feed back system for other neurological disorders mentioned above. The monitoring and control of tremor in Parkinson's disease can be simulated on a skeleton via wireless telemetry system communicating with electroactive polymer actuator, and microsensors attached to the skeleton hand and legs. Upon sensing any abnormal motor activity which represent the characteristic rhythmic motion of a typical Parkinson's (PD) patient, these sensors will generate necessary control pulses which will be transmitted to a hat sensor system on the skeleton head. Tiny inductively coupled antennas attached to the hat sensor system can receive these control pulses, demodulate and deliver it to actuate the parts of the skeleton to control the abnormal motor activity. This feedback sensor system can further monitor and control depending on the amplitude of the abnormal motor activity. This microsystem offers cost effective means of monitoring and controlling of neurological disorders in real PD patients. Also, this network system offers a remote monitoring of the patients conditions without visiting doctors office or hospitals. The data can be monitored using PDA and can be accessed using internet (or cell phone). Cellular phone technology will allow a health care worker to be automatically notified if monitoring indicates an emergency situation. The main advantage of such system is that it can effectively monitor large number of patients at the same time, which helps to compensate the present shortage of health care workers.

Fires and Heavy Smoke in Alaska

NASA Technical Reports Server (NTRS)

2002-01-01

On May 28, 2002, the Moderate Resolution Imaging Spectroradiometer (MODIS) captured this image of fires that continue to burn in central Alaska. Alaska is very dry and warm for this time of year, and has experienced over 230 wildfires so far this season. Please note that the high-resolution scene provided here is 500 meters per pixel. For a copy of the scene at the sensor's fullest resolution, visit the MODIS Rapid Response Image Gallery.

Providing Home Visiting to High-Risk Pregnant and Postpartum Families: The Development and Evaluation of the MOMobile® Program

ERIC Educational Resources Information Center

Hadley, Barbara; Rudolph, Kara E.; Mogul, Marjie; Perry, Deborah F.

2014-01-01

Maternal, Infant, and Early Childhood Home Visiting legislation permits states to fund "promising practices"--with the understanding that these models will have a rigorous evaluation component. This article describes an innovative, low cost paraprofessional home visiting model developed in Pennsylvania by the Maternity Care Coalition. In…

42 CFR § 512.600 - Waiver of direct supervision requirement for certain post-discharge home visits.

Code of Federal Regulations, 2010 CFR

2017-10-01

... & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) HEALTH CARE INFRASTRUCTURE AND MODEL PROGRAMS EPISODE PAYMENT MODEL Waivers § 512.600 Waiver of direct supervision requirement for certain post...-discharge home visits. (c) Payment. Up to the maximum post-discharge home visits for a specific EPM episode...

Modeling of a Surface Acoustic Wave Strain Sensor

NASA Technical Reports Server (NTRS)

Wilson, W. C.; Atkinson, Gary M.

2010-01-01

NASA Langley Research Center is investigating Surface Acoustic Wave (SAW) sensor technology for harsh environments aimed at aerospace applications. To aid in development of sensors a model of a SAW strain sensor has been developed. The new model extends the modified matrix method to include the response of Orthogonal Frequency Coded (OFC) reflectors and the response of SAW devices to strain. These results show that the model accurately captures the strain response of a SAW sensor on a Langasite substrate. The results of the model of a SAW Strain Sensor on Langasite are presented

A sneak peek into digital innovations and wearable sensors for cardiac monitoring.

PubMed

Michard, Frederic

2017-04-01

Many mobile phone or tablet applications have been designed to control cardiovascular risk factors (obesity, smoking, sedentary lifestyle, diabetes and hypertension) or to optimize treatment adherence. Some have been shown to be useful but the long-term benefits remain to be demonstrated. Digital stethoscopes make easier the interpretation of abnormal heart sounds, and the development of pocket-sized echo machines may quickly and significantly expand the use of ultrasounds. Daily home monitoring of pulmonary artery pressures with wireless implantable sensors has been shown to be associated with a significant decrease in hospital readmissions for heart failure. There are more and more non-invasive, wireless, and wearable sensors designed to monitor heart rate, heart rate variability, respiratory rate, arterial oxygen saturation, and thoracic fluid content. They have the potential to change the way we monitor and treat patients with cardiovascular diseases in the hospital and beyond. Some may have the ability to improve quality of care, decrease the number of medical visits and hospitalization, and ultimately health care costs. Validation and outcome studies are needed to clarify, among the growing number of digital innovations and wearable sensors, which tools have real clinical value.

Modeling Analysis of a Six-axis Force/Tactile Sensor for Robot Fingers and a Method for Decreasing Error

NASA Astrophysics Data System (ADS)

Luo, Minghua; Shimizu, Etsuro; Zhang, Feifei; Ito, Masanori

This paper describes a six-axis force/tactile sensor for robot fingers. A mathematical model of this sensor is proposed. By this model, the grasping force and its moments, and touching position of robot finger for holding an object can be calculated. A new sensor is fabricated based on this model, where the elastic sensing unit of the sensor is made of a brazen plate. A new compensating method for decreasing error is proposed. Furthermore, the performance of this sensor is examined. The test results present approximate relationship between theoretical input and output of the sensor. It is obvious that the performance of the new sensor is better than the sensor with no compensation.

Using Google Flu Trends data in forecasting influenza-like-illness related ED visits in Omaha, Nebraska.

PubMed

Araz, Ozgur M; Bentley, Dan; Muelleman, Robert L

2014-09-01

Emergency department (ED) visits increase during the influenza seasons. It is essential to identify statistically significant correlates in order to develop an accurate forecasting model for ED visits. Forecasting influenza-like-illness (ILI)-related ED visits can significantly help in developing robust resource management strategies at the EDs. We first performed correlation analyses to understand temporal correlations between several predictors of ILI-related ED visits. We used the data available for Douglas County, the biggest county in Nebraska, for Omaha, the biggest city in the state, and for a major hospital in Omaha. The data set included total and positive influenza test results from the hospital (ie, Antigen rapid (Ag) and Respiratory Syncytial Virus Infection (RSV) tests); an Internet-based influenza surveillance system data, that is, Google Flu Trends, for both Nebraska and Omaha; total ED visits in Douglas County attributable to ILI; and ILI surveillance network data for Douglas County and Nebraska as the predictors and data for the hospital's ILI-related ED visits as the dependent variable. We used Seasonal Autoregressive Integrated Moving Average and Holt Winters methods with3 linear regression models to forecast ILI-related ED visits at the hospital and evaluated model performances by comparing the root means square errors (RMSEs). Because of strong positive correlations with ILI-related ED visits between 2008 and 2012, we validated the use of Google Flu Trends data as a predictor in an ED influenza surveillance tool. Of the 5 forecasting models we have tested, linear regression models performed significantly better when Google Flu Trends data were included as a predictor. Regression models including Google Flu Trends data as a predictor variable have lower RMSE, and the lowest is achieved when all other variables are also included in the model in our forecasting experiments for the first 5 weeks of 2013 (with RMSE = 57.61). Google Flu Trends data statistically improve the performance of predicting ILI-related ED visits in Douglas County, and this result can be generalized to other communities. Timely and accurate estimates of ED volume during the influenza season, as well as during pandemic outbreaks, can help hospitals plan their ED resources accordingly and lower their costs by optimizing supplies and staffing and can improve service quality by decreasing ED wait times and overcrowding. Copyright © 2014 Elsevier Inc. All rights reserved.

Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan.

PubMed

Juang, Wang-Chuan; Huang, Sin-Jhih; Huang, Fong-Dee; Cheng, Pei-Wen; Wann, Shue-Ren

2017-12-01

Emergency department (ED) overcrowding is acknowledged as an increasingly important issue worldwide. Hospital managers are increasingly paying attention to ED crowding in order to provide higher quality medical services to patients. One of the crucial elements for a good management strategy is demand forecasting. Our study sought to construct an adequate model and to forecast monthly ED visits. We retrospectively gathered monthly ED visits from January 2009 to December 2016 to carry out a time series autoregressive integrated moving average (ARIMA) analysis. Initial development of the model was based on past ED visits from 2009 to 2016. A best-fit model was further employed to forecast the monthly data of ED visits for the next year (2016). Finally, we evaluated the predicted accuracy of the identified model with the mean absolute percentage error (MAPE). The software packages SAS/ETS V.9.4 and Office Excel 2016 were used for all statistical analyses. A series of statistical tests showed that six models, including ARIMA (0, 0, 1), ARIMA (1, 0, 0), ARIMA (1, 0, 1), ARIMA (2, 0, 1), ARIMA (3, 0, 1) and ARIMA (5, 0, 1), were candidate models. The model that gave the minimum Akaike information criterion and Schwartz Bayesian criterion and followed the assumptions of residual independence was selected as the adequate model. Finally, a suitable ARIMA (0, 0, 1) structure, yielding a MAPE of 8.91%, was identified and obtained as Visit t =7111.161+(a t +0.37462 a t -1). The ARIMA (0, 0, 1) model can be considered adequate for predicting future ED visits, and its forecast results can be used to aid decision-making processes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Impact of continuous glucose monitoring on quality of life, treatment satisfaction, and use of medical care resources: analyses from the SWITCH study.

PubMed

Hommel, E; Olsen, B; Battelino, T; Conget, I; Schütz-Fuhrmann, I; Hoogma, R; Schierloh, U; Sulli, N; Gough, H; Castañeda, J; de Portu, S; Bolinder, J

2014-10-01

To investigate the impact of continuous glucose monitoring (CGM) on health-related quality of life (HRQOL), treatment satisfaction (TS) medical resource use, and indirect costs in the SWITCH study. SWITCH was a multicentre, randomized, crossover study. Patients with type 1 diabetes (n = 153) using continuous subcutaneous insulin infusion (CSII) were randomized to a 12 month sensor-On/Off or sensor-Off/On sequence (6 months each treatment), with a 4-month washout between periods. HRQOL in children and TS in adults were measured using validated questionnaires. Medical resource utilization data were collected. In adults, TS was significantly higher in the sensor-On arm, and there were significant improvements in ratings for treatment convenience and flexibility. There were no clinically significant differences in children's HRQOL or parents' proxy ratings. The incidence of severe hypoglycaemia, unscheduled visits, or diabetes-related hospitalizations did not differ significantly between the two arms. Adult patients made fewer telephone consultations during the sensor-On arm; children's caregivers made similar numbers of telephone consultations during both arms, and calls were on average only 3 min longer during the sensor-On arm. Regarding indirect costs, children with >70 % sensor usage missed fewer school days, compared with the sensor-Off arm (P = 0.0046) but there was no significant difference in the adults days of work off. The addition of CGM to CSII resulted in better metabolic control without imposing an additional burden on the patient or increased medical resource use, and offered the potential for cost offsets.

Burden of norovirus gastroenteritis in the ambulatory setting--United States, 2001-2009.

PubMed

Gastañaduy, Paul A; Hall, Aron J; Curns, Aaron T; Parashar, Umesh D; Lopman, Benjamin A

2013-04-01

Gastroenteritis remains an important cause of morbidity in the United States. The burden of norovirus gastroenteritis in ambulatory US patients is not well understood. Cause-specified and cause-unspecified gastroenteritis emergency department (ED) and outpatient visits during July 2001-June 2009 were extracted from MarketScan insurance claim databases. By using cause-specified encounters, time-series regression models were fitted to predict the number of unspecified gastroenteritis visits due to specific pathogens other than norovirus. Model residuals were used to estimate norovirus visits. MarketScan rates were extrapolated to the US population to estimate national ambulatory visits. During 2001-2009, the estimated annual mean rates of norovirus-associated ED and outpatient visits were 14 and 57 cases per 10 000 persons, respectively, across all ages. Rates for ages 0-4, 5-17, 18-64, and ≥65 years were 38, 10, 12, and 15 ED visits per 10 000 persons, respectively, and 233, 85, 35, and 54 outpatient visits per 10 000 persons, respectively. Norovirus was estimated to cause 13% of all gastroenteritis-associated ambulatory visits, with ~50% of such visits occurring during November-February. Nationally, norovirus contributed to approximately 400 000 ED visits and 1.7 million office visits annually, resulting in $284 million in healthcare charges. Norovirus is a substantial cause of gastroenteritis in the ambulatory setting.

Application of zonal model on indoor air sensor network design

NASA Astrophysics Data System (ADS)

Chen, Y. Lisa; Wen, Jin

2007-04-01

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

PubMed

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

2014-08-25

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

PubMed Central

Dinh, Thanh; Kim, Younghan

2016-01-01

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

PubMed

Dinh, Thanh; Kim, Younghan

2016-06-28

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

A Multi-factorial Model for Examining Racial and Ethnic Disparities in Acute Asthma Visits by Children

PubMed Central

Feldman, Jonathan M.; Serebrisky, Denise; Spray, Amanda

2012-01-01

Background Causes of children’s asthma health disparities are complex. Parents’ asthma illness representations may play a role. Purpose The study aims to test a theoretically based, multi-factorial model for ethnic disparities in children’s acute asthma visits through parental illness representations. Methods Structural equation modeling investigated the association of parental asthma illness representations, sociodemographic characteristics, health care provider factors, and social–environmental context with children’s acute asthma visits among 309 White, Puerto Rican, and African American families was conducted. Results Forty-five percent of the variance in illness representations and 30% of the variance in acute visits were accounted for. Statistically significant differences in illness representations were observed by ethnic group. Approximately 30% of the variance in illness representations was explained for whites, 23% for African Americans, and 26% for Puerto Ricans. The model accounted for >30% of the variance in acute visits for African Americans and Puerto Ricans but only 19% for the whites. Conclusion The model provides preliminary support that ethnic heterogeneity in asthma illness representations affects children’s health outcomes. PMID:22160799

Innovative Home Visit Models Associated With Reductions In Costs, Hospitalizations, And Emergency Department Use.

PubMed

Ruiz, Sarah; Snyder, Lynne Page; Rotondo, Christina; Cross-Barnet, Caitlin; Colligan, Erin Murphy; Giuriceo, Katherine

2017-03-01

While studies of home-based care delivered by teams led by primary care providers have shown cost savings, little is known about outcomes when practice-extender teams-that is, teams led by registered nurses or lay health workers-provide home visits with similar components (for example, care coordination and education). We evaluated findings from five models funded by Health Care Innovation Awards of the Centers for Medicare and Medicaid Services. Each model used a mix of different components to strengthen connections to primary care among fee-for-service Medicare beneficiaries with multiple chronic conditions; these connections included practice-extender home visits. Two models achieved significant reductions in Medicare expenditures, and three models reduced utilization in the form of emergency department visits, hospitalizations, or both for beneficiaries relative to comparators. These findings present a strong case for the potential value of home visits by practice-extender teams to reduce Medicare expenditures and service use in a particularly vulnerable and costly segment of the Medicare population. Project HOPE—The People-to-People Health Foundation, Inc.

Protected Area Tourism in a Changing Climate: Will Visitation at US National Parks Warm Up or Overheat?

PubMed

Fisichelli, Nicholas A; Schuurman, Gregor W; Monahan, William B; Ziesler, Pamela S

2015-01-01

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979-2013) at 340 parks and projected potential future visitation (2041-2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67-77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8-23%) and expansion of the visitation season at individual parks (13-31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation.

Protected Area Tourism in a Changing Climate: Will Visitation at US National Parks Warm Up or Overheat?

PubMed Central

Fisichelli, Nicholas A.; Schuurman, Gregor W.; Monahan, William B.; Ziesler, Pamela S.

2015-01-01

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979–2013) at 340 parks and projected potential future visitation (2041–2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67–77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8–23%) and expansion of the visitation season at individual parks (13–31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation. PMID:26083361

Perspectives of family medicine physicians on the importance of adolescent preventive care: a multivariate analysis.

PubMed

Taylor, Jaime L; Aalsma, Matthew C; Gilbert, Amy L; Hensel, Devon J; Rickert, Vaughn I

2016-01-20

The study objective was to identify commonalities amongst family medicine physicians who endorse annual adolescent visits. A nationally weighted representative on-line survey was used to explore pediatrician (N = 204) and family medicine physicians (N = 221) beliefs and behaviors surrounding adolescent wellness. Our primary outcome was endorsement that adolescents should receive annual preventive care visits. Pediatricians were significantly more likely (p < .01) to endorse annual well visits. Among family medicine physicians, bivariate comparisons were conducted between those who endorsed an annual visit (N = 164) compared to those who did not (N = 57) with significant predictors combined into two multivariate logistic regression models. Model 1 controlled for: patient race, proportion of 13-17 year olds in provider's practice, discussion beliefs scale and discussion behaviors with parents scale. Model 2 controlled for the same first three variables as well as discussion behaviors with adolescents scale. Model 1 showed for each discussion beliefs scale topic selected, family medicine physicians had 1.14 increased odds of endorsing annual visits (p < .001) and had 1.11 greater odds of endorsing annual visits with each one-point increase in discussion behaviors with parents scale (p = .51). Model 2 showed for each discussion beliefs scale topic selected, family medicine physicians had 1.15 increased odds of also endorsing the importance of annual visits (p < .001). Family medicine physicians that endorse annual visits are significantly more likely to affirm they hold strong beliefs about topics that should be discussed during the annual exam. They also act on these beliefs by talking to parents of teens about these topics. This group appears to focus on quality of care in thought and deed.

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites

PubMed Central

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-01-01

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons. PMID:27092508

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites.

PubMed

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-04-15

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons.

Implementation Differences of Two Staffing Models in the German Home Visiting Program "Pro Kind"

ERIC Educational Resources Information Center

Brand, Tilman; Jungmann, Tanja

2012-01-01

As different competencies or professional backgrounds may affect the quality of program implementation, staffing is a critical issue in home visiting. In this study, N = 430 women received home visits delivered either by a tandem of a midwife and a social worker or by only one home visitor (primarily midwives, continuous model). The groups were…

Development of esMOCA Biomechanic, Motion Capture Instrumentation for Biomechanics Analysis

NASA Astrophysics Data System (ADS)

Arendra, A.; Akhmad, S.

2018-01-01

This study aims to build motion capture instruments using inertial measurement unit sensors to assist in the analysis of biomechanics. Sensors used are accelerometer and gyroscope. Estimation of orientation sensors is done by digital motion processing in each sensor nodes. There are nine sensor nodes attached to the upper limbs. This sensor is connected to the pc via a wireless sensor network. The development of kinematics and inverse dynamamic models of the upper limb is done in simulink simmechanic. The kinematic model receives streaming data of sensor nodes mounted on the limbs. The output of the kinematic model is the pose of each limbs and visualized on display. The dynamic inverse model outputs the reaction force and reaction moment of each joint based on the limb motion input. Model validation in simulink with mathematical model of mechanical analysis showed results that did not differ significantly

Modelling the impact of new patient visits on risk adjusted access at 2 clinics.

PubMed

Kolber, Michael A; Rueda, Germán; Sory, John B

2018-06-01

To evaluate the effect new outpatient clinic visits has on the availability of follow-up visits for established patients when patient visit frequency is risk adjusted. Diagnosis codes for patients from 2 Internal Medicine Clinics were extracted through billing data. The HHS-HCC risk adjusted scores for each clinic were determined based upon the average of all clinic practitioners' profiles. These scores were then used to project encounter frequencies for established patients, and for new patients entering the clinic based on risk and time of entry into the clinics. A distinct mean risk frequency distribution for physicians in each clinic could be defined providing model parameters. Within the model, follow-up visit utilization at the highest risk adjusted visit frequencies would require more follow-up slots than currently available when new patient no-show rates and annual patient loss are included. Patients seen at an intermediate or lower visit risk adjusted frequency could be accommodated when new patient no-show rates and annual patient clinic loss are considered. Value-based care is driven by control of cost while maintaining quality of care. In order to control cost, there has been a drive to increase visit frequency in primary care for those patients at increased risk. Adding new patients to primary care clinics limits the availability of follow-up slots that accrue over time for those at highest risk, thereby limiting disease and, potentially, cost control. If frequency of established care visits can be reduced by improved disease control, closing the practice to new patients, hiring health care extenders, or providing non-face to face care models then quality and cost of care may be improved. © 2018 John Wiley & Sons, Ltd.

Color regeneration from reflective color sensor using an artificial intelligent technique.

PubMed

Saracoglu, Ömer Galip; Altural, Hayriye

2010-01-01

A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

An Econometric Model of Healthcare Demand With Nonlinear Pricing.

PubMed

Kunz, Johannes S; Winkelmann, Rainer

2017-06-01

From 2004 to 2012, the German social health insurance levied a co-payment for the first doctor visit in a calendar quarter. We develop a new model for estimating the effect of such a co-payment on the individual number of visits per quarter. The model combines a one-time increase in the otherwise constant hazard rate determining the timing of doctor visits with a difference-in-differences strategy to identify the reform effect. An extended version of the model accounts for a mismatch between reporting period and calendar quarter. Using data from the German Socio-Economic Panel, we do not find an effect of the co-payment on demand for doctor visits. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sensor fusion display evaluation using information integration models in enhanced/synthetic vision applications

NASA Technical Reports Server (NTRS)

Foyle, David C.

1993-01-01

Based on existing integration models in the psychological literature, an evaluation framework is developed to assess sensor fusion displays as might be implemented in an enhanced/synthetic vision system. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The pilot's performance with the sensor fusion image is compared to models' predictions based on the pilot's performance when viewing the original component sensor images prior to fusion. This allows for the determination as to when a sensor fusion system leads to: poorer performance than one of the original sensor displays, clearly an undesirable system in which the fused sensor system causes some distortion or interference; better performance than with either single sensor system alone, but at a sub-optimal level compared to model predictions; optimal performance compared to model predictions; or, super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays.

The TECH@HOME study, a technological intervention to reduce caregiver burden for informal caregivers of people with dementia: study protocol for a randomized controlled trial.

PubMed

Malmgren Fänge, Agneta; Schmidt, Steven M; Nilsson, Maria H; Carlsson, Gunilla; Liwander, Anna; Dahlgren Bergström, Caroline; Olivetti, Paolo; Johansson, Per; Chiatti, Carlos

2017-02-09

It is estimated that global dementia rates will more than triple by 2050 and result in a staggering economic burden on families and societies. Dementia carries significant physical, psychological and social challenges for individuals and caregivers. Informal caregiving is common and increasing as more people with dementia are being cared for at home instead of in nursing homes. Caregiver burden is associated with lower perceived health, lower social coherence, and increased risk of morbidity and mortality. The aim of this trial is to evaluate the effects of information and communication technology (ICT) on caregiver burden among informal caregivers of people with dementia by reducing the need for supervision. This randomized controlled trial aims to recruit 320 dyads composed of people with dementia living in community settings and their primary informal caregivers. In the intervention group, people with dementia will have a home monitoring kit installed in their home while dyads in the control group will receive usual care. The ICT kit includes home-leaving sensors, smoke and water leak sensors, bed sensors, and automatic lights that monitor the individual's behavior. Alerts (text message and/or phone call) will be sent to the caregiver if anything unusual occurs. All study dyads will receive three home visits by project administrators who have received project-specific training in order to harmonize data collection. Home visits will take place at enrollment and 3 and 12 months following installation of the ICT kit. At every home visit, a standardized questionnaire will be administered to all dyads to assess their health, quality of life and resource utilization. The primary outcome of this trial is the amount of informal care support provided by primary informal caregivers to people with dementia. This is the first randomized controlled trial exploring the implementation of ICT for people with dementia in a large sample in Sweden and one of the first at the international level. Results hold the potential to inform regional and national policy-makers in Sweden and beyond about the cost-effectiveness of ICT and its impact on caregiver burden. ClinicalTrials.gov, NCT02733939 . Registered on 10 March 2016.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

PubMed

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-10-27

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information

PubMed Central

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-01-01

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794

Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan

PubMed Central

Juang, Wang-Chuan; Huang, Sin-Jhih; Huang, Fong-Dee; Cheng, Pei-Wen; Wann, Shue-Ren

2017-01-01

Objective Emergency department (ED) overcrowding is acknowledged as an increasingly important issue worldwide. Hospital managers are increasingly paying attention to ED crowding in order to provide higher quality medical services to patients. One of the crucial elements for a good management strategy is demand forecasting. Our study sought to construct an adequate model and to forecast monthly ED visits. Methods We retrospectively gathered monthly ED visits from January 2009 to December 2016 to carry out a time series autoregressive integrated moving average (ARIMA) analysis. Initial development of the model was based on past ED visits from 2009 to 2016. A best-fit model was further employed to forecast the monthly data of ED visits for the next year (2016). Finally, we evaluated the predicted accuracy of the identified model with the mean absolute percentage error (MAPE). The software packages SAS/ETS V.9.4 and Office Excel 2016 were used for all statistical analyses. Results A series of statistical tests showed that six models, including ARIMA (0, 0, 1), ARIMA (1, 0, 0), ARIMA (1, 0, 1), ARIMA (2, 0, 1), ARIMA (3, 0, 1) and ARIMA (5, 0, 1), were candidate models. The model that gave the minimum Akaike information criterion and Schwartz Bayesian criterion and followed the assumptions of residual independence was selected as the adequate model. Finally, a suitable ARIMA (0, 0, 1) structure, yielding a MAPE of 8.91%, was identified and obtained as Visitt=7111.161+(at+0.37462 at−1). Conclusion The ARIMA (0, 0, 1) model can be considered adequate for predicting future ED visits, and its forecast results can be used to aid decision-making processes. PMID:29196487

Does information available at admission for delivery improve prediction of vaginal birth after cesarean?

PubMed Central

Grobman, William A.; Lai, Yinglei; Landon, Mark B.; Spong, Catherine Y.; Leveno, Kenneth J.; Rouse, Dwight J.; Varner, Michael W.; Moawad, Atef H.; Simhan, Hyagriv N.; Harper, Margaret; Wapner, Ronald J.; Sorokin, Yoram; Miodovnik, Menachem; Carpenter, Marshall; O'sullivan, Mary J.; Sibai, Baha M.; Langer, Oded; Thorp, John M.; Ramin, Susan M.; Mercer, Brian M.

2010-01-01

Objective To construct a predictive model for vaginal birth after cesarean (VBAC) that combines factors that can be ascertained only as the pregnancy progresses with those known at initiation of prenatal care. Study design Using multivariable modeling, we constructed a predictive model for VBAC that included patient factors known at the initial prenatal visit as well as those that only became evident as the pregancy progressed to the admission for delivery. Results 9616 women were analyzed. The regression equation for VBAC success included multiple factors that could not be known at the first prenatal visit. The area under the curve for this model was significantly greater (P < .001) than that of a model that included only factors available at the first prenatal visit. Conclusion A prediction model for VBAC success that incorporates factors that can be ascertained only as the pregnancy progresses adds to the predictive accuracy of a model that uses only factors available at a first prenatal visit. PMID:19813165

Stream Tracker: Crowd sourcing and remote sensing to monitor stream flow intermittence

NASA Astrophysics Data System (ADS)

Puntenney, K.; Kampf, S. K.; Newman, G.; Lefsky, M. A.; Weber, R.; Gerlich, J.

2017-12-01

Streams that do not flow continuously in time and space support diverse aquatic life and can be critical contributors to downstream water supply. However, these intermittent streams are rarely monitored and poorly mapped. Stream Tracker is a community powered stream monitoring project that pairs citizen contributed observations of streamflow presence or absence with a network of streamflow sensors and remotely sensed data from satellites to track when and where water is flowing in intermittent stream channels. Citizens can visit sites on roads and trails to track flow and contribute their observations to the project site hosted by CitSci.org. Data can be entered using either a mobile application with offline capabilities or an online data entry portal. The sensor network provides a consistent record of streamflow and flow presence/absence across a range of elevations and drainage areas. Capacitance, resistance, and laser sensors have been deployed to determine the most reliable, low cost sensor that could be mass distributed to track streamflow intermittence over a larger number of sites. Streamflow presence or absence observations from the citizen and sensor networks are then compared to satellite imagery to improve flow detection algorithms using remotely sensed data from Landsat. In the first two months of this project, 1,287 observations have been made at 241 sites by 24 project members across northern and western Colorado.

A model-based reasoning approach to sensor placement for monitorability

NASA Technical Reports Server (NTRS)

Chien, Steve; Doyle, Richard; Homemdemello, Luiz

1992-01-01

An approach is presented to evaluating sensor placements to maximize monitorability of the target system while minimizing the number of sensors. The approach uses a model of the monitored system to score potential sensor placements on the basis of four monitorability criteria. The scores can then be analyzed to produce a recommended sensor set. An example from our NASA application domain is used to illustrate our model-based approach to sensor placement.

Chaparral Model 60 Infrasound Sensor Evaluation.

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

Slad, George William; Merchant, Bion J.

2016-03-01

Sandia National Laboratories has tested and evaluated an infrasound sensor, the Model 60 manufactured by Chaparral Physics, a Division of Geophysical Institute of the University of Alaska, Fairbanks. The purpose of the infrasound sensor evaluation was to determine a measured sensitivity, transfer function, power, self-noise, dynamic range, and seismic sensitivity. The Model 60 infrasound sensor is a new sensor developed by Chaparral Physics intended to be a small, rugged sensor used in more flexible application conditions.

Greek Wildfires

NASA Technical Reports Server (NTRS)

2002-01-01

Hot, dry weather has contributed to a string of fires that burned in Greece during the first two weeks of July 2000. Smoke from one of these fires is streaming across Greece and out into the Aegean Sea in this image taken July 13, 2000, by the Sea-viewing Wide Field of view Sensor (SeaWiFS). For more about SeaWiFS, visit the SeaWiFS home page. Provided by the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE

KSC-2014-4826

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander soars 800 feet above the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida on free flight test No. 15 at. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4825

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander soars 800 feet above the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida on free flight test No. 15 at. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4829

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander soars overhead during free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4824

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander takes off on free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4827

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander soars 800 feet above the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida on free flight test No. 15. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4828

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander soars overhead during free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

Man-Portable Vector EMI Sensor for Full UXO Characterization

DTIC Science & Technology

2012-03-01

receivers (for survey in forest and/or in steep terrain). Left inset shows data acquisition (DAQ) and power unit mounted on a backpack frame. Right panel...survey list was created such as to minimize the overall travel distance to visit every anomaly. After the daily IVS survey field operators walked to...the red star at coordinates (0, 0), is generally offset from the signal peak. This observation motivated use of a conservative 3x3-point-grid survey

Automated Water Quality Survey and Evaluation Using an IoT Platform with Mobile Sensor Nodes

PubMed Central

Li, Teng; Xia, Min; Chen, Jiahong; Zhao, Yuanjie; de Silva, Clarence

2017-01-01

An Internet of Things (IoT) platform with capabilities of sensing, data processing, and wireless communication has been deployed to support remote aquatic environmental monitoring. In this paper, the design and development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the spatiotemporal quality evaluation of surface water is presented. A survey planner is proposed to distribute the Sampling Locations of Interest (SLoIs) over the study area and generate paths for MSNs to visit the SLoIs, given the limited energy and time budgets. The SLoIs are chosen based on a cellular decomposition that is composed of uniform hexagonal cells. They are visited by the MSNs along a path ring generated by a planning approach that uses a spanning tree. For quality evaluation, an Online Water Quality Index (OLWQI) is developed to interpret the large quantities of online measurements. The index formulations are modified by a state-of-the-art index, the CCME WQI, which has been developed by the Canadian Council of Ministers of Environment (CCME) for off-line indexing. The proposed index has demonstrated effective and reliable performance in online indexing a large volume of measurements of water quality parameters. The IoT platform is deployed in the field, and its performance is demonstrated and discussed in this paper. PMID:28788098

The visiting specialist model of rural health care delivery: a survey in Massachusetts.

PubMed

Drew, Jacob; Cashman, Suzanne B; Savageau, Judith A; Stenger, Joseph

2006-01-01

Hospitals in rural communities may seek to increase specialty care access by establishing clinics staffed by visiting specialists. To examine the visiting specialist care delivery model in Massachusetts, including reasons specialists develop secondary rural practices and distances they travel, as well as their degree of satisfaction and intention to continue the visiting arrangement. Visiting specialists at 11 rural hospitals were asked to complete a mailed survey. Visiting specialists were almost evenly split between the medical (54%) and surgical (46%) specialties, with ophthalmology, nephrology, and obstetrics/gynecology the most common specialties reported. A higher proportion of visiting specialists than specialists statewide were male (P = .001). Supplementing their patient base and income were the most important reasons visiting specialists reported for having initiated an ancillary clinic. There was a significant negative correlation between a hospital's number of staffed beds and the total number of visiting specialists it hosted (r =-0.573, P = .032); study hospitals ranged in bed size from 15 to 129. The goal of matching supply of health care services with demand has been elusive. Visiting specialist clinics may represent an element of a market structure that expands access to needed services in rural areas. They should be included in any enumeration of physician availability.

Modeling Carbon-Black/Polymer Composite Sensors

PubMed Central

Lei, Hua; Pitt, William G.; McGrath, Lucas K.; Ho, Clifford K.

2012-01-01

Conductive polymer composite sensors have shown great potential in identifying gaseous analytes. To more thoroughly understand the physical and chemical mechanisms of this type of sensor, a mathematical model was developed by combining two sub-models: a conductivity model and a thermodynamic model, which gives a relationship between the vapor concentration of analyte(s) and the change of the sensor signals. In this work, 64 chemiresistors representing eight different carbon concentrations (8–60 vol% carbon) were constructed by depositing thin films of a carbon-black/polyisobutylene composite onto concentric spiral platinum electrodes on a silicon chip. The responses of the sensors were measured in dry air and at various vapor pressures of toluene and trichloroethylene. Three parameters in the conductivity model were determined by fitting the experimental data. It was shown that by applying this model, the sensor responses can be adequately predicted for given vapor pressures; furthermore the analyte vapor concentrations can be estimated based on the sensor responses. This model will guide the improvement of the design and fabrication of conductive polymer composite sensors for detecting and identifying mixtures of organic vapors. PMID:22518071

Detection of multiple airborne targets from multisensor data

NASA Astrophysics Data System (ADS)

Foltz, Mark A.; Srivastava, Anuj; Miller, Michael I.; Grenander, Ulf

1995-08-01

Previously we presented a jump-diffusion based random sampling algorithm for generating conditional mean estimates of scene representations for the tracking and recongition of maneuvering airborne targets. These representations include target positions and orientations along their trajectories and the target type associated with each trajectory. Taking a Bayesian approach, a posterior measure is defined on the parameter space by combining sensor models with a sophisticated prior based on nonlinear airplane dynamics. The jump-diffusion algorithm constructs a Markov process which visits the elements of the parameter space with frequencies proportional to the posterior probability. It consititutes both the infinitesimal, local search via a sample path continuous diffusion transform and the larger, global steps through discrete jump moves. The jump moves involve the addition and deletion of elements from the scene configuration or changes in the target type assoviated with each target trajectory. One such move results in target detection by the addition of a track seed to the inference set. This provides initial track data for the tracking/recognition algorithm to estimate linear graph structures representing tracks using the other jump moves and the diffusion process, as described in our earlier work. Target detection ideally involves a continuous research over a continuum of the observation space. In this work we conclude that for practical implemenations the search space must be discretized with lattice granularity comparable to sensor resolution, and discuss how fast Fourier transforms are utilized for efficient calcuation of sufficient statistics given our array models. Some results are also presented from our implementation on a networked system including a massively parallel machine architecture and a silicon graphics onyx workstation.

Optical modeling toward optimizing monitoring of intestinal perfusion in trauma patients

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

Akl, Tony; Wilson, Mark A.; Ericson, Milton Nance

2013-01-01

Trauma is the number one cause of death for people between the ages 1 and 44 years in the United States. In addition, according to the Centers of Disease Control and Prevention, injury results in over 31 million emergency department visits annually. Minimizing the resuscitation period in major abdominal injuries increases survival rates by correcting impaired tissue oxygen delivery. Optimization of resuscitation requires a monitoring method to determine sufficient tissue oxygenation. Oxygenation can be assessed by determining the adequacy of tissue perfusion. In this work, we present the design of a wireless perfusion and oxygenation sensor based on photoplethysmography. Throughmore » optical modeling, the benefit of using the visible wavelengths 470, 525 and 590nm (around the 525nm hemoglobin isobestic point) for intestinal perfusion monitoring is compared to the typical near infrared (NIR) wavelengths (805nm isobestic point) used in such sensors. Specifically, NIR wavelengths penetrate through the thin intestinal wall (~4mm) leading to high background signals. However, these visible wavelengths have two times shorter penetration depth that the NIR wavelengths. Monte-Carlo simulations show that the transmittance of the three selected wavelengths is lower by 5 orders of magnitude depending on the perfusion state. Due to the high absorbance of hemoglobin in the visible range, the perfusion signal carried by diffusely reflected light is also enhanced by an order of magnitude while oxygenation signal levels are maintained. In addition, short source-detector separations proved to be beneficial for limiting the probing depth to the thickness of the intestinal wall.« less

The association of weather on pediatric emergency department visits in Changwon, Korea (2005-2014).

PubMed

Lee, Hae Jeong; Jin, Mi Hyeon; Lee, Jun Hwa

2016-05-01

It is widely believed that patients are less likely to visit hospitals during bad weather. We hypothesized that weather and emergency department (ED) visits are associated. Thus, we investigated the association between pediatric ED visits and weather, and sought to determine whether admissions to the ED are affected by meteorological factors. We retrospectively analyzed all 87,242 emergency visits to Samsung Changwon Hospital by pediatric patients under 19years of age from January 2005 to December 2014. ED visits were categorized by disease. We used Poisson regression and generalized linear model to examine the relationships between current weather and ED visits. Additionally a distributed lag non-linear model was used to investigate the effect of weather on ED visits. During this 10-year study period, the average temperature and diurnal temperature range (DTR) were 14.7°C and 8.2°C, respectively. There were 1,145days of rain or snow (31.4%) during the 3,652-day study period. The volume of ED visits decreased on days of rain or snow. Additionally ED visits increased 2days after rainy or snowy days. The volume of ED visits increased 1.013 times with every 1°C increase in DTR. The volume of ED visits by patients with trauma, digestive diseases, and respiratory diseases increased when DTR was over 10°C. As rainfall increased to over 25mm, the ward admission rate (23.8%, p=0.018) of ED patients increased significantly. The volume of ED visits decreased on days of rain or snow and the ED visits were increased 2days after rainy or snowy days. The volume of ED visits increased for every 1°C increase in DTR. Copyright © 2016. Published by Elsevier B.V.

Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction

PubMed Central

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J.

2014-01-01

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model. PMID:25157546

Sensor trustworthiness in uncertain time varying stochastic environments

NASA Astrophysics Data System (ADS)

Verma, Ajay; Fernandes, Ronald; Vadakkeveedu, Kalyan

2011-06-01

Persistent surveillance applications require unattended sensors deployed in remote regions to track and monitor some physical stimulant of interest that can be modeled as output of time varying stochastic process. However, the accuracy or the trustworthiness of the information received through a remote and unattended sensor and sensor network cannot be readily assumed, since sensors may get disabled, corrupted, or even compromised, resulting in unreliable information. The aim of this paper is to develop information theory based metric to determine sensor trustworthiness from the sensor data in an uncertain and time varying stochastic environment. In this paper we show an information theory based determination of sensor data trustworthiness using an adaptive stochastic reference sensor model that tracks the sensor performance for the time varying physical feature, and provides a baseline model that is used to compare and analyze the observed sensor output. We present an approach in which relative entropy is used for reference model adaptation and determination of divergence of the sensor signal from the estimated reference baseline. We show that that KL-divergence is a useful metric that can be successfully used in determination of sensor failures or sensor malice of various types.

Virtual sensors for robust on-line monitoring (OLM) and Diagnostics

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

Tipireddy, Ramakrishna; Lerchen, Megan E.; Ramuhalli, Pradeep

Unscheduled shutdown of nuclear power facilities for recalibration and replacement of faulty sensors can be expensive and disruptive to grid management. In this work, we present virtual (software) sensors that can replace a faulty physical sensor for a short duration thus allowing recalibration to be safely deferred to a later time. The virtual sensor model uses a Gaussian process model to process input data from redundant and other nearby sensors. Predicted data includes uncertainty bounds including spatial association uncertainty and measurement noise and error. Using data from an instrumented cooling water flow loop testbed, the virtual sensor model has predictedmore » correct sensor measurements and the associated error corresponding to a faulty sensor.« less

A Low-Signal-to-Noise-Ratio Sensor Framework Incorporating Improved Nighttime Capabilities in DIRSIG

NASA Astrophysics Data System (ADS)

Rizzuto, Anthony P.

When designing new remote sensing systems, it is difficult to make apples-to-apples comparisons between designs because of the number of sensor parameters that can affect the final image. Using synthetic imagery and a computer sensor model allows for comparisons to be made between widely different sensor designs or between competing design parameters. Little work has been done in fully modeling low-SNR systems end-to-end for these types of comparisons. Currently DIRSIG has limited capability to accurately model nighttime scenes under new moon conditions or near large cities. An improved DIRSIG scene modeling capability is presented that incorporates all significant sources of nighttime radiance, including new models for urban glow and airglow, both taken from the astronomy community. A low-SNR sensor modeling tool is also presented that accounts for sensor components and noise sources to generate synthetic imagery from a DIRSIG scene. The various sensor parameters that affect SNR are discussed, and example imagery is shown with the new sensor modeling tool. New low-SNR detectors have recently been designed and marketed for remote sensing applications. A comparison of system parameters for a state-of-the-art low-SNR sensor is discussed, and a sample design trade study is presented for a hypothetical scene and sensor.

Data-driven Modeling of Metal-oxide Sensors with Dynamic Bayesian Networks

NASA Astrophysics Data System (ADS)

Gosangi, Rakesh; Gutierrez-Osuna, Ricardo

2011-09-01

We present a data-driven probabilistic framework to model the transient response of MOX sensors modulated with a sequence of voltage steps. Analytical models of MOX sensors are usually built based on the physico-chemical properties of the sensing materials. Although building these models provides an insight into the sensor behavior, they also require a thorough understanding of the underlying operating principles. Here we propose a data-driven approach to characterize the dynamical relationship between sensor inputs and outputs. Namely, we use dynamic Bayesian networks (DBNs), probabilistic models that represent temporal relations between a set of random variables. We identify a set of control variables that influence the sensor responses, create a graphical representation that captures the causal relations between these variables, and finally train the model with experimental data. We validated the approach on experimental data in terms of predictive accuracy and classification performance. Our results show that DBNs can accurately predict the dynamic response of MOX sensors, as well as capture the discriminatory information present in the sensor transients.

Accuracy of a Fourth-Generation Subcutaneous Continuous Glucose Sensor

PubMed Central

Garg, Satish K.; Brazg, Ronald; Bode, Bruce W.; Bailey, Timothy S.; Slover, Robert H.; Sullivan, Ashley; Huang, Suiying; Shin, John; Lee, Scott W.; Kaufman, Francine R.

2017-01-01

Abstract Background: This study evaluated the accuracy and performance of a fourth-generation subcutaneous glucose sensor (Guardian™ Sensor 3) in the abdomen and arm. Methods: Eighty-eight subjects (14–75 years of age, mean ± standard deviation [SD] of 42.0 ± 19.1 years) with type 1 or type 2 diabetes participated in the study. Subjects wore two sensors in the abdomen that were paired with either a MiniMed™ 640G insulin pump, or an iPhone® or iPod® touch® running a glucose monitoring mobile application (Guardian Connect system) and a third sensor in the arm, which was connected to a glucose sensor recorder (GSR). Subjects were also asked to undergo in-clinic visits of 12–14 h on study days 1, 3, and 7 for frequent blood glucose sample testing using a Yellow Springs Instrument (YSI) reference. Results: The overall mean absolute relative difference (MARD ± SD) between abdomen sensor glucose (SG) and YSI reference values was 9.6% ± 9.0% and 9.4% ± 9.8% for the MiniMed 640G insulin pump and Guardian Connect system, respectively; and 8.7% ± 8.0% between arm SG and YSI reference values. The percentage of SG values within 20% agreement of the YSI reference value (for YSI >80 mg/dL) was 90.7% with the MiniMed 640G insulin pump, 91.8% with the Guardian Connect system, and 93.1% for GSR-connected arm sensors. Mean functional sensor life, when calibrating 3–4 times/day, was 145.9 ± 39.3 h for sensors paired with the MiniMed 640G insulin pump, 146.1 ± 41.6 h for sensors paired with the Guardian Connect system, and 147.6 ± 40.4 h for sensors connected to the GSR. Responses to survey questions regarding sensor comfort and ease of use were favorable. Conclusions: The Guardian Sensor 3 glucose sensor, whether located in abdomen or the arm, provided accurate glucose readings when compared with the YSI reference and demonstrated functional life commensurate with the intended 7-day use. ClinicalTrials.gov: NCT02246582 PMID:28700272

Accuracy of a Fourth-Generation Subcutaneous Continuous Glucose Sensor.

PubMed

Christiansen, Mark P; Garg, Satish K; Brazg, Ronald; Bode, Bruce W; Bailey, Timothy S; Slover, Robert H; Sullivan, Ashley; Huang, Suiying; Shin, John; Lee, Scott W; Kaufman, Francine R

2017-08-01

This study evaluated the accuracy and performance of a fourth-generation subcutaneous glucose sensor (Guardian ™ Sensor 3) in the abdomen and arm. Eighty-eight subjects (14-75 years of age, mean ± standard deviation [SD] of 42.0 ± 19.1 years) with type 1 or type 2 diabetes participated in the study. Subjects wore two sensors in the abdomen that were paired with either a MiniMed ™ 640G insulin pump, or an iPhone ® or iPod ® touch ® running a glucose monitoring mobile application (Guardian Connect system) and a third sensor in the arm, which was connected to a glucose sensor recorder (GSR). Subjects were also asked to undergo in-clinic visits of 12-14 h on study days 1, 3, and 7 for frequent blood glucose sample testing using a Yellow Springs Instrument (YSI) reference. The overall mean absolute relative difference (MARD ± SD) between abdomen sensor glucose (SG) and YSI reference values was 9.6% ± 9.0% and 9.4% ± 9.8% for the MiniMed 640G insulin pump and Guardian Connect system, respectively; and 8.7% ± 8.0% between arm SG and YSI reference values. The percentage of SG values within 20% agreement of the YSI reference value (for YSI >80 mg/dL) was 90.7% with the MiniMed 640G insulin pump, 91.8% with the Guardian Connect system, and 93.1% for GSR-connected arm sensors. Mean functional sensor life, when calibrating 3-4 times/day, was 145.9 ± 39.3 h for sensors paired with the MiniMed 640G insulin pump, 146.1 ± 41.6 h for sensors paired with the Guardian Connect system, and 147.6 ± 40.4 h for sensors connected to the GSR. Responses to survey questions regarding sensor comfort and ease of use were favorable. The Guardian Sensor 3 glucose sensor, whether located in abdomen or the arm, provided accurate glucose readings when compared with the YSI reference and demonstrated functional life commensurate with the intended 7-day use. ClinicalTrials.gov : NCT02246582.

Enhanced modeling and simulation of EO/IR sensor systems

NASA Astrophysics Data System (ADS)

Hixson, Jonathan G.; Miller, Brian; May, Christopher

2015-05-01

The testing and evaluation process developed by the Night Vision and Electronic Sensors Directorate (NVESD) Modeling and Simulation Division (MSD) provides end to end systems evaluation, testing, and training of EO/IR sensors. By combining NV-LabCap, the Night Vision Integrated Performance Model (NV-IPM), One Semi-Automated Forces (OneSAF) input sensor file generation, and the Night Vision Image Generator (NVIG) capabilities, NVESD provides confidence to the M&S community that EO/IR sensor developmental and operational testing and evaluation are accurately represented throughout the lifecycle of an EO/IR system. This new process allows for both theoretical and actual sensor testing. A sensor can be theoretically designed in NV-IPM, modeled in NV-IPM, and then seamlessly input into the wargames for operational analysis. After theoretical design, prototype sensors can be measured by using NV-LabCap, then modeled in NV-IPM and input into wargames for further evaluation. The measurement process to high fidelity modeling and simulation can then be repeated again and again throughout the entire life cycle of an EO/IR sensor as needed, to include LRIP, full rate production, and even after Depot Level Maintenance. This is a prototypical example of how an engineering level model and higher level simulations can share models to mutual benefit.

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA Technical Reports Server (NTRS)

Goodman, M.; Blakeslee, R.; Hood, R.; Jedlovec, G.; Botts, M.; Li, X.

2006-01-01

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Dynamic model inversion techniques for breath-by-breath measurement of carbon dioxide from low bandwidth sensors.

PubMed

Sivaramakrishnan, Shyam; Rajamani, Rajesh; Johnson, Bruce D

2009-01-01

Respiratory CO(2) measurement (capnography) is an important diagnosis tool that lacks inexpensive and wearable sensors. This paper develops techniques to enable use of inexpensive but slow CO(2) sensors for breath-by-breath tracking of CO(2) concentration. This is achieved by mathematically modeling the dynamic response and using model-inversion techniques to predict input CO(2) concentration from the slow-varying output. Experiments are designed to identify model-dynamics and extract relevant model-parameters for a solidstate room monitoring CO(2) sensor. A second-order model that accounts for flow through the sensor's filter and casing is found to be accurate in describing the sensor's slow response. The resulting estimate is compared with a standard-of-care respiratory CO(2) analyzer and shown to effectively track variation in breath-by-breath CO(2) concentration. This methodology is potentially useful for measuring fast-varying inputs to any slow sensor.

The effect of prenatal care on birthweight: a full-information maximum likelihood approach.

PubMed

Rous, Jeffrey J; Jewell, R Todd; Brown, Robert W

2004-03-01

This paper uses a full-information maximum likelihood estimation procedure, the Discrete Factor Method, to estimate the relationship between birthweight and prenatal care. This technique controls for the potential biases surrounding both the sample selection of the pregnancy-resolution decision and the endogeneity of prenatal care. In addition, we use the actual number of prenatal care visits; other studies have normally measured prenatal care as the month care is initiated. We estimate a birthweight production function using 1993 data from the US state of Texas. The results underscore the importance of correcting for estimation problems. Specifically, a model that does not control for sample selection and endogeneity overestimates the benefit of an additional visit for women who have relatively few visits. This overestimation may indicate 'positive fetal selection,' i.e., women who did not abort may have healthier babies. Also, a model that does not control for self-selection and endogenity predicts that past 17 visits, an additional visit leads to lower birthweight, while a model that corrects for these estimation problems predicts a positive effect for additional visits. This result shows the effect of mothers with less healthy fetuses making more prenatal care visits, known as 'adverse selection' in prenatal care. Copyright 2003 John Wiley & Sons, Ltd.

Forecasting daily emergency department visits using calendar variables and ambient temperature readings.

PubMed

Marcilio, Izabel; Hajat, Shakoor; Gouveia, Nelson

2013-08-01

This study aimed to develop different models to forecast the daily number of patients seeking emergency department (ED) care in a general hospital according to calendar variables and ambient temperature readings and to compare the models in terms of forecasting accuracy. The authors developed and tested six different models of ED patient visits using total daily counts of patient visits to an ED in Sao Paulo, Brazil, from January 1, 2008, to December 31, 2010. The first 33 months of the data set were used to develop the ED patient visits forecasting models (the training set), leaving the last 3 months to measure each model's forecasting accuracy by the mean absolute percentage error (MAPE). Forecasting models were developed using three different time-series analysis methods: generalized linear models (GLM), generalized estimating equations (GEE), and seasonal autoregressive integrated moving average (SARIMA). For each method, models were explored with and without the effect of mean daily temperature as a predictive variable. The daily mean number of ED visits was 389, ranging from 166 to 613. Data showed a weekly seasonal distribution, with highest patient volumes on Mondays and lowest patient volumes on weekends. There was little variation in daily visits by month. GLM and GEE models showed better forecasting accuracy than SARIMA models. For instance, the MAPEs from GLM models and GEE models at the first month of forecasting (October 2012) were 11.5 and 10.8% (models with and without control for the temperature effect, respectively), while the MAPEs from SARIMA models were 12.8 and 11.7%. For all models, controlling for the effect of temperature resulted in worse or similar forecasting ability than models with calendar variables alone, and forecasting accuracy was better for the short-term horizon (7 days in advance) than for the longer term (30 days in advance). This study indicates that time-series models can be developed to provide forecasts of daily ED patient visits, and forecasting ability was dependent on the type of model employed and the length of the time horizon being predicted. In this setting, GLM and GEE models showed better accuracy than SARIMA models. Including information about ambient temperature in the models did not improve forecasting accuracy. Forecasting models based on calendar variables alone did in general detect patterns of daily variability in ED volume and thus could be used for developing an automated system for better planning of personnel resources. © 2013 by the Society for Academic Emergency Medicine.

Implantation of a novel telemetric intraocular pressure sensor in patients with glaucoma (ARGOS study): 1-year results.

PubMed

Koutsonas, Antonis; Walter, Peter; Roessler, Gernot; Plange, Niklas

2015-01-22

We investigated the safety of a telemetric IOP sensor and the accuracy of its IOP measurements in six patients with open-angle glaucoma and cataract. The study design was a prospective, single-center clinical trial. Here we present 1-year follow-up data. A ring-shaped telemetric IOP sensor was implanted in the ciliary sulcus after implantation of the intracapsular lens, during planned cataract surgery. The sensor is encapsulated in silicone rubber and consists of a miniature device with eight pressure-sensitive capacitors and a circular microcoil antenna. IOP measurements are performed with a reader unit held in front of the eye. IOP is calculated as the differences between the absolute pressure inside the eye (pressure sensor) and that outside the eye (reader unit). The sensor was successfully implanted in all patients. Four patients developed sterile anterior chamber inflammation that resolved completely within 9 days after surgery with anti-inflammatory treatment. All patients showed mild to moderate pupillary distortion and pigment dispersion after surgery. Telemetric IOP measurement was performed in all patients at all visits, and the patients successfully performed self-tonometry at home after receiving instructions. Telemetric IOP values showed similar profiles compared to those of Goldmann applanation tonometry (GAT). Three patients showed a relevant IOP step during follow-up, and in one patient, negative values were obtained throughout the study. Despite early postoperative anterior chamber inflammation, the IOP sensor was well tolerated by all patients. We describe the first prospective clinical study of a noncontact IOP sensor that potentially enables continuous IOP monitoring in patients with glaucoma. The sensor shape and size needs to be adapted to avoid pupillary distortion and to confirm that IOP measurements are accurately recorded in comparison to those of GAT. ( www.germanctr.de; number DRKS00003335.). Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

Clean water billing monitoring system using flow liquid meter sensor and SMS gateway

NASA Astrophysics Data System (ADS)

Fahmi, F.; Hizriadi, A.; Khairani, F.; Andayani, U.; Siregar, B.

2018-03-01

Public clean water company (PDAM) as a public service is designed and organized to meet the needs of the community. Currently, the number of PDAM subscribers is very big and will continue to grow, but the service and facilities to customers are still done conventionally by visiting the customer’s home to record the last position of the meter. One of the problems of PDAM is the lack of disclosure of PDAM customers’ invoice because it is only done monthly. This, of course, makes PDAM customers difficult to remember the date of payment of water account. Therefore it is difficult to maintain the efficiency. The purpose of this research is to facilitate customers of PDAM water users to know the details of water usage and the time of payment of water bills easily. It also facilitates customers in knowing information related to the form of water discharge data used, payment rates, and time grace payments using SMS Gateway. In this study, Flow Liquid Meter Sensor was used for data retrieval of water flowing in the piping system. Sensors used to require the help of Hall Effect sensor that serves to measure the speed of water discharge and placed on the pipe that has the same diameter size with the sensor diameter. The sensor will take the data from the rate of water discharge it passes; this data is the number of turns of the mill on the sensor. The results of the tests show that the built system works well in helping customers know in detail the amount of water usage in a month and the bill to be paid

Does Physiological Stress Slow Down Wound Healing in Patients With Diabetes?

PubMed Central

Razjouyan, Javad; Grewal, Gurtej Singh; Talal, Talal K.; Armstrong, David G.; Mills, Joseph L.; Najafi, Bijan

2017-01-01

Background: Poor healing is an important contributing factor to amputation among patients with diabetic foot ulcers (DFUs). Physiological stress may slow wound healing and increase susceptibility to infection. Objectives: The objective was to examine the association between heart rate variability (HRV) as an indicator of physiological stress response and healing speed (HealSpeed) among outpatients with active DFUs. Design and Methods: Ambulatory patients with diabetes with DFUs (n = 25, age: 59.3 ± 8.3 years) were recruited. HRV during pre–wound dressing was measured using a wearable sensor attached to participants’ chest. HRVs were quantified in both time and frequency domains to assess physiological stress response and vagal tone (relaxation). Change in wound size between two consecutive visits was used to estimate HealSpeed. Participants were then categorized into slow healing and fast healing groups. Between the two groups, comparisons were performed for demographic, clinical, and HRV derived parameters. Associations between different descriptors of HRV and HealSpeed were also assessed. Results: HealSpeed was significantly correlated with both vagal tone (r = –.705, P = .001) and stress response (r = .713, P = .001) extracted from frequency domain. No between-group differences were observed except those from HRV-derived parameters. Models based on HRVs were the highest predictors of slow/fast HealSpeed (AUC > 0.90), while models based on demographic and clinical information had poor classification performance (AUC = 0.44). Conclusion: This study confirms an association between stress/vagal tone and wound healing in patients with DFUs. In particular, it highlights the importance of vagal tone (relaxation) in expediting wound healing. It also demonstrates the feasibility of assessing physiological stress responses using wearable technology in outpatient clinic during routine clinic visits. PMID:28436270

Does Physiological Stress Slow Down Wound Healing in Patients With Diabetes?

PubMed

Razjouyan, Javad; Grewal, Gurtej Singh; Talal, Talal K; Armstrong, David G; Mills, Joseph L; Najafi, Bijan

2017-07-01

Poor healing is an important contributing factor to amputation among patients with diabetic foot ulcers (DFUs). Physiological stress may slow wound healing and increase susceptibility to infection. The objective was to examine the association between heart rate variability (HRV) as an indicator of physiological stress response and healing speed (Heal Speed ) among outpatients with active DFUs. Ambulatory patients with diabetes with DFUs (n = 25, age: 59.3 ± 8.3 years) were recruited. HRV during pre-wound dressing was measured using a wearable sensor attached to participants' chest. HRVs were quantified in both time and frequency domains to assess physiological stress response and vagal tone (relaxation). Change in wound size between two consecutive visits was used to estimate Heal Speed . Participants were then categorized into slow healing and fast healing groups. Between the two groups, comparisons were performed for demographic, clinical, and HRV derived parameters. Associations between different descriptors of HRV and Heal Speed were also assessed. Heal Speed was significantly correlated with both vagal tone ( r = -.705, P = .001) and stress response ( r = .713, P = .001) extracted from frequency domain. No between-group differences were observed except those from HRV-derived parameters. Models based on HRVs were the highest predictors of slow/fast Heal Speed (AUC > 0.90), while models based on demographic and clinical information had poor classification performance (AUC = 0.44). This study confirms an association between stress/vagal tone and wound healing in patients with DFUs. In particular, it highlights the importance of vagal tone (relaxation) in expediting wound healing. It also demonstrates the feasibility of assessing physiological stress responses using wearable technology in outpatient clinic during routine clinic visits.

The Rendezvous Monitoring Display Capabilities of the Rendezvous and Proximity Operations Program

NASA Technical Reports Server (NTRS)

Brazzel, Jack; Spehar, Pete; Clark, Fred; Foster, Chris; Eldridge, Erin

2013-01-01

The Rendezvous and Proximity Operations Program (RPOP) is a laptop computer- based relative navigation tool and piloting aid that was developed during the Space Shuttle program. RPOP displays a graphical representation of the relative motion between the target and chaser vehicles in a rendezvous, proximity operations and capture scenario. After being used in over 60 Shuttle rendezvous missions, some of the RPOP display concepts have become recognized as a minimum standard for cockpit displays for monitoring the rendezvous task. To support International Space Station (ISS) based crews in monitoring incoming visiting vehicles, RPOP has been modified to allow crews to compare the Cygnus visiting vehicle s onboard navigated state to processed range measurements from an ISS-based, crew-operated Hand Held Lidar sensor. This paper will discuss the display concepts of RPOP that have proven useful in performing and monitoring rendezvous and proximity operations.

Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems

DOE PAGES

Sundar, Kaarthik; Rathinam, Sivakumar

2016-12-26

Unmanned vehicles, both aerial and ground, are being used in several monitoring applications to collect data from a set of targets. This article addresses a problem where a group of heterogeneous aerial or ground vehicles with different motion constraints located at distinct depots visit a set of targets. The vehicles also may be equipped with different sensors, and therefore, a target may not be visited by any vehicle. The objective is to find an optimal path for each vehicle starting and ending at its respective depot such that each target is visited at least once by some vehicle, the vehicle–targetmore » constraints are satisfied, and the sum of the length of the paths for all the vehicles is minimized. Two variants of this problem are formulated (one for ground vehicles and another for aerial vehicles) as mixed-integer linear programs and a branchand- cut algorithm is developed to compute an optimal solution to each of the variants. Computational results show that optimal solutions for problems involving 100 targets and 5 vehicles can be obtained within 300 seconds on average, further corroborating the effectiveness of the proposed approach.« less

Ambient ozone concentration and emergency department visits for panic attacks.

PubMed

Cho, Jaelim; Choi, Yoon Jung; Sohn, Jungwoo; Suh, Mina; Cho, Seong-Kyung; Ha, Kyoung Hwa; Kim, Changsoo; Shin, Dong Chun

2015-03-01

The effect of ambient air pollution on panic disorder in the general population has not yet been thoroughly elucidated, although the occurrence of panic disorder in workers exposed to organic solvents has been reported previously. We investigated the association of ambient air pollution with the risk of panic attack-related emergency department visits. Using health insurance claims, we collected data from emergency department visits for panic attacks in Seoul, Republic of Korea (2005-2009). Daily air pollutant concentrations were obtained using automatic monitoring system data. We conducted a time-series study using a generalized additive model with Poisson distribution, which included spline variables (date of visit, daily mean temperature, and relative humidity) and parametric variables (daily mean air pollutant concentration, national holiday, and day of the week). In addition to single lag models (lag1 to lag3), cumulative lag models (lag0-1 to lag0-3) were constructed using moving-average concentrations on the days leading up to the visit. The risk was expressed as relative risk (RR) per one standard deviation of each air pollutant and its 95% confidence interval (95% CI). A total of 2320 emergency department visits for panic attacks were observed during the study period. The adjusted RR of panic attack-related emergency department visits was 1.051 (95% CI, 1.014-1.090) for same-day exposure to ozone. In cumulative models, adjusted RRs were 1.068 (1.029-1.107) in lag0-2 and 1.074 (1.035-1.114) in lag0-3. The ambient ozone concentration was significantly associated with emergency department visits for panic attacks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of supplementary private health insurance on physician visits in Korea.

PubMed

Kang, Sungwook; You, Chang Hoon; Kwon, Young Dae; Oh, Eun-Hwan

2009-12-01

The coverage of social health insurance has remained limited, despite it being compulsory in Korea. Accordingly, Koreans have come to rely upon supplementary private health insurance (PHI) to cover their medical costs. We examined the effects of supplementary PHI on physician visits in Korea. This study used individual data from 11,043 respondents who participated in the Korean Labor and Income Panel Survey in 2001. We conducted a single probit model to identify the relationship between PHI and physician visits, with adjustment for the following covariates: demographic characteristics, socioeconomic status, health status, and health-related behavior. Finally, we performed a bivariate probit model to examine the true effect of PHI on physician visits, with adjustment for the above covariates plus unobservable covariates that might affect not only physician visit, but also the purchase of PHI. We found that about 38% of all respondents had one or more private health plans. Forty-five percent of all respondents visited one or more physicians, and 49% of those who were privately insured had physician visits compared with 42% of the uninsured. The single probit model showed that those with PHI were about 14 percentage points more likely to visit physicians than those who do not have PHI. However, this distinction disappears in the bivariate probit model. This result might have been a consequence of the nature of private health plans in Korea. Private insurance companies pay a fixed amount directly to their enrollees in case of illness/injury, and the individuals are responsible subsequently for purchasing their own healthcare services. This study demonstrated the potential of Korean PHI to address the problem of moral hazard. These results serve as a reference for policy makers when considering how to finance healthcare services, as well as to contain healthcare expenditure.

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

PubMed Central

Zhang, Feng; Xu, Yuetong; Chou, Jarong

2016-01-01

The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. PMID:27681730

A model for ionic polymer metal composites as sensors

NASA Astrophysics Data System (ADS)

Bonomo, C.; Fortuna, L.; Giannone, P.; Graziani, S.; Strazzeri, S.

2006-06-01

This paper introduces a comprehensive model of sensors based on ionic polymer metal composites (IPMCs) working in air. Significant quantities ruling the sensing properties of IPMC-based sensors are taken into account and the dynamics of the sensors are modelled. A large amount of experimental evidence is given for the excellent agreement between estimations obtained using the proposed model and the observed signals. Furthermore, the effect of sensor scaling is investigated, giving interesting support to the activities involved in the design of sensing devices based on these novel materials. We observed that the need for a wet environment is not a key issue for IPMC-based sensors to work well. This fact allows us to put IPMC-based sensors in a totally different light to the corresponding actuators, showing that sensors do not suffer from the same drawbacks.

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm.

PubMed

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-24

Indoor occupants' positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans' position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm

PubMed Central

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-01

Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization. PMID:29364188

Phytoplankton Bloom Off Portugal

NASA Technical Reports Server (NTRS)

2002-01-01

Turquoise and greenish swirls marked the presence of a large phytoplankton bloom off the coast of Portugal on April 23, 2002. This true-color image was acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard NASA's Terra satellite. There are also several fires burning in northwest Spain, near the port city of A Coruna. Please note that the high-resolution scene provided here is 500 meters per pixel. For a copy of this scene at the sensor's fullest resolution, visit the MODIS Rapidfire site.

KSC-2014-4821

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander is enveloped in a cloud of dust as it takes off on free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4822

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander is enveloped in a cloud of dust as it takes off on free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4831

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander is moved into position at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida in preparation for free flight test No. 15. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA/Jim Grossman

KSC-2014-4818

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander rises above a cloud of dust as it takes off on free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4819

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander is enveloped in a cloud of dust as it takes off on free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4823

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander comes to rest after a successful landing, capping free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

KSC-2014-4832

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – Engineers and technicians prepare NASA's Project Morpheus prototype lander for free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA/Jim Grossman

KSC-2014-4820

NASA Image and Video Library

2014-12-15

CAPE CANAVERAL, Fla. – NASA’s Project Morpheus prototype lander is enveloped in a cloud of dust as it takes off on free flight test No. 15 at the north end of the Shuttle Landing Facility at Kennedy Space Center in Florida. During the 97-second test, onboard autonomous landing and hazard avoidance technology sensors, or ALHAT, surveyed the hazard field for safe landing sites, then guided the lander forward and downward to a successful landing. For more information on Morpheus, visit: http://www.morpheuslander.jsc.nasa.gov. Photo credit: NASA

Wearable nanosensor systems and their applications in healthcare

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Kumar, Prashanth S.; Varadan, Vijay K.

2017-04-01

The development of intelligent miniaturized nano-bio-and info-tech based sensors capable of wireless communication will fundamentally change the way we monitor and treat patients with chronic disease and after surgery. These new sensors will allow the monitoring of the patients as they maintain their normal daily activities, and provide warning to healthcare workers when critical events arise. This will facilitate early discharge of patients from hospitals as well as providing reassurance to patients and family that potential problems will be detected at an early stage. The use of continuous monitoring allows both transient and progressive abnormalities to be reliably detected thus avoiding the problems of conventional diagnosis and monitoring methods where by data is captured only for a brief period during hospital/clinic visits. We have been working with a printable organic semiconductor and thin film transistor, and have fabricated and tested various biosensors that can measure important physiological signs before and after surgery. Integrated into "smart" fabrics - garments with wireless technology - and independent e-bandaid sensors, nanosensors in tattoos and socks, minimally invasive implantable devices, the sensor systems will be able to monitor a patient's condition in real time and thus provide point-of-care diagnostics to health-care professionals and greater freedom for patients.

Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application.

PubMed

Velásquez-Villada, Carlos; Donoso, Yezid

2016-03-25

Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river's course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas' movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.

A better start for health equity? Qualitative content analysis of implementation of extended postnatal home visiting in a disadvantaged area in Sweden.

PubMed

Barboza, Madelene; Kulane, Asli; Burström, Bo; Marttila, Anneli

2018-04-10

Health inequities among children in Sweden persist despite the country's well-developed welfare system and near universal access to the national child health care programme. A multisectoral extended home visiting intervention, based on the principles of proportionate universalism, has been carried out in a disadvantaged area since 2013. The present study investigates the content of the meetings between families and professionals during the home visits to gain a deeper understanding of how it relates to a health equity perspective on early childhood development. Three child health care nurses documented 501 visits to the families of 98 children between 2013 and 2016. A qualitative data-driven conventional content analysis was performed on all data from the cycle of six visits per child, and a general content model was developed. Additional content analysis was carried out on the data from visits to families who experienced adverse situations or greater needs. The analysis revealed that the home visits covered three main categories of content related to the health, care and development of the child; the strengthening of roles and relations within the new family unit; and the influence and support located in the broader external context around the family. The model of categories and sub-categories proved stable over all six visits. Families with extra needs received continuous attention to their additional issues during the visits, as well as the standard content described in the content model. This study on home visiting implementation indicates that the participating families received programme content which covered all the domains of nurturing care as recommended by the WHO Commission on Social Determinants of Health and recent research. The content of the home visits can be understood to create enabling conditions for health equity effects. The intervention can be seen to represent a practical example of proportionate universalism.

Finite element modelling of fibre Bragg grating strain sensors and experimental validation

NASA Astrophysics Data System (ADS)

Malik, Shoaib A.; Mahendran, Ramani S.; Harris, Dee; Paget, Mark; Pandita, Surya D.; Machavaram, Venkata R.; Collins, David; Burns, Jonathan M.; Wang, Liwei; Fernando, Gerard F.

2009-03-01

Fibre Bragg grating (FBG) sensors continue to be used extensively for monitoring strain and temperature in and on engineering materials and structures. Previous researchers have also developed analytical models to predict the loadtransfer characteristics of FBG sensors as a function of applied strain. The general properties of the coating or adhesive that is used to surface-bond the FBG sensor to the substrate has also been modelled using finite element analysis. In this current paper, a technique was developed to surface-mount FBG sensors with a known volume and thickness of adhesive. The substrates used were aluminium dog-bone tensile test specimens. The FBG sensors were tensile tested in a series of ramp-hold sequences until failure. The reflected FBG spectra were recorded using a commercial instrument. Finite element analysis was performed to model the response of the surface-mounted FBG sensors. In the first instance, the effect of the mechanical properties of the adhesive and substrate were modelled. This was followed by modelling the volume of adhesive used to bond the FBG sensor to the substrate. Finally, the predicted values obtained via finite element modelling were correlated to the experimental results. In addition to the FBG sensors, the tensile test specimens were instrumented with surface-mounted electrical resistance strain gauges.

Fault Diagnostics for Turbo-Shaft Engine Sensors Based on a Simplified On-Board Model

PubMed Central

Lu, Feng; Huang, Jinquan; Xing, Yaodong

2012-01-01

Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient. PMID:23112645

Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

PubMed

Lu, Feng; Huang, Jinquan; Xing, Yaodong

2012-01-01

Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

New Delivery Model for Rising-Risk Patients: The Forgotten Lot?

PubMed

Cheung, Lauren; Norden, Justin; Harrington, Robert A; Desai, Sumbul A

2017-08-01

Shared-risk models encourage providers to engage young patients early. Telemedicine may be well suited for younger, healthier patients although it is unclear how best to incorporate telemedicine into routine clinical care. We test the assumptions surrounding the use of telemedicine, younger and rising-risk patients, and primary care in ClickWell Care (CWC), a care model developed at our institution for our own accountable care organization. CWC's team of physicians and wellness coaches work together to provide comprehensive primary care through in-person, phone, and video visits. This study examines usage of the clinic over its initial year in operation. 1,464 unique patients conducted a total of 3,907 visits. 2,294 (58.7%) visits were completed virtually (1,382 [35.4%] by phone and 912 [23.3%] by video). Patients were more inclined to see the physician in-person for a new visit (1,065 visits [70.5%] vs. 362 [24%] phone and 83 [6%] video) and more likely to see the physician virtually for a return visit (606 [43.2%] phone and 249 [17.7%] video vs. 548 [39.1%] in-person), a statistically significant difference (X 2  = 306.7, p < 0.00001). This new care model successfully engaged a younger population of patients. However, our data suggest young patients may not be inclined to establish care with a primary care physician virtually and, in fact, choose an initial in-person touch point, although many are willing to conduct return visits virtually. This new model of care could have a large impact on how care is delivered to low- and rising-risk patients.

Modeling Common Cause Failures of Thrusters on ISS Visiting Vehicles

NASA Technical Reports Server (NTRS)

Haught, Megan

2014-01-01

This paper discusses the methodology used to model common cause failures of thrusters on the International Space Station (ISS) Visiting Vehicles. The ISS Visiting Vehicles each have as many as 32 thrusters, whose redundancy makes them susceptible to common cause failures. The Global Alpha Model (as described in NUREG/CR-5485) can be used to represent the system common cause contribution, but NUREG/CR-5496 supplies global alpha parameters for groups only up to size six. Because of the large number of redundant thrusters on each vehicle, regression is used to determine parameter values for groups of size larger than six. An additional challenge is that Visiting Vehicle thruster failures must occur in specific combinations in order to fail the propulsion system; not all failure groups of a certain size are critical.

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Choi, Sang H.; Chrisman, Dan A., Jr.; Samms, Richard W.

1987-01-01

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

A Gaussian Mixture Model-based continuous Boundary Detection for 3D sensor networks.

PubMed

Chen, Jiehui; Salim, Mariam B; Matsumoto, Mitsuji

2010-01-01

This paper proposes a high precision Gaussian Mixture Model-based novel Boundary Detection 3D (BD3D) scheme with reasonable implementation cost for 3D cases by selecting a minimum number of Boundary sensor Nodes (BNs) in continuous moving objects. It shows apparent advantages in that two classes of boundary and non-boundary sensor nodes can be efficiently classified using the model selection techniques for finite mixture models; furthermore, the set of sensor readings within each sensor node's spatial neighbors is formulated using a Gaussian Mixture Model; different from DECOMO [1] and COBOM [2], we also formatted a BN Array with an additional own sensor reading to benefit selecting Event BNs (EBNs) and non-EBNs from the observations of BNs. In particular, we propose a Thick Section Model (TSM) to solve the problem of transition between 2D and 3D. It is verified by simulations that the BD3D 2D model outperforms DECOMO and COBOM in terms of average residual energy and the number of BNs selected, while the BD3D 3D model demonstrates sound performance even for sensor networks with low densities especially when the value of the sensor transmission range (r) is larger than the value of Section Thickness (d) in TSM. We have also rigorously proved its correctness for continuous geometric domains and full robustness for sensor networks over 3D terrains.

Walk on the wild side: estimating the global magnitude of visits to protected areas.

PubMed

Balmford, Andrew; Green, Jonathan M H; Anderson, Michael; Beresford, James; Huang, Charles; Naidoo, Robin; Walpole, Matt; Manica, Andrea

2015-02-01

How often do people visit the world's protected areas (PAs)? Despite PAs covering one-eighth of the land and being a major focus of nature-based recreation and tourism, we don't know. To address this, we compiled a globally-representative database of visits to PAs and built region-specific models predicting visit rates from PA size, local population size, remoteness, natural attractiveness, and national income. Applying these models to all but the very smallest of the world's terrestrial PAs suggests that together they receive roughly 8 billion (8 x 109) visits/y-of which more than 80% are in Europe and North America. Linking our region-specific visit estimates to valuation studies indicates that these visits generate approximately US $600 billion/y in direct in-country expenditure and US $250 billion/y in consumer surplus. These figures dwarf current, typically inadequate spending on conserving PAs. Thus, even without considering the many other ecosystem services that PAs provide to people, our findings underscore calls for greatly increased investment in their conservation.

Walk on the Wild Side: Estimating the Global Magnitude of Visits to Protected Areas

PubMed Central

Balmford, Andrew; Green, Jonathan M. H.; Anderson, Michael; Beresford, James; Huang, Charles; Naidoo, Robin; Walpole, Matt; Manica, Andrea

2015-01-01

How often do people visit the world’s protected areas (PAs)? Despite PAs covering one-eighth of the land and being a major focus of nature-based recreation and tourism, we don’t know. To address this, we compiled a globally-representative database of visits to PAs and built region-specific models predicting visit rates from PA size, local population size, remoteness, natural attractiveness, and national income. Applying these models to all but the very smallest of the world’s terrestrial PAs suggests that together they receive roughly 8 billion (8 x 109) visits/y—of which more than 80% are in Europe and North America. Linking our region-specific visit estimates to valuation studies indicates that these visits generate approximately US $600 billion/y in direct in-country expenditure and US $250 billion/y in consumer surplus. These figures dwarf current, typically inadequate spending on conserving PAs. Thus, even without considering the many other ecosystem services that PAs provide to people, our findings underscore calls for greatly increased investment in their conservation. PMID:25710450

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Precipitation and primary health care visits for gastrointestinal illness in Gothenburg, Sweden.

PubMed

Tornevi, Andreas; Barregård, Lars; Forsberg, Bertil

2015-01-01

The river Göta Älv is a source of freshwater for the City of Gothenburg, Sweden, and we recently identified a clear influence of upstream precipitation on concentrations of indicator bacteria in the river water, as well as an association with the daily number of phone calls to the nurse advice line related to acute gastrointestinal illnesses (AGI calls). This study aimed to examine visits to primary health-care centers owing to similar symptoms (AGI visits) in the same area, to explore associations with precipitation, and to compare variability in AGI visits and AGI calls. We obtained data covering six years (2007-2012) of daily AGI visits and studied their association with prior precipitation (0-28 days) using a distributed lag nonlinear Poisson regression model, adjusting for seasonal patterns and covariates. In addition, we studied the effects of prolonged wet and dry weather on AGI visits. We analyzed lagged short-term relations between AGI visits and AGI calls, and we studied differences in their seasonal patterns using a binomial regression model. The study period saw a total of 17,030 AGI visits, and the number of daily visits decreased on days when precipitation occurred. However, prolonged wet weather was associated with an elevated number of AGI visits. Differences in seasonality patterns were observed between AGI visits and AGI calls, as visits were relatively less frequent during winter and relatively more frequent in August, and only weak short-term relations were found. AGI visits and AGI calls seems to partly reflect different types of AGI illnesses, and the patients' choice of medical contact (in-person visits versus phone calls) appears to depend on current weather conditions. An association between prolonged wet weather and increased AGI visits supports the hypothesis that the drinking water is related to an increased risk of AGI illnesses.

International Normalized Ratio values in group versus individual appointments in a pharmacist-managed anticoagulation clinic.

PubMed

Griffin, Brooke L; Burkiewicz, Jill S; Peppers, Laura R; Warholak, Terri L

2009-07-01

The clinical effectiveness of a group-visit model versus individual point-of-care visits is compared by International Normalized Ratio (INR) monitoring in a pharmacist-managed anticoagulation clinic. This study was a prospective, randomized, repeated-measures, two-group, intention-to-treat comparison and survey at a pharmacist-managed anticoagulation clinic in a managed-care ambulatory care setting. Patients were eligible for this study if they were taking warfarin therapy for at least 30 days, had a goal INR range, and provided consent. At a routine point-of-care visit, eligible patients were randomly invited to participate in group visits. The number of visits and INR values were documented prospectively for both groups during the 16-week study period. Of the 45 patients who consented and enrolled in group visits, 28 patients participated for the 16-week study period. The control group included 108 patients seen by a pharmacist for individual anticoagulation appointments. No significant difference in the percentage of INR values within the therapeutic range was detected between patients in the group-visit model versus patients receiving individual visits (59% versus 56.6%, respectively; p = 0.536). Seventy-three percent of INR values for patients who attended group visits were within +/- 0.2 of the desired INR range compared with 71.9% of those in the control group ( p = 0.994). In addition, 79% of group-visit patients were within the therapeutic range at their last clinic visit compared with 67% of patients who attended individual appointments (p = 0.225). Group visits were preferred by 51% (n = 38) of patients who completed the satisfaction survey. Of the 92 patients who declined group-visit participation, 36% indicated that the time of day that group visits were offered was inconvenient. There were no thromboembolic or hemorrhagic events documented in either group during the study period. Group visits in a pharmacist-managed anticoagulation clinic may provide a safe and effective alternative to individual appointments.

Floral traits influencing plant attractiveness to three bee species: Consequences for plant reproductive success.

PubMed

Bauer, Austin A; Clayton, Murray K; Brunet, Johanne

2017-05-01

The ability to attract pollinators is crucial to plants that rely on insects for pollination. We contrasted the roles of floral display size and flower color in attracting three bee species and determined the relationships between plant attractiveness (number of pollinator visits) and seed set for each bee species. We recorded pollinator visits to plants, measured plant traits, and quantified plant reproductive success. A zero-inflated Poisson regression model indicated plant traits associated with pollinator attraction. It identified traits that increased the number of bee visits and traits that increased the probability of a plant not receiving any visits. Different components of floral display size were examined and two models of flower color contrasted. Relationships between plant attractiveness and seed set were determined using regression analyses. Plants with more racemes received more bee visits from all three bee species. Plants with few racemes were more likely not to receive any bee visits. The role of flower color varied with bee species and was influenced by the choice of the flower color model. Increasing bee visits increased seed set for all three bee species, with the steepest slope for leafcutting bees, followed by bumble bees, and finally honey bees. Floral display size influenced pollinator attraction more consistently than flower color. The same plant traits affected the probability of not being visited and the number of pollinator visits received. The impact of plant attractiveness on female reproductive success varied, together with pollinator effectiveness, by pollinator species. © 2017 Bauer et al. Published by the Botanical Society of America. This work is licensed under a Creative Commons public domain license (CC0 1.0).

Leonardo DiCaprio visited Goddard Saturday to discuss Earth science with Piers Sellers

NASA Image and Video Library

2017-12-08

Academy Award®- winning actor and environmental activist Leonardo DiCaprio visited NASA’s Goddard Space Flight Center in Greenbelt, Maryland on Saturday, April 23, 2016. During his visit, Mr. DiCaprio interviewed Dr. Piers Sellers, an Earth scientist, former astronaut and current deputy director of Goddard’s Sciences and Exploration Directorate. The two discussed the different missions NASA has underway to study changes in the Earth’s atmosphere, water and land masses for a climate change documentary that Mr. DiCaprio has in production. Using a wall-size, high-definition display system that shows visual representations based on actual science data, Mr. DiCaprio and Dr. Sellers discussed data results from NASA’s fleet of satellites in Earth’s orbit. The background visual shows the biosphere with data from a NASA satellite instrument called the Sea-viewing Wide Field-of-View Sensor (SeaWiFS). svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=10704 During his visit, Mr. DiCaprio also visited the facility holding NASA’s James Webb Space Telescope that is being developed as a large infrared telescope with a 6.5-meter primary mirror. The telescope will be launched on an Ariane 5 rocket from French Guiana in October of 2018, and will be a premier observatory of the next decade, serving thousands of astronomers worldwide. Credit: NASA/Goddard/Rebecca Roth NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

PubMed

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

Telehealth Management of Parkinson's Disease Using Wearable Sensors: An Exploratory Study.

PubMed

Heldman, Dustin A; Harris, Denzil A; Felong, Timothy; Andrzejewski, Kelly L; Dorsey, E Ray; Giuffrida, Joseph P; Goldberg, Barry; Burack, Michelle A

2017-09-01

Parkinson's disease (PD) motor symptoms can fluctuate and may not be accurately reflected during a clinical evaluation. In addition, access to movement disorder specialists is limited for many with PD. The objective was to assess the impact of motion sensor-based telehealth diagnostics on PD clinical care and management. Eighteen adults with PD were randomized to control or experimental groups. All participants were instructed to use a motion sensor-based monitoring system at home one day per week, for seven months. The system included a finger-worn motion sensor and tablet-based software interface that guided patients through tasks to quantify tremor, bradykinesia, and dyskinesia. Data were processed into motor symptom severity reports, which were reviewed by a movement disorders neurologist for experimental group participants. After three months and six months, control group participants visited the clinic for a routine appointment, while experimental group participants had a videoconference or phone call instead. Home based assessments were completed with median compliance of 95.7%. For a subset of participants, the neurologist successfully used information in the reports such as quantified response to treatment or progression over time to make therapy adjustments. Changes in clinical characteristics from study start to end were not significantly different between groups. Individuals with PD were able and willing to use remote monitoring technology. Patient management aided by telehealth diagnostics provided comparable outcomes to standard care. Telehealth technologies combined with wearable sensors have the potential to improve care for disparate PD populations or those unable to travel.

COMSOL-Based Modeling and Simulation of SnO2/rGO Gas Sensor for Detection of NO2.

PubMed

Yaghouti Niyat, Farshad; Shahrokh Abadi, M H

2018-02-01

Despite SIESTA and COMSOL being increasingly used for the simulation of the sensing mechanism in the gas sensors, there are no modeling and simulation reports in literature for detection of NO 2 based rGO/SnO 2 sensors. In the present study, we model, simulate, and characterize an NO 2 based rGO/SnO 2 gas sensor using COMSOL by solving the Poisson's equations under associated boundary conditions of mass, heat and electrical transitions. To perform the simulation, we use an exposure model for presenting the required NO 2 , a heat transfer model to obtain a reaction temperature, and an electrical model to characterize the sensor's response in the presence of the gas. We characterize the sensor's response in the presence of different concentrations of NO 2 at different working temperatures and compare the results with the experimental data, reported by Zhang et al. The results from the simulated sensor show a good agreement with the real sensor with some inconsistencies due to differences between the practical conditions in the real chamber and applied conditions to the analytical equations. The results also show that the method can be used to define and predict the behavior of the rGO-based gas sensors before undergoing the fabrication process.

Development of a nonlinear model for the prediction of response times of glucose affinity sensors using concanavalin A and dextran and the development of a differential osmotic glucose affinity sensor

NASA Astrophysics Data System (ADS)

Reis, Louis G.

With the increasing prevalence of diabetes in the United States and worldwide, blood glucose monitoring must be accurate and reliable. Current enzymatic sensors have numerous disadvantages that make them unreliable and unfavorable among patients. Recent research in glucose affinity sensors correct some of the problems that enzymatic sensors experience. Dextran and concanavalin A are two of the more common components used in glucose affinity sensors. When these sensors were first explored, a model was derived to predict the response time of a glucose affinity sensor using concanavalin A and dextran. However, the model assumed the system was linear and fell short of calculating times representative of the response times determined through experimental tests with the sensors. In this work, a new model that uses the Stokes-Einstein Equation to demonstrate the nonlinear behavior of the glucose affinity assay was developed to predict the response times of similar glucose affinity sensors. In addition to the device tested by the original linear model, additional devices were identified and tested with the proposed model. The nonlinear model was designed to accommodate the many different variations between systems. The proposed model was able to accurately calculate response times for sensors using the concanavalin A-dextran affinity assay with respect to the experimentally reported times by the independent research groups. Parameter studies using the nonlinear model were able to identify possible setbacks that could compromise the response of thesystem. Specifically, the model showed that the improper use of asymmetrical membranes could increase the response time by as little as 20% or more as the device is miniaturized. The model also demonstrated that systems using the concanavalin Adextran assay would experience higher response times in the hypoglycemic range. This work attempted to replicate and improve an osmotic glucose affinity sensor. The system was designed to negate additional effects that could cause artifacts or irregular readings such as external osmotic differences and external pressure differences. However, the experimental setup and execution faced numerous setbacks that highlighted the additional difficulty that sensors using asymmetrical ceramic membranes and the concanavalin A-dextran affinity assay may experience.

Modeling and simulation of soft sensor design for real-time speed and position estimation of PMSM.

PubMed

Omrane, Ines; Etien, Erik; Dib, Wissam; Bachelier, Olivier

2015-07-01

This paper deals with the design of a speed soft sensor for permanent magnet synchronous motor. At high speed, model-based soft sensor is used and it gives excellent results. However, it fails to deliver satisfactory performance at zero or very low speed. High-frequency soft sensor is used at low speed. We suggest to use a model-based soft sensor together with the high-frequency soft sensor to overcome the limitations of the first one at low speed range. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Vibration analysis and experiment of giant magnetostrictive force sensor

NASA Astrophysics Data System (ADS)

Zhu, Zhiwen; Liu, Fang; Zhu, Xingqiao; Wang, Haibo; Xu, Jia

2017-12-01

In this paper, a kind of giant magnetostrictive force sensor is proposed, ans its magneto-mechanical coupled model is developed. The relationship between output voltage of giant magnetostrictive force sensor and input excitation force is obtained. The phenomena of accuracy aggravation in high frequency and delay of giant magnetostrictive sensor are explained. The experimental results show that the model can describe the actual response of giant magnetostrictive force sensor. The new model of giant magnetostrictive sensor has simple form and is easy to be analyzed in theory, which is helpful to be applied in measuring and control fields.

Access to Transportation and Health Care Visits for Medicaid Enrollees With Diabetes.

PubMed

Thomas, Leela V; Wedel, Kenneth R; Christopher, Jan E

2018-03-01

Diabetes is a chronic condition that requires frequent health care visits for its management. Individuals without nonemergency medical transportation often miss appointments and do not receive optimal care. This study aims to evaluate the association between Medicaid-provided nonemergency medical transportation and diabetes care visits. A retrospective analysis was conducted of demographic and claims data obtained from the Oklahoma Medicaid program. Participants consisted of Medicaid enrollees with diabetes who made at least 1 visit for diabetes care in a year. The sample was predominantly female and white, with an average age of 46.38 years. Two zero-truncated Poisson regression models were estimated to assess the independent effect of transportation use on number of diabetes care visits. Use of nonemergency medical transportation is a significant predictor of diabetes care visits. Zero-truncated Poisson regression coefficients showed a positive association between the use of transportation and number of visits (0.6563, P < .001). Age, gender, race/ethnicity, area of residence, and presence of additional chronic conditions had independent associations with number of visits. Older enrollees were likely to make more visits than younger enrollees with diabetes (0.02382); controlling for all other factors in the model, rural residents made more visits than urban; women made fewer visits than men (-0.09312; P < .001); and minorities made fewer visits than whites, with pronounced differences for Hispanics and Asians compared to whites. Findings underscore the importance of ensuring transportation to Medicaid populations with diabetes, particularly in the rural areas where the prevalence of diabetes and complications are higher and the availability of medical resources lower than in the urban areas. © 2017 National Rural Health Association.

Modeling Common Cause Failures of Thrusters on ISS Visiting Vehicles

NASA Technical Reports Server (NTRS)

Haught, Megan; Duncan, Gary

2014-01-01

This paper discusses the methodology used to model common cause failures of thrusters on the International Space Station (ISS) Visiting Vehicles. The ISS Visiting Vehicles each have as many as 32 thrusters, whose redundancy and similar design make them susceptible to common cause failures. The Global Alpha Model (as described in NUREG/CR-5485) can be used to represent the system common cause contribution, but NUREG/CR-5496 supplies global alpha parameters for groups only up to size six. Because of the large number of redundant thrusters on each vehicle, regression is used to determine parameter values for groups of size larger than six. An additional challenge is that Visiting Vehicle thruster failures must occur in specific combinations in order to fail the propulsion system; not all failure groups of a certain size are critical.

Development of a Modular, Provider Customized Airway Trainer

DTIC Science & Technology

2015-11-25

Instructions for Airway Model with sensors and computer ( Raspberry PI ) ........................................ 31 Appendix B: Instructions for...Appendix A: Instructions for Airway Model with sensors and computer ( Raspberry PI ) RASPBERRY PI INSTRUCTIONS 1. Connect multicolor sensor...cable and two blue sensor cables (blue sensor cable orientation does not matter) 2. Plug in power to the screen and raspberry pi ( two separate

Timing of First Dental Visits for Newly Medicaid-Enrolled Children With an Intellectual or Developmental Disability in Iowa, 2005–2007

PubMed Central

Momany, Elizabeth T.; Jones, Michael P.; Damiano, Peter C.

2011-01-01

Objectives. We evaluated the relationship between having an intellectual or developmental disability (IDD) and the timing of the first dental visit for children who were newly enrolled in Medicaid in Iowa. Methods. We identified children aged 3 to 8 years with and without IDD who were newly enrolled in the Iowa Medicaid program in 2005 (N = 5391). We gathered data on presence of IDD, health status, age at baseline, gender, length of Medicaid enrollment, medical care visits, household Medicaid enrollment, urbanization, residence in a federally designated Health Professional Shortage Area (HPSA), and time of first dental visit through 2007. Results. About 32% of children had a first dental visit within 6 months of enrollment; this proportion increased to 49%, 64%, and 74% by years 1, 2, and 3, respectively. In the unadjusted models, there was no significant difference between children with and without IDD in time to first dental visit (P = .22). After adjusting for model covariates, however, children with IDD were 31% more likely to have a delayed first dental visit (P = .04). Conclusions. Newly Medicaid-enrolled children aged 3 to 8 years with IDD in Iowa were significantly more likely to have a later first dental visit. Future interventions should focus on ensuring timely access to first dental visits for all Medicaid-enrolled children, with an emphasis on those with IDD. PMID:21088261

A Qualitative Exploration of Co-location as an Intervention to Strengthen Home Visiting Implementation in Addressing Maternal Child Health.

PubMed

Kellom, Katherine S; Matone, Meredith; Adejare, Aderinola; Barg, Frances K; Rubin, David M; Cronholm, Peter F

2018-06-01

Objectives The aim of this paper is to explore the process and impact of co-locating evidence-based maternal and child service models to inform future implementation efforts. Methods As part of a state-wide evaluation of maternal and child home visiting programs, we conducted semi-structured interviews with administrators and home visitors from home visiting agencies across Pennsylvania. We collected 33 interviews from 4 co-located agencies. We used the Consolidated Framework for Implementation Research (CFIR) to describe the key elements mitigating implementation of multiple home visiting models. Results A primary advantage of co-location described by participants was the ability to increase the agency's base of eligible clients through the implementation of a model with different program eligibility (e.g. income, child age) than the existing agency offering. Model differences related to curriculum (e.g. content or intensity/meeting frequency) enabled programs to more selectively match clients to models. To recruit eligible clients, new models were able to build upon the existing service networks of the initial program. Co-location provided organizational opportunities for shared trainings, enabling administrative efficiencies and collaborative staff learning. Programs implemented strategies to build synergies with complementary model features, for instance using the additional program option to serve waitlisted clients and to transition services after one model is completed. Conclusions for Practice Considerable benefits are experienced when home visiting models co-locate. This research builds on literature encouraging collaboration among community agencies and provides insight on a specific facilitative approach. This implementation strategy informs policy across the social services spectrum and competitive funding contexts.

Modeling and simulation of soft sensor design for real-time speed estimation, measurement and control of induction motor.

PubMed

Etien, Erik

2013-05-01

This paper deals with the design of a speed soft sensor for induction motor. The sensor is based on the physical model of the motor. Because the validation step highlight the fact that the sensor cannot be validated for all the operating points, the model is modified in order to obtain a fully validated sensor in the whole speed range. An original feature of the proposed approach is that the modified model is derived from stability analysis using automatic control theory. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Redundancy in Glucose Sensing: Enhanced Accuracy and Reliability of an Electrochemical Redundant Sensor for Continuous Glucose Monitoring.

PubMed

Sharifi, Amin; Varsavsky, Andrea; Ulloa, Johanna; Horsburgh, Jodie C; McAuley, Sybil A; Krishnamurthy, Balasubramanian; Jenkins, Alicia J; Colman, Peter G; Ward, Glenn M; MacIsaac, Richard J; Shah, Rajiv; O'Neal, David N

2016-05-01

Current electrochemical glucose sensors use a single electrode. Multiple electrodes (redundancy) may enhance sensor performance. We evaluated an electrochemical redundant sensor (ERS) incorporating two working electrodes (WE1 and WE2) onto a single subcutaneous insertion platform with a processing algorithm providing a single real-time continuous glucose measure. Twenty-three adults with type 1 diabetes each wore two ERSs concurrently for 168 hours. Post-insertion a frequent sampling test (FST) was performed with ERS benchmarked against a glucose meter (Bayer Contour Link). Day 4 and 7 FSTs were performed with a standard meal and venous blood collected for reference glucose measurements (YSI and meter). Between visits, ERS was worn with capillary blood glucose testing ≥8 times/day. Sensor glucose data were processed prospectively. Mean absolute relative deviation (MARD) for ERS day 1-7 (3,297 paired points with glucose meter) was (mean [SD]) 10.1 [11.5]% versus 11.4 [11.9]% for WE1 and 12.0 [11.9]% for WE2; P < .0001. ERS Clarke A and A+B were 90.2% and 99.8%, respectively. ERS day 4 plus day 7 MARD (1,237 pairs with YSI) was 9.4 [9.5]% versus 9.6 [9.7]% for WE1 and 9.9 [9.7]% for WE2; P = ns. ERS day 1-7 precision absolute relative deviation (PARD) was 9.9 [3.6]% versus 11.5 [6.2]% for WE1 and 10.1 [4.4]% for WE2; P = ns. ERS sensor display time was 97.8 [6.0]% versus 91.0 [22.3]% for WE1 and 94.1 [14.3]% for WE2; P < .05. Electrochemical redundancy enhances glucose sensor accuracy and display time compared with each individual sensing element alone. ERS performance compares favorably with 'best-in-class' of non-redundant sensors. © 2015 Diabetes Technology Society.

A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits

PubMed Central

Neelon, Brian; Ghosh, Pulak; Loebs, Patrick F.

2012-01-01

Summary We develop a spatial Poisson hurdle model to explore geographic variation in emergency department (ED) visits while accounting for zero inflation. The model consists of two components: a Bernoulli component that models the probability of any ED use (i.e., at least one ED visit per year), and a truncated Poisson component that models the number of ED visits given use. Together, these components address both the abundance of zeros and the right-skewed nature of the nonzero counts. The model has a hierarchical structure that incorporates patient- and area-level covariates, as well as spatially correlated random effects for each areal unit. Because regions with high rates of ED use are likely to have high expected counts among users, we model the spatial random effects via a bivariate conditionally autoregressive (CAR) prior, which introduces dependence between the components and provides spatial smoothing and sharing of information across neighboring regions. Using a simulation study, we show that modeling the between-component correlation reduces bias in parameter estimates. We adopt a Bayesian estimation approach, and the model can be fit using standard Bayesian software. We apply the model to a study of patient and neighborhood factors influencing emergency department use in Durham County, North Carolina. PMID:23543242

Analysis and modeling of leakage current sensor under pulsating direct current

NASA Astrophysics Data System (ADS)

Li, Kui; Dai, Yihua; Wang, Yao; Niu, Feng; Chen, Zhao; Huang, Shaopo

2017-05-01

In this paper, the transformation characteristics of current sensor under pulsating DC leakage current is investigated. The mathematical model of current sensor is proposed to accurately describe the secondary side current and excitation current. The transformation process of current sensor is illustrated in details and the transformation error is analyzed from multi aspects. A simulation model is built and a sensor prototype is designed to conduct comparative evaluation, and both simulation and experimental results are presented to verify the correctness of theoretical analysis.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Use of Midlevel Practitioners to Achieve Labor Cost Savings in the Primary Care Practice of an MCO

PubMed Central

Roblin, Douglas W; Howard, David H; Becker, Edmund R; Kathleen Adams, E; Roberts, Melissa H

2004-01-01

Objective To estimate the savings in labor costs per primary care visit that might be realized from increased use of physician assistants (PAs) and nurse practitioners (NPs) in the primary care practices of a managed care organization (MCO). Study Setting/Data Sources Twenty-six capitated primary care practices of a group model MCO. Data on approximately two million visits provided by 206 practitioners were extracted from computerized visit records for 1997–2000. Computerized payroll ledgers were the source of annual labor costs per practice from 1997–2000. Study Design Likelihood of a visit attended by a PA/NP versus MD was modeled using logistic regression, with practice fixed effects, by department (adult medicine, pediatrics) and year. Parameter estimates and practice fixed effects from these regressions were used to predict the proportion of PA/NP visits per practice per year given a standard case mix. Least squares regressions, with practice fixed effects, were used to estimate the association of this standardized predicted proportion of PA/NP visits with average annual practitioner and total labor costs per visit, controlling for other practice characteristics. Results On average, PAs/NPs attended one in three adult medicine visits and one in five pediatric medicine visits. Likelihood of a PA/NP visit was significantly higher than average among patients presenting with minor acute illness (e.g., acute pharyngitis). In adult medicine, likelihood of a PA/NP visit was lower than average among older patients. Practitioner labor costs per visit and total labor costs per visit were lower (p<.01 and p=.08, respectively) among practices with greater use of PAs/NPs, standardized for case mix. Conclusions Primary care practices that used more PAs/NPs in care delivery realized lower practitioner labor costs per visit than practices that used less. Future research should investigate the cost savings and cost-effectiveness potential of delivery designs that change staffing mix and division of labor among clinical disciplines. PMID:15149481

Optimization of Self-Directed Target Coverage in Wireless Multimedia Sensor Network

PubMed Central

Yang, Yang; Wang, Yufei; Pi, Dechang; Wang, Ruchuan

2014-01-01

Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset. PMID:25136667

Supply-and-demand discrepancy in academic pigmented lesion clinics: a case for a new health care delivery model.

PubMed

Vickery, Erin L; Seidler, Elizabeth M; Jones, Todd E; Veledar, Emir; Chen, Suephy C

2014-11-01

There is an increasing demand for a limited number of pigmented lesion clinic (PLC) visits at dermatology centers. To determine the proportion of visits to PLCs that are more frequent ("additional screening") than the recommended ("standard") follow-up schedule and to determine if certain patient characteristics correlate with the demand for these visits. A retrospective medical chart review of all PLC visits at an academic dermatology center from October 2010 to January 2012. A total of 609 patients associated with 1756 visits were identified. Of these, 25 patients associated with 26 visits were excluded owing to lack of melanoma diagnosis or risk factors, leaving 584 patients and 1730 visits. Diagnoses of these patients included in situ and invasive melanoma, dysplastic nevi, Spitz nevi, atypical nevus syndrome, family history of melanoma only, and other risk factors. The mean (SD) age was 48 (16) years, and 235 (40.2%) of the patients were male. The proportion of additional screening visits compared with standard visits. Standard visits were defined as occurring at the following frequencies: annually for mildly dysplastic nevi, Spitz nevi, or solely family history of melanoma; biannually for the first year, then annually thereafter for moderately dysplastic nevi or atypical nevus syndrome; biannually for up to 3 years, then annually thereafter for severely dysplastic nevi or melanomas in situ; every 3 months for 2 years, biannually for the following 2 years, then annually thereafter for invasive melanoma. A total of 1400 visits (80.9%) were standard, 257 (14.9%) were for additional screening, and 73 (4.2%) were "problem focused." Thirty percent of patients had at least 1 additional screening visit. The distribution of diagnoses among standard vs additional screening visits differed significantly, with "family history only" and "other risk factors" taking up a larger percentage of standard visits (15.1%) than the percentage of additional screening visits (8.9%), and all other diagnoses being better represented among additional screening visits (P = .04). No particular patient characteristic described those who sought additional screening visits. A substantial proportion of additional screening PLC visits exist and are desired by all patients with pigmented lesions. We propose alternative clinic models, such as diagnosis-specific, adjunctive fee-for-additional-service, and teledermatology clinics to meet patient needs while creating resources to expand PLC visits.

The output voltage model and experiment of magnetostrictive displacement sensor based on Weidemann effect

NASA Astrophysics Data System (ADS)

Wang, Bowen; Li, Yuanyuan; Xie, Xinliang; Huang, Wenmei; Weng, Ling; Zhang, Changgeng

2018-05-01

Based on the Wiedemann effect and inverse magnetostritive effect, the output voltage model of a magnetostrictive displacement sensor has been established. The output voltage of the magnetostrictive displacement sensor is calculated in different magnetic fields. It is found that the calculating result is in an agreement with the experimental one. The theoretical and experimental results show that the output voltage of the displacement sensor is linearly related to the magnetostrictive differences, (λl-λt), of waveguide wires. The measured output voltages for Fe-Ga and Fe-Ni wire sensors are 51.5mV and 36.5mV, respectively, and the output voltage of Fe-Ga wire sensor is obviously higher than that of Fe-Ni wire sensor under the same magnetic field. The model can be used to predict the output voltage of the sensor and to provide guidance for the optimization design of the sensor.

Mobile Sensing in Environmental Health and Neighborhood Research.

PubMed

Chaix, Basile

2018-04-01

Public health research has witnessed a rapid development in the use of location, environmental, behavioral, and biophysical sensors that provide high-resolution objective time-stamped data. This burgeoning field is stimulated by the development of novel multisensor devices that collect data for an increasing number of channels and algorithms that predict relevant dimensions from one or several data channels. Global positioning system (GPS) tracking, which enables geographic momentary assessment, permits researchers to assess multiplace personal exposure areas and the algorithm-based identification of trips and places visited, eventually validated and complemented using a GPS-based mobility survey. These methods open a new space-time perspective that considers the full dynamic of residential and nonresidential momentary exposures; spatially and temporally disaggregates the behavioral and health outcomes, thus replacing them in their immediate environmental context; investigates complex time sequences; explores the interplay among individual, environmental, and situational predictors; performs life-segment analyses considering infraindividual statistical units using case-crossover models; and derives recommendations for just-in-time interventions.

Human Activity Recognition by Combining a Small Number of Classifiers.

PubMed

Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

2016-09-01

We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small number of sensors. We also incorporate the dynamic nature of human activities as a first-order homogeneous Markov chain. We develop both inductive and transductive inference methods for each model to be employed in supervised and semisupervised situations, respectively. Using different real HAR databases, we compare our classifiers combination models against a single classifier that employs all the signals from the sensors. Our models exhibit consistently a reduction of the error rate and an increase of robustness against sensor failures. Our models also outperform other classifiers combination models that do not consider soft outputs and an Markovian structure of the human activities.

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

Roy, Surajit; Ladpli, Purim; Chang, Fu-Kuo

Accurate interpretation of in-situ piezoelectric sensor signals is a challenging task. This article presents the development of a numerical compensation model based on physical insight to address the influence of structural loads on piezo-sensor signals. The model requires knowledge of in-situ strain and temperature distribution in a structure while acquiring sensor signals. The parameters of the numerical model are obtained using experiments on flat aluminum plate under uniaxial tensile loading. It is shown that the model parameters obtained experimentally can be used for different structures, and sensor layout. Furthermore, the combined effects of load and temperature on the piezo-sensor responsemore » are also investigated and it is observed that both of these factors have a coupled effect on the sensor signals. It is proposed to obtain compensation model parameters under a range of operating temperatures to address this coupling effect. An important outcome of this study is a new load monitoring concept using in-situ piezoelectric sensor signals to track changes in the load paths in a structure.« less

A Neural Network Approach for Building An Obstacle Detection Model by Fusion of Proximity Sensors Data

PubMed Central

Peralta, Emmanuel; Vargas, Héctor; Hermosilla, Gabriel

2018-01-01

Proximity sensors are broadly used in mobile robots for obstacle detection. The traditional calibration process of this kind of sensor could be a time-consuming task because it is usually done by identification in a manual and repetitive way. The resulting obstacles detection models are usually nonlinear functions that can be different for each proximity sensor attached to the robot. In addition, the model is highly dependent on the type of sensor (e.g., ultrasonic or infrared), on changes in light intensity, and on the properties of the obstacle such as shape, colour, and surface texture, among others. That is why in some situations it could be useful to gather all the measurements provided by different kinds of sensor in order to build a unique model that estimates the distances to the obstacles around the robot. This paper presents a novel approach to get an obstacles detection model based on the fusion of sensors data and automatic calibration by using artificial neural networks. PMID:29495338

VUV-Photoionization CES-Detector of Volatile Bio-Marker Molecules

NASA Astrophysics Data System (ADS)

Mustafaev, Alexander; Luneva, Nataliya; Panasyuk, George; Timofeev, Nikolay; Tsyganov, Alexander

2014-10-01

Energy spectra of characteristic electrons released via photoionization by vacuum ultraviolet (VUV) radiation of admixture molecules in the atmospheric air, not using traditional evacuated energy analyzers, can be determined by Collisional Electron Spectroscopy (CES) method. Some details of CES-photoionization sensor were described in. Our further developments are devoted to application of CES-detectors for a mobile continuous bio-chemical diagnostics. It is known that ``on breathing'' it is possible to find out volatile bio-marker molecules of a lot of diseases (lung cancer, tuberculosis, COPD, asthma, diabetes, kidney disease, mammary cancer, Crohn's disease, ulcerative colitis, etc). But today's weighty and expensive laboratory equipment (like GC MS) provides observation of these bio-markers only during patients' visits to a doctor. In this way we study pocket-size CES-sensor with micro-plasma krypton resonance radiation source (10.6 eV photons) for the photoionization detection of metabolic ammonia, ethanol, acetone and pentane molecules directly in atmospheric air.

Charge modeling of ionic polymer-metal composites for dynamic curvature sensing

NASA Astrophysics Data System (ADS)

Bahramzadeh, Yousef; Shahinpoor, Mohsen

2011-04-01

A curvature sensor based on Ionic Polymer-Metal Composite (IPMC) is proposed and characterized for sensing of curvature variation in structures such as inflatable space structures in which using low power and flexible curvature sensor is of high importance for dynamic monitoring of shape at desired points. The linearity of output signal of sensor for calibration, effect of deflection rate at low frequencies and the phase delay between the output signal and the input deformation of IPMC curvature sensor is investigated. An analytical chemo-electro-mechanical model for charge dynamic of IPMC sensor is presented based on Nernst-Planck partial differential equation which can be used to explain the phenomena observed in experiments. The rate dependency of output signal and phase delay between the applied deformation and sensor signal is studied using the proposed model. The model provides a background for predicting the general characteristics of IPMC sensor. It is shown that IPMC sensor exhibits good linearity, sensitivity, and repeatability for dynamic curvature sensing of inflatable structures.

Proposed evaluation framework for assessing operator performance with multisensor displays

NASA Technical Reports Server (NTRS)

Foyle, David C.

1992-01-01

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

Incorporating temporal and clinical reasoning in a new measure of continuity of care.

PubMed Central

Spooner, S. A.

1994-01-01

Previously described quantitative methods for measuring continuity of care have assumed that perfect continuity exists when a patient sees only one provider, regardless of the temporal pattern and clinical context of the visits. This paper describes an implementation of a new operational model of continuity--the Temporal Continuity Index--that takes into account time intervals between well visits in a pediatric residency continuity clinic. Ideal continuity in this model is achieved when intervals between visits are appropriate based on the age of the patient and clinical context of the encounters. The fundamental concept in this model is the expectation interval, which contains the length of the maximum ideal follow-up interval for a visit and the maximum follow-up interval. This paper describes an initial implementation of the TCI model and compares TCI calculations to previous quantitative methods and proposes its use as part of the assessment of resident education in outpatient settings. PMID:7950019

Bayesian modeling of consumer behavior in the presence of anonymous visits

NASA Astrophysics Data System (ADS)

Novak, Julie Esther

Tailoring content to consumers has become a hallmark of marketing and digital media, particularly as it has become easier to identify customers across usage or purchase occasions. However, across a wide variety of contexts, companies find that customers do not consistently identify themselves, leaving a substantial fraction of anonymous visits. We develop a Bayesian hierarchical model that allows us to probabilistically assign anonymous sessions to users. These probabilistic assignments take into account a customer's demographic information, frequency of visitation, activities taken when visiting, and times of arrival. We present two studies, one with synthetic and one with real data, where we demonstrate improved performance over two popular practices (nearest-neighbor matching and deleting the anonymous visits) due to increased efficiency and reduced bias driven by the non-ignorability of which types of events are more likely to be anonymous. Using our proposed model, we avoid potential bias in understanding the effect of a firm's marketing on its customers, improve inference about the total number of customers in the dataset, and provide more precise targeted marketing to both previously observed and unobserved customers.

Home Visiting: Looking Back and Moving Forward

ERIC Educational Resources Information Center

Boller, Kimberly; Strong, Debra A.; Daro, Deborah

2010-01-01

Recent large federal investments in services for pregnant women and young children will fuel the expansion of home visiting services across the U.S. The authors summarize the history of home visiting and describe trends toward evidence-based and national program models. Moving to an integrated system requires supports for implementation with…

Economic tour package model using heuristic

NASA Astrophysics Data System (ADS)

Rahman, Syariza Abdul; Benjamin, Aida Mauziah; Bakar, Engku Muhammad Nazri Engku Abu

2014-07-01

A tour-package is a prearranged tour that includes products and services such as food, activities, accommodation, and transportation, which are sold at a single price. Since the competitiveness within tourism industry is very high, many of the tour agents try to provide attractive tour-packages in order to meet tourist satisfaction as much as possible. Some of the criteria that are considered by the tourist are the number of places to be visited and the cost of the tour-packages. Previous studies indicate that tourists tend to choose economical tour-packages and aiming to visit as many places as they can cover. Thus, this study proposed tour-package model using heuristic approach. The aim is to find economical tour-packages and at the same time to propose as many places as possible to be visited by tourist in a given geographical area particularly in Langkawi Island. The proposed model considers only one starting point where the tour starts and ends at an identified hotel. This study covers 31 most attractive places in Langkawi Island from various categories of tourist attractions. Besides, the allocation of period for lunch and dinner are included in the proposed itineraries where it covers 11 popular restaurants around Langkawi Island. In developing the itinerary, the proposed heuristic approach considers time window for each site (hotel/restaurant/place) so that it represents real world implementation. We present three itineraries with different time constraints (1-day, 2-day and 3-day tour-package). The aim of economic model is to minimize the tour-package cost as much as possible by considering entrance fee of each visited place. We compare the proposed model with our uneconomic model from our previous study. The uneconomic model has no limitation to the cost with the aim to maximize the number of places to be visited. Comparison between the uneconomic and economic itinerary has shown that the proposed model have successfully achieved the objective that minimize the tour cost and cover maximum number of places to be visited.

Combined group and individual model for postbariatric surgery follow-up care.

PubMed

Lorentz, Paul A; Swain, James M; Gall, Margaret M; Collazo-Clavell, Maria L

2012-01-01

The prevalence of bariatric surgery in the United States has increased significantly during the past decade, increasing the number of patients requiring postbariatric surgery follow-up care. Our objective was to develop and implement an efficient, financially viable, postbariatric surgery practice model that would be acceptable to patients. The setting was the Mayo Clinic (Rochester, MN). By monitoring the attendance rates and using patient surveys, we tested patient acceptance of a new, shared medical appointment practice model in the care of postbariatric surgery patients. Efficiency was assessed by comparing differences in time per patient and total provider time required between the former and new care models. Individual-only patient/provider visits were replaced by combined group and individual visits (CGV). Our CGV model was well-attended and accepted. The patient attendance rate was >90% at all postoperative follow-up points. Furthermore, 83%, 85.2%, and 75.7% of the 3-, 6-, and 12-month postbariatric surgery patients, respectively, responded that they would not prefer to have only individual visits with their healthcare providers. The CGV model also resulted in greater time efficiency and cost reduction. On average, 5 patients were seen within 4.9 provider hours compared with 10.4 provider hours with the individual-only patient/provider visit model. Furthermore, the average billable charge for the CGV model's group medical nutrition therapy was 50-64% less than the equivalent individual medical nutrition therapy used in the individual-only patient/provider visit model. Shared medical appointments have a valuable role in the care of the postbariatric surgery population, offering a time- and cost-effective model for healthcare provision that is well-accepted by patients. Copyright © 2012 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Impact of a Community Dental Access Program on Emergency Dental Admissions in Rural Maryland.

PubMed

Rowland, Sandi; Leider, Jonathon P; Davidson, Clare; Brady, Joanne; Knudson, Alana

2016-12-01

To characterize the expansion of a community dental access program (CDP) in rural Maryland providing urgent dental care to low-income individuals, as well as the CDP's impact on dental-related visits to a regional emergency department (ED). We used de-identified CDP and ED claims data to construct a data set of weekly counts of CDP visits and dental-related ED visits among Maryland adults. A time series model examined the association over time between visits to the CDP and ED visits for fiscal years (FYs) 2011 through 2015. The CDP served approximately 1600 unique clients across 2700 visits during FYs 2011 through 2015. The model suggested that if the CDP had not provided services during that time period, about 670 more dental-related visits to the ED would have occurred, resulting in $215 000 more in charges. Effective ED dental diversion programs can result in substantial cost savings to taxpayers, and more appropriate and cost-effective care for the patient. Community dental access programs may be a viable way to patch the dental safety net in rural communities while holistic solutions are developed.

Impact of a Community Dental Access Program on Emergency Dental Admissions in Rural Maryland

PubMed Central

Rowland, Sandi; Davidson, Clare; Brady, Joanne; Knudson, Alana

2016-01-01

Objectives. To characterize the expansion of a community dental access program (CDP) in rural Maryland providing urgent dental care to low-income individuals, as well as the CDP’s impact on dental-related visits to a regional emergency department (ED). Methods. We used de-identified CDP and ED claims data to construct a data set of weekly counts of CDP visits and dental-related ED visits among Maryland adults. A time series model examined the association over time between visits to the CDP and ED visits for fiscal years (FYs) 2011 through 2015. Results. The CDP served approximately 1600 unique clients across 2700 visits during FYs 2011 through 2015. The model suggested that if the CDP had not provided services during that time period, about 670 more dental-related visits to the ED would have occurred, resulting in $215 000 more in charges. Conclusions. Effective ED dental diversion programs can result in substantial cost savings to taxpayers, and more appropriate and cost-effective care for the patient. Policy Implications. Community dental access programs may be a viable way to patch the dental safety net in rural communities while holistic solutions are developed. PMID:27736218

Virtual sensor models for real-time applications

NASA Astrophysics Data System (ADS)

Hirsenkorn, Nils; Hanke, Timo; Rauch, Andreas; Dehlink, Bernhard; Rasshofer, Ralph; Biebl, Erwin

2016-09-01

Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

Advanced sensor-simulation capability

NASA Astrophysics Data System (ADS)

Cota, Stephen A.; Kalman, Linda S.; Keller, Robert A.

1990-09-01

This paper provides an overview of an advanced simulation capability currently in use for analyzing visible and infrared sensor systems. The software system, called VISTAS (VISIBLE/INFRARED SENSOR TRADES, ANALYSES, AND SIMULATIONS) combines classical image processing techniques with detailed sensor models to produce static and time dependent simulations of a variety of sensor systems including imaging, tracking, and point target detection systems. Systems modelled to date include space-based scanning line-array sensors as well as staring 2-dimensional array sensors which can be used for either imaging or point source detection.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors.

PubMed

Dasgupta, Rumpa; Yoon, Seokhoon

2017-04-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs' traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs' paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay.

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors

PubMed Central

Dasgupta, Rumpa; Yoon, Seokhoon

2017-01-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs’ traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs’ paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay. PMID:28368300

Assessing older adults' perceptions of sensor data and designing visual displays for ambient environments. An exploratory study.

PubMed

Reeder, B; Chung, J; Le, T; Thompson, H; Demiris, G

2014-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Using Data from Ambient Assisted Living and Smart Homes in Electronic Health Records". Our objectives were to: 1) characterize older adult participants' perceived usefulness of in-home sensor data and 2) develop novel visual displays for sensor data from Ambient Assisted Living environments that can become part of electronic health records. Semi-structured interviews were conducted with community-dwelling older adult participants during three and six-month visits. We engaged participants in two design iterations by soliciting feedback about display types and visual displays of simulated data related to a fall scenario. Interview transcripts were analyzed to identify themes related to perceived usefulness of sensor data. Thematic analysis identified three themes: perceived usefulness of sensor data for managing health; factors that affect perceived usefulness of sensor data and; perceived usefulness of visual displays. Visual displays were cited as potentially useful for family members and health care providers. Three novel visual displays were created based on interview results, design guidelines derived from prior AAL research, and principles of graphic design theory. Participants identified potential uses of personal activity data for monitoring health status and capturing early signs of illness. One area for future research is to determine how visual displays of AAL data might be utilized to connect family members and health care providers through shared understanding of activity levels versus a more simplified view of self-management. Connecting informal and formal caregiving networks may facilitate better communication between older adults, family members and health care providers for shared decision-making.

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

PubMed

Howcroft, Jennifer; Lemaire, Edward D; Kofman, Jonathan

2016-01-01

Wearable sensors have potential for quantitative, gait-based, point-of-care fall risk assessment that can be easily and quickly implemented in clinical-care and older-adult living environments. This investigation generated models for wearable-sensor based fall-risk classification in older adults and identified the optimal sensor type, location, combination, and modelling method; for walking with and without a cognitive load task. A convenience sample of 100 older individuals (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m under single-task and dual-task conditions while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, and left and right shanks. Participants also completed the Activities-specific Balance Confidence scale, Community Health Activities Model Program for Seniors questionnaire, six minute walk test, and ranked their fear of falling. Fall risk classification models were assessed for all sensor combinations and three model types: multi-layer perceptron neural network, naïve Bayesian, and support vector machine. The best performing model was a multi-layer perceptron neural network with input parameters from pressure-sensing insoles and head, pelvis, and left shank accelerometers (accuracy = 84%, F1 score = 0.600, MCC score = 0.521). Head sensor-based models had the best performance of the single-sensor models for single-task gait assessment. Single-task gait assessment models outperformed models based on dual-task walking or clinical assessment data. Support vector machines and neural networks were the best modelling technique for fall risk classification. Fall risk classification models developed for point-of-care environments should be developed using support vector machines and neural networks, with a multi-sensor single-task gait assessment.

VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls.

PubMed

Kim, Byoungjip; Kang, Seungwoo; Ha, Jin-Young; Song, Junehwa

2015-07-16

In this paper, we introduce a novel smartphone framework called VisitSense that automatically detects and predicts a smartphone user's place visits from ambient radio to enable behavioral targeting for mobile ads in large shopping malls. VisitSense enables mobile app developers to adopt visit-pattern-aware mobile advertising for shopping mall visitors in their apps. It also benefits mobile users by allowing them to receive highly relevant mobile ads that are aware of their place visit patterns in shopping malls. To achieve the goal, VisitSense employs accurate visit detection and prediction methods. For accurate visit detection, we develop a change-based detection method to take into consideration the stability change of ambient radio and the mobility change of users. It performs well in large shopping malls where ambient radio is quite noisy and causes existing algorithms to easily fail. In addition, we proposed a causality-based visit prediction model to capture the causality in the sequential visit patterns for effective prediction. We have developed a VisitSense prototype system, and a visit-pattern-aware mobile advertising application that is based on it. Furthermore, we deploy the system in the COEX Mall, one of the largest shopping malls in Korea, and conduct diverse experiments to show the effectiveness of VisitSense.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Integrating Parenting Support Within and Beyond the Pediatric Medical Home.

PubMed

Linton, Julie M; Stockton, Maria Paz; Andrade, Berta; Daniel, Stephanie

2018-01-01

Positive parenting programs, developmental support services, and evidence-based home visiting programs can effectively provide parenting support and improve health and developmental outcomes for at-risk children. Few models, however, have integrated referrals for on-site support and home visiting programs into the provision of routine pediatric care within a medical home. This article describes an innovative approach, through partnership with a community-based organization, to deliver on-site and home visiting support services for children and families within and beyond the medical home. Our model offers a system of on-site services, including parenting, behavior, and/or development support, with optional intensive home visiting services. Assessment included description of the population served, delineation of services provided, and qualitative identification of key themes of the impact of services, illustrated by case examples. This replicable model describes untapped potential of the pediatric medical home as a springboard to mitigate risk and optimize children's health and development.

Delivery of primary health care to persons who are socio-economically disadvantaged: does the organizational delivery model matter?

PubMed Central

2013-01-01

Background As health systems evolve, it is essential to evaluate their impact on the delivery of health services to socially disadvantaged populations. We evaluated the delivery of primary health services for different socio-economic groups and assessed the performance of different organizational models in terms of equality of health care delivery in Ontario, Canada. Methods Cross sectional study of 5,361 patients receiving care from primary care practices using Capitation, Salaried or Fee-For-Service remuneration models. We assessed self-reported health status of patients, visit duration, number of visits per year, quality of health service delivery, and quality of health promotion. We used multi-level regressions to study service delivery across socio-economic groups and within each delivery model. Identified disparities were further analysed using a t-test to determine the impact of service delivery model on equity. Results Low income individuals were more likely to be women, unemployed, recent immigrants, and in poorer health. These individuals were overrepresented in the Salaried model, reported more visits/year across all models, and tended to report longer visits in the Salaried model. Measures of primary care services generally did not differ significantly between low and higher income/education individuals; when they did, the difference favoured better service delivery for at-risk groups. At-risk patients in the Salaried model were somewhat more likely to report health promotion activities than patients from Capitation and Fee-For-Service models. At-risk patients from Capitation models reported a smaller increase in the number of additional clinic visits/year than Fee-For-Service and Salaried models. At-risk patients reported better first contact accessibility than their non-at-risk counterparts in the Fee-For-Service model only. Conclusions Primary care service measures did not differ significantly across socio-economic status or primary care delivery models. In Ontario, capitation-based remuneration is age and sex adjusted only. Patients of low socio-economic status had fewer additional visits compared to those with high socio-economic status under the Capitation model. This raises the concern that Capitation may not support the provision of additional care for more vulnerable groups. Regions undertaking primary care model reforms need to consider the potential impact of the changes on the more vulnerable populations. PMID:24341530

Delivery of primary health care to persons who are socio-economically disadvantaged: does the organizational delivery model matter?

PubMed

Dahrouge, Simone; Hogg, William; Ward, Natalie; Tuna, Meltem; Devlin, Rose Anne; Kristjansson, Elizabeth; Tugwell, Peter; Pottie, Kevin

2013-12-17

As health systems evolve, it is essential to evaluate their impact on the delivery of health services to socially disadvantaged populations. We evaluated the delivery of primary health services for different socio-economic groups and assessed the performance of different organizational models in terms of equality of health care delivery in Ontario, Canada. Cross sectional study of 5,361 patients receiving care from primary care practices using Capitation, Salaried or Fee-For-Service remuneration models. We assessed self-reported health status of patients, visit duration, number of visits per year, quality of health service delivery, and quality of health promotion. We used multi-level regressions to study service delivery across socio-economic groups and within each delivery model. Identified disparities were further analysed using a t-test to determine the impact of service delivery model on equity. Low income individuals were more likely to be women, unemployed, recent immigrants, and in poorer health. These individuals were overrepresented in the Salaried model, reported more visits/year across all models, and tended to report longer visits in the Salaried model. Measures of primary care services generally did not differ significantly between low and higher income/education individuals; when they did, the difference favoured better service delivery for at-risk groups. At-risk patients in the Salaried model were somewhat more likely to report health promotion activities than patients from Capitation and Fee-For-Service models. At-risk patients from Capitation models reported a smaller increase in the number of additional clinic visits/year than Fee-For-Service and Salaried models. At-risk patients reported better first contact accessibility than their non-at-risk counterparts in the Fee-For-Service model only. Primary care service measures did not differ significantly across socio-economic status or primary care delivery models. In Ontario, capitation-based remuneration is age and sex adjusted only. Patients of low socio-economic status had fewer additional visits compared to those with high socio-economic status under the Capitation model. This raises the concern that Capitation may not support the provision of additional care for more vulnerable groups. Regions undertaking primary care model reforms need to consider the potential impact of the changes on the more vulnerable populations.

A Polygon Model for Wireless Sensor Network Deployment with Directional Sensing Areas

PubMed Central

Wu, Chun-Hsien; Chung, Yeh-Ching

2009-01-01

The modeling of the sensing area of a sensor node is essential for the deployment algorithm of wireless sensor networks (WSNs). In this paper, a polygon model is proposed for the sensor node with directional sensing area. In addition, a WSN deployment algorithm is presented with topology control and scoring mechanisms to maintain network connectivity and improve sensing coverage rate. To evaluate the proposed polygon model and WSN deployment algorithm, a simulation is conducted. The simulation results show that the proposed polygon model outperforms the existed disk model and circular sector model in terms of the maximum sensing coverage rate. PMID:22303159

Vibration sensing in flexible structures using a distributed-effect modal domain optical fiber sensor

NASA Technical Reports Server (NTRS)

Reichard, Karl M.; Lindner, Douglas K.; Claus, Richard O.

1991-01-01

Modal domain optical fiber sensors have recently been employed in the implementation of system identification algorithms and the closed-loop control of vibrations in flexible structures. The mathematical model of the modal domain optical fiber sensor used in these applications, however, only accounted for the effects of strain in the direction of the fiber's longitudinal axis. In this paper, we extend this model to include the effects of arbitrary stress. Using this sensor model, we characterize the sensor's sensitivity and dynamic range.

Statistical analysis of target acquisition sensor modeling experiments

NASA Astrophysics Data System (ADS)

Deaver, Dawne M.; Moyer, Steve

2015-05-01

The U.S. Army RDECOM CERDEC NVESD Modeling and Simulation Division is charged with the development and advancement of military target acquisition models to estimate expected soldier performance when using all types of imaging sensors. Two elements of sensor modeling are (1) laboratory-based psychophysical experiments used to measure task performance and calibrate the various models and (2) field-based experiments used to verify the model estimates for specific sensors. In both types of experiments, it is common practice to control or measure environmental, sensor, and target physical parameters in order to minimize uncertainty of the physics based modeling. Predicting the minimum number of test subjects required to calibrate or validate the model should be, but is not always, done during test planning. The objective of this analysis is to develop guidelines for test planners which recommend the number and types of test samples required to yield a statistically significant result.

Air pollution is associated with primary health care visits for asthma in Sweden: A case-crossover design with a distributed lag non-linear model.

PubMed

Taj, Tahir; Jakobsson, Kristina; Stroh, Emilie; Oudin, Anna

2016-05-01

Air pollution can increase the symptoms of asthma and has an acute effect on the number of emergency room visits and hospital admissions because of asthma, but little is known about the effect of air pollution on the number of primary health care (PHC) visits for asthma. To investigate the association between air pollution and the number of PHC visits for asthma in Scania, southern Sweden. Data on daily PHC visits for asthma were obtained from a regional healthcare database in Scania, which covers approximately half a million people. Air pollution data from 2005 to 2010 were obtained from six urban background stations. We used a case-crossover study design and a distributed lag non-linear model in the analysis. The air pollution levels were generally within the EU air quality guidelines. The mean number of daily PHC visits for asthma was 34. The number of PHC visits increased by 5% (95% confidence interval (CI): 3.91-6.25%) with every 10µg m(-3) increase in daily mean NO2 lag (0-15), suggesting that daily air pollution levels are associated with PHC visits for asthma. Even though the air quality in Scania between 2005 and 2010 was within EU's guidelines, the number of PHC visits for asthma increased with increasing levels of air pollution. This suggests that as well as increasing hospital and emergency room visits, air pollution increases the burden on PHC due to milder symptoms of asthma. Copyright © 2016 Elsevier Ltd. All rights reserved.

75 FR 61820 - Model Specifications for Breath Alcohol Ignition Interlock Devices (BAIIDs)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-06

... technology to alcohol-specific sensors (such as fuel cell technology based on electro-chemical oxidation of alcohol) or other emerging sensor technologies? Or, should NHTSA not specify the sensor technology and... require alcohol- specific technology in the Model Specifications, but that the particular sensor design...

Deposition Of Thin-Film Sensors On Glass-Fiber/Epoxy Models

NASA Technical Reports Server (NTRS)

Tran, Sang Q.

1995-01-01

Direct-deposition process devised for fabrication of thin-film sensors on three-dimensional, curved surfaces of models made of stainless steel covered with glass-fiber/epoxy-matrix composite material. Models used under cryogenic conditions, and sensors used to detect on-line transitions between laminar and turbulent flows in wind tunnel environments. Sensors fabricated by process used at temperatures from minus 300 degrees F to 175 degrees F.

Fiber-optic instrumentation: Cryogenic sensor model description. [for measurement of conditions in cryogenic liquid propellant tanks

NASA Technical Reports Server (NTRS)

Sharma, M. M.

1979-01-01

An assessment and determination of technology requirements for developing a demonstration model to evaluate feasibility of practical cryogenic liquid level, pressure, and temperature sensors is presented. The construction of a demonstration model to measure characteristics of the selected sensor and to develop test procedures are discussed as well as the development of an appropriate electronic subsystem to operate the sensors.

Timing and adequate attendance of antenatal care visits among women in Ethiopia.

PubMed

Yaya, Sanni; Bishwajit, Ghose; Ekholuenetale, Michael; Shah, Vaibhav; Kadio, Bernard; Udenigwe, Ogochukwu

2017-01-01

Although ANC services are increasingly available to women in low and middle-income countries, their inadequate use persists. This suggests a misalignment between aims of the services and maternal beliefs and circumstances. Owing to the dearth of studies examining the timing and adequacy of content of care, this current study aims to investigate the timing and frequency of ANC visits in Ethiopia. Data was obtained from the nationally representative 2011 Ethiopian Demographic and Health Survey (EDHS) which used a two-stage cluster sampling design to provide estimates for the health and demographic variables of interest for the country. Our study focused on a sample of 10,896 women with history of at least one childbirth event. Percentages of timing and adequacy of ANC visits were conducted across the levels of selected factors. Variables which were associated at 5% significance level were examined in the multivariable logistic regression model for association between timing and frequency of ANC visits and the explanatory variables while controlling for covariates. Furthermore, we presented the approach to estimate marginal effects involving covariate-adjusted logistic regression with corresponding 95%CI of delayed initiation of ANC visits and inadequate ANC attendance. The method used involved predicted probabilities added up to a weighted average showing the covariate distribution in the population. Results indicate that 66.3% of women did not use ANC at first trimester and 22.3% had ANC less than 4 visits. The results of this study were unique in that the association between delayed ANC visits and adequacy of ANC visits were examined using multivariable logistic model and the marginal effects using predicted probabilities. Results revealed that older age interval has higher odds of inadequate ANC visits. More so, type of place of residence was associated with delayed initiation of ANC visits, with rural women having the higher odds of delayed initiation of ANC visits (OR = 1.65; 95%CI: 1.26-2.18). However, rural women had 44% reduction in the odds of having inadequate ANC visits. In addition, multi-parity showed higher odds of delayed initiation of ANC visit when compared to the primigravida (OR = 2.20; 95%CI: 1.07-2.69). On the contrary, there was 36% reduction in the odds of multigravida having inadequate ANC visits when compared to the women who were primigravida. There were higher odds of inadequacy in ANC visits among women who engaged in sales/business, agriculture, skilled manual and other jobs when compared to women who currently do not work, after adjusting for covariates. From the predictive margins, assuming the distribution of all covariates remained the same among respondents, but everyone was aged 15-19 years, we would expect 71.8% delayed initiation of ANC visit. If everyone was aged 20-24years, 73.4%; 25-29years, 66.5%; 30-34years, 64.8%; 35-39years, 65.6%; 40-44years, 59.6% and 45-49years, we would expect 70.1% delayed initiation of ANC visit. If instead the distribution of age was as observed and for other covariates remained the same among respondents, but no respondent lived in the rural, we would expect about 61.4% delayed initiation of ANC visit; if however, everyone lived in the rural, and we would expect 71.6% delayed initiation in ANC visit. Model III revealed the predictive margins of all factors examined for delayed initiation for ANC visits, while Model IV presented the predictive marginal effects of the determinants of adequacy of ANC visits. The precise mechanism by which these factors affect ANC visits remain blurred at best. There may be factors on the demand side like the women's empowerment, financial support of the husband, knowledge of ANC visits in the context of timing, frequency and the expectations of ANC visits might be mediating the effects through the factors found associated in this study. Supply side factors like the quality of ANC services, skilled staff, and geographic location of the health centers also mediate their effects through the highlighted factors. Irrespective of the knowledge about the precise mechanism of action, policy makers could focus on improving women's empowerment, improving women's education, reducing wealth inequity and facilitating improved utilization of ANC through modifications on the supply side factors such as geographic location and focus on hard to reach women.

Racial-Ethnic Differences in Health Service Use in a Large Sample of Homeless Adults With Mental Illness From Five Canadian Cities.

PubMed

Stergiopoulos, Vicky; Gozdzik, Agnes; Nisenbaum, Rosane; Vasiliadis, Helen-Maria; Chambers, Catharine; McKenzie, Kwame; Misir, Vachan

2016-09-01

This study examined factors associated with health care use in an ethnically diverse Canadian sample of homeless adults with mental illness, a particularly disadvantaged group. Baseline survey data were available from five sites across Canada for 2,195 At Home/Chez Soi demonstration project participants. Negative binomial regression models examined the relationship between racial-ethnic or cultural group membership (white, N=1,085; Aboriginal, N=476; black, N=244; and other ethnoracial minority groups, N=390) and self-reported emergency department (ED) visits and hospitalizations in the past six months and past-month visits to a medical, other clinical, or social service provider. Adjusted models included other predisposing, enabling, and need factors, based on Andersen's behavioral model for vulnerable populations. Compared with white participants, black participants had a lower rate of ED visits (adjusted rate ratio [ARR]=.54, 95% confidence interval [CI]=.43-.69) and Aboriginal participants had a lower rate of medical visits (ARR=.84, CI=.71-.99) and a higher rate of visits to social service providers (ARR=1.54, CI=1.18-2.01). Participants in other ethnoracial minority groups had a higher rate of social service provider visits than white participants (ARR=1.44, CI=1.10-1.89). Access to a family physician, having at least high school education, and high needs for mental health services were associated with greater use of ED and medical visits and hospitalizations. Rates of ED and medical visits were lower with increased age and better physical health. In a system of universal health insurance that prioritizes access to and quality of care, the presence of racial-ethnic disparities experienced by this vulnerable population merits further attention.

The Impacts of Air Temperature on Accidental Casualties in Beijing, China.

PubMed

Ma, Pan; Wang, Shigong; Fan, Xingang; Li, Tanshi

2016-11-02

Emergency room (ER) visits for accidental casualties, according to the International Classification of Deceases 10th Revision Chapters 19 and 20, include injury, poisoning, and external causes (IPEC). Annual distribution of 187,008 ER visits that took place between 2009 and 2011 in Beijing, China displayed regularity rather than random characteristics. The annual cycle from the Fourier series fitting of the number of ER visits was found to explain 63.2% of its total variance. In this study, the possible effect and regulation of meteorological conditions on these ER visits are investigated through the use of correlation analysis, as well as statistical modeling by using the Distributed Lag Non-linear Model and Generalized Additive Model. Correlation analysis indicated that meteorological variables that positively correlated with temperature have a positive relationship with the number of ER visits, and vice versa. The temperature metrics of maximum, minimum, and mean temperatures were found to have similar overall impacts, including both the direct impact on human mental/physical conditions and indirect impact on human behavior. The lag analysis indicated that the overall impacts of temperatures higher than the 50th percentile on ER visits occur immediately, whereas low temperatures show protective effects in the first few days. Accidental casualties happen more frequently on warm days when the mean temperature is higher than 14 °C than on cold days. Mean temperatures of around 26 °C result in the greatest possibility of ER visits for accidental casualties. In addition, males were found to face a higher risk of accidental casualties than females at high temperatures. Therefore, the IPEC-classified ER visits are not pure accidents; instead, they are associated closely with meteorological conditions, especially temperature.

Implementation of a new prenatal care model to reduce office visits and increase connectivity and continuity of care: protocol for a mixed-methods study.

PubMed

Ridgeway, Jennifer L; LeBlanc, Annie; Branda, Megan; Harms, Roger W; Morris, Megan A; Nesbitt, Kate; Gostout, Bobbie S; Barkey, Lenae M; Sobolewski, Susan M; Brodrick, Ellen; Inselman, Jonathan; Baron, Anne; Sivly, Angela; Baker, Misty; Finnie, Dawn; Chaudhry, Rajeev; Famuyide, Abimbola O

2015-12-02

Most low-risk pregnant women receive the standard model of prenatal care with frequent office visits. Research suggests that a reduced schedule of visits among low-risk women could be implemented without increasing adverse maternal or fetal outcomes, but patient satisfaction with these models varies. We aim to determine the effectiveness and feasibility of a new prenatal care model (OB Nest) that enhances a reduced visit model by adding virtual connections that improve continuity of care and patient-directed access to care. This mixed-methods study uses a hybrid effectiveness-implementation design in a single center randomized controlled trial (RCT). Embedding process evaluation in an experimental design like an RCT allows researchers to answer both "Did it work?" and "How or why did it work (or not work)?" when studying complex interventions, as well as providing knowledge for translation into practice after the study. The RE-AIM framework was used to ensure attention to evaluating program components in terms of sustainable adoption and implementation. Low-risk patients recruited from the Obstetrics Division at Mayo Clinic (Rochester, MN) will be randomized to OB Nest or usual care. OB Nest patients will be assigned to a dedicated nursing team, scheduled for 8 pre-planned office visits with a physician or midwife and 6 telephone or online nurse visits (compared to 12 pre-planned physician or midwife office visits in the usual care group), and provided fetal heart rate and blood pressure home monitoring equipment and information on joining an online care community. Quantitative methods will include patient surveys and medical record abstraction. The primary quantitative outcome is patient-reported satisfaction. Other outcomes include fidelity to items on the American Congress of Obstetricians and Gynecologists standards of care list, health care utilization (e.g. numbers of antenatal office visits), and maternal and fetal outcomes (e.g. gestational age at delivery), as well as validated patient-reported measures of pregnancy-related stress and perceived quality of care. Quantitative analysis will be performed according to the intention to treat principle. Qualitative methods will include interviews and focus groups with providers, staff, and patients, and will explore satisfaction, intervention adoption, and implementation feasibility. We will use methods of qualitative thematic analysis at three stages. Mixed methods analysis will involve the use of qualitative data to lend insight to quantitative findings. This study will make important contributions to the literature on reduced visit models by evaluating a novel prenatal care model with components to increase patient connectedness (even with fewer pre-scheduled office visits), as demonstrated on a range of patient-important outcomes. The use of a hybrid effectiveness-implementation approach, as well as attention to patient and provider perspectives on program components and implementation, may uncover important information that can inform long-term feasibility and potentially speed future translation. Trial registration identifier: NCT02082275 Submitted: March 6, 2014.

Control systems using modal domain optical fiber sensors for smart structure applications

NASA Technical Reports Server (NTRS)

Lindner, Douglas K.; Reichard, Karl M.

1991-01-01

Recently, a new class of sensors has emerged for structural control which respond to environmental changes over a significant gauge length; these sensors are called distributed-effect sensors. These sensors can be fabricated with spatially varying sensitivity to the distributed measurand, and can be configured to measure a variety of structural parameters which can not be measured directly using point sensors. Examples of distributed-effect sensors include piezoelectric film, holographic sensors, and modal domain optical fiber sensors. Optical fiber sensors are particularly attractive for smart structure applications because they are flexible, have low mass, and can easily be embedded directly into materials. In this paper we describe the implementation of weighted modal domain optical fiber sensors. The mathematical model of the modal domain optical fiber sensor model is described and used to derive an expression for the sensor sensitivity. The effects of parameter variations on the sensor sensitivity are demonstrated to illustrate methods of spatially varying the sensor sensitivity.

Theory and data for simulating fine-scale human movement in an urban environment

PubMed Central

Perkins, T. Alex; Garcia, Andres J.; Paz-Soldán, Valerie A.; Stoddard, Steven T.; Reiner, Robert C.; Vazquez-Prokopec, Gonzalo; Bisanzio, Donal; Morrison, Amy C.; Halsey, Eric S.; Kochel, Tadeusz J.; Smith, David L.; Kitron, Uriel; Scott, Thomas W.; Tatem, Andrew J.

2014-01-01

Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it. PMID:25142528

Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application

PubMed Central

Velásquez-Villada, Carlos; Donoso, Yezid

2016-01-01

Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river’s course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols. PMID:27023554

Vice President Pence Visits SLS Engineering Test Facility

NASA Image and Video Library

2017-09-25

The Vice President toured the SLS engineering facility where the engine section of the rocket’s massive core stage is undergoing a major stress test. The rocket’s four RS-25 engines and the two solid rocket boosters that attach to the SLS engine section will produce more than 8 million pounds of thrust to launch the Orion spacecraft beyond low-Earth orbit. More than 3,000 measurements using sensors installed on the test section will help ensure the core stage for all SLS missions can withstand the extreme forces of flight.

Report on an Overseas Visit in October/November 1986 to Review Maintenance Procedures for F404 Engine Electrical Control Unit and Related Matters

DTIC Science & Technology

1989-11-01

proposal for F404 control] DEEC Digital Electronic Engine Controller - first generation cf FADEC DMICS Design Methods for Integrated Control Systems...the aircraft configuration, but the method will not work with insufficient control power. Although some parameter, may vary by as much as 100 to I...34’red tie merits of ’similar n a d "dissimilar ’ redundancy, fault detection methods . sensor connections and representation ol tie svstenl ’ting con

Chemiresistive Graphene Sensors for Ammonia Detection.

PubMed

Mackin, Charles; Schroeder, Vera; Zurutuza, Amaia; Su, Cong; Kong, Jing; Swager, Timothy M; Palacios, Tomás

2018-05-09

The primary objective of this work is to demonstrate a novel sensor system as a convenient vehicle for scaled-up repeatability and the kinetic analysis of a pixelated testbed. This work presents a sensor system capable of measuring hundreds of functionalized graphene sensors in a rapid and convenient fashion. The sensor system makes use of a novel array architecture requiring only one sensor per pixel and no selector transistor. The sensor system is employed specifically for the evaluation of Co(tpfpp)ClO 4 functionalization of graphene sensors for the detection of ammonia as an extension of previous work. Co(tpfpp)ClO 4 treated graphene sensors were found to provide 4-fold increased ammonia sensitivity over pristine graphene sensors. Sensors were also found to exhibit excellent selectivity over interfering compounds such as water and common organic solvents. The ability to monitor a large sensor array with 160 pixels provides insights into performance variations and reproducibility-critical factors in the development of practical sensor systems. All sensors exhibit the same linearly related responses with variations in response exhibiting Gaussian distributions, a key finding for variation modeling and quality engineering purposes. The mean correlation coefficient between sensor responses was found to be 0.999 indicating highly consistent sensor responses and excellent reproducibility of Co(tpfpp)ClO 4 functionalization. A detailed kinetic model is developed to describe sensor response profiles. The model consists of two adsorption mechanisms-one reversible and one irreversible-and is shown capable of fitting experimental data with a mean percent error of 0.01%.

New Research Strengthens Home Visiting Field: The Pew Home Visiting Campaign

ERIC Educational Resources Information Center

Doggett, Libby

2013-01-01

Extensive research has shown that home visiting parental education programs improve child and family outcomes, and they save money for states and taxpayers. Now, the next generation of research is deepening understanding of those program elements that are essential to success, ways to improve existing models, and factors to consider in tailoring…

Fusion of intraoperative force sensoring, surface reconstruction and biomechanical modeling

NASA Astrophysics Data System (ADS)

Röhl, S.; Bodenstedt, S.; Küderle, C.; Suwelack, S.; Kenngott, H.; Müller-Stich, B. P.; Dillmann, R.; Speidel, S.

2012-02-01

Minimally invasive surgery is medically complex and can heavily benefit from computer assistance. One way to help the surgeon is to integrate preoperative planning data into the surgical workflow. This information can be represented as a customized preoperative model of the surgical site. To use it intraoperatively, it has to be updated during the intervention due to the constantly changing environment. Hence, intraoperative sensor data has to be acquired and registered with the preoperative model. Haptic information which could complement the visual sensor data is still not established. In addition, biomechanical modeling of the surgical site can help in reflecting the changes which cannot be captured by intraoperative sensors. We present a setting where a force sensor is integrated into a laparoscopic instrument. In a test scenario using a silicone liver phantom, we register the measured forces with a reconstructed surface model from stereo endoscopic images and a finite element model. The endoscope, the instrument and the liver phantom are tracked with a Polaris optical tracking system. By fusing this information, we can transfer the deformation onto the finite element model. The purpose of this setting is to demonstrate the principles needed and the methods developed for intraoperative sensor data fusion. One emphasis lies on the calibration of the force sensor with the instrument and first experiments with soft tissue. We also present our solution and first results concerning the integration of the force sensor as well as accuracy to the fusion of force measurements, surface reconstruction and biomechanical modeling.

A predictive model for biomimetic plate type broadband frequency sensor

NASA Astrophysics Data System (ADS)

Ahmed, Riaz U.; Banerjee, Sourav

2016-04-01

In this work, predictive model for a bio-inspired broadband frequency sensor is developed. Broadband frequency sensing is essential in many domains of science and technology. One great example of such sensor is human cochlea, where it senses a frequency band of 20 Hz to 20 KHz. Developing broadband sensor adopting the physics of human cochlea has found tremendous interest in recent years. Although few experimental studies have been reported, a true predictive model to design such sensors is missing. A predictive model is utmost necessary for accurate design of selective broadband sensors that are capable of sensing very selective band of frequencies. Hence, in this study, we proposed a novel predictive model for the cochlea-inspired broadband sensor, aiming to select the frequency band and model parameters predictively. Tapered plate geometry is considered mimicking the real shape of the basilar membrane in the human cochlea. The predictive model is intended to develop flexible enough that can be employed in a wide variety of scientific domains. To do that, the predictive model is developed in such a way that, it can not only handle homogeneous but also any functionally graded model parameters. Additionally, the predictive model is capable of managing various types of boundary conditions. It has been found that, using the homogeneous model parameters, it is possible to sense a specific frequency band from a specific portion (B) of the model length (L). It is also possible to alter the attributes of `B' using functionally graded model parameters, which confirms the predictive frequency selection ability of the developed model.

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

PubMed Central

Kessler, Ronald C.; Stein, Murray B.; Petukhova, Maria V.; Bliese, Paul; Bossarte, Robert M.; Bromet, Evelyn J.; Fullerton, Carol S.; Gilman, Stephen E.; Ivany, Christopher; Lewandowski-Romps, Lisa; Bell, Amy Millikan; Naifeh, James A.; Nock, Matthew K.; Reis, Benjamin Y.; Rosellini, Anthony J.; Sampson, Nancy A.; Zaslavsky, Alan M.; Ursano, Robert J.

2016-01-01

The 2013 U.S. Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are known not to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male non-deployed Regular U.S. Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naïve Bayes, random forests, support vector regression, elastic net penalized regression) were explored. 41.5% of Army suicides in 2004-2009 occurred among the 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100,000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded. PMID:27431294

Non-Traumatic Dental Condition-Related Emergency Department Visits and Associated Costs for Children and Adults with Autism Spectrum Disorders

PubMed Central

Nakao, Sy; Scott, JoAnna M.; Masterson, Erin E.; Chi, Donald L.

2014-01-01

We analyzed 2010 U.S. National Emergency Department Sample data and ran regression models to test the hypotheses that individuals with ASD are more likely to have non-traumatic dental condition (NTDC)-related emergency department (ED) visits and to incur greater costs for these visits than those without ASD. There were nearly 2.3 million NTDC-related ED visits in 2010. Less than 1.0% (children) and 2.1% (adults) of all ED visits were for NTDC. There was no significant difference in NTDC-related ED visits or costs for children by ASD status. Adults with ASD had significantly lower odds of NTDC-related ED visits (OR=0.39; 95% CI: 0.29, 0.52; P<0.001) but incurred significantly greater mean costs for NTDC-related ED visits (P<0.006) than did adults without ASD. PMID:25374135

Aluminum Gallium Nitride (GaN)/GaN High Electron Mobility Transistor-Based Sensors for Glucose Detection in Exhaled Breath Condensate

PubMed Central

Chu, Byung Hwan; Kang, Byoung Sam; Hung, Sheng Chun; Chen, Ke Hung; Ren, Fan; Sciullo, Andrew; Gila, Brent P.; Pearton, Stephen J.

2010-01-01

Background Immobilized aluminum gallium nitride (AlGaN)/GaN high electron mobility transistors (HEMTs) have shown great potential in the areas of pH, chloride ion, and glucose detection in exhaled breath condensate (EBC). HEMT sensors can be integrated into a wireless data transmission system that allows for remote monitoring. This technology offers the possibility of using AlGaN/GaN HEMTs for extended investigations of airway pathology of detecting glucose in EBC without the need for clinical visits. Methods HEMT structures, consisting of a 3-μm-thick undoped GaN buffer, 30-Å-thick Al0.3Ga0.7N spacer, and 220-Å-thick silicon-doped Al0.3Ga0.7N cap layer, were used for fabricating the HEMT sensors. The gate area of the pH, chloride ion, and glucose detection was immobilized with scandium oxide (Sc2O3), silver chloride (AgCl) thin film, and zinc oxide (ZnO) nanorods, respectively. Results The Sc2O3-gated sensor could detect the pH of solutions ranging from 3 to 10 with a resolution of ∼0.1 pH. A chloride ion detection limit of 10-8 M was achievedt with a HEMT sensor immobilized with the AgCl thin film. The drain–source current of the ZnO nanorod-gated AlGaN/GaN HEMT sensor immobilized with glucose oxidase showed a rapid response of less than 5 seconds when the sensor was exposed to the target glucose in a buffer with a pH value of 7.4. The sensor could detect a wide range of concentrations from 0.5 nM to 125 μM. Conclusion There is great promise for using HEMT-based sensors to enhance the detection sensitivity for glucose detection in EBC. Depending on the immobilized material, HEMT-based sensors can be used for sensingt different materials. These electronic detection approaches with rapid response and good repeatability show potential for the investigation of airway pathology. The devices can also be integrated into a wireless data transmission system for remote monitoring applications. This sensor technology could use the exhaled breath condensate to measure the glucose concentration for diabetic applications. PMID:20167182

Aluminum gallium nitride (GaN)/GaN high electron mobility transistor-based sensors for glucose detection in exhaled breath condensate.

PubMed

Chu, Byung Hwan; Kang, Byoung Sam; Hung, Sheng Chun; Chen, Ke Hung; Ren, Fan; Sciullo, Andrew; Gila, Brent P; Pearton, Stephen J

2010-01-01

Immobilized aluminum gallium nitride (AlGaN)/GaN high electron mobility transistors (HEMTs) have shown great potential in the areas of pH, chloride ion, and glucose detection in exhaled breath condensate (EBC). HEMT sensors can be integrated into a wireless data transmission system that allows for remote monitoring. This technology offers the possibility of using AlGaN/GaN HEMTs for extended investigations of airway pathology of detecting glucose in EBC without the need for clinical visits. HEMT structures, consisting of a 3-microm-thick undoped GaN buffer, 30-A-thick Al(0.3)Ga(0.7)N spacer, and 220-A-thick silicon-doped Al(0.3)Ga(0.7)N cap layer, were used for fabricating the HEMT sensors. The gate area of the pH, chloride ion, and glucose detection was immobilized with scandium oxide (Sc(2)O(3)), silver chloride (AgCl) thin film, and zinc oxide (ZnO) nanorods, respectively. The Sc(2)O(3)-gated sensor could detect the pH of solutions ranging from 3 to 10 with a resolution of approximately 0.1 pH. A chloride ion detection limit of 10(-8) M was achieved with a HEMT sensor immobilized with the AgCl thin film. The drain-source current of the ZnO nanorod-gated AlGaN/GaN HEMT sensor immobilized with glucose oxidase showed a rapid response of less than 5 seconds when the sensor was exposed to the target glucose in a buffer with a pH value of 7.4. The sensor could detect a wide range of concentrations from 0.5 nM to 125 microM. There is great promise for using HEMT-based sensors to enhance the detection sensitivity for glucose detection in EBC. Depending on the immobilized material, HEMT-based sensors can be used for sensing different materials. These electronic detection approaches with rapid response and good repeatability show potential for the investigation of airway pathology. The devices can also be integrated into a wireless data transmission system for remote monitoring applications. This sensor technology could use the exhaled breath condensate to measure the glucose concentration for diabetic applications. 2010 Diabetes Technology Society.

Guidelines for the collection of continuous stream water-temperature data in Alaska

USGS Publications Warehouse

Toohey, Ryan C.; Neal, Edward G.; Solin, Gary L.

2014-01-01

Objectives of stream monitoring programs differ considerably among many of the academic, Federal, state, tribal, and non-profit organizations in the state of Alaska. Broad inclusion of stream-temperature monitoring can provide an opportunity for collaboration in the development of a statewide stream-temperature database. Statewide and regional coordination could reduce overall monitoring cost, while providing better analyses at multiple spatial and temporal scales to improve resource decision-making. Increased adoption of standardized protocols and data-quality standards may allow for validation of historical modeling efforts with better projection calibration. For records of stream water temperature to be generally consistent, unbiased, and reproducible, data must be collected and analyzed according to documented protocols. Collection of water-temperature data requires definition of data-quality objectives, good site selection, proper selection of instrumentation, proper installation of sensors, periodic site visits to maintain sensors and download data, pre- and post-deployment verification against an NIST-certified thermometer, potential data corrections, and proper documentation, review, and approval. A study created to develop a quality-assurance project plan, data-quality objectives, and a database management plan that includes procedures for data archiving and dissemination could provide a means to standardize a statewide stream-temperature database in Alaska. Protocols can be modified depending on desired accuracy or specific needs of data collected. This document is intended to guide users in collecting time series water-temperature data in Alaskan streams and draws extensively on the broader protocols already published by the U.S. Geological Survey.

Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing

PubMed Central

Papadopoulou, Maria; Vernay, Didier; Smith, Ian F. C.

2017-01-01

Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called structural identification. Error-domain model falsification (EDMF) is an easy-to-use model-based structural-identification methodology which robustly accommodates systematic uncertainties originating from sources such as boundary conditions, numerical modelling and model fidelity, as well as aleatory uncertainties from sources such as measurement error and material parameter-value estimations. In most practical applications of structural identification, sensors are placed using engineering judgment and experience. However, since sensor placement is fundamental to the success of structural identification, a more rational and systematic method is justified. This study presents a measurement system design methodology to identify the best sensor locations and sensor types using information from static-load tests. More specifically, three static-load tests were studied for the sensor system design using three types of sensors for a performance evaluation of a full-scale bridge in Singapore. Several sensor placement strategies are compared using joint entropy as an information-gain metric. A modified version of the hierarchical algorithm for sensor placement is proposed to take into account mutual information between load tests. It is shown that a carefully-configured measurement strategy that includes multiple sensor types and several load tests maximizes information gain. PMID:29240684

Valuation of National Park System Visitation: The Efficient Use of Count Data Models, Meta-Analysis, and Secondary Visitor Survey Data

NASA Astrophysics Data System (ADS)

Neher, Christopher; Duffield, John; Patterson, David

2013-09-01

The National Park Service (NPS) currently manages a large and diverse system of park units nationwide which received an estimated 279 million recreational visits in 2011. This article uses park visitor data collected by the NPS Visitor Services Project to estimate a consistent set of count data travel cost models of park visitor willingness to pay (WTP). Models were estimated using 58 different park unit survey datasets. WTP estimates for these 58 park surveys were used within a meta-regression analysis model to predict average and total WTP for NPS recreational visitation system-wide. Estimated WTP per NPS visit in 2011 averaged 102 system-wide, and ranged across park units from 67 to 288. Total 2011 visitor WTP for the NPS system is estimated at 28.5 billion with a 95% confidence interval of 19.7-43.1 billion. The estimation of a meta-regression model using consistently collected data and identical specification of visitor WTP models greatly reduces problems common to meta-regression models, including sample selection bias, primary data heterogeneity, and heteroskedasticity, as well as some aspects of panel effects. The article provides the first estimate of total annual NPS visitor WTP within the literature directly based on NPS visitor survey data.

Automated real time constant-specificity surveillance for disease outbreaks.

PubMed

Wieland, Shannon C; Brownstein, John S; Berger, Bonnie; Mandl, Kenneth D

2007-06-13

For real time surveillance, detection of abnormal disease patterns is based on a difference between patterns observed, and those predicted by models of historical data. The usefulness of outbreak detection strategies depends on their specificity; the false alarm rate affects the interpretation of alarms. We evaluate the specificity of five traditional models: autoregressive, Serfling, trimmed seasonal, wavelet-based, and generalized linear. We apply each to 12 years of emergency department visits for respiratory infection syndromes at a pediatric hospital, finding that the specificity of the five models was almost always a non-constant function of the day of the week, month, and year of the study (p < 0.05). We develop an outbreak detection method, called the expectation-variance model, based on generalized additive modeling to achieve a constant specificity by accounting for not only the expected number of visits, but also the variance of the number of visits. The expectation-variance model achieves constant specificity on all three time scales, as well as earlier detection and improved sensitivity compared to traditional methods in most circumstances. Modeling the variance of visit patterns enables real-time detection with known, constant specificity at all times. With constant specificity, public health practitioners can better interpret the alarms and better evaluate the cost-effectiveness of surveillance systems.

Percutaneous window chamber method for chronic intravital microscopy of sensor-tissue interactions.

PubMed

Koschwanez, Heidi E; Klitzman, Bruce; Reichert, W Monty

2008-11-01

A dorsal, two-sided skin-fold window chamber model was employed previously by Gough in glucose sensor research to characterize poorly understood physiological factors affecting sensor performance. We have extended this work by developing a percutaneous one-sided window chamber model for the rodent dorsum that offers both a larger subcutaneous area and a less restrictive tissue space than previous animal models. A surgical procedure for implanting a sensor into the subcutis beneath an acrylic window (15 mm diameter) is presented. Methods to quantify changes in the microvascular network and red blood cell perfusion around the sensors using noninvasive intravital microscopy and laser Doppler flowmetry are described. The feasibility of combining interstitial glucose monitoring from an implanted sensor with intravital fluorescence microscopy was explored using a bolus injection of fluorescein and dextrose to observe real-time mass transport of a small molecule at the sensor-tissue interface. The percutaneous window chamber provides an excellent model for assessing the influence of different sensor modifications, such as surface morphologies, on neovascularization using real-time monitoring of the microvascular network and tissue perfusion. However, the tissue response to an implanted sensor was variable, and some sensors migrated entirely out of the field of view and could not be observed adequately. A percutaneous optical window provides direct, real-time images of the development and dynamics of microvascular networks, microvessel patency, and fibrotic encapsulation at the tissue-sensor interface. Additionally, observing microvessels following combined bolus injections of a fluorescent dye and glucose in the local sensor environment demonstrated a valuable technique to visualize mass transport at the sensor surface.

A Prototype Land Information Sensor Web: Design, Implementation and Implication for the SMAP Mission

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Geiger, J. K.; Kumar, S. V.; Gates, L.

2009-12-01

Land Surface Model (LSM) predictions are regular in time and space, but these predictions are influenced by errors in model structure, input variables, parameters and inadequate treatment of sub-grid scale spatial variability. Consequently, LSM predictions are significantly improved through observation constraints made in a data assimilation framework. Several multi-sensor satellites are currently operating which provide multiple global observations of the land surface, and its related near-atmospheric properties. However, these observations are not optimal for addressing current and future land surface environmental problems. To meet future earth system science challenges, NASA will develop constellations of smart satellites in sensor web configurations which provide timely on-demand data and analysis to users, and can be reconfigured based on the changing needs of science and available technology. A sensor web is more than a collection of satellite sensors. That means a sensor web is a system composed of multiple platforms interconnected by a communication network for the purpose of performing specific observations and processing data required to support specific science goals. Sensor webs can eclipse the value of disparate sensor components by reducing response time and increasing scientific value, especially when the two-way interaction between the model and the sensor web is enabled. The study of a prototype Land Information Sensor Web (LISW) is sponsored by NASA, trying to integrate the Land Information System (LIS) in a sensor web framework which allows for optimal 2-way information flow that enhances land surface modeling using sensor web observations, and in turn allows sensor web reconfiguration to minimize overall system uncertainty. This prototype is based on a simulated interactive sensor web, which is then used to exercise and optimize the sensor web modeling interfaces. The Land Information Sensor Web Service-Oriented Architecture (LISW-SOA) has been developed and it is the very first sensor web framework developed especially for the land surface studies. Synthetic experiments based on the LISW-SOA and the virtual sensor web provide a controlled environment in which to examine the end-to-end performance of the prototype, the impact of various sensor web design trade-offs and the eventual value of sensor webs for a particular prediction or decision support. In this paper, the design, implementation of the LISW-SOA and the implication for the Soil Moisture Active and Passive (SMAP) mission is presented. Particular attention is focused on examining the relationship between the economic investment on a sensor web (space and air borne, ground based) and the accuracy of the model predicted soil moisture, which can be achieved by using such sensor observations. The Study of Virtual Land Information Sensor Web (LISW) is expected to provide some necessary a priori knowledge for designing and deploying the next generation Global Earth Observing System of systems (GEOSS).

Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Conover, Helen; Zavodsky, Bradley; Maskey, Manil; Jedlovec, Gary; Regner, Kathryn; Li, Xiang; Lu, Jessica; Botts, Mike; Berthiau, Gregoire

2008-01-01

The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls

PubMed Central

Kim, Byoungjip; Kang, Seungwoo; Ha, Jin-Young; Song, Junehwa

2015-01-01

In this paper, we introduce a novel smartphone framework called VisitSense that automatically detects and predicts a smartphone user’s place visits from ambient radio to enable behavioral targeting for mobile ads in large shopping malls. VisitSense enables mobile app developers to adopt visit-pattern-aware mobile advertising for shopping mall visitors in their apps. It also benefits mobile users by allowing them to receive highly relevant mobile ads that are aware of their place visit patterns in shopping malls. To achieve the goal, VisitSense employs accurate visit detection and prediction methods. For accurate visit detection, we develop a change-based detection method to take into consideration the stability change of ambient radio and the mobility change of users. It performs well in large shopping malls where ambient radio is quite noisy and causes existing algorithms to easily fail. In addition, we proposed a causality-based visit prediction model to capture the causality in the sequential visit patterns for effective prediction. We have developed a VisitSense prototype system, and a visit-pattern-aware mobile advertising application that is based on it. Furthermore, we deploy the system in the COEX Mall, one of the largest shopping malls in Korea, and conduct diverse experiments to show the effectiveness of VisitSense. PMID:26193275

Preventive Services by Medical and Dental Providers and Treatment Outcomes.

PubMed

Kranz, A M; Rozier, R G; Preisser, J S; Stearns, S C; Weinberger, M; Lee, J Y

2014-07-01

Nearly all state Medicaid programs reimburse nondental primary care providers (PCPs) for providing preventive oral health services to young children; yet, little is known about how treatment outcomes compare with children visiting dentists. This study compared the association between the provider of preventive services (PCP, dentist, or both) with Medicaid-enrolled children before their third birthday and subsequent dental caries-related treatment (CRT) and CRT payment. We conducted a retrospective study of young children enrolled in North Carolina Medicaid during 2000 to 2006. The annual number of CRT and CRT payments per child between the ages of 3 and 5 yr were estimated with a zero-inflated negative binomial regression and a hurdle model, respectively. Models were adjusted for relevant child- and county-level characteristics and used propensity score weighting to address observed confounding. We examined 41,453 children with > 1 preventive oral health visit from a PCP, dentist, or both before their third birthday. Unadjusted annual mean CRT and payments were lowest among children who had only PCP visits (CRT = 0.87, payment = $172) and higher among children with only dentist visits (CRT = 1.48, payment = $234) and both PCP and dentist visits (CRT = 1.52, payment = $273). Adjusted results indicated that children who had dentist visits (with or without PCP visits) had significantly more CRT and higher CRT payments per year during the ages of 3 and 4 yr than children who had only PCP visits. However, these differences attenuated each year after age 3 yr. Because of children's increased opportunity to receive multiple visits in medical offices during well-child visits, preventive oral health services provided by PCPs may lead to a greater reduction in CRT than dentist visits alone. This study supports guidelines and reimbursement policies that allow preventive dental visits based on individual needs. © International & American Associations for Dental Research.

Treatment of Nausea and Vomiting in Pregnancy: Factors Associated with ED Revisits

PubMed Central

Sharp, Brian R.; Sharp, Kristen M.; Patterson, Brian; Dooley-Hash, Suzanne

2016-01-01

Introduction Nausea and vomiting in pregnancy (NVP) is a condition that commonly affects women in the first trimester of pregnancy. Despite frequently leading to emergency department (ED) visits, little evidence exists to characterize the nature of ED visits or to guide its treatment in the ED. Our objectives were to evaluate the treatment of NVP in the ED and to identify factors that predict return visits to the ED for NVP. Methods We conducted a retrospective database analysis using the electronic medical record from a single, large academic hospital. Demographic and treatment variables were collected using a chart review of 113 ED patient visits with a billing diagnosis of “nausea and vomiting in pregnancy” or “hyperemesis gravidarum.” Logistic regression analysis was used with a primary outcome of return visit to the ED for the same diagnoses. Results There was wide treatment variability of nausea and vomiting in pregnancy patients in the ED. Of the 113 patient visits, 38 (33.6%) had a return ED visit for NVP. High gravidity (OR 1.31, 95% CI [1.06–1.61]), high parity (OR 1.50 95% CI [1.12–2.00]), and early gestational age (OR 0.74 95% CI [0.60–0.90]) were associated with an increase in return ED visits in univariate logistic regression models, while only early gestational age (OR 0.74 95% CI [0.59–0.91]) was associated with increased return ED visits in a multiple regression model. Admission to the hospital was found to decrease the likelihood of return ED visits (p=0.002). Conclusion NVP can be difficult to manage and has a high ED return visit rate. Optimizing care with aggressive, standardized treatment in the ED and upon discharge, particularly if factors predictive of return ED visits are present, may improve quality of care and reduce ED utilization for this condition. PMID:27625723

Fiber-optical sensor with intensity compensation model in college teaching of physics experiment

NASA Astrophysics Data System (ADS)

Su, Liping; Zhang, Yang; Li, Kun; Zhang, Yu

2017-08-01

Optical fiber sensor technology is one of the main contents of modern information technology, which has a very important position in modern science and technology. Fiber optic sensor experiment can improve students' enthusiasm and broaden their horizons in college physics experiment. In this paper the main structure and working principle of fiberoptical sensor with intensity compensation model are introduced. And thus fiber-optical sensor with intensity compensation model is applied to measure micro displacement of Young's modulus measurement experiment and metal linear expansion coefficient measurement experiment in the college physics experiment. Results indicate that the measurement accuracy of micro displacement is higher than that of the traditional methods using fiber-optical sensor with intensity compensation model. Meanwhile this measurement method makes the students understand on the optical fiber, sensor and nature of micro displacement measurement method and makes each experiment strengthen relationship and compatibility, which provides a new idea for the reform of experimental teaching.

Tracking Object Existence From an Autonomous Patrol Vehicle

NASA Technical Reports Server (NTRS)

Wolf, Michael; Scharenbroich, Lucas

2011-01-01

An autonomous vehicle patrols a large region, during which an algorithm receives measurements of detected potential objects within its sensor range. The goal of the algorithm is to track all objects in the region over time. This problem differs from traditional multi-target tracking scenarios because the region of interest is much larger than the sensor range and relies on the movement of the sensor through this region for coverage. The goal is to know whether anything has changed between visits to the same location. In particular, two kinds of alert conditions must be detected: (1) a previously detected object has disappeared and (2) a new object has appeared in a location already checked. For the time an object is within sensor range, the object can be assumed to remain stationary, changing position only between visits. The problem is difficult because the upstream object detection processing is likely to make many errors, resulting in heavy clutter (false positives) and missed detections (false negatives), and because only noisy, bearings-only measurements are available. This work has three main goals: (1) Associate incoming measurements with known objects or mark them as new objects or false positives, as appropriate. For this, a multiple hypothesis tracker was adapted to this scenario. (2) Localize the objects using multiple bearings-only measurements to provide estimates of global position (e.g., latitude and longitude). A nonlinear Kalman filter extension provides these 2D position estimates using the 1D measurements. (3) Calculate the probability that a suspected object truly exists (in the estimated position), and determine whether alert conditions have been triggered (for new objects or disappeared objects). The concept of a probability of existence was created, and a new Bayesian method for updating this probability at each time step was developed. A probabilistic multiple hypothesis approach is chosen because of its superiority in handling the uncertainty arising from errors in sensors and upstream processes. However, traditional target tracking methods typically assume a stationary detection volume of interest, whereas in this case, one must make adjustments for being able to see only a small portion of the region of interest and understand when an alert situation has occurred. To track object existence inside and outside the vehicle's sensor range, a probability of existence was defined for each hypothesized object, and this value was updated at every time step in a Bayesian manner based on expected characteristics of the sensor and object and whether that object has been detected in the most recent time step. Then, this value feeds into a sequential probability ratio test (SPRT) to determine the status of the object (suspected, confirmed, or deleted). Alerts are sent upon selected status transitions. Additionally, in order to track objects that move in and out of sensor range and update the probability of existence appropriately a variable probability detection has been defined and the hypothesis probability equations have been re-derived to accommodate this change. Unsupervised object tracking is a pervasive issue in automated perception systems. This work could apply to any mobile platform (ground vehicle, sea vessel, air vehicle, or orbiter) that intermittently revisits regions of interest and needs to determine whether anything interesting has changed.

Maintaining High Quality Data and Consistency Across a Diverse Flux Network: The Ameriflux QA/QC Technical Team

NASA Astrophysics Data System (ADS)

Chan, S.; Billesbach, D. P.; Hanson, C. V.; Biraud, S.

2014-12-01

The AmeriFlux quality assurance and quality control (QA/QC) technical team conducts short term (<2 weeks) intercomparisons using a portable eddy covariance system (PECS) to maintain high quality data observations and data consistency across the AmeriFlux network (http://ameriflux.lbl.gov/). Site intercomparisons identify discrepancies between the in situ and portable measurements and calculated fluxes. Findings are jointly discussed by the site staff and the QA/QC team to improve in the situ observations. Despite the relatively short duration of an individual site intercomparison, the accumulated record of all site visits (numbering over 100 since 2002) is a unique dataset. The ability to deploy redundant sensors provides a rare opportunity to identify, quantify, and understand uncertainties in eddy covariance and ancillary measurements. We present a few specific case studies from QA/QC site visits to highlight and share new and relevant findings related to eddy covariance instrumentation and operation.

Redundancy in Glucose Sensing

PubMed Central

Sharifi, Amin; Varsavsky, Andrea; Ulloa, Johanna; Horsburgh, Jodie C.; McAuley, Sybil A.; Krishnamurthy, Balasubramanian; Jenkins, Alicia J.; Colman, Peter G.; Ward, Glenn M.; MacIsaac, Richard J.; Shah, Rajiv; O’Neal, David N.

2015-01-01

Background: Current electrochemical glucose sensors use a single electrode. Multiple electrodes (redundancy) may enhance sensor performance. We evaluated an electrochemical redundant sensor (ERS) incorporating two working electrodes (WE1 and WE2) onto a single subcutaneous insertion platform with a processing algorithm providing a single real-time continuous glucose measure. Methods: Twenty-three adults with type 1 diabetes each wore two ERSs concurrently for 168 hours. Post-insertion a frequent sampling test (FST) was performed with ERS benchmarked against a glucose meter (Bayer Contour Link). Day 4 and 7 FSTs were performed with a standard meal and venous blood collected for reference glucose measurements (YSI and meter). Between visits, ERS was worn with capillary blood glucose testing ≥8 times/day. Sensor glucose data were processed prospectively. Results: Mean absolute relative deviation (MARD) for ERS day 1-7 (3,297 paired points with glucose meter) was (mean [SD]) 10.1 [11.5]% versus 11.4 [11.9]% for WE1 and 12.0 [11.9]% for WE2; P < .0001. ERS Clarke A and A+B were 90.2% and 99.8%, respectively. ERS day 4 plus day 7 MARD (1,237 pairs with YSI) was 9.4 [9.5]% versus 9.6 [9.7]% for WE1 and 9.9 [9.7]% for WE2; P = ns. ERS day 1-7 precision absolute relative deviation (PARD) was 9.9 [3.6]% versus 11.5 [6.2]% for WE1 and 10.1 [4.4]% for WE2; P = ns. ERS sensor display time was 97.8 [6.0]% versus 91.0 [22.3]% for WE1 and 94.1 [14.3]% for WE2; P < .05. Conclusions: Electrochemical redundancy enhances glucose sensor accuracy and display time compared with each individual sensing element alone. ERS performance compares favorably with ‘best-in-class’ of non-redundant sensors. PMID:26499476

Proceedings of the Augmented VIsual Display (AVID) Research Workshop

NASA Technical Reports Server (NTRS)

Kaiser, Mary K. (Editor); Sweet, Barbara T. (Editor)

1993-01-01

The papers, abstracts, and presentations were presented at a three day workshop focused on sensor modeling and simulation, and image enhancement, processing, and fusion. The technical sessions emphasized how sensor technology can be used to create visual imagery adequate for aircraft control and operations. Participants from industry, government, and academic laboratories contributed to panels on Sensor Systems, Sensor Modeling, Sensor Fusion, Image Processing (Computer and Human Vision), and Image Evaluation and Metrics.

Three-Dimensional Sensor Common Operating Picture (3-D Sensor COP)

DTIC Science & Technology

2017-01-01

created. Additionally, a 3-D model of the sensor itself can be created. Using these 3-D models, along with emerging virtual and augmented reality tools...augmented reality 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 20 19a...iii Contents List of Figures iv 1. Introduction 1 2. The 3-D Sensor COP 2 3. Virtual Sensor Placement 7 4. Conclusions 10 5. References 11

Soft Sensors: Chemoinformatic Model for Efficient Control and Operation in Chemical Plants.

PubMed

Funatsu, Kimito

2016-12-01

Soft sensor is statistical model as an essential tool for controlling pharmaceutical, chemical and industrial plants. I introduce soft sensor, the roles, the applications, the problems and the research examples such as adaptive soft sensor, database monitoring and efficient process control. The use of soft sensor enables chemical industrial plants to be operated more effectively and stably. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Home visiting programs for HIV-affected families: a comparison of service quality between volunteer-driven and paraprofessional models.

PubMed

Kidman, Rachel; Nice, Johanna; Taylor, Tory; Thurman, Tonya R

2014-10-02

Home visiting is a popular component of programs for HIV-affected children in sub-Saharan Africa, but its implementation varies widely. While some home visitors are lay volunteers, other programs invest in more highly trained paraprofessional staff. This paper describes a study investigating whether additional investment in paraprofessional staffing translated into higher quality service delivery in one program context. Beneficiary children and caregivers at sites in KwaZulu-Natal, South Africa were interviewed after 2 years of program enrollment and asked to report about their experiences with home visiting. Analysis focused on intervention exposure, including visit intensity, duration and the kinds of emotional, informational and tangible support provided. Few beneficiaries reported receiving home visits in program models primarily driven by lay volunteers; when visits did occur, they were shorter and more infrequent. Paraprofessional-driven programs not only provided significantly more home visits, but also provided greater interaction with the child, communication on a larger variety of topics, and more tangible support to caregivers. These results suggest that programs that invest in compensation and extensive training for home visitors are better able to serve and retain beneficiaries, and they support a move toward establishing a professional workforce of home visitors to support vulnerable children and families in South Africa.

The Association Between Internet Use and Ambulatory Care-Seeking Behaviors in Taiwan: A Cross-Sectional Study

PubMed Central

Chen, Tsung-Fu; Liang, Jyh-Chong; Lin, Tzu-Bin; Tsai, Chin-Chung

2016-01-01

Background Compared with the traditional ways of gaining health-related information from newspapers, magazines, radio, and television, the Internet is inexpensive, accessible, and conveys diverse opinions. Several studies on how increasing Internet use affected outpatient clinic visits were inconclusive. Objective The objective of this study was to examine the role of Internet use on ambulatory care-seeking behaviors as indicated by the number of outpatient clinic visits after adjusting for confounding variables. Methods We conducted this study using a sample randomly selected from the general population in Taiwan. To handle the missing data, we built a multivariate logistic regression model for propensity score matching using age and sex as the independent variables. The questionnaires with no missing data were then included in a multivariate linear regression model for examining the association between Internet use and outpatient clinic visits. Results We included a sample of 293 participants who answered the questionnaire with no missing data in the multivariate linear regression model. We found that Internet use was significantly associated with more outpatient clinic visits (P=.04). The participants with chronic diseases tended to make more outpatient clinic visits (P<.01). Conclusions The inconsistent quality of health-related information obtained from the Internet may be associated with patients’ increasing need for interpreting and discussing the information with health care professionals, thus resulting in an increasing number of outpatient clinic visits. In addition, the media literacy of Web-based health-related information seekers may also affect their ambulatory care-seeking behaviors, such as outpatient clinic visits. PMID:27927606

Advance Care Planning Meets Group Medical Visits: The Feasibility of Promoting Conversations

PubMed Central

Lum, Hillary D.; Jones, Jacqueline; Matlock, Daniel D.; Glasgow, Russell E.; Lobo, Ingrid; Levy, Cari R.; Schwartz, Robert S.; Sudore, Rebecca L.; Kutner, Jean S.

2016-01-01

PURPOSE Primary care needs new models to facilitate advance care planning conversations. These conversations focus on preferences regarding serious illness and may involve patients, decision makers, and health care providers. We describe the feasibility of the first primary care–based group visit model focused on advance care planning. METHODS We conducted a pilot demonstration of an advance care planning group visit in a geriatrics clinic. Patients were aged at least 65 years. Groups of patients met in 2 sessions of 2 hours each facilitated by a geriatrician and a social worker. Activities included considering personal values, discussing advance care planning, choosing surrogate decision-makers, and completing advance directives. We used the RE-AIM framework to evaluate the project. RESULTS Ten of 11 clinicians referred patients for participation. Of 80 patients approached, 32 participated in 5 group visit cohorts (a 40% participation rate) and 27 participated in both sessions (an 84% retention rate). Mean age was 79 years; 59% of participants were female and 72% white. Most evaluated the group visit as better than usual clinic visits for discussing advance care planning. Patients reported increases in detailed advance care planning conversations after participating (19% to 41%, P = .02). Qualitative analysis found that older adults were willing to share personal values and challenges related to advance care planning and that they initiated discussions about a broad range of relevant topics. CONCLUSION A group visit to facilitate discussions about advance care planning and increase patient engagement is feasible. This model warrants further evaluation for effectiveness in improving advance care planning outcomes for patients, clinicians, and the system. PMID:26951587

Patient-Centered Medical Home Implementation in the Veterans Health Administration and Primary Care Use: Differences by Patient Comorbidity Burden.

PubMed

Wong, Edwin S; Rosland, Ann-Marie; Fihn, Stephan D; Nelson, Karin M

2016-12-01

The patient-centered medical home (PCMH) model has several components to improve care for patients with high comorbidity, including greater access to face-to-face primary care. We examined whether high-comorbidity patients had larger increases in primary care provider (PCP) visits attributable to PCMH implementation in a large integrated health system relative to other patients enrolled in primary care. This longitudinal study examined a 1 % random sample of 9.3 million patients enrolled in the Veterans Health Administration (VHA) at any time between 2003 and 2013. Face-to-face visits with PCPs per quarter were identified through VHA administrative data. Comorbidity was measured using the Gagne index and patients with a weighted score of ≥ 2 were defined as high comorbidity. We applied interrupted time-series models to estimate marginal changes in PCP visits attributable to PCMH implementation. Differences in marginal changes were calculated across comorbidity groups (high vs. low). Analyses were stratified by age group to account for Medicare eligibility. Among age 65+ patients, PCMH was associated with greater PCP visits starting four and ten quarters following implementation for high- and low-comorbidity patients, respectively. Changes were larger for high-comorbidity patients (eight to 11 greater visits per 1000 patients per quarter). Among patients age < 65, PCMH was associated with greater visits for high-comorbidity patients starting eight quarters following implementation, but fewer visits for low-comorbidity patients in all quarters. The difference in visit changes across groups ranged from 18 to 67 visits per 1000 patients per quarter. Increases in PCP visits attributable to PCMH were greater among patients with higher comorbidity. Health systems implementing PCMH should account for population-level comorbidity burden when planning for PCMH-related changes in PCP utilization.

Unscheduled-return-visits after an emergency department (ED) attendance and clinical link between both visits in patients aged 75 years and over: a prospective observational study.

PubMed

Pereira, Laurent; Choquet, Christophe; Perozziello, Anne; Wargon, Mathias; Juillien, Gaelle; Colosi, Luisa; Hellmann, Romain; Ranaivoson, Michel; Casalino, Enrique

2015-01-01

Predictors of unscheduled return visits (URV), best time-frame to evaluate URV rate and clinical relationship between both visits have not yet been determined for the elderly following an ED visit. We conducted a prospective-observational study including 11,521 patients aged ≥75-years and discharged from ED (5,368 patients (53.5%)) or hospitalized after ED visit (6,153 patients). Logistic Regression and time-to-failure analyses including Cox proportional model were performed. Mean time to URV was 17 days; 72-hour, 30-day and 90-day URV rates were 1.8%, 6.1% and 10% respectively. Multivariate analysis indicates that care-pathway and final disposition decisions were significantly associated with a 30-day URV. Thus, we evaluated predictors of 30-day URV rates among non-admitted and hospitalized patient groups. By using the Cox model we found that, for non-admitted patients, triage acuity and diagnostic category and, for hospitalized patients, that visit time (day, night) and diagnostic categories were significant predictors (p<0.001). For URV, we found that 25% were due to closely related-clinical conditions. Time lapses between both visits constituted the strongest predictor of closely related-clinical conditions. Our study shows that a decision of non-admission in emergency departments is linked with an accrued risk of URV, and that some diagnostic categories are also related for non-admitted and hospitalized subjects alike. Our study also demonstrates that the best time frame to evaluate the URV rate after an ED visit is 30 days, because this is the time period during which most URVs and cases with close clinical relationships between two visits are concentrated. Our results suggest that URV can be used as an indicator or quality.

Modelling the Energy Efficient Sensor Nodes for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Dahiya, R.; Arora, A. K.; Singh, V. R.

2015-09-01

Energy is an important requirement of wireless sensor networks for better performance. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to low-power consumption as well as to reduce operational capabilities. In this paper, Markov model of a sensor network is developed. The node is considered to enter a sleep mode. This model is used to investigate the system performance in terms of energy consumption, network capacity and data delivery delay.

Air pollution and ED visits for asthma in Australian children: a case-crossover analysis.

PubMed

Jalaludin, Bin; Khalaj, Behnoosh; Sheppeard, Vicky; Morgan, Geoff

2008-08-01

We aimed to determine the effects of ambient air pollutants on emergency department (ED) visits for asthma in children. We obtained routinely collected ED visit data for asthma (ICD9 493) and air pollution (PM(10), PM(2.5), O(3), NO(2), CO and SO(2)) and meteorological data for metropolitan Sydney for 1997-2001. We used the time stratified case-crossover design and conditional logistic regression to model the association between air pollutants and ED visits for four age-groups (1-4, 5-9, 10-14 and 1-14 years). Estimated relative risks for asthma ED visits were calculated for an exposure corresponding to the inter-quartile range in pollutant level. We included same day average temperature, same day relative humidity, daily temperature range, school holidays and public holidays in all models. Associations between ambient air pollutants and ED visits for asthma in children were most consistent for all six air pollutants in the 1-4 years age-group, for particulates and CO in the 5-9 years age-group and for CO in the 10-14 years age-group. The greatest effects were most consistently observed for lag 0 and effects were greater in the warm months for particulates, O(3) and NO(2). In two pollutant models, effect sizes were generally smaller compared to those derived from single pollutant models. We observed the effects of ambient air pollutants on ED attendances for asthma in a city where the ambient concentrations of air pollutants are relatively low.

Understanding clinicians' attitudes toward a mobile health strategy to childhood asthma management: A qualitative study.

PubMed

Hollenbach, Jessica P; Cushing, Anna; Melvin, Emilie; McGowan, Bryanna; Cloutier, Michelle M; Manice, Melissa

2017-09-01

Mobile technology for childhood asthma can provide real-time data to enhance care. What real-time adherence information clinicians want, how they may use it, and if the data meet their clinical needs have not been fully explored. Our goal was to determine whether pediatric primary care and pulmonary clinicians believe if a sensor-based mobile intervention is useful in caring for patients with asthma. We recruited participants from 3 urban, primary care and 1 pulmonary practice from July to September 2015 in Hartford, CT. Forty-one participated in four focus groups, which included a demonstration of the technology. Participants were probed with open-ended questions on the type, frequency, and format of inter-visit patient information they found useful. 41 participants (mean age 49 (±13.7) years) were board-certified clinicians (41% MDs and 20% mid-level practitioners), practiced medicine on an average of 19 (±14) years, were primarily white (59%) and women (78%). Clinicians wanted 1) adherence to prescribed inhaler therapy and 2) data on inhaler technique. Clinicians wanted it at the time of a scheduled clinic visit but also wanted inter-visit alerts for excessive use of rescue therapy. Pulmonologists liked the mobile spirometer's provision of inter-visit lung function data; pediatricians did not share this view. Concerns with data accuracy were raised due to families who shared inhalers, access to smartphones, and protection of health information. Overall, clinicians view an asthma mobile health technology as enhancing the patient-centered medical home. Pediatric primary care clinicians and pulmonologists want different information from a mobile app.

"Purely for You": Inmates' Perceptions of Prison Visitation by Volunteers in the Netherlands.

PubMed

Schuhmann, Carmen; Kuis, Esther; Goossensen, Anne

2018-03-01

Research suggests that prison visitation by volunteers may significantly reduce the risk of recidivism. Community volunteers offer sustained, prosocial support to inmates which may account for these beneficial effects. However, the question of how inmates themselves evaluate volunteer visitation has hardly been studied. This study explores how inmates of Dutch prisons who receive one-on-one volunteer visits experience and value these visits. To that end, semistructured interviews were conducted with 21 inmates across six penitentiaries. These show that the value of volunteer visitation for inmates has to be understood in terms of a human-to-human encounter. Visits by volunteers provide inmates with rare opportunities to have a confidential conversation, away from the harshness of the usual prison life. Furthermore, inmates perceive volunteer visitation as beneficial beyond the actual visits. Inmates draw hope, strength, or self-respect from the conversations; they see volunteers as role models and develop a more positive view of the future. Two potential obstacles to beneficial volunteer visitation were detected: lack of chemistry between volunteer and inmate and imposition of worldview beliefs by volunteers.

The wildfire experiment (WIFE): observations with airborne remote sensors

Treesearch

L.F. Radke; T.L. Clark; J.L. Coen; C.A. Walther; R.N. Lockwood; P.J. Riggan; J.A. Brass; R.G. Higgins

2000-01-01

Airborne remote sensors have long been a cornerstone of wildland fire research, and recently three-dimensional fire behaviour models fully coupled to the atmosphere have begun to show a convincing level of verisimilitude. The WildFire Experiment (WiFE) attempted the marriage of airborne remote sensors, multi-sensor observations together with fire model development and...

Modeling and experimental study on characterization of micromachined thermal gas inertial sensors.

PubMed

Zhu, Rong; Ding, Henggao; Su, Yan; Yang, Yongjun

2010-01-01

Micromachined thermal gas inertial sensors based on heat convection are novel devices that compared with conventional micromachined inertial sensors offer the advantages of simple structures, easy fabrication, high shock resistance and good reliability by virtue of using a gaseous medium instead of a mechanical proof mass as key moving and sensing elements. This paper presents an analytical modeling for a micromachined thermal gas gyroscope integrated with signal conditioning. A simplified spring-damping model is utilized to characterize the behavior of the sensor. The model relies on the use of the fluid mechanics and heat transfer fundamentals and is validated using experimental data obtained from a test-device and simulation. Furthermore, the nonideal issues of the sensor are addressed from both the theoretical and experimental points of view. The nonlinear behavior demonstrated in experimental measurements is analyzed based on the model. It is concluded that the sources of nonlinearity are mainly attributable to the variable stiffness of the sensor system and the structural asymmetry due to nonideal fabrication.

Multi-hierarchical movements in self-avoiding walks

NASA Astrophysics Data System (ADS)

Sakiyama, Tomoko; Gunji, Yukio-Pegio

2017-07-01

A self-avoiding walk (SAW) is a series of moves on a lattice that visit the same place only once. Several studies reported that repellent reactions of foragers to previously visited sites induced power-law tailed SAWs in animals. In this paper, we show that modelling the agent's multi-avoidance reactions to its trails enables it to show ballistic movements which result in heavy-tailed movements. There is no literature showing emergent ballistic movements in SAWs. While following SAWs, the agent in my model changed its reactions to marked patches (visited sites) by considering global trail patterns based on local trail patterns when the agent was surrounded by previously visited sites. As a result, we succeeded in producing ballistic walks by the agents which exhibited emergent power-law tailed movements.

Space Station racks weight and CG measurement using the rack insertion end-effector

NASA Technical Reports Server (NTRS)

Brewer, William V.

1994-01-01

The objective was to design a method to measure weight and center of gravity (C.G.) location for Space Station Modules by adding sensors to the existing Rack Insertion End Effector (RIEE). Accomplishments included alternative sensor placement schemes organized into categories. Vendors were queried for suitable sensor equipment recommendations. Inverse mathematical models for each category determine expected maximum sensor loads. Sensors are selected using these computations, yielding cost and accuracy data. Accuracy data for individual sensors are inserted into forward mathematical models to estimate the accuracy of an overall sensor scheme. Cost of the schemes can be estimated. Ease of implementation and operation are discussed.

Commercial Television Exposure, Fast Food Toy Collecting, and Family Visits to Fast Food Restaurants among Families Living in Rural Communities.

PubMed

Emond, Jennifer A; Bernhardt, Amy M; Gilbert-Diamond, Diane; Li, Zhigang; Sargent, James D

2016-01-01

To assess the associations between children's exposure to television (TV) networks that aired child-directed advertisements for children's fast food meals with the collection of fast food meal toy premiums and frequency of family visits to those restaurants. One hundred parents of children 3-7 years old were recruited from a rural pediatrics clinic during 2011; families receiving Medicaid were oversampled. Parents reported the child's TV viewing habits and family visit frequency to the fast food restaurants participating in child-directed TV marketing at the time, and their child's requests for visits to and the collecting of toy premiums from those restaurants. Logistic regression models assessed adjusted associations between a child's TV viewing with more frequent restaurant visits (≥monthly in this population). Structural equation modeling assessed if child requests or toy collecting mediated that association. Thirty-seven percent of parents reported ≥monthly visits to the select fast food restaurants. Among children, 54% requested visits to and 29% collected toys from those restaurants. Greater child commercial TV viewing was significantly associated with more frequent family visits to those fast food restaurants (aOR 2.84 for each 1-unit increase in the child's commercial TV viewing scale, P < .001); toy collecting partially mediated that positive association. Higher exposure among children to commercial TV networks that aired child-directed ads for children's fast food meals was associated with more frequent family visits to those fast food restaurants. Child desire for toy premiums may be a mediating factor. Copyright © 2016 Elsevier Inc. All rights reserved.

Commercial TV exposure, fast-food toy collecting and family visits to fast food restaurants among families living in rural communities

PubMed Central

Emond, Jennifer A.; Bernhardt, Amy M.; Gilbert-Diamond, Diane; Li, Zhigang; Sargent, James D.

2015-01-01

Objective To assess the associations between children's exposure to TV networks that aired child-directed advertisements for children's fast food meals with the collection of fast food meal toy premiums and frequency of family visits to those restaurants. Study design One hundred parents of children 3–7 years old were recruited from a rural pediatrics clinic during 2011; families receiving Medicaid were oversampled. Parents reported the child's television viewing habits and family visit frequency to the fast food restaurants participating in child-directed TV marketing at the time, and their child's requests for visits to and the collecting of toy premiums from those restaurants. Logistic regression models assessed adjusted associations between a child's TV viewing with more frequent restaurant visits (≥monthly in this population). Structural equation modeling assessed if child requests or toy collecting mediated that association. Results Thirty-seven percent of parents reported ≥monthly visits to the select fast food restaurants. Among children, 54% requested visits to and 29% collected toys from those restaurants. Greater child commercial TV viewing was significantly associated with more frequent family visits to those fast food restaurants (adjusted odds ratio 2.84 for each one-unit increase in the child's commercial TV viewing scale, p<0.001); toy collecting partially mediated that positive association. Conclusions Higher exposure among children to commercial TV networks that aired child-directed ads for children's fast food meals was associated with more frequent family visits to those fast food restaurants. Child desire for toy premiums may be a mediating factor. PMID:26526362

Maternal relationship security as a moderator of home visiting impacts on maternal psychosocial functioning.

PubMed

McFarlane, Elizabeth; Burrell, Lori; Crowne, Sarah; Cluxton-Keller, Fallon; Fuddy, Loretta; Leaf, Philip J; Duggan, Anne

2013-02-01

There is variability in home visiting program impacts on the outcomes achieved by high risk families. An understanding of how effects vary among families is important for refining service targeting and content. The current study assessed whether and how maternal attributes, including relationship security, moderate short- and long-term home visiting impacts on maternal psychosocial functioning. In this multisite RCT of home visiting in a population-based, ethnically-diverse sample of families at risk for maltreatment of their newborns (n = 643), families were randomly assigned to home visited (HV) and control groups. HV families were to receive intensive services by trained paraprofessionals from birth-3 years. Outcome data were collected when children were 1, 2, and 3 years old and 7, 8, and 9 years old. Overall, short- and long-term outcomes for HV and control mothers did not differ significantly. Demographic attributes, a general measure of overall maternal risk, and partner violence did not moderate program impact on psychosocial functioning outcomes. Maternal relationship security did moderate program impact. Mothers who scored high on relationship anxiety but not on relationship avoidance showed the greatest benefits, particularly at the long-term follow-up. Mothers scoring high for both relationship anxiety and avoidance experienced some adverse consequences of home visiting. Further research is needed to determine mediating pathways and to inform and test ways to improve the targeting of home visiting and the tailoring of home visit service models to extend positive home visiting impacts to targeted families not benefiting from current models.

Tooth loss in middle-aged adults with diabetes and hypertension: Social determinants, health perceptions, oral impact on daily performance (OIDP) and treatment need

PubMed Central

Maia, Fabiana-Barros-Marinho; Sampaio, Fábio-Correia; Freitas, Cláudia-Helena-Soares-de Morais; Forte, Franklin-Delano-Soares

2018-01-01

Background This study aimed to explore the association between tooth loss and social determinants, health self-perceptions, OIDP and self-concept of dental treatment need in middle-aged adults with diabetes and hypertension. Material and Methods A cross-sectional study was developed with 212 hypertensive and diabetic middle-aged adults (50-65 years). Data were collected from clinical examinations (DMFT) and a questionnaire regarding socioeconomic status, dental health assistance, self-perceptions of oral and general health, OIDP, and the self-concept of dental treatment need. Tooth loss was dichotomized considering the cutoff point of 12 (Model I) or 24 missing teeth (Model II). Data were analyzed using Chi-square, Fisher’s exact test and logistic regression (p≤0.05). Results Tooth loss was significantly associated with variables such as last dental visit, reason for dental visit, OIDP, perception of dental treatment need, and general self-perception (Model I). Schooling, last dental visit, oral health self-perception and perception of dental treatment need were significantly associated with tooth loss in the Model II. When Model 1 and 2 were adjusted, they demonstrated that last dental visit and perception of dental treatment need were predictor variables. Conclusions The annual dental visit and the self-concept of dental treatment need were associated with tooth loss, demonstrating that these variables reduce the tooth loss prevalence. Key words:Access /barriers to care, Dental treatment, Geriatric dentistry. PMID:29476679

Crack Detection in Fibre Reinforced Plastic Structures Using Embedded Fibre Bragg Grating Sensors: Theory, Model Development and Experimental Validation

PubMed Central

Pereira, G. F.; Mikkelsen, L. P.; McGugan, M.

2015-01-01

In a fibre-reinforced polymer (FRP) structure designed using the emerging damage tolerance and structural health monitoring philosophy, sensors and models that describe crack propagation will enable a structure to operate despite the presence of damage by fully exploiting the material’s mechanical properties. When applying this concept to different structures, sensor systems and damage types, a combination of damage mechanics, monitoring technology, and modelling is required. The primary objective of this article is to demonstrate such a combination. This article is divided in three main topics: the damage mechanism (delamination of FRP), the structural health monitoring technology (fibre Bragg gratings to detect delamination), and the finite element method model of the structure that incorporates these concepts into a final and integrated damage-monitoring concept. A novel method for assessing a crack growth/damage event in fibre-reinforced polymer or structural adhesive-bonded structures using embedded fibre Bragg grating (FBG) sensors is presented by combining conventional measured parameters, such as wavelength shift, with parameters associated with measurement errors, typically ignored by the end-user. Conjointly, a novel model for sensor output prediction (virtual sensor) was developed using this FBG sensor crack monitoring concept and implemented in a finite element method code. The monitoring method was demonstrated and validated using glass fibre double cantilever beam specimens instrumented with an array of FBG sensors embedded in the material and tested using an experimental fracture procedure. The digital image correlation technique was used to validate the model prediction by correlating the specific sensor response caused by the crack with the developed model. PMID:26513653

Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

PubMed

Zhou, Tony; Dickson, Jennifer L; Geoffrey Chase, J

2018-01-01

Continuous glucose monitoring (CGM) devices have been effective in managing diabetes and offer potential benefits for use in the intensive care unit (ICU). Use of CGM devices in the ICU has been limited, primarily due to the higher point accuracy errors over currently used traditional intermittent blood glucose (BG) measures. General models of CGM errors, including drift and random errors, are lacking, but would enable better design of protocols to utilize these devices. This article presents an autoregressive (AR) based modeling method that separately characterizes the drift and random noise of the GlySure CGM sensor (GlySure Limited, Oxfordshire, UK). Clinical sensor data (n = 33) and reference measurements were used to generate 2 AR models to describe sensor drift and noise. These models were used to generate 100 Monte Carlo simulations based on reference blood glucose measurements. These were then compared to the original CGM clinical data using mean absolute relative difference (MARD) and a Trend Compass. The point accuracy MARD was very similar between simulated and clinical data (9.6% vs 9.9%). A Trend Compass was used to assess trend accuracy, and found simulated and clinical sensor profiles were similar (simulated trend index 11.4° vs clinical trend index 10.9°). The model and method accurately represents cohort sensor behavior over patients, providing a general modeling approach to any such sensor by separately characterizing each type of error that can arise in the data. Overall, it enables better protocol design based on accurate expected CGM sensor behavior, as well as enabling the analysis of what level of each type of sensor error would be necessary to obtain desired glycemic control safety and performance with a given protocol.

JSC engineers visit area schools for National Engineers Week

NASA Image and Video Library

1996-02-28

Johnson Space Center (JSC) engineers visit Houston area schools for National Engineers Week. Students examine a machine that generates static electricity (4296-7). Students examine model rockets (4298).

Clinical evaluation of the Jay Sensitivity Sensor Probe: a new microprocessor-controlled instrument to evaluate dentin hypersensitivity.

PubMed

Sowinski, Joseph A; Kakar, Ashish; Kakar, Kanupriya

2013-05-01

To compare the Jay Sensitivity Sensor Probe (Jay Probe), a new microprocessor-based, pre-calibrated instrument, with well accepted methods used to evaluate sensitivity, i.e. tactile response to the Yeaple Probe, air blast (Schiff scale), and patient responses by Visual Analog Score (VAS). Jay Probe assessments were accomplished using several approaches. With a cohort of 12 subjects, two clinical examiners compared the repeatability of the Jay and Yeaple Probes. A second evaluation of both probes was conducted during two independent parallel design clinical studies each enrolling 100 adults with dentin hypersensitivity (DH). In each study, subjects were evaluated for DH responses after twice daily oral hygiene with a negative control fluoride dentifrice or a positive control dentifrice formulated with ingredients proven to reduce sensitivity, i.e. potassium nitrate or 8.0% arginine with calcium carbonate. Tactile evaluations by the Jay and Yeaple Probes were conducted at baseline and recall visits over the 8-week duration of each study. Also evaluated at each visit were responses to air blast and to patient reported DH assessment by VAS. Low inter-examiner variability with no significant differences between replicate measurements (P > 0.05) was observed with the Jay Probe. Consistent with results from previous studies, subjects assigned dentifrices formulated with potassium nitrate or 8% arginine/calcium carbonate demonstrated improvements in Yeaple, air blast and VAS responses in comparison to those assigned the fluoride dentifrice (P < 0.05). Jay Probe responses correlated significantly with all other sensitivity measures (P < 0.05). Differences between these treatments were observed at all post-treatment evaluations using these methods.

Performance Evaluation Modeling of Network Sensors

NASA Technical Reports Server (NTRS)

Clare, Loren P.; Jennings, Esther H.; Gao, Jay L.

2003-01-01

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

PubMed Central

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-01-01

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes. PMID:26712766

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation.

PubMed

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-12-26

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and 24 fuzzy rules for the robot's movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.

Error Modeling and Experimental Study of a Flexible Joint 6-UPUR Parallel Six-Axis Force Sensor.

PubMed

Zhao, Yanzhi; Cao, Yachao; Zhang, Caifeng; Zhang, Dan; Zhang, Jie

2017-09-29

By combining a parallel mechanism with integrated flexible joints, a large measurement range and high accuracy sensor is realized. However, the main errors of the sensor involve not only assembly errors, but also deformation errors of its flexible leg. Based on a flexible joint 6-UPUR (a kind of mechanism configuration where U-universal joint, P-prismatic joint, R-revolute joint) parallel six-axis force sensor developed during the prephase, assembly and deformation error modeling and analysis of the resulting sensors with a large measurement range and high accuracy are made in this paper. First, an assembly error model is established based on the imaginary kinematic joint method and the Denavit-Hartenberg (D-H) method. Next, a stiffness model is built to solve the stiffness matrix. The deformation error model of the sensor is obtained. Then, the first order kinematic influence coefficient matrix when the synthetic error is taken into account is solved. Finally, measurement and calibration experiments of the sensor composed of the hardware and software system are performed. Forced deformation of the force-measuring platform is detected by using laser interferometry and analyzed to verify the correctness of the synthetic error model. In addition, the first order kinematic influence coefficient matrix in actual circumstances is calculated. By comparing the condition numbers and square norms of the coefficient matrices, the conclusion is drawn theoretically that it is very important to take into account the synthetic error for design stage of the sensor and helpful to improve performance of the sensor in order to meet needs of actual working environments.

Error Modeling and Experimental Study of a Flexible Joint 6-UPUR Parallel Six-Axis Force Sensor

PubMed Central

Zhao, Yanzhi; Cao, Yachao; Zhang, Caifeng; Zhang, Dan; Zhang, Jie

2017-01-01

By combining a parallel mechanism with integrated flexible joints, a large measurement range and high accuracy sensor is realized. However, the main errors of the sensor involve not only assembly errors, but also deformation errors of its flexible leg. Based on a flexible joint 6-UPUR (a kind of mechanism configuration where U-universal joint, P-prismatic joint, R-revolute joint) parallel six-axis force sensor developed during the prephase, assembly and deformation error modeling and analysis of the resulting sensors with a large measurement range and high accuracy are made in this paper. First, an assembly error model is established based on the imaginary kinematic joint method and the Denavit-Hartenberg (D-H) method. Next, a stiffness model is built to solve the stiffness matrix. The deformation error model of the sensor is obtained. Then, the first order kinematic influence coefficient matrix when the synthetic error is taken into account is solved. Finally, measurement and calibration experiments of the sensor composed of the hardware and software system are performed. Forced deformation of the force-measuring platform is detected by using laser interferometry and analyzed to verify the correctness of the synthetic error model. In addition, the first order kinematic influence coefficient matrix in actual circumstances is calculated. By comparing the condition numbers and square norms of the coefficient matrices, the conclusion is drawn theoretically that it is very important to take into account the synthetic error for design stage of the sensor and helpful to improve performance of the sensor in order to meet needs of actual working environments. PMID:28961209

Modeling, Detection, and Disambiguation of Sensor Faults for Aerospace Applications

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai F.; Curran, Simon

2009-01-01

Sensor faults continue to be a major hurdle for systems health management to reach its full potential. At the same time, few recorded instances of sensor faults exist. It is equally difficult to seed particular sensor faults. Therefore, research is underway to better understand the different fault modes seen in sensors and to model the faults. The fault models can then be used in simulated sensor fault scenarios to ensure that algorithms can distinguish between sensor faults and system faults. The paper illustrates the work with data collected from an electro-mechanical actuator in an aerospace setting, equipped with temperature, vibration, current, and position sensors. The most common sensor faults, such as bias, drift, scaling, and dropout were simulated and injected into the experimental data, with the goal of making these simulations as realistic as feasible. A neural network based classifier was then created and tested on both experimental data and the more challenging randomized data sequences. Additional studies were also conducted to determine sensitivity of detection and disambiguation efficacy to severity of fault conditions.

Pervasive Computing Technologies to Continuously Assess Alzheimer's Disease Progression and Intervention Efficacy.

PubMed

Lyons, Bayard E; Austin, Daniel; Seelye, Adriana; Petersen, Johanna; Yeargers, Jonathan; Riley, Thomas; Sharma, Nicole; Mattek, Nora; Wild, Katherine; Dodge, Hiroko; Kaye, Jeffrey A

2015-01-01

Traditionally, assessment of functional and cognitive status of individuals with dementia occurs in brief clinic visits during which time clinicians extract a snapshot of recent changes in individuals' health. Conventionally, this is done using various clinical assessment tools applied at the point of care and relies on patients' and caregivers' ability to accurately recall daily activity and trends in personal health. These practices suffer from the infrequency and generally short durations of visits. Since 2004, researchers at the Oregon Center for Aging and Technology (ORCATECH) at the Oregon Health and Science University have been working on developing technologies to transform this model. ORCATECH researchers have developed a system of continuous in-home monitoring using pervasive computing technologies that make it possible to more accurately track activities and behaviors and measure relevant intra-individual changes. We have installed a system of strategically placed sensors in over 480 homes and have been collecting data for up to 8 years. Using this continuous in-home monitoring system, ORCATECH researchers have collected data on multiple behaviors such as gait and mobility, sleep and activity patterns, medication adherence, and computer use. Patterns of intra-individual variation detected in each of these areas are used to predict outcomes such as low mood, loneliness, and cognitive function. These methods have the potential to improve the quality of patient health data and in turn patient care especially related to cognitive decline. Furthermore, the continuous real-world nature of the data may improve the efficiency and ecological validity of clinical intervention studies.

Pervasive Computing Technologies to Continuously Assess Alzheimer’s Disease Progression and Intervention Efficacy

PubMed Central

Lyons, Bayard E.; Austin, Daniel; Seelye, Adriana; Petersen, Johanna; Yeargers, Jonathan; Riley, Thomas; Sharma, Nicole; Mattek, Nora; Wild, Katherine; Dodge, Hiroko; Kaye, Jeffrey A.

2015-01-01

Traditionally, assessment of functional and cognitive status of individuals with dementia occurs in brief clinic visits during which time clinicians extract a snapshot of recent changes in individuals’ health. Conventionally, this is done using various clinical assessment tools applied at the point of care and relies on patients’ and caregivers’ ability to accurately recall daily activity and trends in personal health. These practices suffer from the infrequency and generally short durations of visits. Since 2004, researchers at the Oregon Center for Aging and Technology (ORCATECH) at the Oregon Health and Science University have been working on developing technologies to transform this model. ORCATECH researchers have developed a system of continuous in-home monitoring using pervasive computing technologies that make it possible to more accurately track activities and behaviors and measure relevant intra-individual changes. We have installed a system of strategically placed sensors in over 480 homes and have been collecting data for up to 8 years. Using this continuous in-home monitoring system, ORCATECH researchers have collected data on multiple behaviors such as gait and mobility, sleep and activity patterns, medication adherence, and computer use. Patterns of intra-individual variation detected in each of these areas are used to predict outcomes such as low mood, loneliness, and cognitive function. These methods have the potential to improve the quality of patient health data and in turn patient care especially related to cognitive decline. Furthermore, the continuous real-world nature of the data may improve the efficiency and ecological validity of clinical intervention studies. PMID:26113819

Implementing CUAHSI and SWE observation data models in the long-term monitoring infrastructure TERENO

NASA Astrophysics Data System (ADS)

Klump, J. F.; Stender, V.; Schroeder, M.

2013-12-01

Terrestrial Environmental Observatories (TERENO) is an interdisciplinary and long-term research project spanning an Earth observation network across Germany. It includes four test sites within Germany from the North German lowlands to the Bavarian Alps and is operated by six research centers of the Helmholtz Association. The contribution by the participating research centers is organized as regional observatories. The challenge for TERENO and its observatories is to integrate all aspects of data management, data workflows, data modeling and visualizations into the design of a monitoring infrastructure. TERENO Northeast is one of the sub-observatories of TERENO and is operated by the German Research Centre for Geosciences GFZ in Potsdam. This observatory investigates geoecological processes in the northeastern lowland of Germany by collecting large amounts of environmentally relevant data. The success of long-term projects like TERENO depends on well-organized data management, data exchange between the partners involved and on the availability of the captured data. Data discovery and dissemination are facilitated not only through data portals of the regional TERENO observatories but also through a common spatial data infrastructure TEODOOR. TEODOOR bundles the data, provided by the different web services of the single observatories, and provides tools for data discovery, visualization and data access. The TERENO Northeast data infrastructure integrates data from more than 200 instruments and makes the data available through standard web services. Data are stored following the CUAHSI observation data model in combination with the 52° North Sensor Observation Service data model. The data model was implemented using the PostgreSQL/PostGIS DBMS. Especially in a long-term project, such as TERENO, care has to be taken in the data model. We chose to adopt the CUAHSI observational data model because it is designed to store observations and descriptive information (metadata) about the data values in combination with information about the sensor systems. Also the CUAHSI model is supported by a large and active international user community. The 52° North SOS data model can be modeled as a sub-set of the CUHASI data model. In our implementation the 52° North SWE data model is implemented as database views of the CUHASI model to avoid redundant data storage. An essential aspect in TERENO Northeast is the use of standard OGS web services to facilitate data exchange and interoperability. A uniform treatment of sensor data can be realized through OGC Sensor Web Enablement (SWE) which makes a number of standards and interface definitions available: Observation & Measurement (O&M) model for the description of observations and measurements, Sensor Model Language (SensorML) for the description of sensor systems, Sensor Observation Service (SOS) for obtaining sensor observations, Sensor Planning Service (SPS) for tasking sensors, Web Notification Service (WNS) for asynchronous dialogues and Sensor Alert Service (SAS) for sending alerts.

Sensors Umbra Package v 1.0

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

Oppel, Fred J.; Hart, Brian E.; Whitford, Gregg Douglas

2016-08-25

This package contains modules that model sensors in Umbra. There is a mix of modalities for both accumulating and tracking energy sensors: seismic, magnetic, and radiation. Some modules fuss information from multiple sensor types. Sensor devices (e.g., seismic sensors), detect objects such as people and vehicles that have sensor properties attached (e.g., seismic properties).

The Selection of an Appropriate Count Data Model for Modelling Health Insurance and Health Care Demand: Case of Indonesia

PubMed Central

Hidayat, Budi; Pokhrel, Subhash

2010-01-01

We apply several estimators to Indonesian household data to estimate the relationship between health insurance and the number of outpatient visits to public and private providers. Once endogeneity of insurance is taken into account, there is a 63 percent increase in the average number of public visits by the beneficiaries of mandatory insurance for civil servants. Individuals’ decisions to make first contact with private providers is affected by private insurance membership. However, insurance status does not make any difference for the number of future outpatient visits. PMID:20195429

Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter

PubMed Central

Chowdhury, Amor; Sarjaš, Andrej

2016-01-01

The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation. PMID:27649197

Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

PubMed

Chowdhury, Amor; Sarjaš, Andrej

2016-09-15

The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

Peer-to-peer model for the area coverage and cooperative control of mobile sensor networks

NASA Astrophysics Data System (ADS)

Tan, Jindong; Xi, Ning

2004-09-01

This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.

Associations between sugar-sweetened beverage consumption and fast-food restaurant frequency among adolescents and their friends.

PubMed

Bruening, Meg; MacLehose, Richard; Eisenberg, Marla E; Nanney, Marilyn S; Story, Mary; Neumark-Sztainer, Dianne

2014-01-01

To assess associations between adolescents and their friends with regard to sugar-sweetened beverage (SSB)/diet soda intake and fast-food (FF) restaurant visits. Population-based, cross-sectional survey study with direct measures from friends. Twenty Minneapolis/St Paul schools during 2009-2010. Adolescents (n = 2,043; mean age, 14.2 ± 1.9 years; 46.2% female; 80% non-white). Adolescent SSB/diet soda intake and FF visits. Generalized estimating equation logistic models were used to examine associations between adolescents' SSB/diet soda intake and FF visits and similar behaviors in nominated friends (friend groups and best friends). School-level (middle vs high school) interactions were assessed. Significant associations were found between adolescents and friends behaviors for each of the beverages assessed (P < .05), but they varied by friendship type and school level. Five of 6 models of FF visits (including all FF visits) were significantly associated (P < .05) among adolescents and their friends. Significant interactions by school level were present among adolescents' and friends' FF visits, with associations generally for high school participants compared with middle school participants (P < .05). Findings suggest that for many beverages and FF restaurant types, friends' behaviors are associated, especially FF visits for older adolescents. Nutrition education efforts may benefit by integrating knowledge of the impact of adolescents' friends on FF visits. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Associations between sugar-sweetened beverage consumption and fast food restaurant frequency among adolescents and their friends

PubMed Central

Bruening, Meg; MacLehose, Richard; Eisenberg, Marla E; Nanney, Marilyn S.; Story, Mary; Neumark-Sztainer, Dianne

2016-01-01

Objective To assess associations between adolescents and their friends with regard to sugar-sweetened beverage (SSB)/diet soda intake, and fast food (FF) restaurant visits. Design Population-based, cross-sectional survey study with direct measures from friends. Setting Twenty Minneapolis/St. Paul schools during 2009–2010. Participants Adolescents (n=2,043; mean age=14.2±1.9; 46.2% female; 80% non-white). Main outcome measures Adolescent SSB/diet soda intake and FF visits. Analysis Generalized estimating equation logistic models were used to examine associations between adolescents’ SSB/diet soda intake and FF visits and similar behaviors in nominated friends (friend groups, best friends). School-level (middle vs. high school) interactions were assessed. Results Significant associations were found between adolescents and friends behaviors for each of the beverages assessed (P<0.05), but varied by friendship type and school level. Five of six models of FF visits (including all FF visits) were significantly associated (P <0.05) among adolescents and their friends. Significant interactions by school level were present among adolescents’ and friends’ FF visits, with associations generally for high school participants compared to middle school participants (P <0.05). Conclusions and implications Findings suggest for many beverages and FF restaurant types, friends’ behaviors are associated, especially FF visits for older adolescents. Nutrition education efforts may benefit by integrating the knowledge of the impact of adolescents’ friends on FF visits. PMID:24735768

Evaluation of electrolytic tilt sensors for measuring model angle of attack in wind tunnel tests

NASA Technical Reports Server (NTRS)

Wong, Douglas T.

1992-01-01

The results of a laboratory evaluation of electrolytic tilt sensors as potential candidates for measuring model attitude or angle of attack in wind tunnel tests are presented. The performance of eight electrolytic tilt sensors was compared with that of typical servo accelerometers used for angle-of-attack measurements. The areas evaluated included linearity, hysteresis, repeatability, temperature characteristics, roll-on-pitch interaction, sensitivity to lead-wire resistance, step response time, and rectification. Among the sensors being evaluated, the Spectron model RG-37 electrolytic tilt sensors have the highest overall accuracy in terms of linearity, hysteresis, repeatability, temperature sensitivity, and roll sensitivity. A comparison of the sensors with the servo accelerometers revealed that the accuracy of the RG-37 sensors was on the average about one order of magnitude worse. Even though a comparison indicates that the cost of each tilt sensor is about one-third the cost of each servo accelerometer, the sensors are considered unsuitable for angle-of-attack measurements. However, the potential exists for other applications such as wind tunnel wall-attitude measurements where the errors resulting from roll interaction, vibration, and response time are less and sensor temperature can be controlled.

Persistence in the WFC3 IR Detector: Intrinsic Variability

NASA Astrophysics Data System (ADS)

Long, Knox S.; Baggett, Sylvia M.

2018-03-01

When the WFC3 IR detector is exposed to a bright source or sources, the sources can appear as afterimages in subsequent exposures, a phenomenon known as persistence. This can affect the science obtained with the IR channel. We have been involved in an effort to predict the brightness of the afterimages so that users can (at a minimum) flag the affected pixels and remove them from their analysis or (even better) subtract the afterimages from their science images to salvage the data. The ability of any model to remove afterimages depends on the degree to which persistence is the same for identical sets of exposures. We investigate possible time variability of persistence in the WFC3 detector using sets of (almost) identical visits comprised of single exposures of Omega Cen followed by a series of darks in which persistence is measured. We analyze 8 data sets, each consisting of two or three identical visits, with stimulus exposures between 49 and 1199 s, and find clear evidence of variability in several of the datasets in darks taken within 1000 s of the stimulus exposure. In most of the datasets, the difference in persistence for saturated pixels in the stimulus exposure is < 0.01 e-/s for darks taken 1000 s after the initial exposure. One of three 274-second visits has significantly more persistence than its two identical visits. Persistence in this visit was higher in all 4 detector quadrants. The persistence in all three visits is well modeled as a power law decay; the visit with higher persistence has a higher power law amplitude. There was nothing unusual about the observing conditions preceding and during each of these visits that can explain the discrepancy in persistence levels. Variation in persistence implies that: (1) Unless and until the source of the variability is understood, any persistence model for the WFC3 array will be limited in its ability to predict persistence in a single observation, and, (2) as a consequence, users should always carefully inspect the results of any attempt to subtract persistence from WFC3 IR data based on a model prediction.

Study protocol to assess the effectiveness and safety of a flexible family visitation model for delirium prevention in adult intensive care units: a cluster-randomised, crossover trial (The ICU Visits Study).

PubMed

Rosa, Regis Goulart; Falavigna, Maicon; Robinson, Caroline Cabral; da Silva, Daiana Barbosa; Kochhann, Renata; de Moura, Rafaela Moraes; Santos, Mariana Martins Siqueira; Sganzerla, Daniel; Giordani, Natalia Elis; Eugênio, Cláudia; Ribeiro, Tarissa; Cavalcanti, Alexandre Biasi; Bozza, Fernando; Azevedo, Luciano Cesar Pontes; Machado, Flávia Ribeiro; Salluh, Jorge Ibrain Figueira; Pellegrini, José Augusto Santos; Moraes, Rafael Barberena; Hochegger, Taís; Amaral, Alexandre; Teles, José Mario Meira; da Luz, Lucas Gobetti; Barbosa, Mirceli Goulart; Birriel, Daniella Cunha; Ferraz, Iris de Lima; Nobre, Vandack; Valentim, Helen Martins; Corrêa E Castro, Livia; Duarte, Péricles Almeida Delfino; Tregnago, Rogério; Barilli, Sofia Louise Santin; Brandão, Nilton; Giannini, Alberto; Teixeira, Cassiano

2018-04-13

Flexible intensive care unit (ICU) visiting hours have been proposed as a means to improve patient-centred and family-centred care. However, randomised trials evaluating the effects of flexible family visitation models (FFVMs) are scarce. This study aims to compare the effectiveness and safety of an FFVM versus a restrictive family visitation model (RFVM) on delirium prevention among ICU patients, as well as to analyse its potential effects on family members and ICU professionals. A cluster-randomised crossover trial involving adult ICU patients, family members and ICU professionals will be conducted. Forty medical-surgical Brazilian ICUs with RFVMs (<4.5 hours/day) will be randomly assigned to either an RFVM (visits according to local policies) or an FFVM (visitation during 12 consecutive hours per day) group at a 1:1 ratio. After enrolment and follow-up of 25 patients, each ICU will be switched over to the other visitation model, until 25 more patients per site are enrolled and followed. The primary outcome will be the cumulative incidence of delirium among ICU patients, measured twice a day using the Confusion Assessment Method for the ICU. Secondary outcome measures will include daily hazard of delirium, ventilator-free days, any ICU-acquired infections, ICU length of stay and hospital mortality among the patients; symptoms of anxiety and depression and satisfaction among the family members; and prevalence of burnout symptoms among the ICU professionals. Tertiary outcomes will include need for antipsychotic agents and/or mechanical restraints, coma-free days, unplanned loss of invasive devices and ICU-acquired pneumonia, urinary tract infection or bloodstream infection among the patients; self-perception of involvement in patient care among the family members; and satisfaction among the ICU professionals. The study protocol has been approved by the research ethics committee of all participant institutions. We aim to disseminate the findings through conferences and peer-reviewed journals. NCT02932358. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

USGS Publications Warehouse

David, Hamilton P; Carey, Cayelan C.; Arvola, Lauri; Arzberger, Peter; Brewer, Carol A.; Cole, Jon J; Gaiser, Evelyn; Hanson, Paul C.; Ibelings, Bas W; Jennings, Eleanor; Kratz, Tim K; Lin, Fang-Pang; McBride, Christopher G.; de Motta Marques, David; Muraoka, Kohji; Nishri, Ami; Qin, Boqiang; Read, Jordan S.; Rose, Kevin C.; Ryder, Elizabeth; Weathers, Kathleen C.; Zhu, Guangwei; Trolle, Dennis; Brookes, Justin D

2014-01-01

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

Structural Stability Monitoring of a Physical Model Test on an Underground Cavern Group during Deep Excavations Using FBG Sensors.

PubMed

Li, Yong; Wang, Hanpeng; Zhu, Weishen; Li, Shucai; Liu, Jian

2015-08-31

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction.

Structural Stability Monitoring of a Physical Model Test on an Underground Cavern Group during Deep Excavations Using FBG Sensors

PubMed Central

Li, Yong; Wang, Hanpeng; Zhu, Weishen; Li, Shucai; Liu, Jian

2015-01-01

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction. PMID:26404287

Effect of ambient temperature on emergency department visits in Shanghai, China: a time series study.

PubMed

Zhang, Yue; Yan, Chenyang; Kan, Haidong; Cao, Junshan; Peng, Li; Xu, Jianming; Wang, Weibing

2014-11-25

Many studies have examined the association between ambient temperature and mortality. However, less evidence is available on the temperature effects on gender- and age-specific emergency department visits, especially in developing countries. In this study, we examined the short-term effects of daily ambient temperature on emergency department visits (ED visits) in Shanghai. Daily ED visits and daily ambient temperatures between January 2006 and December 2011 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) was used to examine the associations between ambient temperature and gender- and age-specific ED visits. A moving average lag model was used to evaluate the lag effects of temperature on ED visits. Low temperature was associated with an overall 2.76% (95% confidence interval (CI): 1.73 to 3.80) increase in ED visits per 1°C decrease in temperature at Lag1 day, 2.03% (95% CI: 1.04 to 3.03) and 2.45% (95% CI: 1.40 to 3.52) for males and females. High temperature resulted in an overall 1.78% (95% CI: 1.05 to 2.51) increase in ED visits per 1°C increase in temperature on the same day, 1.81% (95% CI: 1.08 to 2.54) among males and 1.75% (95% CI: 1.03 to 2.49) among females. The cold effect appeared to be more acute among younger people aged <45 years, whereas the effects were consistent on individuals aged ≥65 years. In contrast, the effects of high temperature were relatively consistent over all age groups. These findings suggest a significant association between ambient temperature and ED visits in Shanghai. Both cold and hot temperatures increased the relative risk of ED visits. This knowledge has the potential to advance prevention efforts targeting weather-sensitive conditions.

Affordable and personalized lighting using inverse modeling and virtual sensors

NASA Astrophysics Data System (ADS)

Basu, Chandrayee; Chen, Benjamin; Richards, Jacob; Dhinakaran, Aparna; Agogino, Alice; Martin, Rodney

2014-03-01

Wireless sensor networks (WSN) have great potential to enable personalized intelligent lighting systems while reducing building energy use by 50%-70%. As a result WSN systems are being increasingly integrated in state-ofart intelligent lighting systems. In the future these systems will enable participation of lighting loads as ancillary services. However, such systems can be expensive to install and lack the plug-and-play quality necessary for user-friendly commissioning. In this paper we present an integrated system of wireless sensor platforms and modeling software to enable affordable and user-friendly intelligent lighting. It requires ⇠ 60% fewer sensor deployments compared to current commercial systems. Reduction in sensor deployments has been achieved by optimally replacing the actual photo-sensors with real-time discrete predictive inverse models. Spatially sparse and clustered sub-hourly photo-sensor data captured by the WSN platforms are used to develop and validate a piece-wise linear regression of indoor light distribution. This deterministic data-driven model accounts for sky conditions and solar position. The optimal placement of photo-sensors is performed iteratively to achieve the best predictability of the light field desired for indoor lighting control. Using two weeks of daylight and artificial light training data acquired at the Sustainability Base at NASA Ames, the model was able to predict the light level at seven monitored workstations with 80%-95% accuracy. We estimate that 10% adoption of this intelligent wireless sensor system in commercial buildings could save 0.2-0.25 quads BTU of energy nationwide.

A sensor simulation framework for the testing and evaluation of external hazard monitors and integrated alerting and notification functions

NASA Astrophysics Data System (ADS)

Uijt de Haag, Maarten; Venable, Kyle; Bezawada, Rajesh; Adami, Tony; Vadlamani, Ananth K.

2009-05-01

This paper discusses a sensor simulator/synthesizer framework that can be used to test and evaluate various sensor integration strategies for the implementation of an External Hazard Monitor (EHM) and Integrated Alerting and Notification (IAN) function as part of NASA's Integrated Intelligent Flight Deck (IIFD) project. The IIFD project under the NASA's Aviation Safety program "pursues technologies related to the flight deck that ensure crew workload and situational awareness are both safely optimized and adapted to the future operational environment as envisioned by NextGen." Within the simulation framework, various inputs to the IIFD and its subsystems, the EHM and IAN, are simulated, synthesized from actual collected data, or played back from actual flight test sensor data. Sensors and avionics included in this framework are TCAS, ADS-B, Forward-Looking Infrared, Vision cameras, GPS, Inertial navigators, EGPWS, Laser Detection and Ranging sensors, altimeters, communication links with ATC, and weather radar. The framework is implemented in Simulink, a modeling language developed by The Mathworks. This modeling language allows for test and evaluation of various sensor and communication link configurations as well as the inclusion of feedback from the pilot on the performance of the aircraft. Specifically, this paper addresses the architecture of the simulator, the sensor model interfaces, the timing and database (environment) aspects of the sensor models, the user interface of the modeling environment, and the various avionics implementations.

An articulated predictive model for fluid-free artificial basilar membrane as broadband frequency sensor

NASA Astrophysics Data System (ADS)

Ahmed, Riaz; Banerjee, Sourav

2018-02-01

In this article, an extremely versatile predictive model for a newly developed Basilar meta-Membrane (BM2) sensors is reported with variable engineering parameters that contribute to it's frequency selection capabilities. The predictive model reported herein is for advancement over existing method by incorporating versatile and nonhomogeneous (e.g. functionally graded) model parameters that could not only exploit the possibilities of creating complex combinations of broadband frequency sensors but also explain the unique unexplained physical phenomenon that prevails in BM2, e.g. tailgating waves. In recent years, few notable attempts were made to fabricate the artificial basilar membrane, mimicking the mechanics of the human cochlea within a very short range of frequencies. To explain the operation of these sensors a few models were proposed. But, we fundamentally argue the "fabrication to explanation" approach and proposed the model driven predictive design process for the design any (BM2) as broadband sensors. Inspired by the physics of basilar membrane, frequency domain predictive model is proposed where both the material and geometrical parameters can be arbitrarily varied. Broadband frequency is applicable in many fields of science, engineering and technology, such as, sensors for chemical, biological and acoustic applications. With the proposed model, which is three times faster than its FEM counterpart, it is possible to alter the attributes of the selected length of the designed sensor using complex combinations of model parameters, based on target frequency applications. Finally, the tailgating wave peaks in the artificial basilar membranes that prevails in the previously reported experimental studies are also explained using the proposed model.

Method of Forming a Hot Film Sensor System on a Model

NASA Technical Reports Server (NTRS)

Tran, Sang Q. (Inventor)

1998-01-01

A method of forming a hot film sensor directly on a model is provided. A polyimide solution is sprayed onto the model. The model so sprayed is then heated in air. The steps of spraying and heating are repeated until a polyimide film of desired thickness is achieved on the model. The model with the polyimide film thereon is then thoroughly dried in air. One or more hot film sensors and corresponding electrical conducting leads are then applied directly onto the polyimide film.

Timing and adequate attendance of antenatal care visits among women in Ethiopia

PubMed Central

Bishwajit, Ghose; Ekholuenetale, Michael; Shah, Vaibhav; Kadio, Bernard; Udenigwe, Ogochukwu

2017-01-01

Introduction Although ANC services are increasingly available to women in low and middle-income countries, their inadequate use persists. This suggests a misalignment between aims of the services and maternal beliefs and circumstances. Owing to the dearth of studies examining the timing and adequacy of content of care, this current study aims to investigate the timing and frequency of ANC visits in Ethiopia. Methods Data was obtained from the nationally representative 2011 Ethiopian Demographic and Health Survey (EDHS) which used a two-stage cluster sampling design to provide estimates for the health and demographic variables of interest for the country. Our study focused on a sample of 10,896 women with history of at least one childbirth event. Percentages of timing and adequacy of ANC visits were conducted across the levels of selected factors. Variables which were associated at 5% significance level were examined in the multivariable logistic regression model for association between timing and frequency of ANC visits and the explanatory variables while controlling for covariates. Furthermore, we presented the approach to estimate marginal effects involving covariate-adjusted logistic regression with corresponding 95%CI of delayed initiation of ANC visits and inadequate ANC attendance. The method used involved predicted probabilities added up to a weighted average showing the covariate distribution in the population. Results Results indicate that 66.3% of women did not use ANC at first trimester and 22.3% had ANC less than 4 visits. The results of this study were unique in that the association between delayed ANC visits and adequacy of ANC visits were examined using multivariable logistic model and the marginal effects using predicted probabilities. Results revealed that older age interval has higher odds of inadequate ANC visits. More so, type of place of residence was associated with delayed initiation of ANC visits, with rural women having the higher odds of delayed initiation of ANC visits (OR = 1.65; 95%CI: 1.26–2.18). However, rural women had 44% reduction in the odds of having inadequate ANC visits. In addition, multi-parity showed higher odds of delayed initiation of ANC visit when compared to the primigravida (OR = 2.20; 95%CI: 1.07–2.69). On the contrary, there was 36% reduction in the odds of multigravida having inadequate ANC visits when compared to the women who were primigravida. There were higher odds of inadequacy in ANC visits among women who engaged in sales/business, agriculture, skilled manual and other jobs when compared to women who currently do not work, after adjusting for covariates. From the predictive margins, assuming the distribution of all covariates remained the same among respondents, but everyone was aged 15–19 years, we would expect 71.8% delayed initiation of ANC visit. If everyone was aged 20-24years, 73.4%; 25-29years, 66.5%; 30-34years, 64.8%; 35-39years, 65.6%; 40-44years, 59.6% and 45-49years, we would expect 70.1% delayed initiation of ANC visit. If instead the distribution of age was as observed and for other covariates remained the same among respondents, but no respondent lived in the rural, we would expect about 61.4% delayed initiation of ANC visit; if however, everyone lived in the rural, and we would expect 71.6% delayed initiation in ANC visit. Model III revealed the predictive margins of all factors examined for delayed initiation for ANC visits, while Model IV presented the predictive marginal effects of the determinants of adequacy of ANC visits. Conclusion The precise mechanism by which these factors affect ANC visits remain blurred at best. There may be factors on the demand side like the women’s empowerment, financial support of the husband, knowledge of ANC visits in the context of timing, frequency and the expectations of ANC visits might be mediating the effects through the factors found associated in this study. Supply side factors like the quality of ANC services, skilled staff, and geographic location of the health centers also mediate their effects through the highlighted factors. Irrespective of the knowledge about the precise mechanism of action, policy makers could focus on improving women’s empowerment, improving women’s education, reducing wealth inequity and facilitating improved utilization of ANC through modifications on the supply side factors such as geographic location and focus on hard to reach women. PMID:28922383

Disaster as an Agent of Change for New Educational Models

ERIC Educational Resources Information Center

Bjorn-Andersen, Niels

2011-01-01

This "Postcard" reports how the earthquake on Tuesday, 22 February 2011 in Christchurch, New Zealand, forced a visiting professor to transform his educational model in one week. It was the first week of the academic year 2011 for the University of Canterbury--and the author's first week in New Zealand. As a Visiting Erskine Fellow at the…

Patient Perceptions of Telehealth Primary Care Video Visits.

PubMed

Powell, Rhea E; Henstenburg, Jeffrey M; Cooper, Grace; Hollander, Judd E; Rising, Kristin L

2017-05-01

Telehealth is a care delivery model that promises to increase the flexibility and reach of health services. Our objective is to describe patient experiences with video visits performed with their established primary care clinicians. We constructed semistructured, in-depth qualitative interviews with adult patients following video visits with their primary care clinicians at a single academic medical center. Data were analyzed with a content analysis approach. Of 32 eligible patients, 19 were successfully interviewed. All patients reported overall satisfaction with video visits, with the majority interested in continuing to use video visits as an alternative to in-person visits. The primary benefits cited were convenience and decreased costs. Some patients felt more comfortable with video visits than office visits and expressed a preference for receiving future serious news via video visit, because they could be in their own supportive environment. Primary concerns with video visits were privacy, including the potential for work colleagues to overhear conversations, and questions about the ability of the clinician to perform an adequate physical examination. Primary care video visits are acceptable in a variety of situations. Patients identified convenience, efficiency, communication, privacy, and comfort as domains that are potentially important to consider when assessing video visits vs in-person encounters. Future studies should explore which patients and conditions are best suited for video visits. © 2017 Annals of Family Medicine, Inc.

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks.

PubMed

Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei

2017-01-13

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator's mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost.

A New Calibration Method for Commercial RGB-D Sensors.

PubMed

Darwish, Walid; Tang, Shenjun; Li, Wenbin; Chen, Wu

2017-05-24

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter‑level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges.

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

Mou, J.I.; King, C.

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess themore » status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.« less

1st Order Modeling of a SAW Delay Line using MathCAD(Registered)

NASA Technical Reports Server (NTRS)

Wilson, William C.; Atkinson, Gary M.

2007-01-01

To aid in the development of SAW sensors for Integrated Vehicle Health Monitoring applications, a first order model of a SAW Delay line has been created using MathCadA. The model implements the Impulse Response method to calculate the frequency response, impedance, and insertion loss. This paper presents the model and the results from the model for a SAW delay line design. Integrated Vehicle Health Monitoring (IVHM) of aerospace vehicles requires rugged sensors having reduced volume, mass, and power that can be used to measure a variety of phenomena. Wireless systems are preferred when retro-fitting sensors onto existing vehicles [1]. Surface Acoustic Wave (SAW) devices are capable of sensing: temperature, pressure, strain, chemical species, mass loading, acceleration, and shear stress. SAW technology is low cost, rugged, lightweight, and extremely low power. Passive wireless sensors have been developed using SAW technology. For these reasons new SAW sensors are being investigated for aerospace applications.

Parametric modeling of wideband piezoelectric polymer sensors: Design for optoacoustic applications

NASA Astrophysics Data System (ADS)

Fernández Vidal, A.; Ciocci Brazzano, L.; Matteo, C. L.; Sorichetti, P. A.; González, M. G.

2017-09-01

In this work, we present a three-dimensional model for the design of wideband piezoelectric polymer sensors which includes the geometry and the properties of the transducer materials. The model uses FFT and numerical integration techniques in an explicit, semi-analytical approach. To validate the model, we made electrical and mechanical measurements on homemade sensors for optoacoustic applications. Each device was implemented using a polyvinylidene fluoride thin film piezoelectric polymer with a thickness of 25 μm. The sensors had detection areas in the range between 0.5 mm2 and 35 mm2 and were excited by acoustic pressure pulses of 5 ns (FWHM) from a source with a diameter around 10 μm. The experimental data obtained from the measurements agree well with the model results. We discuss the relative importance of the sensor design parameters for optoacoustic applications and we provide guidelines for the optimization of devices.

Parametric modeling of wideband piezoelectric polymer sensors: Design for optoacoustic applications.

PubMed

Fernández Vidal, A; Ciocci Brazzano, L; Matteo, C L; Sorichetti, P A; González, M G

2017-09-01

In this work, we present a three-dimensional model for the design of wideband piezoelectric polymer sensors which includes the geometry and the properties of the transducer materials. The model uses FFT and numerical integration techniques in an explicit, semi-analytical approach. To validate the model, we made electrical and mechanical measurements on homemade sensors for optoacoustic applications. Each device was implemented using a polyvinylidene fluoride thin film piezoelectric polymer with a thickness of 25 μm. The sensors had detection areas in the range between 0.5 mm 2 and 35 mm 2 and were excited by acoustic pressure pulses of 5 ns (FWHM) from a source with a diameter around 10 μm. The experimental data obtained from the measurements agree well with the model results. We discuss the relative importance of the sensor design parameters for optoacoustic applications and we provide guidelines for the optimization of devices.

Attitude Estimation for Large Field-of-View Sensors

NASA Technical Reports Server (NTRS)

Cheng, Yang; Crassidis, John L.; Markley, F. Landis

2005-01-01

The QUEST measurement noise model for unit vector observations has been widely used in spacecraft attitude estimation for more than twenty years. It was derived under the approximation that the noise lies in the tangent plane of the respective unit vector and is axially symmetrically distributed about the vector. For large field-of-view sensors, however, this approximation may be poor, especially when the measurement falls near the edge of the field of view. In this paper a new measurement noise model is derived based on a realistic noise distribution in the focal-plane of a large field-of-view sensor, which shows significant differences from the QUEST model for unit vector observations far away from the sensor boresight. An extended Kalman filter for attitude estimation is then designed with the new measurement noise model. Simulation results show that with the new measurement model the extended Kalman filter achieves better estimation performance using large field-of-view sensor observations.

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

The Association Between Internet Use and Ambulatory Care-Seeking Behaviors in Taiwan: A Cross-Sectional Study.

PubMed

Hsieh, Ronan Wenhan; Chen, Likwang; Chen, Tsung-Fu; Liang, Jyh-Chong; Lin, Tzu-Bin; Chen, Yen-Yuan; Tsai, Chin-Chung

2016-12-07

Compared with the traditional ways of gaining health-related information from newspapers, magazines, radio, and television, the Internet is inexpensive, accessible, and conveys diverse opinions. Several studies on how increasing Internet use affected outpatient clinic visits were inconclusive. The objective of this study was to examine the role of Internet use on ambulatory care-seeking behaviors as indicated by the number of outpatient clinic visits after adjusting for confounding variables. We conducted this study using a sample randomly selected from the general population in Taiwan. To handle the missing data, we built a multivariate logistic regression model for propensity score matching using age and sex as the independent variables. The questionnaires with no missing data were then included in a multivariate linear regression model for examining the association between Internet use and outpatient clinic visits. We included a sample of 293 participants who answered the questionnaire with no missing data in the multivariate linear regression model. We found that Internet use was significantly associated with more outpatient clinic visits (P=.04). The participants with chronic diseases tended to make more outpatient clinic visits (P<.01). The inconsistent quality of health-related information obtained from the Internet may be associated with patients' increasing need for interpreting and discussing the information with health care professionals, thus resulting in an increasing number of outpatient clinic visits. In addition, the media literacy of Web-based health-related information seekers may also affect their ambulatory care-seeking behaviors, such as outpatient clinic visits. ©Ronan Wenhan Hsieh, Likwang Chen, Tsung-Fu Chen, Jyh-Chong Liang, Tzu-Bin Lin, Yen-Yuan Chen, Chin-Chung Tsai. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.12.2016.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

PubMed

Sonter, Laura J; Watson, Keri B; Wood, Spencer A; Ricketts, Taylor H

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

Effects of room temperature aging on two cryogenic temperature sensor models used in aerospace applications

NASA Astrophysics Data System (ADS)

Courts, S. Scott; Krause, John

2012-06-01

Cryogenic temperature sensors used in aerospace applications are typically procured far in advance of the mission launch date. Depending upon the program, the temperature sensors may be stored at room temperature for extended periods as installation and groundbased testing can take years before the actual flight. The effects of long term storage at room temperature are sometimes approximated by the use of accelerated aging at temperatures well above room temperature, but this practice can yield invalid results as the sensing material and/or electrical contacting method can be increasingly unstable with higher temperature exposure. To date, little data are available on the effects of extended room temperature aging on sensors commonly used in aerospace applications. This research examines two such temperature sensors models - the Lake Shore Cryotronics, Inc. model CernoxTM and DT-670-SD temperature sensors. Sample groups of each model type have been maintained for ten years or longer with room temperature storage between calibrations. Over an eighteen year period, the CernoxTM temperature sensors exhibited a stability of better than ±20 mK for T<30 K and better than ±0.1% of temperature for T>30 K. Over a ten year period the model DT-670-SD sensors exhibited a stability of better than ±140 mK for T<25 K and better than ±75 mK for T>25 K.

Corporate working in health visiting: a concept analysis.

PubMed

Houston, A M; Clifton, J

2001-05-01

The aim of this paper is to examine individualized health visiting care and compare it to corporate working within a consensual management style. Corporate working has been discussed and used in many different ways since the idea first came to light at the end of the 1980s. Resource management makes it an appealing model, however, analysing how corporate working functions in the practice setting reveals the complexity of this method of service provision. This paper is based on a method of practice developed by health visitors in Haywards Heath, West Sussex, who implemented the process. The article examines individualized health visiting care and compares it to corporate working within a consensual management style. Important in this analysis are the elements of reflexivity, active listening, reflection and the application of 'praxis' within the corporate caseload approach. Rogers' evolutionary concept model was used to illuminate and explain the different ways of delivering the health visiting service. There are benefits in working corporately: shared workload, increased professional support and improved accountability. Alongside the integrated supervision of this model is the opportunity offered to practitioners to innovate. This offsets any initial difficulty experienced in setting up this method and makes it a worthwhile change of style in health visiting practice. Improved service delivery, enhanced professional growth and increased opportunity for public health work can be demonstrated as outcomes of this model. For professionals this method may prevent 'burn-out', enhance practice and increase innovation in health visiting practice. Using this method as a blueprint, practitioners can develop their own style of corporate working that offers a service that is equitable, proactive, efficient and accessible to clients.

Impact of a group-based model of disease management for headache.

PubMed

Maizels, Morris; Saenz, Valerie; Wirjo, Jonathan

2003-06-01

To assess the impact of a group-based model of disease management for patients with headache. Despite advances in the acute and preventive treatment of migraine, many patients with headache remain misdiagnosed and undertreated. Models of care that incorporate principles of disease management may improve headache care. This was a prospective, open-label, observational study. Patients with headache were referred by physicians or identified from emergency department records. Patients attended a group session led by a registered nurse practitioner, and later had follow-up consultation. Charts and computer records were reviewed to document triptan costs and headache-related visits for 6 months before and after the intervention. Changes in headache frequency and severity were assessed. Triptan costs for 264 patients and chart review for 250 were available. Six-month triptan costs increased $5423 US dollars(19%), headache-related visits were reduced by 32%, and headache-related emergency department visits were reduced by 49%. Severe headache frequency was reduced in 62 (86%) of 72 patients who initially had severe headaches more than 2 days per week. Patients identified by emergency department screening accounted for 21% of the study group, 31% of the baseline triptan costs, and 46% of the baseline visits. For the entire study group, reduced visits yielded a net savings of $18,757 US dollars despite increased triptan costs. Implementation of this group-based model produced a reduction in emergency department and clinic visits, significant clinical improvement, a small increase in pharmacy costs, and overall cost reduction. The greatest improvement in each outcome measure was seen in patients most severely afflicted at baseline. Our results suggest that the principles of disease management may be applied effectively to a headache population, with a positive financial impact on a managed care organization.

Health Monitoring for Airframe Structural Characterization

NASA Technical Reports Server (NTRS)

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

Long-term screening for sleep apnoea in paced patients: preliminary assessment of a novel patient management flowchart by using automatic pacemaker indexes and sleep lab polygraphy.

PubMed

Aimé, Ezio; Rovida, Marina; Contardi, Danilo; Ricci, Cristian; Gaeta, Maddalena; Innocenti, Ester; Cabral Tantchou-Tchoumi, Jacques

2014-10-01

The primary aim of this pilot study was to prospectively assess a flowchart to screen and diagnose paced patients (pts) affected by sleep apnoeas, by crosschecking indexes derived from pacemakers (minute ventilation sensor on-board) with Sleep-Lab Polygraphy (PG) outcomes. Secondarily, "smoothed" long-term pacemaker indexes (all the information between two consecutive follow-up visits) have been retrospectively compared vs. standard short-term pacemaker indexes (last 24h) at each follow-up (FU) visit, to test their correlation and diagnostic concordance. Data from long-term FU of 61 paced pts were collected. At each visit, the standard short-term apnoea+hypopnoea (PM_AHI) index was retrieved from the pacemaker memory. Patients showing PM_AHI ≥ 30 at least once during FU were proposed to undergo a PG for diagnostic confirmation. Smoothed pacemaker (PM_SAHI) indexes were calculated by averaging the overall number of apnoeas/hypopnoeas over the period between two FU visits, and retrospectively compared with standard PM_AHI. Data were available from 609 consecutive visits (overall 4.64 ± 1.78 years FU). PM_AHI indexes were positive during FU in 40/61 pts (65.6%); 26/40 pts (65%) accepted to undergo a PG recording; Sleep-Lab confirmed positivity in 22/26 pts (84.6% positive predictive value for PM_AHI). A strong correlation (r=0.73) and a high level of concordance were found between smoothed and standard indexes (multivariate analysis, Cohen's-k and Z-score tests). Pacemaker-derived indexes may help in screening paced pts potentially affected by sleep apnoeas. Long-term "smoothed" apnoea indexes could improve the accuracy of pacemaker screening capability, even though this hypothesis must be prospectively confirmed by larger studies. Copyright © 2014 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

A Smart Sensor Web for Ocean Observation: Integrated Acoustics, Satellite Networking, and Predictive Modeling

NASA Astrophysics Data System (ADS)

Arabshahi, P.; Chao, Y.; Chien, S.; Gray, A.; Howe, B. M.; Roy, S.

2008-12-01

In many areas of Earth science, including climate change research, there is a need for near real-time integration of data from heterogeneous and spatially distributed sensors, in particular in-situ and space- based sensors. The data integration, as provided by a smart sensor web, enables numerous improvements, namely, 1) adaptive sampling for more efficient use of expensive space-based sensing assets, 2) higher fidelity information gathering from data sources through integration of complementary data sets, and 3) improved sensor calibration. The specific purpose of the smart sensor web development presented here is to provide for adaptive sampling and calibration of space-based data via in-situ data. Our ocean-observing smart sensor web presented herein is composed of both mobile and fixed underwater in-situ ocean sensing assets and Earth Observing System (EOS) satellite sensors providing larger-scale sensing. An acoustic communications network forms a critical link in the web between the in-situ and space-based sensors and facilitates adaptive sampling and calibration. After an overview of primary design challenges, we report on the development of various elements of the smart sensor web. These include (a) a cable-connected mooring system with a profiler under real-time control with inductive battery charging; (b) a glider with integrated acoustic communications and broadband receiving capability; (c) satellite sensor elements; (d) an integrated acoustic navigation and communication network; and (e) a predictive model via the Regional Ocean Modeling System (ROMS). Results from field experiments, including an upcoming one in Monterey Bay (October 2008) using live data from NASA's EO-1 mission in a semi closed-loop system, together with ocean models from ROMS, are described. Plans for future adaptive sampling demonstrations using the smart sensor web are also presented.

Soft sensor for real-time cement fineness estimation.

PubMed

Stanišić, Darko; Jorgovanović, Nikola; Popov, Nikola; Čongradac, Velimir

2015-03-01

This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.

PubMed

Biagi, Lyvia; Ramkissoon, Charrise M; Facchinetti, Andrea; Leal, Yenny; Vehi, Josep

2017-06-12

Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor.

Impact of diffuse large B-cell lymphoma on visits to different provider specialties among elderly Medicare beneficiaries: challenges for care coordination.

PubMed

Garg, Rahul; Sambamoorthi, Usha; Tan, Xi; Basu, Soumit K; Haggerty, Treah; Kelly, Kimberly M

2018-01-23

Newly diagnosed diffuse large B-cell lymphoma (DLBCL) can pose significant challenges to care coordination. We utilized a social-ecological model to understand the impact of DLBCL diagnosis on visits to primary care providers (PCPs) and specialists, a key component of care coordination, over a 3-year period of cancer diagnosis and treatment. We used hurdle models and multivariable logistic regression with the Surveillance Epidemiology and End Result-Medicare linked dataset to analyze visits to PCPs and specialists by DLBCL patients (n = 5,455) compared with noncancer patients (n = 14,770). DLBCL patients were more likely to visit PCPs (adjusted odds ratio, AOR [95% confidence interval, CI]: 1.25 [1.18, 1.31]) and had greater number of visits to PCPs (β, SE: 0.384, -0.014) than noncancer patients. Further, DLBCL patients were more likely to have any visit to cardiologists (AOR [95% CI]: 1.40 [1.32, 1.47]), endocrinologists (1.43, [1.21, 1.70]), and pulmonologists (1.51 [1.36, 1.67]) than noncancer patients. Among DLBCL patients, the number of PCP visits markedly increased during the treatment period compared with the baseline period (β, SE: 0.491, -0.028) and then decreased to baseline levels (-0.464, -0.022). Visits to PCPs and specialists were much more frequent for DLBCL patients than noncancer patients, which drastically increased during the DLBCL treatment period for chronic care. More chronic conditions, treatment side effects, and frequent testing may have increased visits to PCPs and specialists. Interventions to improve care coordination may need to target the DLBCL treatment period, when patients are most vulnerable to poor care coordination. © The Society of Behavioral Medicine 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Using sensors to measure activity in people with stroke.

PubMed

Fulk, George D; Sazonov, Edward

2011-01-01

The purpose of this study was to determine the ability of a novel shoe-based sensor that uses accelerometers, pressure sensors, and pattern recognition with a support vector machine (SVM) to accurately identify sitting, standing, and walking postures in people with stroke. Subjects with stroke wore the shoe-based sensor while randomly assuming 3 main postures: sitting, standing, and walking. A SVM classifier was used to train and validate the data to develop individual and group models, which were tested for accuracy, recall, and precision. Eight subjects participated. Both individual and group models were able to accurately identify the different postures (99.1% to 100% individual models and 76.9% to 100% group models). Recall and precision were also high for both individual (0.99 to 1.00) and group (0.82 to 0.99) models. The unique combination of accelerometer and pressure sensors built into the shoe was able to accurately identify postures. This shoe sensor could be used to provide accurate information on community performance of activities in people with stroke as well as provide behavioral enhancing feedback as part of a telerehabilitation intervention.

Approach to Privacy-Preserve Data in Two-Tiered Wireless Sensor Network Based on Linear System and Histogram

NASA Astrophysics Data System (ADS)

Dang, Van H.; Wohlgemuth, Sven; Yoshiura, Hiroshi; Nguyen, Thuc D.; Echizen, Isao

Wireless sensor network (WSN) has been one of key technologies for the future with broad applications from the military to everyday life [1,2,3,4,5]. There are two kinds of WSN model models with sensors for sensing data and a sink for receiving and processing queries from users; and models with special additional nodes capable of storing large amounts of data from sensors and processing queries from the sink. Among the latter type, a two-tiered model [6,7] has been widely adopted because of its storage and energy saving benefits for weak sensors, as proved by the advent of commercial storage node products such as Stargate [8] and RISE. However, by concentrating storage in certain nodes, this model becomes more vulnerable to attack. Our novel technique, called zip-histogram, contributes to solving the problems of previous studies [6,7] by protecting the stored data's confidentiality and integrity (including data from the sensor and queries from the sink) against attackers who might target storage nodes in two-tiered WSNs.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Using URIs to effectively transmit sensor data and metadata

NASA Astrophysics Data System (ADS)

Kokkinaki, Alexandra; Buck, Justin; Darroch, Louise; Gardner, Thomas

2017-04-01

Autonomous ocean observation is massively increasing the number of sensors in the ocean. Accordingly, the continuing increase in datasets produced, makes selecting sensors that are fit for purpose a growing challenge. Decision making on selecting quality sensor data, is based on the sensor's metadata, i.e. manufacturer specifications, history of calibrations etc. The Open Geospatial Consortium (OGC) has developed the Sensor Web Enablement (SWE) standards to facilitate integration and interoperability of sensor data and metadata. The World Wide Web Consortium (W3C) Semantic Web technologies enable machine comprehensibility promoting sophisticated linking and processing of data published on the web. Linking the sensor's data and metadata according to the above-mentioned standards can yield practical difficulties, because of internal hardware bandwidth restrictions and a requirement to constrain data transmission costs. Our approach addresses these practical difficulties by uniquely identifying sensor and platform models and instances through URIs, which resolve via content negotiation to either OGC's sensor meta language, sensorML or W3C's Linked Data. Data transmitted by a sensor incorporate the sensor's unique URI to refer to its metadata. Sensor and platform model URIs and descriptions are created and hosted by the British Oceanographic Data Centre (BODC) linked systems service. The sensor owner creates the sensor and platform instance URIs prior and during sensor deployment, through an updatable web form, the Sensor Instance Form (SIF). SIF enables model and instance URI association but also platform and sensor linking. The use of URIs, which are dynamically generated through the SIF, offers both practical and economical benefits to the implementation of SWE and Linked Data standards in near real time systems. Data can be linked to metadata dynamically in-situ while saving on the costs associated to the transmission of long metadata descriptions. The transmission of short URIs also enables the implementation of standards on systems where it is impractical, such as legacy hardware.

Non-Traumatic Dental Condition-Related Emergency Department Visits and Associated Costs for Children and Adults with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Nakao, Sy; Scott, JoAnna M.; Masterson, Erin E.; Chi, Donald L.

2015-01-01

We analyzed 2010 US National Emergency Department Sample data and ran regression models to test the hypotheses that individuals with ASD are more likely to have non-traumatic dental condition (NTDC)-related emergency department (ED) visits and to incur greater costs for these visits than those without ASD. There were nearly 2.3 million…

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

Multiple Fan-Beam Optical Tomography: Modelling Techniques

PubMed Central

Rahim, Ruzairi Abdul; Chen, Leong Lai; San, Chan Kok; Rahiman, Mohd Hafiz Fazalul; Fea, Pang Jon

2009-01-01

This paper explains in detail the solution to the forward and inverse problem faced in this research. In the forward problem section, the projection geometry and the sensor modelling are discussed. The dimensions, distributions and arrangements of the optical fibre sensors are determined based on the real hardware constructed and these are explained in the projection geometry section. The general idea in sensor modelling is to simulate an artificial environment, but with similar system properties, to predict the actual sensor values for various flow models in the hardware system. The sensitivity maps produced from the solution of the forward problems are important in reconstructing the tomographic image. PMID:22291523

Acute effects of air pollution on respiratory disease mortalities and outpatients in Southeastern China.

PubMed

Mo, Zhe; Fu, Qiuli; Zhang, Lifang; Lyu, Danni; Mao, Guangming; Wu, Lizhi; Xu, Peiwei; Wang, Zhifang; Pan, Xuejiao; Chen, Zhijian; Wang, Xiaofeng; Lou, Xiaoming

2018-02-22

The objective of this study was to investigate the potential association between air pollutants and respiratory diseases (RDs). Generalized additive models were used to analyze the effect of air pollutants on mortalities or outpatient visits. The average concentrations of air pollutants in Hangzhou (HZ) were 1.6-2.8 times higher than those in Zhoushan (ZS), except for O 3 . In a single pollutant model, the increased concentrations of PM 2.5 , NO 2 , and SO 2 were strongly associated with deaths caused by RD in HZ, while PM 2.5 and O 3 were associated with deaths caused by RD in ZS. All air pollutants (PM 2.5 , NO 2 , SO 2 , and O 3 ) were strongly associated with outpatient visits for RD in both HZ and ZS. In multiple pollutant models, a significant association was only observed between PM 2.5 and the mortality rate of RD patients in both HZ and in ZS. Moreover, strong associations between SO 2 , NO 2 , and outpatient visits for RD were observed in HZ and ZS. This study has provided evidence that both the mortality rates and outpatient visits for RD were significantly associated with air pollutants. Furthermore, the results showed that different air pollutant levels lead to regional differences between mortality rates and outpatient visits.

Linking intended visitation to regional economic impact models of bison and elk management

USGS Publications Warehouse

Loomis, J.; Caughlan, L.

2004-01-01

This article links intended National Park visitation estimates to regional economic models to calculate the employment impacts of alternative bison and elk management strategies. The survey described alternative National Elk Refuge (NER) management actions and the effects on elk and bison populations at the NER and adjacent Grand Teton National Park (GTNP). Park visitors were then asked if they would change their number of visits with each potential management action. Results indicate there would be a 10% decrease in visitation if bison populations were reduced from 600 to 400 animals and elk populations were reduced in GTNP and the NER. The related decrease in jobs in Teton counties of Wyoming and Idaho is estimated at 5.5%. Adopting a “no active management” option of never feeding elk and bison on the NER yields about one-third the current bison population (200 bison) and about half the elk population. Visitors surveyed about this management option would take about 20% fewer trips, resulting in an 11.3% decrease in employment. Linking intended visitation surveys and regional economic models represents a useful tool for natural resource planners who must present the consequences of potential actions in Environmental Impact Statements and plans to the public and decision makers prior to any action being implemented.

A Model of Solid State Gas Sensors

NASA Astrophysics Data System (ADS)

Woestman, J. T.; Brailsford, A. D.; Shane, M.; Logothetis, E. M.

1997-03-01

Solid state gas sensors are widely used to measure the concentrations of gases such as CO, CH_4, C_3H_6, H_2, C_3H8 and O2 The applications of these sensors range from air-to-fuel ratio control in combustion processes including those in automotive engines and industrial furnaces to leakage detection of inflammable and toxic gases in domestic and industrial environments. As the need increases to accurately measure smaller and smaller concentrations, problems such as poor selectivity, stability and response time limit the use of these sensors. In an effort to overcome some of these limitations, a theoretical model of the transient behavior of solid state gas sensors has been developed. In this presentation, a model for the transient response of an electrochemical gas sensor to gas mixtures containing O2 and one reducing species, such as CO, is discussed. This model accounts for the transport of the reactive species to the sampling electrode, the catalyzed oxidation/reduction reaction of these species and the generation of the resulting electrical signal. The model will be shown to reproduce the results of published steady state models and to agree with experimental steady state and transient data.

Using finite element modelling and experimental methods to investigate planar coil sensor topologies for inductive measurement of displacement

NASA Astrophysics Data System (ADS)

Moreton, Gregory; Meydan, Turgut; Williams, Paul

2018-04-01

The usage of planar sensors is widespread due to their non-contact nature and small size profiles, however only a few basic design types are generally considered. In order to develop planar coil designs we have performed extensive finite element modelling (FEM) and experimentation to understand the performance of different planar sensor topologies when used in inductive sensing. We have applied this approach to develop a novel displacement sensor. Models of different topologies with varying pitch values have been analysed using the ANSYS Maxwell FEM package, furthermore the models incorporated a movable soft magnetic amorphous ribbon element. The different models used in the FEM were then constructed and experimentally tested with topologies that included mesh, meander, square coil, and circular coil configurations. The sensors were used to detect the displacement of the amorphous ribbon. A LabView program controlled both the displacement stage and the impedance analyser, the latter capturing the varying inductance values with ribbon displacement. There was good correlation between the FEM models and the experimental data confirming that the methodology described here offers an effective way for developing planar coil based sensors with improved performance.

Behavioral Analysis of Visitors to a Medical Institution's Website Using Markov Chain Monte Carlo Methods.

PubMed

Suzuki, Teppei; Tani, Yuji; Ogasawara, Katsuhiko

2016-07-25

Consistent with the "attention, interest, desire, memory, action" (AIDMA) model of consumer behavior, patients collect information about available medical institutions using the Internet to select information for their particular needs. Studies of consumer behavior may be found in areas other than medical institution websites. Such research uses Web access logs for visitor search behavior. At this time, research applying the patient searching behavior model to medical institution website visitors is lacking. We have developed a hospital website search behavior model using a Bayesian approach to clarify the behavior of medical institution website visitors and determine the probability of their visits, classified by search keyword. We used the website data access log of a clinic of internal medicine and gastroenterology in the Sapporo suburbs, collecting data from January 1 through June 31, 2011. The contents of the 6 website pages included the following: home, news, content introduction for medical examinations, mammography screening, holiday person-on-duty information, and other. The search keywords we identified as best expressing website visitor needs were listed as the top 4 headings from the access log: clinic name, clinic name + regional name, clinic name + medical examination, and mammography screening. Using the search keywords as the explaining variable, we built a binomial probit model that allows inspection of the contents of each purpose variable. Using this model, we determined a beta value and generated a posterior distribution. We performed the simulation using Markov Chain Monte Carlo methods with a noninformation prior distribution for this model and determined the visit probability classified by keyword for each category. In the case of the keyword "clinic name," the visit probability to the website, repeated visit to the website, and contents page for medical examination was positive. In the case of the keyword "clinic name and regional name," the probability for a repeated visit to the website and the mammography screening page was negative. In the case of the keyword "clinic name + medical examination," the visit probability to the website was positive, and the visit probability to the information page was negative. When visitors referred to the keywords "mammography screening," the visit probability to the mammography screening page was positive (95% highest posterior density interval = 3.38-26.66). Further analysis for not only the clinic website but also various other medical institution websites is necessary to build a general inspection model for medical institution websites; we want to consider this in future research. Additionally, we hope to use the results obtained in this study as a prior distribution for future work to conduct higher-precision analysis.

Behavioral Analysis of Visitors to a Medical Institution’s Website Using Markov Chain Monte Carlo Methods

PubMed Central

Tani, Yuji

2016-01-01

Background Consistent with the “attention, interest, desire, memory, action” (AIDMA) model of consumer behavior, patients collect information about available medical institutions using the Internet to select information for their particular needs. Studies of consumer behavior may be found in areas other than medical institution websites. Such research uses Web access logs for visitor search behavior. At this time, research applying the patient searching behavior model to medical institution website visitors is lacking. Objective We have developed a hospital website search behavior model using a Bayesian approach to clarify the behavior of medical institution website visitors and determine the probability of their visits, classified by search keyword. Methods We used the website data access log of a clinic of internal medicine and gastroenterology in the Sapporo suburbs, collecting data from January 1 through June 31, 2011. The contents of the 6 website pages included the following: home, news, content introduction for medical examinations, mammography screening, holiday person-on-duty information, and other. The search keywords we identified as best expressing website visitor needs were listed as the top 4 headings from the access log: clinic name, clinic name + regional name, clinic name + medical examination, and mammography screening. Using the search keywords as the explaining variable, we built a binomial probit model that allows inspection of the contents of each purpose variable. Using this model, we determined a beta value and generated a posterior distribution. We performed the simulation using Markov Chain Monte Carlo methods with a noninformation prior distribution for this model and determined the visit probability classified by keyword for each category. Results In the case of the keyword “clinic name,” the visit probability to the website, repeated visit to the website, and contents page for medical examination was positive. In the case of the keyword “clinic name and regional name,” the probability for a repeated visit to the website and the mammography screening page was negative. In the case of the keyword “clinic name + medical examination,” the visit probability to the website was positive, and the visit probability to the information page was negative. When visitors referred to the keywords “mammography screening,” the visit probability to the mammography screening page was positive (95% highest posterior density interval = 3.38-26.66). Conclusions Further analysis for not only the clinic website but also various other medical institution websites is necessary to build a general inspection model for medical institution websites; we want to consider this in future research. Additionally, we hope to use the results obtained in this study as a prior distribution for future work to conduct higher-precision analysis. PMID:27457537

Population-Tailored Care for Homeless Veterans and Acute Care Use, Cost, and Satisfaction: A Prospective Quasi-Experimental Trial

PubMed Central

Johnson, Erin E.; Borgia, Matthew; Noack, Amy; Yoon, Jean; Gehlert, Elizabeth; Lo, Jeanie

2018-01-01

Introduction Although traditional patient-centered medical homes (PCMHs) are effective for patients with complex needs, it is unclear whether homeless-tailored PCMHs work better for homeless veterans. We examined the impact of enrollment in a Veterans Health Administration (VHA) homeless-tailored PCMH on health services use, cost, and satisfaction compared with enrollment in a traditional, nontailored PCMH. Methods We conducted a prospective, multicenter, quasi-experimental, single-blinded study at 2 VHA medical centers to assess health services use, cost, and satisfaction during 12 months among 2 groups of homeless veterans: 1) veterans receiving VHA homeless-tailored primary care (Homeless-Patient Aligned Care Team [H-PACT]) and 2) veterans receiving traditional primary care services (PACT). A cohort of 266 homeless veterans enrolled from June 2012 through January 2014. Results Compared with PACT patients, H-PACT patients had more social work visits (4.6 vs 2.7 visits) and fewer emergency department (ED) visits for ambulatory care-sensitive conditions (0 vs 0.2 visits); a significantly smaller percentage of veterans in H-PACT were hospitalized (23.1% vs 35.4%) or had mental health–related ED visits (34.1% vs 47.6%). We found significant differences in primary care provider–specific visits (H-PACT, 5.1 vs PACT, 3.6 visits), mental health care visits (H-PACT, 8.8 vs PACT, 13.4 visits), 30-day prescription drug fills (H-PACT, 40.5 vs PACT, 58.8 fills), and use of group therapy (H-PACT, 40.1% vs PACT, 53.7%). Annual costs per patient were significantly higher in the PACT group than the H-PACT group ($37,415 vs $28,036). In logistic regression model of acute care use, assignment to the H-PACT model was protective as was rating health “good” or better. Conclusion Homeless veterans enrolled in the population-tailored primary care approach used less acute care and costs were lower. Tailored-care models have implications for care coordination in the US Department of Veterans Affairs VA and community health systems. PMID:29451116

The Remote Brief Intervention and Referral to Treatment Model: Development, Functionality, Acceptability, and Feasibility

PubMed Central

Boudreaux, Edwin D.; Haskins, Brianna; Harralson, Tina; Bernstein, Edward

2015-01-01

Background Screening, brief intervention, and referral to treatment (SBIRT) is effective for reducing risky alcohol use across a variety of medical settings. However, most programs have been unsustainable because of cost and time demands. Telehealth may alleviate on-site clinician burden. This exploratory study examines the feasibility of a new Remote Brief Intervention and Referral to Treatment (R-BIRT) model. Methods Eligible emergency department (ED) patients were enrolled into one of five models. (1) Warm Handoff: clinician-facilitated phone call during ED visit. (2) Patient Direct: patient-initiated call during visit. (3) Electronic Referral: patient contacted by R-BIRT personnel post visit. (4) Patient Choice: choice of models 1–3. (5) Modified Patient Choice: choice of models 1–2, Electronic Referral offered if 1–2 were declined. Once connected, a health coach offered assessment, counseling, and referral to treatment. Follow up assessments were conducted at 1 and 3 months. Primary outcomes measured were acceptance, satisfaction, and completion rates. Results Of 125 eligible patients, 50 were enrolled, for an acceptance rate of 40%. Feedback and satisfaction ratings were generally positive. Completion rates were 58% overall, with patients enrolled into a model wherein the consultation occurred during the ED visit, as opposed to after the visit, much more likely to complete a consultation, 90% vs. 10%, χ2 (4, N=50) = 34.8, p<0.001. Conclusions The R-BIRT offers a feasible alternative to in-person alcohol SBIRT and should be studied further. The public health impact of having accessible, sustainable, evidence-based SBIRT for substance use across a range of medical settings could be considerable. PMID:26297297

The remote brief intervention and referral to treatment model: Development, functionality, acceptability, and feasibility.

PubMed

Boudreaux, Edwin D; Haskins, Brianna; Harralson, Tina; Bernstein, Edward

2015-10-01

Screening, brief intervention, and referral to treatment (SBIRT) is effective for reducing risky alcohol use across a variety of medical settings. However, most programs have been unsustainable because of cost and time demands. Telehealth may alleviate on-site clinician burden. This exploratory study examines the feasibility of a new Remote Brief Intervention and Referral to Treatment (R-BIRT) model. Eligible emergency department (ED) patients were enrolled into one of five models. (1) Warm Handoff: clinician-facilitated phone call during ED visit. (2) Patient Direct: patient-initiated call during visit. (3) Electronic Referral: patient contacted by R-BIRT personnel post visit. (4) Patient Choice: choice of models 1-3. (5) Modified Patient Choice: choice of models 1-2, Electronic Referral offered if 1-2 were declined. Once connected, a health coach offered assessment, counseling, and referral to treatment. Follow up assessments were conducted at 1 and 3 months. Primary outcomes measured were acceptance, satisfaction, and completion rates. Of 125 eligible patients, 50 were enrolled, for an acceptance rate of 40%. Feedback and satisfaction ratings were generally positive. Completion rates were 58% overall, with patients enrolled into a model wherein the consultation occurred during the ED visit, as opposed to after the visit, much more likely to complete a consultation, 90% vs. 10%, χ(2) (4, N=50)=34.8, p<0.001. The R-BIRT offers a feasible alternative to in-person alcohol SBIRT and should be studied further. The public health impact of having accessible, sustainable, evidence-based SBIRT for substance use across a range of medical settings could be considerable. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An Improved High-Sensitivity Airborne Transient Electromagnetic Sensor for Deep Penetration

PubMed Central

Chen, Shudong; Guo, Shuxu; Wang, Haofeng; He, Miao; Liu, Xiaoyan; Qiu, Yu; Zhang, Shuang; Yuan, Zhiwen; Zhang, Haiyang; Fang, Dong; Zhu, Jun

2017-01-01

The investigation depth of transient electromagnetic sensors can be effectively increased by reducing the system noise, which is mainly composed of sensor internal noise, electromagnetic interference (EMI), and environmental noise, etc. A high-sensitivity airborne transient electromagnetic (AEM) sensor with low sensor internal noise and good shielding effectiveness is of great importance for deep penetration. In this article, the design and optimization of such an AEM sensor is described in detail. To reduce sensor internal noise, a noise model with both a damping resistor and a preamplifier is established and analyzed. The results indicate that a sensor with a large diameter, low resonant frequency, and low sampling rate will have lower sensor internal noise. To improve the electromagnetic compatibility of the sensor, an electromagnetic shielding model for a central-tapped coil is established and discussed in detail. Previous studies have shown that unclosed shields with multiple layers and center grounding can effectively suppress EMI and eddy currents. According to these studies, an improved differential AEM sensor is constructed with a diameter, resultant effective area, resonant frequency, and normalized equivalent input noise of 1.1 m, 114 m2, 35.6 kHz, and 13.3 nV/m2, respectively. The accuracy of the noise model and the shielding effectiveness of the sensor have been verified experimentally. The results show a good agreement between calculated and measured results for the sensor internal noise. Additionally, over 20 dB shielding effectiveness is achieved in a complex electromagnetic environment. All of these results show a great improvement in sensor internal noise and shielding effectiveness. PMID:28106718

Modeling of Regional Climate Change Effects on Ground-Level Ozone and Childhood Asthma

PubMed Central

Sheffield, Perry E.; Knowlton, Kim; Carr, Jessie L.; Kinney, Patrick L.

2011-01-01

Background The adverse respiratory effects of ground-level ozone are well-established. Ozone is the air pollutant most consistently projected to increase under future climate change. Purpose To project future pediatric asthma emergency department visits associated with ground-level ozone changes, comparing 1990s to 2020s. Methods This study assessed future numbers of asthma emergency department visits for children aged 0–17 years using (1) baseline New York City metropolitan area emergency department rates, (2) a dose–response relationship between ozone levels and pediatric asthma emergency department visits, and (3) projected daily 8-hour maximum ozone concentrations for the 2020s as simulated by a global-to-regional climate change and atmospheric chemistry model. Sensitivity analyses included population projections and ozone precursor changes. This analysis occurred in 2010. Results In this model, climate change could cause an increase in regional summer ozone-related asthma emergency department visits for children aged 0–17 years of 7.3% across the New York City metropolitan region by the 2020s. This effect diminished with inclusion of ozone precursor changes. When population growth is included, the projections of morbidity related to ozone are even larger. Conclusions The results of this analysis demonstrate that the use of regional climate and atmospheric chemistry models make possible the projection of local climate change health effects for specific age groups and specific disease outcomes – such as emergency department visits for asthma. Efforts should be made to improve on this type of modeling to inform local and wider-scale climate change mitigation and adaptation policy. PMID:21855738

Apparatus for sensor failure detection and correction in a gas turbine engine control system

NASA Technical Reports Server (NTRS)

Spang, H. A., III; Wanger, R. P. (Inventor)

1981-01-01

A gas turbine engine control system maintains a selected level of engine performance despite the failure or abnormal operation of one or more engine parameter sensors. The control system employs a continuously updated engine model which simulates engine performance and generates signals representing real time estimates of the engine parameter sensor signals. The estimate signals are transmitted to a control computational unit which utilizes them in lieu of the actual engine parameter sensor signals to control the operation of the engine. The estimate signals are also compared with the corresponding actual engine parameter sensor signals and the resulting difference signals are utilized to update the engine model. If a particular difference signal exceeds specific tolerance limits, the difference signal is inhibited from updating the model and a sensor failure indication is provided to the engine operator.

Numerical modelling of distributed vibration sensor based on phase-sensitive OTDR

NASA Astrophysics Data System (ADS)

Masoudi, A.; Newson, T. P.

2017-04-01

A Distributed Vibration Sensor Based on Phase-Sensitive OTDR is numerically modeled. The advantage of modeling the building blocks of the sensor individually and combining the blocks to analyse the behavior of the sensing system is discussed. It is shown that the numerical model can accurately imitate the response of the experimental setup to dynamic perturbations a signal processing procedure similar to that used to extract the phase information from sensing setup.

Theoretical and experimental investigations of sensor location for optimal aeroelastic system state estimation

NASA Technical Reports Server (NTRS)

Liu, G.

1985-01-01

One of the major concerns in the design of an active control system is obtaining the information needed for effective feedback. This involves the combination of sensing and estimation. A sensor location index is defined as the weighted sum of the mean square estimation errors in which the sensor locations can be regarded as estimator design parameters. The design goal is to choose these locations to minimize the sensor location index. The choice of the number of sensors is a tradeoff between the estimation quality based upon the same performance index and the total costs of installing and maintaining extra sensors. An experimental study for choosing the sensor location was conducted on an aeroelastic system. The system modeling which includes the unsteady aerodynamics model developed by Stephen Rock was improved. Experimental results verify the trend of the theoretical predictions of the sensor location index for different sensor locations at various wind speeds.

Semantically-enabled sensor plug & play for the sensor web.

PubMed

Bröring, Arne; Maúe, Patrick; Janowicz, Krzysztof; Nüst, Daniel; Malewski, Christian

2011-01-01

Environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent over the past years. As consequence of these technological advancements, sensors are increasingly deployed to monitor our environment. The large variety of available sensor types with often incompatible protocols complicates the integration of sensors into observing systems. The standardized Web service interfaces and data encodings defined within OGC's Sensor Web Enablement (SWE) framework make sensors available over the Web and hide the heterogeneous sensor protocols from applications. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The driver software which enables access to sensors has to be implemented and the measured sensor data has to be manually mapped to the SWE models. In this article we introduce a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) semantic matchmaking functionality, (2) a publish/subscribe mechanism underlying the SensorWeb, as well as (3) a model for the declarative description of sensor interfaces which serves as a generic driver mechanism. We implement and evaluate our approach by applying it to an oil spill scenario. The matchmaking is realized using existing ontologies and reasoning engines and provides a strong case for the semantic integration capabilities provided by Semantic Web research.

Semantically-Enabled Sensor Plug & Play for the Sensor Web

PubMed Central

Bröring, Arne; Maúe, Patrick; Janowicz, Krzysztof; Nüst, Daniel; Malewski, Christian

2011-01-01

Environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent over the past years. As consequence of these technological advancements, sensors are increasingly deployed to monitor our environment. The large variety of available sensor types with often incompatible protocols complicates the integration of sensors into observing systems. The standardized Web service interfaces and data encodings defined within OGC’s Sensor Web Enablement (SWE) framework make sensors available over the Web and hide the heterogeneous sensor protocols from applications. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The driver software which enables access to sensors has to be implemented and the measured sensor data has to be manually mapped to the SWE models. In this article we introduce a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) semantic matchmaking functionality, (2) a publish/subscribe mechanism underlying the SensorWeb, as well as (3) a model for the declarative description of sensor interfaces which serves as a generic driver mechanism. We implement and evaluate our approach by applying it to an oil spill scenario. The matchmaking is realized using existing ontologies and reasoning engines and provides a strong case for the semantic integration capabilities provided by Semantic Web research. PMID:22164033

On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

Linking Simulation with Formal Verification and Modeling of Wireless Sensor Network in TLA+

NASA Astrophysics Data System (ADS)

Martyna, Jerzy

In this paper, we present the results of the simulation of a wireless sensor network based on the flooding technique and SPIN protocols. The wireless sensor network was specified and verified by means of the TLA+ specification language [1]. For a model of wireless sensor network built this way simulation was carried with the help of specially constructed software tools. The obtained results allow us to predict the behaviour of the wireless sensor network in various topologies and spatial densities. Visualization of the output data enable precise examination of some phenomenas in wireless sensor networks, such as a hidden terminal, etc.

Evaluation of Smartphone Inertial Sensor Performance for Cross-Platform Mobile Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

Smartphone sensors are being increasingly used in mobile applications. The performance of sensors varies considerably among different smartphone models and the development of a cross-platform mobile application might be a very complex and demanding task. A publicly accessible resource containing real-life-situation smartphone sensor parameters could be of great help for cross-platform developers. To address this issue we have designed and implemented a pilot participatory sensing application for measuring, gathering, and analyzing smartphone sensor parameters. We start with smartphone accelerometer and gyroscope bias and noise parameters. The application database presently includes sensor parameters of more than 60 different smartphone models of different platforms. It is a modest, but important start, offering information on several statistical parameters of the measured smartphone sensors and insights into their performance. The next step, a large-scale cloud-based version of the application, is already planned. The large database of smartphone sensor parameters may prove particularly useful for cross-platform developers. It may also be interesting for individual participants who would be able to check-up and compare their smartphone sensors against a large number of similar or identical models. PMID:27049391

Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies

NASA Technical Reports Server (NTRS)

Talabac, Stephen J.

2004-01-01

Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.

A telegeriatric service in a small rural hospital: A case study and cost analysis.

PubMed

Versleijen, Marloes; Martin-Khan, Melinda G; Whitty, Jennifer A; Smith, Anthony C; Gray, Leonard C

2015-12-01

Small hospitals in rural areas usually have an insufficient caseload of frail old people to justify the regular presence of a geriatrician. This study examined the costs of providing a telegeriatric service by videoconference in a rural hospital, compared to the costs of a visiting geriatrician that travels to undertake in-person consultations. A cost analysis was undertaken to compare the costs of the telegeriatric service model with the costs of a visiting geriatrician service model. A recently established telegeriatric service at Warwick Hospital was used as a case study. In the base case model (assuming four patients per round and a round-trip travel distance of 312 kilometres), an estimated AUD$131 per patient consultation can be saved in favour of the telegeriatric service model. Key drivers of costs are the number of patients per round and the travel distance and time in the visiting geriatrician model. At a workload of four patients per round, it is less expensive to conduct a telegeriatric service than a visiting geriatrician service when the round-trip travel time exceeds 76 minutes. Even under quite conservative assumptions, a telegeriatric service offers an economically feasible approach to the delivery of specialist geriatric assessment in rural and remote settings. © The Author(s) 2015.

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

A novel space-based observation strategy for GEO objects based on daily pointing adjustment of multi-sensors

NASA Astrophysics Data System (ADS)

Hu, Yun-peng; Li, Ke-bo; Xu, Wei; Chen, Lei; Huang, Jian-yu

2016-08-01

Space-based visible (SBV) program has been proved to be with a large advantage to observe geosynchronous earth orbit (GEO) objects. With the development of SBV observation started from 1996, many strategies have come out for the purpose of observing GEO objects more efficiently. However it is a big challenge to visit all the GEO objects in a relatively short time because of the distribution characteristics of GEO belt and limited field of view (FOV) of sensor. And it's also difficult to keep a high coverage of the GEO belt every day in a whole year. In this paper, a space-based observation strategy for GEO objects is designed based on the characteristics of the GEO belt. The mathematical formula of GEO belt is deduced and the evolvement of GEO objects is illustrated. There are basically two kinds of orientation strategies for most observation satellites, i.e., earth-oriented and inertia-directional. Influences of both strategies to their own observation regions are analyzed and compared with each other. A passive optical instrument with daily attitude-adjusting strategies is proposed to increase the daily coverage rate of GEO objects in a whole year. Furthermore, in order to observe more GEO objects in a relatively short time, the strategy of a satellite with multi-sensors is proposed. The installation parameters between different sensors are optimized, more than 98% of GEO satellites can be observed every day and almost all the GEO satellites can be observed every two days with 3 sensors (FOV: 6° × 6°) on the satellite under the strategy of daily pointing adjustment in a whole year.

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Simulation of the spatial frequency-dependent sensitivities of Acoustic Emission sensors

NASA Astrophysics Data System (ADS)

Boulay, N.; Lhémery, A.; Zhang, F.

2018-05-01

Typical configurations of nondestructive testing by Acoustic Emission (NDT/AE) make use of multiple sensors positioned on the tested structure for detecting evolving flaws and possibly locating them by triangulation. Sensors positions must be optimized for ensuring global coverage sensitivity to AE events and minimizing their number. A simulator of NDT/AE is under development to provide help with designing testing configurations and with interpreting measurements. A global model performs sub-models simulating the various phenomena taking place at different spatial and temporal scales (crack growth, AE source and radiation, wave propagation in the structure, reception by sensors). In this context, accurate modelling of sensors behaviour must be developed. These sensors generally consist of a cylindrical piezoelectric element of radius approximately equal to its thickness, without damping and bonded to its case. Sensors themselves are bonded to the structure being tested. Here, a multiphysics finite element simulation tool is used to study the complex behaviour of AE sensor. The simulated behaviour is shown to accurately reproduce the high-amplitude measured contributions used in the AE practice.

Acoustic/seismic signal propagation and sensor performance modeling

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Marlin, David H.; Mackay, Sean

2007-04-01

Performance, optimal employment, and interpretation of data from acoustic and seismic sensors depend strongly and in complex ways on the environment in which they operate. Software tools for guiding non-expert users of acoustic and seismic sensors are therefore much needed. However, such tools require that many individual components be constructed and correctly connected together. These components include the source signature and directionality, representation of the atmospheric and terrain environment, calculation of the signal propagation, characterization of the sensor response, and mimicking of the data processing at the sensor. Selection of an appropriate signal propagation model is particularly important, as there are significant trade-offs between output fidelity and computation speed. Attenuation of signal energy, random fading, and (for array systems) variations in wavefront angle-of-arrival should all be considered. Characterization of the complex operational environment is often the weak link in sensor modeling: important issues for acoustic and seismic modeling activities include the temporal/spatial resolution of the atmospheric data, knowledge of the surface and subsurface terrain properties, and representation of ambient background noise and vibrations. Design of software tools that address these challenges is illustrated with two examples: a detailed target-to-sensor calculation application called the Sensor Performance Evaluator for Battlefield Environments (SPEBE) and a GIS-embedded approach called Battlefield Terrain Reasoning and Awareness (BTRA).

A cloud-based information repository for bridge monitoring applications

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Design and modeling of magnetically driven electric-field sensor for non-contact DC voltage measurement in electric power systems.

PubMed

Wang, Decai; Li, Ping; Wen, Yumei

2016-10-01

In this paper, the design and modeling of a magnetically driven electric-field sensor for non-contact DC voltage measurement are presented. The magnetic drive structure of the sensor is composed of a small solenoid and a cantilever beam with a cylindrical magnet mounted on it. The interaction of the magnet and the solenoid provides the magnetic driving force for the sensor. Employing magnetic drive structure brings the benefits of low driving voltage and large vibrating displacement, which consequently results in less interference from the drive signal. In the theoretical analyses, the capacitance calculation model between the wire and the sensing electrode is built. The expression of the magnetic driving force is derived by the method of linear fitting. The dynamical model of the magnetic-driven cantilever beam actuator is built by using Euler-Bernoulli theory and distributed parameter method. Taking advantage of the theoretical model, the output voltage of proposed sensor can be predicted. The experimental results are in good agreement with the theoretical results. The proposed sensor shows a favorable linear response characteristic. The proposed sensor has a measuring sensitivity of 9.87 μV/(V/m) at an excitation current of 37.5 mA. The electric field intensity resolution can reach 10.13 V/m.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

KSC-2010-5934

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Work platforms inside the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida begin to surround space shuttle Discovery, its solid rocket boosters and external fuel tank at dawn. The shuttle rolled back from Launch Pad 39A so technicians can examine the external tank and re-apply foam where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5887

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery awaits its move, called rollback, from Launch Pad 39A to the Vehicle Assembly Building (VAB) at NASA's Kennedy Space Center in Florida. Rollback was scheduled for 12:30 a.m., but was postponed until 10 p.m. so technicians could resolve an issue with a leveling system on the crawler-transporter. Once inside the VAB, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Kim Shiflett

KSC-2010-5933

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Space shuttle Discovery enters the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, from Launch Pad 39A began at 10:48 p.m. yesterday and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5923

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, begins its 3.4-mile trek, known as rollback, from Launch Pad 39A to the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. Rollback began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5932

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- The bright lights inside the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida invite space shuttle Discovery inside. The 3.4-mile trek, called rollback, from Launch Pad 39A began at 10:48 p.m. yesterday and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5927

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, slowly moves away from Launch Pad 39A at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, to the Vehicle Assembly Building began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5925

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, slowly moves away from Launch Pad 39A at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, to the Vehicle Assembly Building began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5924

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, begins its 3.4-mile trek, known as rollback, from Launch Pad 39A to the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. Rollback began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5888

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery awaits its move, called rollback, from Launch Pad 39A to the Vehicle Assembly Building (VAB) at NASA's Kennedy Space Center in Florida. Rollback was scheduled for 12:30 a.m., but was postponed until 10 p.m. so technicians could resolve an issue with a leveling system on the crawler-transporter. Once inside the VAB, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Kim Shiflett

KSC-2010-5928

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Space shuttle Discovery slowly moves down the crawlerway at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, from Launch Pad 39A to the Vehicle Assembly Building began at 10:48 p.m. yesterday and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5926

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, slowly moves away from Launch Pad 39A at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, to the Vehicle Assembly Building began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5929

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Space shuttle Discovery slowly moves down the crawlerway at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, from Launch Pad 39A to the Vehicle Assembly Building began at 10:48 p.m. yesterday and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

Long term three dimensional tracking of orthodontic patients using registered cone beam CT and photogrammetry.

PubMed

Boulanger, Pierre; Flores-Mir, Carlos; Ramirez, Juan F; Mesa, Elizabeth; Branch, John W

2009-01-01

The measurements from registered images obtained from Cone Beam Computed Tomography (CBCT) and a photogrammetric sensor are used to track three-dimensional shape variations of orthodontic patients before and after their treatments. The methodology consists of five main steps: (1) the patient's bone and skin shapes are measured in 3D using the fusion of images from a CBCT and a photogrammetric sensor. (2) The bone shape is extracted from the CBCT data using a standard marching cube algorithm. (3) The bone and skin shape measurements are registered using titanium targets located on the head of the patient. (4) Using a manual segmentation technique the head and lower jaw geometry are extracted separately to deal with jaw motion at the different record visits. (5) Using natural features of the upper head the two datasets are then registered with each other and then compared to evaluate bone, teeth, and skin displacements before and after treatments. This procedure is now used at the University of Alberta orthodontic clinic.

KSC-2010-5930

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Space shuttle Discovery approached the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, from Launch Pad 39A began at 10:48 p.m. yesterday and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5922

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, slowly moves away from Launch Pad 39A at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, to the Vehicle Assembly Building began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5931

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Space shuttle Discovery begins to enter the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, from Launch Pad 39A began at 10:48 p.m. yesterday and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5935

NASA Image and Video Library

2010-12-22

CAPE CANAVERAL, Fla. -- Work platforms inside the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida begin to surround space shuttle Discovery, its solid rocket boosters and external fuel tank. The shuttle rolled back from Launch Pad 39A so technicians can examine the external tank and re-apply foam where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

KSC-2010-5921

NASA Image and Video Library

2010-12-21

CAPE CANAVERAL, Fla. -- Space shuttle Discovery, secured to a crawler-transporter, slowly moves away from Launch Pad 39A at NASA's Kennedy Space Center in Florida. The 3.4-mile trek, called rollback, to the Vehicle Assembly Building began at 10:48 p.m. and took about eight hours. Next, Discovery's external fuel tank will be examined and foam reapplied where 89 sensors were installed on the tank's aluminum skin for an instrumented tanking test on Dec. 17. The sensors were used to measure changes in the tank as super-cold propellants were pumped in and drained out. Data and analysis from the test will be used to determine what caused the tops of two, 21-foot-long support beams, called stringers, on the outside of the intertank to crack during fueling on Nov. 5. Discovery's next launch opportunity to the International Space Station on the STS-133 mission is no earlier than Feb. 3, 2011. For more information on STS-133, visit www.nasa.gov/mission_pages/shuttle/shuttlemissions/sts133/. Photo credit: NASA/Frank Michaux

A New Calibration Method for Commercial RGB-D Sensors

PubMed Central

Darwish, Walid; Tang, Shenjun; Li, Wenbin; Chen, Wu

2017-01-01

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter-level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges. PMID:28538695

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Impact of malicious servers over trust and reputation models in wireless sensor networks

NASA Astrophysics Data System (ADS)

Verma, Vinod Kumar; Singh, Surinder; Pathak, N. P.

2016-03-01

This article deals with the impact of malicious servers over different trust and reputation models in wireless sensor networks. First, we analysed the five trust and reputation models, namely BTRM-WSN, Eigen trust, peer trust, power trust, linguistic fuzzy trust model. Further, we proposed wireless sensor network design for optimisation of these models. Finally, influence of malicious servers on the behaviour of above mentioned trust and reputation models is discussed. Statistical analysis has been carried out to prove the validity of our proposal.

Real-time GIS data model and sensor web service platform for environmental data management.

PubMed

Gong, Jianya; Geng, Jing; Chen, Zeqiang

2015-01-09

Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

Effects of temperature variation between neighbouring days on daily hospital visits for childhood asthma: a time-series analysis.

PubMed

Li, K; Ni, H; Yang, Z; Wang, Y; Ding, S; Wen, L; Yang, H; Cheng, J; Su, H

2016-07-01

To identify the relationship between temperature variation between neighbouring days (TVN) and hospital visits for childhood asthma in age- and sex-specific groups. An ecological design was used to explore the effect of TVN on hospital visits for childhood asthma. A Poisson generalised linear regression model combined with a distributed lag non-linear model was used to analyse the association between TVN and hospital visits for childhood asthma. All hospital visits for childhood asthma from June 2010 to July 2013 were included (n = 17,022). Daily climate data were obtained from Hefei Meteorological Bureau. A significant correlation was found between TVN and hospital visits for childhood asthma in age- and sex-specific groups. For different gender groups, the effect of TVN on childhood asthma was the greatest at 3 and 5 days lag for males and females. For different age groups, the effect of TVN on childhood asthma was the greatest at 1 and 5 days lag for 0-4 years and 5-14 years children, respectively. A 1 °C increase in TVN was associated with a 4.2% (95% confidence interval 0.9-7.6%) increase in hospital visits for childhood asthma. TVN is associated with hospital visits for childhood asthma. Once the temperature change rapidly, guardians will be urged to pay more attention to their children's health, which may reduce the morbidity of childhood asthma. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Direct-to-consumer and physician promotion of tegaserod correlated with physician visits, diagnoses, and prescriptions.

PubMed

Dorn, Spencer D; Farley, Joel F; Hansen, Richard A; Shah, Nilay D; Sandler, Robert S

2009-08-01

Direct-to-consumer advertisement (DTCA) and physician promotion of drugs can influence patient and physician behaviors. We sought to determine the relationship between promotion of tegaserod and the number of office visits for abdominal pain, constipation, and bloating; diagnoses of irritable bowel syndrome (IBS); and tegaserod prescriptions. We used an Integrated Promotional Services database to estimate tegaserod DTCA and promotion expenditures; the National Ambulatory/Hospital Medical Care Surveys (1997-2005) to estimate the number of ambulatory care visits for abdominal pain, constipation, and bloating and diagnoses of IBS; and IMS Health's National Prescription Audit Plus (Fairfield, CT) to estimate the number of prescriptions. We constructed segmented and multivariate regression models to analyze the data. In the 3 months immediately following the start of tegaserod DTCA, there was a significant increase in physician visits (by 1 million; 95% confidence interval [CI], 0.5-1.6 million) and IBS diagnoses (by 397,025; 95% CI, 3909-790,141). Subsequently, the trend of visits and IBS diagnoses was reduced. In multivariate analyses that examined the overall relationship of promotion with visits, diagnoses, and prescriptions, only the relationship between physician promotion and tegaserod prescribing was significant; every $1 million spent on physician promotion resulted in an additional 4108 prescriptions (95% CI, 2526-5691). The initial DTCA of tegaserod was associated with a significant, immediate increase in physician visits and IBS diagnoses. This trend reversed and, in multivariate models, neither DTCA nor physician promotion correlated with visits or diagnoses. Physician promotion (although not DTCA) correlated with tegaserod prescription volume.

Direct to consumer and physician promotion of tegaserod correlated with physician visits, diagnoses, and prescriptions

PubMed Central

Dorn, Spencer D.; Farley, Joel F.; Hansen, Richard A.; D. Shah, Nilay; Sandler, Robert S.

2009-01-01

Background & Aims Direct to consumer advertisement (DTCA) and physician promotion of drugs can influence patient and physician behaviors. We sought to determine the relationship between promotion of tegaserod and the number of office visits for abdominal pain, constipation, and bloating; diagnoses of irritable bowel syndrome (IBS); and tegaserod prescriptions. Methods We used an Integrated Promotional Services database to estimate tegaserod DTCA and promotion expenditures, The National Ambulatory/Hospital Medical Care Surveys (1997–2005) to estimate the number of ambulatory care visits for abdominal pain, constipation, and bloating and diagnoses of IBS, and IMS Health's National Prescription Audit Plus to estimate the number of prescriptions. We constructed segmented and multivariate regression models to analyze the data. Results In the 3 months immediately following the start of tegaserod DTCA, there was a significant increase in physician visits (by 1 million; 95% CI 0.5–1.6 million) and IBS diagnoses (by 397,025; 95% CI 3,909–790,141). Subsequently, the trend of visits and IBS diagnoses reduced. In multivariate analyses that examined the overall relationship of promotion with visits, diagnoses, and prescriptions, only the relationship between physician promotion and tegaserod prescribing was significant; every $1 million spent on physician promotion resulted in an additional 4,108 prescriptions (95% CI: 2,526–5,691). Conclusions The initial DTCA of tegaserod was associated with a significant, immediate increase in physician visits and IBS diagnoses. This trend reversed and in multivariate models, neither DTCA nor physician promotion correlated with visits or diagnoses. Physician promotion (though not DTCA) correlated with tegaserod prescription volume. PMID:19445943

First Experiences with Kinect v2 Sensor for Close Range 3d Modelling

NASA Astrophysics Data System (ADS)

Lachat, E.; Macher, H.; Mittet, M.-A.; Landes, T.; Grussenmeyer, P.

2015-02-01

RGB-D cameras, also known as range imaging cameras, are a recent generation of sensors. As they are suitable for measuring distances to objects at high frame rate, such sensors are increasingly used for 3D acquisitions, and more generally for applications in robotics or computer vision. This kind of sensors became popular especially since the Kinect v1 (Microsoft) arrived on the market in November 2010. In July 2014, Windows has released a new sensor, the Kinect for Windows v2 sensor, based on another technology as its first device. However, due to its initial development for video games, the quality assessment of this new device for 3D modelling represents a major investigation axis. In this paper first experiences with Kinect v2 sensor are related, and the ability of close range 3D modelling is investigated. For this purpose, error sources on output data as well as a calibration approach are presented.

A visiting scientist program in atmospheric sciences for the Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Davis, M. H.

1989-01-01

A visiting scientist program was conducted in the atmospheric sciences and related areas at the Goddard Laboratory for Atmospheres. Research was performed in mathematical analysis as applied to computer modeling of the atmospheres; development of atmospheric modeling programs; analysis of remotely sensed atmospheric, surface, and oceanic data and its incorporation into atmospheric models; development of advanced remote sensing instrumentation; and related research areas. The specific research efforts are detailed by tasks.

How price responsive is the demand for specialty care?

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Kavee, Andrew L; Olsen, Maren K

2012-08-01

Outpatient visit co-payments have increased in recent years. We estimate the patient response to a price change for specialty care, based on a co-payment increase from $15 to $50 per visit for veterans with hypertension. A retrospective cohort of veterans required to pay co-payments was compared with veterans exempt from co-payments whose nonequivalence was reduced via propensity score matching. Specialty care expenditures in 2000-2003 were estimated via a two-part mixed model to account for the correlation of the use and level outcomes over time, and results from this correlated two-part model were compared with an uncorrelated two-part model and a correlated random intercept two-part mixed model. A $35 specialty visit co-payment increase had no impact on the likelihood of seeking specialty care but induced lower specialty expenditures over time among users who were required to pay co-payments. The log ratio of price responsiveness (semi-elasticity) for specialty care increased from -0.25 to -0.31 after the co-payment increase. Estimates were similar across the three models. A significant increase in specialty visit co-payments reduced specialty expenditures among patients obtaining medications at the Veterans Affairs medical centers. Longitudinal expenditure analysis may be improved using recent advances in two-part model methods. Published 2011. This article is a US Government work and is in the public domain in the USA.

Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

PubMed

Eide, Ingvar; Westad, Frank

2018-01-01

A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5-50, 50-120, 120-250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

Normalization of time-series satellite reflectance data to a standard sun-target-sensor geometry using a semi-empirical model

NASA Astrophysics Data System (ADS)

Zhao, Yongguang; Li, Chuanrong; Ma, Lingling; Tang, Lingli; Wang, Ning; Zhou, Chuncheng; Qian, Yonggang

2017-10-01

Time series of satellite reflectance data have been widely used to characterize environmental phenomena, describe trends in vegetation dynamics and study climate change. However, several sensors with wide spatial coverage and high observation frequency are usually designed to have large field of view (FOV), which cause variations in the sun-targetsensor geometry in time-series reflectance data. In this study, on the basis of semiempirical kernel-driven BRDF model, a new semi-empirical model was proposed to normalize the sun-target-sensor geometry of remote sensing image. To evaluate the proposed model, bidirectional reflectance under different canopy growth conditions simulated by Discrete Anisotropic Radiative Transfer (DART) model were used. The semi-empirical model was first fitted by using all simulated bidirectional reflectance. Experimental result showed a good fit between the bidirectional reflectance estimated by the proposed model and the simulated value. Then, MODIS time-series reflectance data was normalized to a common sun-target-sensor geometry by the proposed model. The experimental results showed the proposed model yielded good fits between the observed and estimated values. The noise-like fluctuations in time-series reflectance data was also reduced after the sun-target-sensor normalization process.

Automated Synthetic Scene Generation

DTIC Science & Technology

2014-07-01

Using the Beard-Maxwell BRDF model , the BRDF from Equations (3.3) and (3.4) is composed of specular, diffuse, and volumetric terms such that x y zSun... models help organizations developing new remote sensing instruments anticipate sensor performance by enabling the ability to create synthetic imagery...for proposed sensor before a sensor is built. One of the largest challenges in modeling realistic synthetic imagery, however, is generating the

Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

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

Cheung, Howard; Braun, James E.

This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment inmore » the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.« less

Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

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

Cheung, Howard; Braun, James E.

2015-12-31

This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment inmore » the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.« less

MTOR ACTIVATION TRIGGERS IL-4 PRODUCTION AND NECROTIC DEATH OF DOUBLE-NEGATIVE T CELLS IN PATIENTS WITH SYSTEMIC LUPUS ERYHTHEMATOSUS

PubMed Central

Lai, Zhi-Wei; Borsuk, Rebecca; Shadakshari, Ashwini; Yu, Jianghong; Dawood, Maha; Garcia, Ricardo; Francis, Lisa; Tily, Hajra; Bartos, Adam; Faraone, Stephen V.; Phillips, Paul; Perl, Andras

2013-01-01

The mechanistic target of rapamycin (mTOR) is recognized as a sensor of mitochondrial dysfunction and effector of T-cell lineage development, however, its role in autoimmunity, including systemic lupus erythematosus, remains unclear. Here, we prospectively evaluated mitochondrial dysfunction and mTOR activation in PBL relative to SLE disease activity index (SLEDAI) during 274 visits of 59 patients and 54 matched healthy subjects. Partial least square-discriminant analysis identified 15 of 212 parameters that accounted for 70.2% of the total variance and discriminated lupus and control samples (p<0.0005); increased mitochondrial mass of CD3+/CD4−/CD8− double-negative (DN) T cells (p=1.1×10−22) and FoxP3 depletion in CD4+/CD25+ T cells were top contributors (p=6.7×10−7). Prominent necrosis and mTOR activation were noted in DN T cells during 15 visits characterized by flares (SLEDAI increase ≥4) relative to 61 visits of remission (SLEDAI decrease ≥4). mTOR activation in DN T cells was also noted at pre-flare visits of SLE patients relative to those of stable disease or healthy controls. DN lupus T cells showed increased production of IL-4, which correlated with depletion of CD25+/CD19+B cells. Rapamycin treatment in vivo blocked the IL-4 production and necrosis of DN T cells, increased the expression of FoxP3 in CD25+/CD4+T cells, and expanded CD25+/CD19+ B cells. These results identify mTOR activation to be a trigger of IL-4 production and necrotic death of DN T cells in patients with SLE. PMID:23913957

A Simple Sensor Model for THUNDER Actuators

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Bryant, Robert G.

2009-01-01

A quasi-static (low frequency) model is developed for THUNDER actuators configured as displacement sensors based on a simple Raleigh-Ritz technique. This model is used to calculate charge as a function of displacement. Using this and the calculated capacitance, voltage vs. displacement and voltage vs. electrical load curves are generated and compared with measurements. It is shown this model gives acceptable results and is useful for determining rough estimates of sensor output for various loads, laminate configurations and thicknesses.

Integrated, Accountable Care For Medicaid Expansion Enrollees: A Comparative Evaluation of Hennepin Health.

PubMed

Vickery, Katherine D; Shippee, Nathan D; Menk, Jeremiah; Owen, Ross; Vock, David M; Bodurtha, Peter; Soderlund, Dana; Hayward, Rodney A; Davis, Matthew M; Connett, John; Linzer, Mark

2018-05-01

Hennepin Health, a Medicaid accountable care organization, began serving early expansion enrollees (very low-income childless adults) in 2012. It uses an integrated care model to address social and behavioral needs. We compared health care utilization in Hennepin Health with other Medicaid managed care in the same area from 2012 to 2014, controlling for demographics, chronic conditions, and enrollment patterns. Homelessness and substance use were higher in Hennepin Health. Overall adjusted results showed Hennepin Health had 52% more emergency department visits and 11% more primary care visits than comparators. Over time, modeling a 6-month exposure to Hennepin Health, emergency department and primary care visits decreased and dental visits increased; hospitalizations decreased nonsignificantly but increased among comparators. Subgroup analysis of high utilizers showed lower hospitalizations in Hennepin Health. Integrated, accountable care under Medicaid expansion showed some desirable trends and subgroup benefits, but overall did not reduce acute health care utilization versus other managed care.

Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks.

PubMed

Yap, Florence G H; Yen, Hong-Hsu

2016-12-30

In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor's visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs.

Ultrasonic imaging of seismic physical models using a fringe visibility enhanced fiber-optic Fabry-Perot interferometric sensor.

PubMed

Zhang, Wenlu; Chen, Fengyi; Ma, Wenwen; Rong, Qiangzhou; Qiao, Xueguang; Wang, Ruohui

2018-04-16

A fringe visibility enhanced fiber-optic Fabry-Perot interferometer based ultrasonic sensor is proposed and experimentally demonstrated for seismic physical model imaging. The sensor consists of a graded index multimode fiber collimator and a PTFE (polytetrafluoroethylene) diaphragm to form a Fabry-Perot interferometer. Owing to the increase of the sensor's spectral sideband slope and the smaller Young's modulus of the PTFE diaphragm, a high response to both continuous and pulsed ultrasound with a high SNR of 42.92 dB in 300 kHz is achieved when the spectral sideband filter technique is used to interrogate the sensor. The ultrasonic reconstructed images can clearly differentiate the shape of models with a high resolution.

Predictive simulations and optimization of nanowire field-effect PSA sensors including screening

NASA Astrophysics Data System (ADS)

Baumgartner, Stefan; Heitzinger, Clemens; Vacic, Aleksandar; Reed, Mark A.

2013-06-01

We apply our self-consistent PDE model for the electrical response of field-effect sensors to the 3D simulation of nanowire PSA (prostate-specific antigen) sensors. The charge concentration in the biofunctionalized boundary layer at the semiconductor-electrolyte interface is calculated using the propka algorithm, and the screening of the biomolecules by the free ions in the liquid is modeled by a sensitivity factor. This comprehensive approach yields excellent agreement with experimental current-voltage characteristics without any fitting parameters. Having verified the numerical model in this manner, we study the sensitivity of nanowire PSA sensors by changing device parameters, making it possible to optimize the devices and revealing the attributes of the optimal field-effect sensor.

A data management infrastructure for bridge monitoring

NASA Astrophysics Data System (ADS)

Jeong, Seongwoon; Byun, Jaewook; Kim, Daeyoung; Sohn, Hoon; Bae, In Hwan; Law, Kincho H.

2015-04-01

This paper discusses a data management infrastructure framework for bridge monitoring applications. As sensor technologies mature and become economically affordable, their deployment for bridge monitoring will continue to grow. Data management becomes a critical issue not only for storing the sensor data but also for integrating with the bridge model to support other functions, such as management, maintenance and inspection. The focus of this study is on the effective data management of bridge information and sensor data, which is crucial to structural health monitoring and life cycle management of bridge structures. We review the state-of-the-art of bridge information modeling and sensor data management, and propose a data management framework for bridge monitoring based on NoSQL database technologies that have been shown useful in handling high volume, time-series data and to flexibly deal with unstructured data schema. Specifically, Apache Cassandra and Mongo DB are deployed for the prototype implementation of the framework. This paper describes the database design for an XML-based Bridge Information Modeling (BrIM) schema, and the representation of sensor data using Sensor Model Language (SensorML). The proposed prototype data management framework is validated using data collected from the Yeongjong Bridge in Incheon, Korea.

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks

PubMed Central

Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei

2017-01-01

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator’s mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost. PMID:28098748

The Importance of Efficacy: Using the Extended Parallel Process Model to Examine Factors Related to Preschool-Age Children Enrolled in Medicaid Receiving Preventive Dental Visits

ERIC Educational Resources Information Center

Askelson, Natoshia M.; Chi, Donald L.; Momany, Elizabeth T.; Kuthy, Raymond A.; Carter, Knute D.; Field, Kathryn; Damiano, Peter C.

2015-01-01

Early preventive dental visits are vital to the oral health of children. Yet many children, especially preschool-age children enrolled in Medicaid, do not receive early visits. This study attempts to uncover factors that can be used to encourage parents to seek preventive dental care for preschool-age children enrolled in Medicaid. The extended…

An optimal state estimation model of sensory integration in human postural balance

NASA Astrophysics Data System (ADS)

Kuo, Arthur D.

2005-09-01

We propose a model for human postural balance, combining state feedback control with optimal state estimation. State estimation uses an internal model of body and sensor dynamics to process sensor information and determine body orientation. Three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These are mated with a two degree-of-freedom model of body dynamics in the sagittal plane. Linear quadratic optimal control is used to design state feedback and estimation gains. Nine free parameters define the control objective and the signal-to-noise ratios of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with normal human responses to alterations in sensory conditions. With a single parameter set, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Parameter variations reveal that the model is highly robust under normal sensory conditions, but not when two or more sensors are inaccurate. This behavior is similar to that of normal human subjects. We propose that age-related sensory changes may be modeled with decreased signal-to-noise ratios, and compare the model's behavior with degraded sensors against experimental measurements from older adults. We also examine removal of the model's vestibular sense, which leads to instability similar to that observed in bilateral vestibular loss subjects. The model may be useful for predicting which sensors are most critical for balance, and how much they can deteriorate before posture becomes unstable.

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

NASA Astrophysics Data System (ADS)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.

Target Coverage in Wireless Sensor Networks with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao

2016-01-01

Sensing coverage is a fundamental problem in wireless sensor networks (WSNs), which has attracted considerable attention. Conventional research on this topic focuses on the 0/1 coverage model, which is only a coarse approximation to the practical sensing model. In this paper, we study the target coverage problem, where the objective is to find the least number of sensor nodes in randomly-deployed WSNs based on the probabilistic sensing model. We analyze the joint detection probability of target with multiple sensors. Based on the theoretical analysis of the detection probability, we formulate the minimum ϵ-detection coverage problem. We prove that the minimum ϵ-detection coverage problem is NP-hard and present an approximation algorithm called the Probabilistic Sensor Coverage Algorithm (PSCA) with provable approximation ratios. To evaluate our design, we analyze the performance of PSCA theoretically and also perform extensive simulations to demonstrate the effectiveness of our proposed algorithm. PMID:27618902

Development of esMOCA RULA, Motion Capture Instrumentation for RULA Assessment

NASA Astrophysics Data System (ADS)

Akhmad, S.; Arendra, A.

2018-01-01

The purpose of this research is to build motion capture instrumentation using sensors fusion accelerometer and gyroscope to assist in RULA assessment. Data processing of sensor orientation is done in every sensor node by digital motion processor. Nine sensors are placed in the upper limb of operator subject. Development of kinematics model is done with Simmechanic Simulink. This kinematics model receives streaming data from sensors via wireless sensors network. The output of the kinematics model is the relative angular angle between upper limb members and visualized on the monitor. This angular information is compared to the look-up table of the RULA worksheet and gives the RULA score. The assessment result of the instrument is compared with the result of the assessment by rula assessors. To sum up, there is no significant difference of assessment by the instrument with an assessment by an assessor.

Automatic Earth observation data service based on reusable geo-processing workflow

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Gong, Jianya; Yu, Genong; Min, Min

2008-12-01

A common Sensor Web data service framework for Geo-Processing Workflow (GPW) is presented as part of the NASA Sensor Web project. This framework consists of a data service node, a data processing node, a data presentation node, a Catalogue Service node and BPEL engine. An abstract model designer is used to design the top level GPW model, model instantiation service is used to generate the concrete BPEL, and the BPEL execution engine is adopted. The framework is used to generate several kinds of data: raw data from live sensors, coverage or feature data, geospatial products, or sensor maps. A scenario for an EO-1 Sensor Web data service for fire classification is used to test the feasibility of the proposed framework. The execution time and influences of the service framework are evaluated. The experiments show that this framework can improve the quality of services for sensor data retrieval and processing.

Mental health status and healthcare utilization among community dwelling older adults.

PubMed

Adepoju, Omolola; Lin, Szu-Hsuan; Mileski, Michael; Kruse, Clemens Scott; Mask, Andrew

2018-04-27

Shifts in mental health utilization patterns are necessary to allow for meaningful access to care for vulnerable populations. There have been long standing issues in how mental health is provided, which has caused problems in that care being efficacious for those seeking it. To assess the relationship between mental health status and healthcare utilization among adults ≥65 years. A negative binomial regression model was used to assess the relationship between mental health status and healthcare utilization related to office-based physician visits, while a two-part model, consisting of logistic regression and negative binomial regression, was used to separately model emergency visits and inpatient services. The receipt of care in office-based settings were marginally higher for subjects with mental health difficulties. Both probabilities and counts of inpatient hospitalizations were similar across mental health categories. The count of ER visits was similar across mental health categories; however, the probability of having an emergency department visit was marginally higher for older adults who reported mental health difficulties in 2012. These findings are encouraging and lend promise to the recent initiatives on addressing gaps in mental healthcare services.

Numerical modeling and performance analysis of zinc oxide (ZnO) thin-film based gas sensor

NASA Astrophysics Data System (ADS)

Punetha, Deepak; Ranjan, Rashmi; Pandey, Saurabh Kumar

2018-05-01

This manuscript describes the modeling and analysis of Zinc Oxide thin film based gas sensor. The conductance and sensitivity of the sensing layer has been described by change in temperature as well as change in gas concentration. The analysis has been done for reducing and oxidizing agents. Simulation results revealed the change in resistance and sensitivity of the sensor with respect to temperature and different gas concentration. To check the feasibility of the model, all the simulated results have been analyze by different experimental reported work. Wolkenstein theory has been used to model the proposed sensor and the simulation results have been shown by using device simulation software.

Allothetic and idiothetic sensor fusion in rat-inspired robot localization

NASA Astrophysics Data System (ADS)

Weitzenfeld, Alfredo; Fellous, Jean-Marc; Barrera, Alejandra; Tejera, Gonzalo

2012-06-01

We describe a spatial cognition model based on the rat's brain neurophysiology as a basis for new robotic navigation architectures. The model integrates allothetic (external visual landmarks) and idiothetic (internal kinesthetic information) cues to train either rat or robot to learn a path enabling it to reach a goal from multiple starting positions. It stands in contrast to most robotic architectures based on SLAM, where a map of the environment is built to provide probabilistic localization information computed from robot odometry and landmark perception. Allothetic cues suffer in general from perceptual ambiguity when trying to distinguish between places with equivalent visual patterns, while idiothetic cues suffer from imprecise motions and limited memory recalls. We experiment with both types of cues in different maze configurations by training rats and robots to find the goal starting from a fixed location, and then testing them to reach the same target from new starting locations. We show that the robot, after having pre-explored a maze, can find a goal with improved efficiency, and is able to (1) learn the correct route to reach the goal, (2) recognize places already visited, and (3) exploit allothetic and idiothetic cues to improve on its performance. We finally contrast our biologically-inspired approach to more traditional robotic approaches and discuss current work in progress.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media

PubMed Central

Watson, Keri B.; Wood, Spencer A.; Ricketts, Taylor H.

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making. PMID:27611325

Enhancing the evaluation of pathogen transmission risk in a hospital by merging hand-hygiene compliance and contact data: a proof-of-concept study.

PubMed

Mastrandrea, Rossana; Soto-Aladro, Alberto; Brouqui, Philippe; Barrat, Alain

2015-09-10

Hand-hygiene compliance and contacts of health-care workers largely determine the potential paths of pathogen transmission in hospital wards. We explored how the combination of data collected by two automated infrastructures based on wearable sensors and recording (1) use of hydro-alcoholic solution and (2) contacts of health-care workers provide an enhanced view of the risk of transmission events in the ward. We perform a proof-of-concept observational study. Detailed data on contact patterns and hand-hygiene compliance of health-care workers were collected by wearable sensors over 12 days in an infectious disease unit of a hospital in Marseilles, France. 10,837 contact events among 10 doctors, 4 nurses, 4 nurses' aids and 4 housekeeping staff were recorded during the study. Most contacts took place among medical doctors. Aggregate contact durations were highly heterogeneous and the resulting contact network was highly structured. 510 visits of health-care workers to patients' rooms were recorded, with a low rate of hand-hygiene compliance. Both data sets were used to construct histories and statistics of contacts informed by the use of hydro-alcoholic solution, or lack thereof, of the involved health-care workers. Hand-hygiene compliance data strongly enrich the information concerning contacts among health-care workers, by assigning a 'safe' or 'at-risk' value to each contact. The global contact network can thus be divided into 'at-risk' and 'safe' contact networks. The combined data could be of high relevance for outbreak investigation and to inform data-driven models of nosocomial disease spread.

Controller adherence following hospital discharge in high risk children: A pilot randomized trial of text message reminders.

PubMed

Kenyon, Chén C; Gruschow, Siobhan M; Quarshie, William O; Griffis, Heather; Leach, Michelle C; Zorc, Joseph J; Bryant-Stephens, Tyra C; Miller, Victoria A; Feudtner, Chris

2018-02-13

To assess the feasibility of a mobile health, inhaled corticosteroid (ICS) adherence reminder intervention and to characterize adherence trajectories immediately following severe asthma exacerbation in high-risk urban children with persistent asthma. Children aged 2-13 with persistent asthma were enrolled in this pilot randomized controlled trial during an asthma emergency department (ED) visit or hospitalization. Intervention arm participants received daily text message reminders for 30 days, and both arms received electronic sensors to measure ICS use. Primary outcomes were feasibility of sensor use and text message acceptability. Secondary outcomes included adherence to prescribed ICS regimen and 30-day adherence trajectories. Group-based trajectory modeling was used to examine adherence trajectories. Forty-one participants (mean age 5.9) were randomized to intervention (n = 21) or control (n = 20). Overall, 85% were Black, 88% had public insurance, and 51% of the caregivers had a high school education or less. Thirty-two participant families (78%) transmitted medication adherence data; of caregivers who completed the acceptability survey, 25 (96%) chose to receive daily reminders beyond that study interval. Secondary outcome analyses demonstrated similar average daily adherence between groups (intervention = 36%; control = 32%, P = 0.73). Three adherence trajectories were identified with none ever exceeding 80% adherence. Within a high-risk pediatric cohort, electronic monitoring of ICS use and adherence reminders delivered via text message were feasible for most participants, but there was no signal of effect. Adherence trajectories following severe exacerbation were suboptimal, demonstrating an important opportunity for asthma care improvement.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

PubMed

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-09-21

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

Active vibration control using a modal-domain fiber optic sensor

NASA Technical Reports Server (NTRS)

Cox, David E.

1992-01-01

A closed-loop control experiment is described in which vibrations of a cantilevered beam are suppressed using measurements from a modal-domain fiber optic sensor. Modal-domain sensors are interference between the modes of a few-mode optical waveguide to detect strain. The fiber is bonded along the length of the beam and provides a measurement related to the strain distribution on the surface of the beam. A model for the fiber optic sensor is derived, and this model is integrated with the dynamic model of the beam. A piezoelectric actuator is also bonded to the beam and used to provide control forces. Control forces are obtained through dynamic compensation of the signal from the fiber optic sensor. The compensator is implemented with a real-time digital controller. Analytical models are verified by comparing simulations to experimental results for both open-loop and closed-loop configurations.

Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

NASA Astrophysics Data System (ADS)

Missif, Lial Raja; Kadhum, Mohammad M.

2017-09-01

Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

Spatiotemporal Patterns of Urban Human Mobility

NASA Astrophysics Data System (ADS)

Hasan, Samiul; Schneider, Christian M.; Ukkusuri, Satish V.; González, Marta C.

2013-04-01

The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others. In this study, we consider the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns. We present a simple mobility model for predicting peoples' visited locations using the popularity of places in the city as an interaction parameter between different individuals. This ingredient is sufficient to reproduce several characteristics of the observed travel behavior such as: the number of trips between different locations in the city, the exploration of new places and the frequency of individual visits of a particular location. Moreover, we indicate the limitations of the proposed model and discuss open questions in the current state of the art statistical models of human mobility.

Characteristics of asthmatic patients with and without repeat emergency department visits at an inner city hospital.

PubMed

Pai, Sucheta; Mancuso, Carol A; Loganathan, Raghu; Boutin-Foster, Carla; Basir, Riyad; Kanna, Balavenkatesh

2014-08-01

Abstract Objective: The objective of this study was to document the frequency and clinical characteristics associated with repeat emergency department (ED) visits for asthma in an inner city population with a high burden of asthma. During an ED visit for asthma in an inner city hospital ('index visit'), patients completed a valid survey addressing disease and behavioral factors. Hospital records were reviewed for information about ED visits and hospitalizations for asthma during the 12 months before and the 90 days after the index visit. One hundred and ninety-two patients were enrolled; the mean age was 42 years, 69% were women, 36% were black, 54% were Latino, 69% had Medicaid, and 17% were uninsured. 100 patients (52%) were treated and released from the ED, 88 patients (46%) were hospitalized, and 4 patients (2%) left against medical advice. During the subsequent 90 days, 64 patients (33%) had at least one repeat ED visit for asthma and 27 (14%) were hospitalized for asthma. In a multivariate model, more past ED visits (OR 1.7, 95% CI 1.4, 2.1; p < 0.0001) and male gender (OR 2.5, 95% CI 1.2, 5.4; p = 0.02) remained associated with having a repeat ED visit. Most patients had the first repeat ED visit within 30 days and 18 returned within only 7 days. Among all patients with a repeat visit, those who were not hospitalized for the index visit were more likely to have a repeat visit within 7 days (37%) compared to those who were hospitalized (17%) (p = 0.05 in multivariate analysis). Repeat ED visits were prevalent among inner city asthma patients and most occurred shortly after the index visit. The strongest predictors of repeat visits were male gender and more ED visits in the 12 months before the index visit.

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

PubMed Central

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-01-01

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

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

PubMed

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-05-05

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

Software sensors for biomass concentration in a SSC process using artificial neural networks and support vector machine.

PubMed

Acuña, Gonzalo; Ramirez, Cristian; Curilem, Millaray

2014-01-01

The lack of sensors for some relevant state variables in fermentation processes can be coped by developing appropriate software sensors. In this work, NARX-ANN, NARMAX-ANN, NARX-SVM and NARMAX-SVM models are compared when acting as software sensors of biomass concentration for a solid substrate cultivation (SSC) process. Results show that NARMAX-SVM outperforms the other models with an SMAPE index under 9 for a 20 % amplitude noise. In addition, NARMAX models perform better than NARX models under the same noise conditions because of their better predictive capabilities as they include prediction errors as inputs. In the case of perturbation of initial conditions of the autoregressive variable, NARX models exhibited better convergence capabilities. This work also confirms that a difficult to measure variable, like biomass concentration, can be estimated on-line from easy to measure variables like CO₂ and O₂ using an adequate software sensor based on computational intelligence techniques.

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

ROBUST ONLINE MONITORING FOR CALIBRATION ASSESSMENT OF TRANSMITTERS AND INSTRUMENTATION

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

Ramuhalli, Pradeep; Tipireddy, Ramakrishna; Lerchen, Megan E.

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Specifically, the next generation of OLM technology is expected to include newly developed advanced algorithms that improve monitoring of sensor/system performance and enable the use of plant data to derive information that currently cannot be measured. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research beingmore » performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation – fault detection and selection of acceptance criteria • Virtual sensing – signal value prediction and acceptance criteria • Response-time assessment – fault detection and acceptance criteria selection A GP-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for use in sensor-fault detection and virtual sensing. For signal validation, the various components to the OLM residual (which is computed using an AAKR model) were explicitly defined and modeled using a GP. Evaluation was conducted using flow loop data from multiple sources. Results using experimental data from laboratory-scale flow loops indicate that the approach, while capable of detecting sensor drift, may be incapable of discriminating between sensor drift and model inadequacy. This may be due to a simplification applied in the initial modeling, where the sensor degradation is assumed to be stationary. In the case of virtual sensors, the GP model was used in a predictive mode to estimate the correct sensor reading for sensors that may have failed. Results have indicated the viability of using this approach for virtual sensing. However, the GP model has proven to be computationally expensive, and so alternative algorithms for virtual sensing are being evaluated. Finally, automated approaches to performing noise analysis for extracting sensor response time were developed. Evaluation of this technique using laboratory-scale data indicates that it compares well with manual techniques previously used for noise analysis. Moreover, the automated and manual approaches for noise analysis also compare well with the current “gold standard”, hydraulic ramp testing, for response time monitoring. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.« less

Approximations to camera sensor noise

NASA Astrophysics Data System (ADS)

Jin, Xiaodan; Hirakawa, Keigo

2013-02-01

Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.

Energy modelling in sensor networks

NASA Astrophysics Data System (ADS)

Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

2007-06-01

Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

Temperature variation effects on stochastic characteristics for low-cost MEMS-based inertial sensor error

NASA Astrophysics Data System (ADS)

El-Diasty, M.; El-Rabbany, A.; Pagiatakis, S.

2007-11-01

We examine the effect of varying the temperature points on MEMS inertial sensors' noise models using Allan variance and least-squares spectral analysis (LSSA). Allan variance is a method of representing root-mean-square random drift error as a function of averaging times. LSSA is an alternative to the classical Fourier methods and has been applied successfully by a number of researchers in the study of the noise characteristics of experimental series. Static data sets are collected at different temperature points using two MEMS-based IMUs, namely MotionPakII and Crossbow AHRS300CC. The performance of the two MEMS inertial sensors is predicted from the Allan variance estimation results at different temperature points and the LSSA is used to study the noise characteristics and define the sensors' stochastic model parameters. It is shown that the stochastic characteristics of MEMS-based inertial sensors can be identified using Allan variance estimation and LSSA and the sensors' stochastic model parameters are temperature dependent. Also, the Kaiser window FIR low-pass filter is used to investigate the effect of de-noising stage on the stochastic model. It is shown that the stochastic model is also dependent on the chosen cut-off frequency.

A hybrid electronically scanned pressure module for cryogenic environments

NASA Technical Reports Server (NTRS)

Chapman, J. J.; Hopson, P., Jr.; Kruse, N.

1995-01-01

Pressure is one of the most important parameters measured when testing models in wind tunnels. For models tested in the cryogenic environment of the National Transonic Facility at NASA Langley Research Center, the technique of utilizing commercially available multichannel pressure modules inside the models is difficult due to the small internal volume of the models and the requirement of keeping the pressure transducer modules within an acceptable temperature range well above the -173 degrees C tunnel temperature. A prototype multichannel pressure transducer module has been designed and fabricated with stable, repeatable sensors and materials optimized for reliable performance in the cryogenic environment. The module has 16 single crystal silicon piezoresistive pressure sensors electrostatically bonded to a metalized Pyrex substrate for sensing the wind tunnel model pressures. An integral temperature sensor mounted on each silicon micromachined pressure sensor senses real-time temperature fluctuations to within 0.1 degrees C to correct for thermally induced non-random sensor drift. The data presented here are from a prototype sensor module tested in the 0.3 M cryogenic tunnel and thermal equilibrium conditions in an environmental chamber which approximates the thermal environment (-173 degrees C to +60 degrees C) of the National Transonic Facility.

Deployment-based lifetime optimization model for homogeneous Wireless Sensor Network under retransmission.

PubMed

Li, Ruiying; Liu, Xiaoxi; Xie, Wei; Huang, Ning

2014-12-10

Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.

An Observation Capability Semantic-Associated Approach to the Selection of Remote Sensing Satellite Sensors: A Case Study of Flood Observations in the Jinsha River Basin.

PubMed

Hu, Chuli; Li, Jie; Lin, Xin; Chen, Nengcheng; Yang, Chao

2018-05-21

Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA) ontology model that is resolved around the task-sensor-observation capability (TSOC) ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO) ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors.

Detection of a Moving Gas Source and Estimation of its Concentration Field with a Sensing Aerial Vehicle Integration of Theoretical Controls and Computational Fluids

DTIC Science & Technology

2016-07-21

constants. The model (2.42) is popular for simulation of the UAV motion [60], [61], [62] due to the fact that it models the aircraft response to...inputs to the dynamic model (2.42). The concentration sensors onboard the UAV record concentration ( simulated ) data according to its spatial location...vehicle dynamics and guidance, and the onboard sensor modeling . 15. SUBJECT TERMS State estimation; UAVs , mobile sensors; grid adaptationj; plume

Review of infrared technology in The Netherlands

NASA Astrophysics Data System (ADS)

de Jong, Arie N.

1993-11-01

The use of infrared sensors in the Netherlands is substantial. Users can be found in a variety of disciplines, military as well as civil. This need for IR sensors implied a long history on IR technology and development. The result was a large technological-capability allowing the realization of IR hardware: specialized measuring equipment, engineering development models, prototype and production sensors for different applications. These applications range from small size, local radiometry up to large space-borne imaging. Large scale production of IR sensors has been realized for army vehicles. IR sensors have been introduced now in all of the armed forces. Facilities have been built to test the performance of these sensors. Models have been developed to predict the performance of a new sensor. A great effort has been spent on atmospheric research, leading to knowledge upon atmospheric- and background limitations of IR sensors.

Development of a Dynamic Web Mapping Service for Vegetation Productivity Using Earth Observation and in situ Sensors in a Sensor Web Based Approach

PubMed Central

Kooistra, Lammert; Bergsma, Aldo; Chuma, Beatus; de Bruin, Sytze

2009-01-01

This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS). A prototype has been developed which provides daily maps of vegetation productivity for the Netherlands with a spatial resolution of 250 m. Daily available MODIS surface reflectance products and meteorological parameters obtained through a Sensor Observation Service (SOS) were used as input for a vegetation productivity model. This paper presents the vegetation productivity model, the sensor data sources and the implementation of the automated processing facility. Finally, an evaluation is made of the opportunities and limitations of sensor web based approaches for the development of web services which combine both satellite and in situ sensor sources. PMID:22574019

Flexible Skins Containing Integrated Sensors and Circuitry

NASA Technical Reports Server (NTRS)

Liu, Chang

2007-01-01

Artificial sensor skins modeled partly in imitation of biological sensor skins are undergoing development. These sensor skins comprise flexible polymer substrates that contain and/or support dense one- and two-dimensional arrays of microscopic sensors and associated microelectronic circuits. They afford multiple tactile sensing modalities for measuring physical phenomena that can include contact forces; hardnesses, temperatures, and thermal conductivities of objects with which they are in contact; and pressures, shear stresses, and flow velocities in fluids. The sensor skins are mechanically robust, and, because of their flexibility, they can be readily attached to curved and possibly moving and flexing surfaces of robots, wind-tunnel models, and other objects that one might seek to equip for tactile sensing. Because of the diversity of actual and potential sensor-skin design criteria and designs and the complexity of the fabrication processes needed to realize the designs, it is not possible to describe the sensor-skin concept in detail within this article.

A funding model for health visiting: baseline requirements--part 1.

PubMed

Cowley, Sarah

2007-11-01

A funding model proposed in two papers will outline the health visiting resource, including team skill mix, required to deliver the recommended approach of 'progressive universalism,' taking account of health inequalities, best evidence and impact on outcomes that might be anticipated. The model has been discussed as far as possible across the professional networks of both the Community Practitioners' and Health Visitors' Association (CPHVA) and United Kingdom Public Health Association (UKPHA), and is a consensus statement agreed by all who have participated.

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

PubMed Central

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated construction of node software using attributes in a ubiquitous sensor network environment.

PubMed

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Model-Based Method for Sensor Validation

NASA Technical Reports Server (NTRS)

Vatan, Farrokh

2012-01-01

Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

NASA Technical Reports Server (NTRS)

Matthies, Larry; Grandjean, Pierrick

1993-01-01

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

Model-Scale Experiment of the Seakeeping Performance for R/V Melville, Model 5720

DTIC Science & Technology

2012-07-01

Angle 1 Y None Deg Sensor Bourns Rotary Potentiometer 6574S-1-103 NA 39596 KVH Sin 2 Y None volts Sensor KVH Fluxgate Compass C-100...NA Deg Sensor KVH Calc Heading NA N None DegM Calculated KVH Fluxgate Compass C-100 39449 Bow Tracker Sensor Bottom NA N None...3DM-3XI combined three axis of angular rate gyros, accelerometers, and magnetometers to provide various combinations of gyro stabilized Euler

Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis.

PubMed

Zhang, Chao; Zhang, Pengcheng; Zhang, Weizhan

2017-09-27

A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation.

Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis

PubMed Central

Zhang, Chao; Zhang, Pengcheng; Zhang, Weizhan

2017-01-01

A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation. PMID:28953231

A theoretical model to predict both horizontal displacement and vertical displacement for electromagnetic induction-based deep displacement sensors.

PubMed

Shentu, Nanying; Zhang, Hongjian; Li, Qing; Zhou, Hongliang; Tong, Renyuan; Li, Xiong

2012-01-01

Deep displacement observation is one basic means of landslide dynamic study and early warning monitoring and a key part of engineering geological investigation. In our previous work, we proposed a novel electromagnetic induction-based deep displacement sensor (I-type) to predict deep horizontal displacement and a theoretical model called equation-based equivalent loop approach (EELA) to describe its sensing characters. However in many landslide and related geological engineering cases, both horizontal displacement and vertical displacement vary apparently and dynamically so both may require monitoring. In this study, a II-type deep displacement sensor is designed by revising our I-type sensor to simultaneously monitor the deep horizontal displacement and vertical displacement variations at different depths within a sliding mass. Meanwhile, a new theoretical modeling called the numerical integration-based equivalent loop approach (NIELA) has been proposed to quantitatively depict II-type sensors' mutual inductance properties with respect to predicted horizontal displacements and vertical displacements. After detailed examinations and comparative studies between measured mutual inductance voltage, NIELA-based mutual inductance and EELA-based mutual inductance, NIELA has verified to be an effective and quite accurate analytic model for characterization of II-type sensors. The NIELA model is widely applicable for II-type sensors' monitoring on all kinds of landslides and other related geohazards with satisfactory estimation accuracy and calculation efficiency.

Exponential Modelling for Mutual-Cohering of Subband Radar Data

NASA Astrophysics Data System (ADS)

Siart, U.; Tejero, S.; Detlefsen, J.

2005-05-01

Increasing resolution and accuracy is an important issue in almost any type of radar sensor application. However, both resolution and accuracy are strongly related to the available signal bandwidth and energy that can be used. Nowadays, often several sensors operating in different frequency bands become available on a sensor platform. It is an attractive goal to use the potential of advanced signal modelling and optimization procedures by making proper use of information stemming from different frequency bands at the RF signal level. An important prerequisite for optimal use of signal energy is coherence between all contributing sensors. Coherent multi-sensor platforms are greatly expensive and are thus not available in general. This paper presents an approach for accurately estimating object radar responses using subband measurements at different RF frequencies. An exponential model approach allows to compensate for the lack of mutual coherence between independently operating sensors. Mutual coherence is recovered from the a-priori information that both sensors have common scattering centers in view. Minimizing the total squared deviation between measured data and a full-range exponential signal model leads to more accurate pole angles and pole magnitudes compared to single-band optimization. The model parameters (range and magnitude of point scatterers) after this full-range optimization process are also more accurate than the parameters obtained from a commonly used super-resolution procedure (root-MUSIC) applied to the non-coherent subband data.

Comparative analysis of tree classification models for detecting fusarium oxysporum f. sp cubense (TR4) based on multi soil sensor parameters

NASA Astrophysics Data System (ADS)

Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica

2017-09-01

Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.

Applying additive logistic regression to data derived from sensors monitoring behavioral and physiological characteristics of dairy cows to detect lameness.

PubMed

Kamphuis, C; Frank, E; Burke, J K; Verkerk, G A; Jago, J G

2013-01-01

The hypothesis was that sensors currently available on farm that monitor behavioral and physiological characteristics have potential for the detection of lameness in dairy cows. This was tested by applying additive logistic regression to variables derived from sensor data. Data were collected between November 2010 and June 2012 on 5 commercial pasture-based dairy farms. Sensor data from weigh scales (liveweight), pedometers (activity), and milk meters (milking order, unadjusted and adjusted milk yield in the first 2 min of milking, total milk yield, and milking duration) were collected at every milking from 4,904 cows. Lameness events were recorded by farmers who were trained in detecting lameness before the study commenced. A total of 318 lameness events affecting 292 cows were available for statistical analyses. For each lameness event, the lame cow's sensor data for a time period of 14 d before observation date were randomly matched by farm and date to 10 healthy cows (i.e., cows that were not lame and had no other health event recorded for the matched time period). Sensor data relating to the 14-d time periods were used for developing univariable (using one source of sensor data) and multivariable (using multiple sources of sensor data) models. Model development involved the use of additive logistic regression by applying the LogitBoost algorithm with a regression tree as base learner. The model's output was a probability estimate for lameness, given the sensor data collected during the 14-d time period. Models were validated using leave-one-farm-out cross-validation and, as a result of this validation, each cow in the data set (318 lame and 3,180 nonlame cows) received a probability estimate for lameness. Based on the area under the curve (AUC), results indicated that univariable models had low predictive potential, with the highest AUC values found for liveweight (AUC=0.66), activity (AUC=0.60), and milking order (AUC=0.65). Combining these 3 sensors improved AUC to 0.74. Detection performance of this combined model varied between farms but it consistently and significantly outperformed univariable models across farms at a fixed specificity of 80%. Still, detection performance was not high enough to be implemented in practice on large, pasture-based dairy farms. Future research may improve performance by developing variables based on sensor data of liveweight, activity, and milking order, but that better describe changes in sensor data patterns when cows go lame. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Smart Elasto-Magneto-Electric (EME) Sensors for Stress Monitoring of Steel Cables: Design Theory and Experimental Validation

PubMed Central

Zhang, Ru; Duan, Yuanfeng; Or, Siu Wing; Zhao, Yang

2014-01-01

An elasto-magnetic (EM) and magneto-electric (ME) effect based elasto-magneto-electric (EME) sensor has been proposed recently by the authors for stress monitoring of steel cables with obvious superiorities over traditional elasto-magnetic sensors. For design optimization and engineering application of the EME sensor, the design theory is interpreted with a developed model taking into account the EM coupling effect and ME coupling effect. This model is able to approximate the magnetization changes that a steel structural component undergoes when subjected to excitation magnetic field and external stress, and to simulate the induced ME voltages of the ME sensing unit located in the magnetization area. A full-scale experiment is then carried out to verify the model and to calibrate the EME sensor as a non-destructive evaluation (NDE) tool to monitor the cable stress. The experimental results agree well with the simulation results using the developed model. The proposed EME sensor proves to be feasible for stress monitoring of steel cables with high sensitivity, fast response, and ease of installation. PMID:25072348

Smart elasto-magneto-electric (EME) sensors for stress monitoring of steel cables: design theory and experimental validation.

PubMed

Zhang, Ru; Duan, Yuanfeng; Or, Siu Wing; Zhao, Yang

2014-07-28

An elasto-magnetic (EM) and magneto-electric (ME) effect based elasto-magneto-electric (EME) sensor has been proposed recently by the authors for stress monitoring of steel cables with obvious superiorities over traditional elasto-magnetic sensors. For design optimization and engineering application of the EME sensor, the design theory is interpreted with a developed model taking into account the EM coupling effect and ME coupling effect. This model is able to approximate the magnetization changes that a steel structural component undergoes when subjected to excitation magnetic field and external stress, and to simulate the induced ME voltages of the ME sensing unit located in the magnetization area. A full-scale experiment is then carried out to verify the model and to calibrate the EME sensor as a non-destructive evaluation (NDE) tool to monitor the cable stress. The experimental results agree well with the simulation results using the developed model. The proposed EME sensor proves to be feasible for stress monitoring of steel cables with high sensitivity, fast response, and ease of installation.

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

PubMed

Yin, Yihang; Liu, Fengzheng; Zhou, Xiang; Li, Quanzhong

2015-08-07

Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

PubMed Central

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

PubMed

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

Space-based infrared scanning sensor LOS determination and calibration using star observation

NASA Astrophysics Data System (ADS)

Chen, Jun; Xu, Zhan; An, Wei; Deng, Xin-Pu; Yang, Jun-Gang

2015-10-01

This paper provides a novel methodology for removing sensor bias from a space based infrared (IR) system (SBIRS) through the use of stars detected in the background field of the sensor. Space based IR system uses the LOS (line of sight) of target for target location. LOS determination and calibration is the key precondition of accurate location and tracking of targets in Space based IR system and the LOS calibration of scanning sensor is one of the difficulties. The subsequent changes of sensor bias are not been taking into account in the conventional LOS determination and calibration process. Based on the analysis of the imaging process of scanning sensor, a theoretical model based on the estimation of bias angles using star observation is proposed. By establishing the process model of the bias angles and the observation model of stars, using an extended Kalman filter (EKF) to estimate the bias angles, and then calibrating the sensor LOS. Time domain simulations results indicate that the proposed method has a high precision and smooth performance for sensor LOS determination and calibration. The timeliness and precision of target tracking process in the space based infrared (IR) tracking system could be met with the proposed algorithm.

The Impact of Ambient Air Pollution on Daily Hospital Visits for Various Respiratory Diseases and the Relevant Medical Expenditures in Shanghai, China.

PubMed

Zhang, Hao; Niu, Yue; Yao, Yili; Chen, Renjie; Zhou, Xianghong; Kan, Haidong

2018-02-28

The evidence concerning the acute effects of ambient air pollution on various respiratory diseases was limited in China, and the attributable medical expenditures were largely unknown. From 2013 to 2015, we collected data on the daily visits to the emergency- and outpatient-department for five main respiratory diseases and their medical expenditures in Shanghai, China. We used the overdispersed generalized additive model together with distributed lag models to fit the associations of criteria air pollutants with hospital visits, and used the linear models to fit the associations with medical expenditures. Generally, we observed significant increments in emergency visits (8.81-17.26%) and corresponding expenditures (0.33-25.81%) for pediatric respiratory diseases, upper respiratory infection (URI), and chronic obstructive pulmonary disease (COPD) for an interquartile range increase of air pollutant concentrations over four lag days. As a comparison, there were significant but smaller increments in outpatient visits (1.36-4.52%) and expenditures (1.38-3.18%) for pediatric respiratory diseases and upper respiratory infection (URI). No meaningful changes were observed for asthma and lower respiratory infection. Our study suggested that short-term exposure to outdoor air pollution may induce the occurrences or exacerbation of pediatric respiratory diseases, URI, and COPD, leading to considerable medical expenditures upon the patients.

The influence of humidity, temperature, and oral contraceptive in tear

NASA Astrophysics Data System (ADS)

Sousa, Raul A. R. C.; Ribeiro, Tânia L. C.; Moreira, Sandra M. B.; Baptista, António M. G.

2013-11-01

The aim of this study is to ascertain whether the quantity and quality of tear and eye subjective comfort are influenced by the temperature, humidity and oral Contraceptives Taking or Non-taking (CTNT). Forty-one students, females, from the University of Minho, Braga, Portugal, aged (mean+/-1standard deviation) of 21.51+/-1.85 years, ranging from 20 to 30 years, participated in this study. The McMonnies Questionnaire (MMQ), Break Up Time (BUT) and Phenol Red Test (PRT) were accessed between 14-17 hours in four sets of visits throughout the year: Visit 1, Visit 2, Visit 3 and Visit 4. The PRT and BUT values (mean+/-1standard deviation) for Visit 1, Visit 2, Visit 3 and Visit 4 were respectively 23.88+/-6.50mm, 22.29+/-8.00mm, 23.61+/-6.75mm, 22.88+/-7.00mm and 6.02+/-1.58s, 5.62+/-1.22s, 5.23+/-0.88s, 5.53+/-1. 42s. The MMQ scores for Visit 1, Visit 2, Visit 3 and Visit 4 ranged from 2-13, 2-15, 1-14 and 2-14 with medians of 6, 7, 6 and 6, respectively. The influence of temperature, humidity and CTNT on PRT, BUT and MMQ were evaluated using generalized linear mixed model. For BUT and MMQ statistical significant effects were found regarding temperature and humidity. The temperature and humidity influenced the tear quality and subjective comfort but did not influence the tear quantity. The CTNT did not influence tear quantity, quality or subjective eye comfort.

A novel approach to quality improvement in a safety-net practice: concurrent peer review visits.

PubMed

Fiscella, Kevin; Volpe, Ellen; Winters, Paul; Brown, Melissa; Idris, Amna; Harren, Tricia

2010-12-01

Concurrent peer review visits are structured office visits conducted by clinician peers of the primary care clinician that are specifically designed to reduce competing demands, clinical inertia, and bias. We assessed whether a single concurrent peer review visit reduced clinical inertia and improved control of hypertension, hyperlipidemia, and diabetes control among underserved patients. We conducted a randomized encouragement trial to evaluate concurrent peer review visits with a community health center. Seven hundred twenty-seven patients with hypertension, hyperlipidemia, and/or diabetes who were not at goal for systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), and/or glycated hemoglobin (A1c) were randomly assigned to an invitation to participate in a concurrent peer review visit or to usual care. We compared change in these measures using mixed models and rates of therapeutic intensification during concurrent peer review visits with control visits. One hundred seventy-one patients completed a concurrent peer review visit. SBP improved significantly (p < .01) more among those completing concurrent peer review visits than among those who failed to respond to a concurrent peer review invitation or those randomized to usual care. There were no differences seen for changes in LDL-C or A1c. Concurrent peer review visits were associated with statistically significant greater clinician intensification of blood pressure (p < .001), lipid (p < .001), and diabetes (p < .005) treatment than either for control visits for patients in either the nonresponse group or usual care group. Concurrent peer review visits represent a promising strategy for improving blood pressure control and improving therapeutic intensification in community health centers.

Family risk as a predictor of initial engagement and follow-through in a universal nurse home visiting program to prevent child maltreatment.

PubMed

Alonso-Marsden, Shelley; Dodge, Kenneth A; O'Donnell, Karen J; Murphy, Robert A; Sato, Jeannine M; Christopoulos, Christina

2013-08-01

As nurse home visiting to prevent child maltreatment grows in popularity with both program administrators and legislators, it is important to understand engagement in such programs in order to improve their community-wide effects. This report examines family demographic and infant health risk factors that predict engagement and follow-through in a universal home-based maltreatment prevention program for new mothers in Durham County, North Carolina. Trained staff members attempted to schedule home visits for all new mothers during the birthing hospital stay, and then nurses completed scheduled visits three to five weeks later. Medical record data was used to identify family demographic and infant health risk factors for maltreatment. These variables were used to predict program engagement (scheduling a visit) and follow-through (completing a scheduled visit). Program staff members were successful in scheduling 78% of eligible families for a visit and completing 85% of scheduled visits. Overall, 66% of eligible families completed at least one visit. Structural equation modeling (SEM) analyses indicated that high demographic risk and low infant health risk were predictive of scheduling a visit. Both low demographic and infant health risk were predictive of visit completion. Findings suggest that while higher demographic risk increases families' initial engagement, it might also inhibit their follow-through. Additionally, parents of medically at-risk infants may be particularly difficult to engage in universal home visiting interventions. Implications for recruitment strategies of home visiting programs are discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of electrolytic tilt sensors for wind tunnel model angle-of-attack (AOA) measurements

NASA Technical Reports Server (NTRS)

Wong, Douglas T.

1991-01-01

The results of a laboratory evaluation of three types of electrolytic tilt sensors as potential candidates for model attitude or angle of attack (AOA) measurements in wind tunnel tests are presented. Their performance was also compared with that from typical servo accelerometers used for AOA measurements. Model RG-37 electrolytic tilt sensors were found to have the highest overall accuracy among the three types. Compared with the servo accelerometer, their accuracies are about one order of magnitude worse and each of them cost about two-thirds less. Therefore, the sensors are unsuitable for AOA measurements although they are less expensive. However, the potential for other applications exists where the errors resulting from roll interaction, vibration, and response time are less, and sensor temperature can be controlled.

A physicochemical mechanism of chemical gas sensors using an AC analysis.

PubMed

Moon, Jaehyun; Park, Jin-Ah; Lee, Su-Jae; Lee, Jeong-Ik; Zyung, Taehyong; Shin, Eui-Chol; Lee, Jong-Sook

2013-06-21

Electrical modeling of the chemical gas sensors was successfully applied to TiO2 nanofiber gas sensors by developing an equivalent circuit model where the junction capacitance as well as the resistance can be separated from the comparable stray capacitance. The Schottky junction impedance exhibited a characteristic skewed arc described by a Cole-Davidson function, and the variation of the fit and derived parameters with temperature, bias, and NO2 gas concentration indicated definitely a physicochemical sensing mechanism based on the Pt|TiO2 Schottky junctions against the conventional supposition of the enhanced sensitivity in nanostructured gas sensors with high grain boundary/surface area. Analysis on a model Pt|TiO2|Pt structure also confirmed the characteristic impedance response of TiO2 nanofiber sensors.

Characteristics of Asthmatic Patients with and without Repeat Emergency Department Visits at an Inner City Hospital

PubMed Central

Pai, Sucheta; Mancuso, Carol A.; Loganathan, Raghu; Boutin-Foster, Carla; Basir, Riyad; Kanna, Balavenkatesh

2014-01-01

Objective The objective of this study was to document the frequency and clinical characteristics associated with repeat emergency department (ED) visits for asthma in an inner city population with a high burden of asthma. Methods During an ED visit for asthma in an inner city hospital (‘index visit’), patients completed a valid survey addressing disease and behavioral factors. Hospital records were reviewed for information about ED visits and hospitalizations for asthma during the 12 months before and the 90 days after the index visit. Results 192 patients were enrolled; the mean age was 42 years, 69% were women, 36% were black, 54% were Latino, 69% had Medicaid, and 17% were uninsured. 100 patients (52%) were treated and released from the ED, 88 patients (46%) were hospitalized, and 4 patients (2%) left against medical advice. During the subsequent 90 days, 64 patients (33%) had at least one repeat ED visit for asthma and 27 (14%) were hospitalized for asthma. In a multivariate model, more past ED visits (OR 1.7, 95% CI 1.4, 2.1; p<.0001) and male gender (OR 2.5, 95% CI 1.2, 5.4; p=.02) remained associated with having a repeat ED visit. Most patients had the first repeat ED visit within 30 days and 18 returned within only 7 days. Among all patients with a repeat visit, those who were not hospitalized for the index visit were more likely to have a repeat visit within 7 days (37%) compared to those who were hospitalized (17%) (p=.05 in multivariate analysis). Conclusions Repeat ED visits were prevalent among inner city asthma patients and most occurred shortly after the index visit. The strongest predictors of repeat visits were male gender and more ED visits in the 12 months before the index visit. PMID:24588683

Association between ozone and asthma emergency department visits in Saint John, New Brunswick, Canada.

PubMed Central

Stieb, D M; Burnett, R T; Beveridge, R C; Brook, J R

1996-01-01

This study examines the relationship of asthma emergency department (ED) visits to daily concentrations of ozone and other air pollutants in Saint John, New Brunswick, Canada. Data on ED visits with a presenting complaint of asthma (n = 1987) were abstracted for the period 1984-1992 (May-September). Air pollution variables included ozone, sulfur dioxide, nitrogen dioxide, sulfate, and total suspended particulate (TSP); weather variables included temperature, humidex, dewpoint, and relative humidity. Daily ED visit frequencies were filtered to remove day of the week and long wave trends, and filtered values were regressed on air pollution and weather variables for the same day and the 3 previous days. The mean daily 1-hr maximum ozone concentration during the study period was 41.6 ppb. A positive, statistically significant (p < 0.05) association was observed between ozone and asthma ED visits 2 days later, and the strength of the association was greater in nonlinear models. The frequency of asthma ED visits was 33% higher (95% CI, 10-56%) when the daily 1-hr maximum ozone concentration exceeded 75 ppb (the 95th percentile). The ozone effect was not significantly influenced by the addition of weather or other pollutant variables into the model or by the exclusion of repeat ED visits. However, given the limited number of sampling days for sulfate and TSP, a particulate effect could not be ruled out. We detected a significant association between ozone and asthma ED visits, despite the vast majority of sampling days being below current U.S. and Canadian standards. Images Figure 1. A Figure 1. B Figure 2. Figure 3. PMID:9118879

Mammalian mesocarnivore visitation at tortoise burrows in a wind farm

USGS Publications Warehouse

Agha, Mickey; Smith, Amanda L.; Lovich, Jeffrey E.; Delaney, David F.; Ennen, Joshua R.; Briggs, Jessica R.; Fleckenstein, Leo J.; Tennant, Laura A.; Puffer, Shellie R.; Walde, Andrew D.; Arundel, Terry; Price, Steven J.; Todd, Brian D.

2017-01-01

There is little information on predator–prey interactions in wind energy landscapes in North America, especially among terrestrial vertebrates. Here, we evaluated how proximity to roads and wind turbines affect mesocarnivore visitation with desert tortoises (Gopherus agassizii) and their burrows in a wind energy landscape. In 2013, we placed motion-sensor cameras facing the entrances of 46 active desert tortoise burrows in a 5.2-km2 wind energy facility near Palm Springs, California, USA. Cameras recorded images of 35 species of reptiles, mammals, and birds. Counts for 4 species of mesocarnivores at desert tortoise burrows increased closer to dirt roads, and decreased closer to wind turbines. Our results suggest that anthropogenic infrastructure associated with wind energy facilities could influence the general behavior of mammalian predators and their prey. Further investigation of proximate mechanisms that underlie road and wind turbine effects (i.e., ground vibrations, sound emission, and traffic volume) and on wind energy facility spatial designs (i.e., road and wind turbine configuration) could prove useful for better understanding wildlife responses to wind energy development. © 2017 The Wildlife Society.

Sensor Data Qualification Technique Applied to Gas Turbine Engines

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Simon, Donald L.

2013-01-01

This paper applies a previously developed sensor data qualification technique to a commercial aircraft engine simulation known as the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k). The sensor data qualification technique is designed to detect, isolate, and accommodate faulty sensor measurements. It features sensor networks, which group various sensors together and relies on an empirically derived analytical model to relate the sensor measurements. Relationships between all member sensors of the network are analyzed to detect and isolate any faulty sensor within the network.

Testing of Streckeisen STS-5A and Nanometrics Trillium 120PH Sensors for the Alaska Transportable Array

NASA Astrophysics Data System (ADS)

Abbasi Baghbadorani, A.; Aderhold, K.; Bloomquist, D.; Frassetto, A.; Miller, P. E.; Busby, R. W.

2017-12-01

Starting in 2014, the IRIS Transportable Array facility began to install and operate seismic stations in Alaska and western Canada. By the end of the project, the full deployment of the array will cover a grid of 280 stations spaced about 85 km apart covering all of mainland Alaska and parts of the Yukon, British Columbia, and the Northwest Territories. Approximately 200 stations will be operated directly by IRIS through at least 2019. A key aspect of the Alaska TA is the need for stations to operate autonomously, on account of the high cost of installation and potential subsequent visits to remote field-sites to repair equipment. The TA is using newly developed broadband seismometers Streckeisen STS-5A and Nanometrics Trillium-120PH, designed for installation in shallow posthole emplacements. These new instruments were extensively vetted beforehand, but they are still relatively new to the TA inventory. Here we will assess their performance under deployment conditions and after repeated commercial shipping and travel to the field. Our objective is to provide a thorough accounting of the identified failures of the existing inventory of posthole instruments. We will assess the practices and results of instrument testing by the PASSCAL Instrument Center/Array Operations Facility (PIC/AOF), Alaska Operations Center (AOC), and broadband seismic sensor manufacturers (Streckeisen, Nanometrics) in order to document potential factors in and stages during the process for instrument failures. This will help to quantify the overall reliability of the TA seismic sensors and quality of TA practices and data collection, and identify potential considerations in future TA operations. Our results show that the overall rate of failure of all posthole instruments is <4% out of 260. This is lower than the rates seen for vault sensor failures in the operation of the Lower 48 Transportable Array. For telemetered stations such as these installed in the TA Alaska array, we also show that noise analyses can capture a failed emplaced sensor and reveal improved station performance after sensor replacement, and that these are key elements in assessing whether or not a sensor should be replaced in the field.

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

PubMed Central

Jiang, Hao; Zhao, Dehua; Cai, Ying; An, Shuqing

2012-01-01

In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT), the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI) as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal) thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV) of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling) normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3%) and overall (92.0%–93.1%) accuracies. Our results suggest that Method of 0.1% index scaling provides a feasible way to apply CT models directly to images from sensors or time periods that differ from those of the images used to develop the original models.

Relationship between office-based provider visits and emergency department encounters among publicly-insured adults with epilepsy.

PubMed

Lekoubou, Alain; Bishu, Kinfe G; Ovbiagele, Bruce

2018-03-01

The proportion of adults with epilepsy using the emergency department (ED) is high. Among this patient population, increased frequency of office-based provider visits may be associated with lesser frequency of ED encounters, and key patient features may be linked to more ED encounters. We analyzed the Medical Expenditure Panel Survey Household Component (MEPS-HC) dataset for years 2003-2014, which represents a weighted sample of 842,249 publicly-insured US adults aged ≥18years. The Hurdle Poisson model that accommodates excess zeros was used to estimate the association between office-based and ED visits. Annual mean ED and office-based visits for publicly-insured adults with epilepsy were 0.70 and 10.8 respectively. Probability of at least one ED visit was 0.4% higher for every unit of office-based visit. Individuals in the high income category were less likely to visit the ED at least once while women with epilepsy had a higher likelihood of visiting the ED at least once. Among those who visited the ED at least once, there was a 0.3% higher likelihood of visiting the ED for every unit of office-based visit. Among individuals who visited the ED at least once, being aged 45-64years, residing in the West, and the year 2011/14 were associated with higher ED visits. In this representative sample of publicly-insured adults with epilepsy, higher frequency of office visits was not associated with lower ED utilization, which may be due to underlying greater disease severity or propensity for more treatment complications. Copyright © 2018 Elsevier Inc. All rights reserved.

An Observation Capability Semantic-Associated Approach to the Selection of Remote Sensing Satellite Sensors: A Case Study of Flood Observations in the Jinsha River Basin

PubMed Central

Hu, Chuli; Li, Jie; Lin, Xin

2018-01-01

Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA) ontology model that is resolved around the task-sensor-observation capability (TSOC) ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO) ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors. PMID:29883425

Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks

PubMed Central

Yap, Florence G. H.; Yen, Hong-Hsu

2016-01-01

In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor’s visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs. PMID:28042829

Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things

PubMed Central

Bagula, Antoine; Abidoye, Ademola Philip; Zodi, Guy-Alain Lusilao

2015-01-01

Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices’ service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes’ life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN. PMID:26703619

Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things.

PubMed

Bagula, Antoine; Abidoye, Ademola Philip; Zodi, Guy-Alain Lusilao

2015-12-23

Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices' service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes' life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN.

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

PubMed Central

He, Xiang; Aloi, Daniel N.; Li, Jia

2015-01-01

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

PubMed

He, Xiang; Aloi, Daniel N; Li, Jia

2015-12-14

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

Development of tube-packaged FBG strain sensor and application in the vibration experiment of submarine pipeline model

NASA Astrophysics Data System (ADS)

Ren, Liang; Li, Hong-Nan; Sun, Li; Li, Dong-Sheng

2005-05-01

Optical fiber sensors have received increasing attention in the fields of aeronautic and civil engineering for their superior ability of explosion proof, immunity to electromagnetic interference and high accuracy, especially fitting for measurement applications in harsh environment. In this paper, a novel FBG (fiber Bragg grating) strain sensor, which was packaged in a 1.2mm stainless steel tube by epoxy resin, was developed. Experiments were conducted on the universal material testing machine to calibrate its strain transferring characteristics. The sensor has the advantages of small size, high precision and flexible use, and demonstrates promising potentials. Ten of tube-packaged strain FBG sensors were applied in the vibration experiment of submarine pipeline model. The strain measured by FBG sensor agrees well with the electric resistance strain sensor.

Development of tube-packaged FBG strain sensor and application in the vibration experiment of submarine pipeline model

NASA Astrophysics Data System (ADS)

Ren, Liang; Li, Hong-Nan; Sun, Li; Li, Dong-Sheng

2005-02-01

Optical fiber sensors have received increasing attention in the fields of aeronautic and civil engineering for their superior ability of explosion proof, immunity to electromagnetic interference and high accuracy, especially fitting for measurement applications in harsh environment. In this paper, a novel FBG (fiber Bragg grating) strain sensor, which was packaged in a 1.2mm stainless steel tube by epoxy resin, was developed. Experiments were conducted on the universal material testing machine to calibrate its strain transferring characteristics. The sensor has the advantages of small size, high precision and flexible use, and demonstrates promising potentials. Ten of tube-packaged strain FBG sensors were applied in the vibration experiment of submarine pipeline model. The strain measured by FBG sensor agrees well with the electric resistance strain sensor.

Semiparametric regression analysis of failure time data with dependent interval censoring.

PubMed

Chen, Chyong-Mei; Shen, Pao-Sheng

2017-09-20

Interval-censored failure-time data arise when subjects are examined or observed periodically such that the failure time of interest is not examined exactly but only known to be bracketed between two adjacent observation times. The commonly used approaches assume that the examination times and the failure time are independent or conditionally independent given covariates. In many practical applications, patients who are already in poor health or have a weak immune system before treatment usually tend to visit physicians more often after treatment than those with better health or immune system. In this situation, the visiting rate is positively correlated with the risk of failure due to the health status, which results in dependent interval-censored data. While some measurable factors affecting health status such as age, gender, and physical symptom can be included in the covariates, some health-related latent variables cannot be observed or measured. To deal with dependent interval censoring involving unobserved latent variable, we characterize the visiting/examination process as recurrent event process and propose a joint frailty model to account for the association of the failure time and visiting process. A shared gamma frailty is incorporated into the Cox model and proportional intensity model for the failure time and visiting process, respectively, in a multiplicative way. We propose a semiparametric maximum likelihood approach for estimating model parameters and show the asymptotic properties, including consistency and weak convergence. Extensive simulation studies are conducted and a data set of bladder cancer is analyzed for illustrative purposes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Modal domain fiber optic sensor for closed loop vibration control of a flexible beam

NASA Technical Reports Server (NTRS)

Cox, D.; Thomas, D.; Reichard, K.; Lindner, D.; Claus, R. O.

1990-01-01

The use of a modal domain sensor in a vibration control experiment is described. An optical fiber is bonded along the length of a flexible beam. A control signal derived from the output of the modal domain sensor is used to suppress vibrations induced in the beam. A distributed effect model for the modal domain sensor is developed and combined with models of the beam and actuator dynamics to produce a system suitable for control design.

Design and Characterization of a High Resolution Microfluidic Heat Flux Sensor with Thermal Modulation

PubMed Central

Nam, Sung-Ki; Kim, Jung-Kyun; Cho, Sung-Cheon; Lee, Sun-Kyu

2010-01-01

A complementary metal-oxide semiconductor-compatible process was used in the design and fabrication of a suspended membrane microfluidic heat flux sensor with a thermopile for the purpose of measuring the heat flow rate. The combination of a thirty-junction gold and nickel thermoelectric sensor with an ultralow noise preamplifier, a low pass filter, and a lock-in amplifier can yield a resolution 20 nW with a sensitivity of 461 V/W. The thermal modulation method is used to eliminate low-frequency noise from the sensor output, and various amounts of fluidic heat were applied to the sensor to investigate its suitability for microfluidic applications. For sensor design and analysis of signal output, a method of modeling and simulating electro-thermal behavior in a microfluidic heat flux sensor with an integrated electronic circuit is presented and validated. The electro-thermal domain model was constructed by using system dynamics, particularly the bond graph. The electro-thermal domain system model in which the thermal and the electrical domains are coupled expresses the heat generation of samples and converts thermal input to electrical output. The proposed electro-thermal domain system model is in good agreement with the measured output voltage response in both the transient and the steady state. PMID:22163568

Pairwise graphical models for structural health monitoring with dense sensor arrays

NASA Astrophysics Data System (ADS)

Mohammadi Ghazi, Reza; Chen, Justin G.; Büyüköztürk, Oral

2017-09-01

Through advances in sensor technology and development of camera-based measurement techniques, it has become affordable to obtain high spatial resolution data from structures. Although measured datasets become more informative by increasing the number of sensors, the spatial dependencies between sensor data are increased at the same time. Therefore, appropriate data analysis techniques are needed to handle the inference problem in presence of these dependencies. In this paper, we propose a novel approach that uses graphical models (GM) for considering the spatial dependencies between sensor measurements in dense sensor networks or arrays to improve damage localization accuracy in structural health monitoring (SHM) application. Because there are always unobserved damaged states in this application, the available information is insufficient for learning the GMs. To overcome this challenge, we propose an approximated model that uses the mutual information between sensor measurements to learn the GMs. The study is backed by experimental validation of the method on two test structures. The first is a three-story two-bay steel model structure that is instrumented by MEMS accelerometers. The second experimental setup consists of a plate structure and a video camera to measure the displacement field of the plate. Our results show that considering the spatial dependencies by the proposed algorithm can significantly improve damage localization accuracy.

A generalised random encounter model for estimating animal density with remote sensor data.

PubMed

Lucas, Tim C D; Moorcroft, Elizabeth A; Freeman, Robin; Rowcliffe, J Marcus; Jones, Kate E

2015-05-01

Wildlife monitoring technology is advancing rapidly and the use of remote sensors such as camera traps and acoustic detectors is becoming common in both the terrestrial and marine environments. Current methods to estimate abundance or density require individual recognition of animals or knowing the distance of the animal from the sensor, which is often difficult. A method without these requirements, the random encounter model (REM), has been successfully applied to estimate animal densities from count data generated from camera traps. However, count data from acoustic detectors do not fit the assumptions of the REM due to the directionality of animal signals.We developed a generalised REM (gREM), to estimate absolute animal density from count data from both camera traps and acoustic detectors. We derived the gREM for different combinations of sensor detection widths and animal signal widths (a measure of directionality). We tested the accuracy and precision of this model using simulations of different combinations of sensor detection widths and animal signal widths, number of captures and models of animal movement.We find that the gREM produces accurate estimates of absolute animal density for all combinations of sensor detection widths and animal signal widths. However, larger sensor detection and animal signal widths were found to be more precise. While the model is accurate for all capture efforts tested, the precision of the estimate increases with the number of captures. We found no effect of different animal movement models on the accuracy and precision of the gREM.We conclude that the gREM provides an effective method to estimate absolute animal densities from remote sensor count data over a range of sensor and animal signal widths. The gREM is applicable for count data obtained in both marine and terrestrial environments, visually or acoustically (e.g. big cats, sharks, birds, echolocating bats and cetaceans). As sensors such as camera traps and acoustic detectors become more ubiquitous, the gREM will be increasingly useful for monitoring unmarked animal populations across broad spatial, temporal and taxonomic scales.

Effects of model-mimic frequency on insect visitation and plant reproduction in a self-mimicry pollination system

PubMed Central

Oleques, Suiane Santos; Marciniak, Brisa; Ribeiro, José Ricardo I

2017-01-01

Abstract The proportion of mimics and models is a key parameter in mimetic systems. In monoecious plants with self-mimicry pollination systems, the mimic-model ratio is determined by the floral sex ratio. While an equal sex ratio (1:1) could provide the perfect balance between pollen donors and stigma surfaces able to receive the pollen, an unequal ratio could increase pollination by production of a greater number of rewarding, model flowers. The aim of the present study is to test the differences in visitation frequency and reproductive rates of different mimic and model flower arrays in order to assess the efficacy of the mimetic system in a Begonia cucullata population. The frequencies of visitors to groups of flowers with three distinctive sex ratio arrays (male-biased, female-biased and equal ratio) were compared using a Bayesian approach. The reproductive outcomes were compared in order to detect advantages of particular sex ratios. Low visitation frequency was recorded in all arrays. Pollinators showed similar behaviour regardless of sex ratio; they tended to avoid female, rewardless flowers. Pollination quality was highest in the equal sex ratio array. The current study shows that sex ratio plays a critical role in the pollination of B. cucullata and that the efficacy of the self-mimicry system appears to be doubtful. Visitation frequency may be associated with visual or chemical cues that allow pollinators to recognize models and mimics, regardless of their frequency in the population. PMID:29255587

Effects of model-mimic frequency on insect visitation and plant reproduction in a self-mimicry pollination system.

PubMed

de Avila, Rubem Samuel; Oleques, Suiane Santos; Marciniak, Brisa; Ribeiro, José Ricardo I

2017-11-01

The proportion of mimics and models is a key parameter in mimetic systems. In monoecious plants with self-mimicry pollination systems, the mimic-model ratio is determined by the floral sex ratio. While an equal sex ratio (1:1) could provide the perfect balance between pollen donors and stigma surfaces able to receive the pollen, an unequal ratio could increase pollination by production of a greater number of rewarding, model flowers. The aim of the present study is to test the differences in visitation frequency and reproductive rates of different mimic and model flower arrays in order to assess the efficacy of the mimetic system in a Begonia cucullata population. The frequencies of visitors to groups of flowers with three distinctive sex ratio arrays (male-biased, female-biased and equal ratio) were compared using a Bayesian approach. The reproductive outcomes were compared in order to detect advantages of particular sex ratios. Low visitation frequency was recorded in all arrays. Pollinators showed similar behaviour regardless of sex ratio; they tended to avoid female, rewardless flowers. Pollination quality was highest in the equal sex ratio array. The current study shows that sex ratio plays a critical role in the pollination of B. cucullata and that the efficacy of the self-mimicry system appears to be doubtful. Visitation frequency may be associated with visual or chemical cues that allow pollinators to recognize models and mimics, regardless of their frequency in the population.

Physician-patient communication in HIV disease: the importance of patient, physician, and visit characteristics.

PubMed

Wilson, I B; Kaplan, S

2000-12-15

Although previous work that considered a variety of chronic conditions has shown that higher quality physician-patient communication care is related to better health outcomes, the quality of physician-patient communication itself for patients with HIV disease has not been well studied. To determine the relationship of patient, visit, physician, and physician practice characteristics to two measures of physician-patient communication for patients with HIV disease. Cross-sectional survey of physicians and patients. Cohort study enrolling patients from throughout eastern Massachusetts. 264 patients with HIV disease and their their primary HIV physicians (n = 69). Two measures of physician-patient communication were used, a five-item general communication measure (Cronbach's alpha = 0.93), and a four-item HIV-specific communication measure that included items about alcohol, drug use, and sexual behaviors (Cronbach's alpha = 0.92). The mean age of patients was 39. 5 years, 24% patients were women, 31.1% were nonwhite, and 52% indicated same-sex contact as their principal HIV risk factor. The mean age of physicians was 39.1 years, 33.3% were female, 39.7% were specialists, and 25.0% self-identified as gay, lesbian, or bisexual. In multivariable models relating patient and visit characteristics to general communication, longer reported visit length (p<.0001), longer duration of the physician-patient relationship (p =.02), and female gender (p =.04) were significantly associated with better communication. The interaction of patient gender and visit length was also significant (p =.02); longer visit length was more strongly associated with better general communication for male than female patients. In similar models relating patient and visit characteristics to HIV-specific communication, longer visit length (p <.0001) and less advanced disease stage (p =.009) were associated with better communication. In multivariable models relating physician and practice characteristics to general communication no variables were significant. However, both female physician gender (p =.002) and gay/lesbian/bisexual sexual preference (p =.003) were significantly associated with better HIV-specific communication. In this study, female and homosexual physicians provided higher quality HIV-specific communication than male and heterosexual physicians. Better understanding the processes by which female and homosexual physicians achieve higher quality communication may help other physicians communicate more effectively. Health care providers and third-party payers should be aware that shorter visits may compromise physician-patient communication, and that this effect may be more consequential for male patients.

Racial disparities in urologist visits among elderly men with prostate cancer: a cohort analysis of patient-related and county of residence-related factors.

PubMed

Onukwugha, Eberechukwu; Osteen, Phillip; Jayasekera, Jinani; Mullins, C Daniel; Mair, Christine A; Hussain, Arif

2014-11-01

Factors contributing to the lower likelihood of urologist follow-up among African American (AA) men diagnosed with prostate cancer may not be strictly related to patient factors. The authors investigated the relationship between crime, poverty, and poor housing, among others, and postdiagnosis urologist visits among AA and white men. The authors used linked cancer registry and Medicare claims data from 1999 through 2007 for men diagnosed with American Joint Committee on Cancer stage I to III prostate cancer. The USA Counties and County Business Patterns data sets provided county-level data. Variance components models reported the percentage of variation attributed to county of residence. Postdiagnosis urologist visits for AA and white men were investigated using logistic and modified Poisson regression models. A total of 65,635 patients were identified; 87% of whom were non-Hispanic white and 9.3% of whom were non-Hispanic AA. Approximately 16% of men diagnosed with stage I to III prostate cancer did not visit a urologist within 1 year after diagnosis (22% of AA men and 15% of white men). County of residence accounted for 10% of the variation in the visit outcome (13% for AA men and 10% for white men). AA men were more likely to live in counties ranked highest in terms of poverty, occupied housing units with no telephone, and crime. AA men were less likely to see a urologist (odds ratio, 0.65 [95% confidence interval, 0.6-0.71]; rate ratio, 0.94 [95% confidence interval, 0.92-0.95]). The sign and magnitude of the coefficients for the county-level measures differed across race-specific regression models of urologist visits. Among older men diagnosed with stage I to III prostate cancer, the social environment appears to contribute to some of the disparities in postdiagnosis urologist visits between AA and white men. © 2014 American Cancer Society.

GOES EXIS Quadruplets Together in a Clean Room "Nursery"

NASA Image and Video Library

2014-02-10

Four Extreme Ultraviolet and X-ray Irradiance Sensors or EXIS instruments that will fly aboard four of NOAA's Geostationary Operational Environmental Satellite-R or GOES-R Series spacecraft were recently lined up like babies in a nursery. The EXIS Team at NOAA's Laboratory for Atmospheric and Space Physics (LASP) in Boulder, Colorado took a short timeout during the week of January 20, 2014 to take advantage of a rare photo opportunity. Each EXIS instrument will fly aboard one of the GOES-R series of spacecraft that include GOES-R, S, T, and U. All four EXIS instruments happened to be in the clean room at the same time. It is expected that this will probably be the last time that all four siblings will be in one place together as Flight Model 1 (seen on the left) is being shipped on February 3 to begin integration and testing onto the GOES-R spacecraft at a Lockheed Martin facility in Littleton, Colo. The other instruments have already dispersed to other areas at LASP for continued build and test operations. The EXIS instruments on the GOES-R series satellites are critical to understanding and monitoring solar irradiance in the upper atmosphere, that is, the power and effect of the Sun’s electromagnetic radiation per unit of area. EXIS will be able to detect solar flares that could interrupt communications and reduce navigational accuracy, affecting satellites, high altitude airlines and power grids on Earth. On board the EXIS are two main sensors, the Extreme Ultraviolet Sensor (EUVS) and the X-Ray Sensor (XRS), which will help scientists monitor activity on the sun. The GOES-R series is a collaborative development and acquisition effort between the National Oceanic and Atmospheric Administration and NASA. The GOES-R satellites will provide continuous imagery and atmospheric measurements of Earth’s Western Hemisphere and space weather monitoring. For more information about the GOES-R series, visit: www.goes-r.gov Credit: NOAA/NASA NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Revalidation and quality assurance: the application of the MUSIQ framework in independent verification visits to healthcare organisations

PubMed Central

Griffin, Ann; Viney, Rowena; Welland, Trevor; Gafson, Irene

2017-01-01

Objectives We present a national evaluation of the impact of independent verification visits (IVVs) performed by National Health Service (NHS) England as part of quality assuring medical revalidation. Organisational visits are central to NHS quality assurance. They are costly, yet little empirical research evidence exists concerning their impact, and what does exist is conflicting. Setting The focus was on healthcare providers in the NHS (in secondary care) and private sector across England, who were designated bodies (DBs). DBs are healthcare organisations that have a statutory responsibility, via the lead clinician, the responsible officer (RO), to implement medical revalidation. Participants All ROs who had undergone an IVV in England in 2014 and 2015 were invited to participate. 46 ROs were interviewed. Ethnographic data were gathered at 18 observations of the IVVs and 20 IVV post visit reports underwent documentary analysis. Primary and secondary outcome measures Primary outcomes were the findings pertaining to the effectiveness of the IVV system in supporting the revalidation processes at the DBs. Secondary outcomes were methodological, relating to the Model for Understanding Success in Quality (MUSIQ) and how its application to the IVV reveals the relevance of contextual factors described in the model. Results The impact of the IVVs varied by DB according to three major themes: the personal context of the RO; the organisational context of the DB; and the visit and its impact. ROs were largely satisfied with visits which raised the status of appraisal within their organisations. Inadequate or untimely feedback was associated with dissatisfaction. Conclusions Influencing teams whose prime responsibility is establishing processes and evaluating progress was crucial for internal quality improvement. Visits acted as a nudge, generating internal quality review, which was reinforced by visit teams with relevant expertise. Diverse team membership, knowledge transfer and timely feedback made visits more impactful. PMID:28196952

Revalidation and quality assurance: the application of the MUSIQ framework in independent verification visits to healthcare organisations.

PubMed

Griffin, Ann; McKeown, Alex; Viney, Rowena; Rich, Antonia; Welland, Trevor; Gafson, Irene; Woolf, Katherine

2017-02-14

We present a national evaluation of the impact of independent verification visits (IVVs) performed by National Health Service (NHS) England as part of quality assuring medical revalidation. Organisational visits are central to NHS quality assurance. They are costly, yet little empirical research evidence exists concerning their impact, and what does exist is conflicting. The focus was on healthcare providers in the NHS (in secondary care) and private sector across England, who were designated bodies (DBs). DBs are healthcare organisations that have a statutory responsibility, via the lead clinician, the responsible officer (RO), to implement medical revalidation. All ROs who had undergone an IVV in England in 2014 and 2015 were invited to participate. 46 ROs were interviewed. Ethnographic data were gathered at 18 observations of the IVVs and 20 IVV post visit reports underwent documentary analysis. Primary outcomes were the findings pertaining to the effectiveness of the IVV system in supporting the revalidation processes at the DBs. Secondary outcomes were methodological, relating to the Model for Understanding Success in Quality (MUSIQ) and how its application to the IVV reveals the relevance of contextual factors described in the model. The impact of the IVVs varied by DB according to three major themes: the personal context of the RO; the organisational context of the DB; and the visit and its impact. ROs were largely satisfied with visits which raised the status of appraisal within their organisations. Inadequate or untimely feedback was associated with dissatisfaction. Influencing teams whose prime responsibility is establishing processes and evaluating progress was crucial for internal quality improvement. Visits acted as a nudge, generating internal quality review, which was reinforced by visit teams with relevant expertise. Diverse team membership, knowledge transfer and timely feedback made visits more impactful. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Annual patient and caregiver burden of oncology clinic visits for granulocyte-colony stimulating factor therapy in the US.

PubMed

Stephens, J Mark; Li, Xiaoyan; Reiner, Maureen; Tzivelekis, Spiros

2016-01-01

Prophylactic treatment with granulocyte-colony stimulating factors (G-CSFs) is indicated for chemotherapy patients with a significant risk of febrile neutropenia. This study estimates the annual economic burden on patients and caregivers of clinic visits for prophylactic G-CSF injections in the US. Annual clinic visits for prophylactic G-CSF injections (all cancers) were estimated from national cancer incidence, chemotherapy treatment and G-CSF utilization data, and G-CSF sales and pricing information. Patient travel times, plus time spent in the clinic, were estimated from patient survey responses collected during a large prospective cohort study (the Prospective Study of the Relationship between Chemotherapy Dose Intensity and Mortality in Early-Stage (I-III) Breast Cancer Patients). Economic models were created to estimate travel costs, patient co-pays and the economic value of time spent by patients and caregivers in G-CSF clinic visits. Estimated total clinic visits for prophylactic G-CSF injections in the US were 1.713 million for 2015. Mean (SD) travel time per visit was 62 (50) min; mean (SD) time in the clinic was 41 (68) min. Total annual time for travel to and from the clinic, plus time at the clinic, is estimated at 4.9 million hours, with patient and caregiver time valued at $91.8 million ($228 per patient). The estimated cumulative annual travel distance for G-CSF visits is 60.2 million miles, with a total transportation cost of $28.9 million ($72 per patient). Estimated patient co-pays were $61.1 million, ∼$36 per visit, $152 per patient. The total yearly economic impact on patients and caregivers is $182 million, ∼$450 per patient. Data to support model parameters were limited. Study estimates are sensitive to the assumptions used. The burden of clinic visits for G-CSF therapy is a significant addition to the total economic burden borne by cancer patients and their families.

A sun-crown-sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery

NASA Astrophysics Data System (ADS)

Fan, Yuanchao; Koukal, Tatjana; Weisberg, Peter J.

2014-10-01

Canopy shadowing mediated by topography is an important source of radiometric distortion on remote sensing images of rugged terrain. Topographic correction based on the sun-canopy-sensor (SCS) model significantly improved over those based on the sun-terrain-sensor (STS) model for surfaces with high forest canopy cover, because the SCS model considers and preserves the geotropic nature of trees. The SCS model accounts for sub-pixel canopy shadowing effects and normalizes the sunlit canopy area within a pixel. However, it does not account for mutual shadowing between neighboring pixels. Pixel-to-pixel shadowing is especially apparent for fine resolution satellite images in which individual tree crowns are resolved. This paper proposes a new topographic correction model: the sun-crown-sensor (SCnS) model based on high-resolution satellite imagery (IKONOS) and high-precision LiDAR digital elevation model. An improvement on the C-correction logic with a radiance partitioning method to address the effects of diffuse irradiance is also introduced (SCnS + C). In addition, we incorporate a weighting variable, based on pixel shadow fraction, on the direct and diffuse radiance portions to enhance the retrieval of at-sensor radiance and reflectance of highly shadowed tree pixels and form another variety of SCnS model (SCnS + W). Model evaluation with IKONOS test data showed that the new SCnS model outperformed the STS and SCS models in quantifying the correlation between terrain-regulated illumination factor and at-sensor radiance. Our adapted C-correction logic based on the sun-crown-sensor geometry and radiance partitioning better represented the general additive effects of diffuse radiation than C parameters derived from the STS or SCS models. The weighting factor Wt also significantly enhanced correction results by reducing within-class standard deviation and balancing the mean pixel radiance between sunlit and shaded slopes. We analyzed these improvements with model comparison on the red and near infrared bands. The advantages of SCnS + C and SCnS + W on both bands are expected to facilitate forest classification and change detection applications.

Disequilibrium: An Instructional Coach's Reflection

ERIC Educational Resources Information Center

Butler, Melinda S.; Votteler, Nancy K.

2016-01-01

When Debbie Miller, educational consultant and author of "Reading with Meaning" (2013) and "Teaching with Intention" (2008) visited a Title I elementary school in Texas, the instructional reading coach was challenged in her thinking about best practices for independent reading. Ms. Miller's visit included modeling interactive…

Using nursing intervention classification in an advance practice registered nurse-led preventive model for adults aging with developmental disabilities.

PubMed

Hahn, Joan Earle

2014-09-01

To describe the most frequently reported and the most central nursing interventions in an advance practice registered nurse (APRN)-led in-home preventive intervention model for adults aging with developmental disabilities using the Nursing Intervention Classification (NIC) system. A descriptive data analysis and a market basket analysis were conducted on de-identified nominal nursing intervention data from two home visits conducted by nurse practitioners (NPs) from October 2010 to June 2012 for 80 community-dwelling adults with developmental disabilities, ages 29 to 68 years. The mean number of NIC interventions was 4.7 in the first visit and 6.0 in the second visit and last visit. NPs reported 45 different intervention types as classified using a standardized language, with 376 in Visit One and 470 in Visit Two. Approximately 85% of the sample received the Health education intervention. The market basket analysis revealed common pairs, triples, and quadruple sets of interventions in this preventive model. The NIC nursing interventions that occurred together repeatedly were: Health education, Weight management, Nutrition management, Health screening, and Behavior management. Five NIC interventions form the basis of an APRN-led preventive intervention model for individuals aging with lifelong disability, with health education as the most common intervention, combined with interventions to manage weight and nutrition, promote healthy behaviors, and encourage routine health screening. Less frequently reported NIC interventions suggest the need to tailor prevention to individual needs, whether acute or chronic. APRNs employing prevention among adults aging with developmental disabilities must anticipate the need to focus on health education strategies for health promotion and prevention as well as tailor and target a patient-centered approach to support self-management of health to promote healthy aging in place. These NIC interventions serve not only as a guide for planning preventive interventions, but for designing nursing curricula to reduce health disparities among people with varying learning needs. © 2014 Sigma Theta Tau International.

Optimal sensor placement for control of a supersonic mixed-compression inlet with variable geometry

NASA Astrophysics Data System (ADS)

Moore, Kenneth Thomas

A method of using fluid dynamics models for the generation of models that are useable for control design and analysis is investigated. The problem considered is the control of the normal shock location in the VDC inlet, which is a mixed-compression, supersonic, variable-geometry inlet of a jet engine. A quasi-one-dimensional set of fluid equations incorporating bleed and moving walls is developed. An object-oriented environment is developed for simulation of flow systems under closed-loop control. A public interface between the controller and fluid classes is defined. A linear model representing the dynamics of the VDC inlet is developed from the finite difference equations, and its eigenstructure is analyzed. The order of this model is reduced using the square root balanced model reduction method to produce a reduced-order linear model that is suitable for control design and analysis tasks. A modification to this method that improves the accuracy of the reduced-order linear model for the purpose of sensor placement is presented and analyzed. The reduced-order linear model is used to develop a sensor placement method that quantifies as a function of the sensor location the ability of a sensor to provide information on the variable of interest for control. This method is used to develop a sensor placement metric for the VDC inlet. The reduced-order linear model is also used to design a closed loop control system to control the shock position in the VDC inlet. The object-oriented simulation code is used to simulate the nonlinear fluid equations under closed-loop control.

Towards real-time assimilation of crowdsourced observations in hydrological modeling

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri

2016-04-01

The continued technological advances have stimulated the spread of low-cost sensors that can be used by citizens to provide crowdsourced observations (CO) of different hydrological variables. An example of such low-cost sensors is a staff gauge connected to a QR code on which people can read the water level indication and send the measurement via a mobile phone application. The goal of this study is to assess the combined effect of the assimilation of CO coming from a distributed network of low-cost sensors, and the existing streamflow observations from physical sensors, on the performance of a semi-distributed hydrological model. The methodology is applied to the Bacchiglione catchment, North East of Italy, where an early warning system is used by the Alto Adriatico Water Authority to issue forecasted water level along the river network which cross important cities such as Vicenza and Padua. In this study, forecasted precipitation values are used as input in the hydrological model to estimate the simulated streamflow hydrograph used as boundary condition for the hydraulic model. Observed precipitation values are used to generate realistic synthetic streamflow values with various characteristics of arrival frequency and accuracy, to simulate CO coming at irregular time steps. These observations are assimilated into the semi-distributed model using a Kalman filter based method. The results of this study show that CO, asynchronous in time and with variable accuracy, can still improve flood prediction when integrated in hydrological models. When both physical and low-cost sensors are located at the same places, the assimilation of CO gives the same model improvement than the assimilation of physical observations only for high number of non-intermittent sensors. However, the integration of observations from low-cost sensors and single physical sensors can improve the flood prediction even when small a number of intermittent CO are available. This study is part of the FP7 European Project WeSenseIt Citizen Water Observatory (www.http://wesenseit.eu/).