WorldWideScience

Sample records for learning time monitoring

  1. Nuclear power plant monitoring using real-time learning neural network

    International Nuclear Information System (INIS)

    Nabeshima, Kunihiko; Tuerkcan, E.; Ciftcioglu, O.

    1994-01-01

    In the present research, artificial neural network (ANN) with real-time adaptive learning is developed for the plant wide monitoring of Borssele Nuclear Power Plant (NPP). Adaptive ANN learning capability is integrated to the monitoring system so that robust and sensitive on-line monitoring is achieved in real-time environment. The major advantages provided by ANN are that system modelling is formed by means of measurement information obtained from a multi-output process system, explicit modelling is not required and the modelling is not restricted to linear systems. Also ANN can respond very fast to anomalous operational conditions. The real-time ANN learning methodology with adaptive real-time monitoring capability is described below for the wide-range and plant-wide data from an operating nuclear power plant. The layered neural network with error backpropagation algorithm for learning has three layers. The network type is auto-associative, inputs and outputs are exactly the same, using 12 plant signals. (author)

  2. The difference of delay time in monitoring system of facial acupressure learning media using bluetooth, wireless and ethernet

    Science.gov (United States)

    Agustin, Eny Widhia; Hangga, Arimaz; Fahrian, Muhammad Iqbal; Azhari, Anis Fikri

    2018-03-01

    The implementation of monitoring system in the facial acupressure learning media could increase the students' proficiency. However the common learning media still has not implemented a monitoring system in their learning process. This research was conducted to implement monitoring system in the mannequin head prototype as a learning media of facial acupressure using Bluetooth, wireless and Ethernet. The results of the implementation of monitoring system in the prototype showed that there were differences in the delay time between Bluetooth and wireless or Ethernet. The results data showed no difference in the average delay time between the use of Bluetooth with wireless and the use of Bluetooth with Ethernet in monitoring system of facial acupressure learning media. From all the facial acupressure points, the forehead facial acupressure point has the longest delay time of 11.93 seconds. The average delay time in all 3 class rooms was 1.96 seconds therefore the use of Bluetooth, wireless and Ethernet is highly recommended in the monitoring system of facial acupressure.

  3. A Just-in-Time Learning based Monitoring and Classification Method for Hyper/Hypocalcemia Diagnosis.

    Science.gov (United States)

    Peng, Xin; Tang, Yang; He, Wangli; Du, Wenli; Qian, Feng

    2017-01-20

    This study focuses on the classification and pathological status monitoring of hyper/hypo-calcemia in the calcium regulatory system. By utilizing the Independent Component Analysis (ICA) mixture model, samples from healthy patients are collected, diagnosed, and subsequently classified according to their underlying behaviors, characteristics, and mechanisms. Then, a Just-in-Time Learning (JITL) has been employed in order to estimate the diseased status dynamically. In terms of JITL, for the purpose of the construction of an appropriate similarity index to identify relevant datasets, a novel similarity index based on the ICA mixture model is proposed in this paper to improve online model quality. The validity and effectiveness of the proposed approach have been demonstrated by applying it to the calcium regulatory system under various hypocalcemic and hypercalcemic diseased conditions.

  4. Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

    Science.gov (United States)

    Li, Xuejian; Wang, Youqing

    2016-12-01

    Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.

  5. A Framework and Algorithms for Multivariate Time Series Analytics (MTSA): Learning, Monitoring, and Recommendation

    Science.gov (United States)

    Ngan, Chun-Kit

    2013-01-01

    Making decisions over multivariate time series is an important topic which has gained significant interest in the past decade. A time series is a sequence of data points which are measured and ordered over uniform time intervals. A multivariate time series is a set of multiple, related time series in a particular domain in which domain experts…

  6. Improving Neuromuscular Monitoring and Reducing Residual Neuromuscular Blockade With E-Learning: Protocol for the Multicenter Interrupted Time Series INVERT Study.

    Science.gov (United States)

    Thomsen, Jakob Louis Demant; Mathiesen, Ole; Hägi-Pedersen, Daniel; Skovgaard, Lene Theil; Østergaard, Doris; Engbaek, Jens; Gätke, Mona Ring

    2017-10-06

    Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Residual neuromuscular blockade occurs when the patient is still partially paralyzed when awakened after surgery. The condition is associated with subjective discomfort and an increased risk of respiratory complications. Use of an objective neuromuscular monitoring device may prevent residual block. Despite this, many anesthetists refrain from using the device. Efforts to increase the use of objective monitoring are time consuming and require the presence of expert personnel. A neuromuscular monitoring e-learning module might support consistent use of neuromuscular monitoring devices. The aim of the study is to assess the effect of a neuromuscular monitoring e-learning module on anesthesia staff's use of objective neuromuscular monitoring and the incidence of residual neuromuscular blockade in surgical patients at 6 Danish teaching hospitals. In this interrupted time series study, we are collecting data repeatedly, in consecutive 3-week periods, before and after the intervention, and we will analyze the effect using segmented regression analysis. Anesthesia departments in the Zealand Region of Denmark are included, and data from all patients receiving a muscle relaxant are collected from the anesthesia information management system MetaVision. We will assess the effect of the module on all levels of potential effect: staff's knowledge and skills, patient care practice, and patient outcomes. The primary outcome is use of neuromuscular monitoring in patients according to the type of muscle relaxant received. Secondary outcomes include last recorded train-of-four value, administration of reversal agents, and time to discharge from the postanesthesia care unit as well as a multiple-choice test to assess knowledge. The e-learning module was developed based on a needs assessment process, including focus group interviews, surveys, and expert opinions. The e-learning

  7. Online neural monitoring of statistical learning.

    Science.gov (United States)

    Batterink, Laura J; Paller, Ken A

    2017-05-01

    The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Learning During Stressful Times

    Science.gov (United States)

    Shors, Tracey J.

    2012-01-01

    Stressful life events can have profound effects on our cognitive and motor abilities, from those that could be construed as adaptive to those not so. In this review, I discuss the general notion that acute stressful experience necessarily impairs our abilities to learn and remember. The effects of stress on operant conditioning, that is, learned helplessness, as well as those on classical conditioning procedures are discussed in the context of performance and adaptation. Studies indicating sex differences in learning during stressful times are discussed, as are those attributing different responses to the existence of multiple memory systems and nonlinear relationships. The intent of this review is to highlight the apparent plasticity of the stress response, how it might have evolved to affect both performance and learning processes, and the potential problems with interpreting stress effects on learning as either good or bad. An appreciation for its plasticity may provide new avenues for investigating its underlying neuronal mechanisms. PMID:15054128

  9. Timing matters: negative emotion elicited 5 min but not 30 min or 45 min after learning enhances consolidation of internal-monitoring source memory.

    Science.gov (United States)

    Wang, Bo; Bukuan, Sun

    2015-05-01

    Two experiments examined the time-dependent effects of negative emotion on consolidation of item and internal-monitoring source memory. In Experiment 1, participants (n=121) learned a list of words. They were asked to read aloud half of the words and to think about the remaining half. They were instructed to memorize each word and its associative cognitive operation ("reading" versus "thinking"). Immediately following learning they conducted free recall and then watched a 3-min either neutral or negative video clip when 5 min, 30 min or 45 min had elapsed after learning. Twenty-four hours later they returned to take surprise tests for item and source memory. Experiment 2 was similar to Experiment 1 except that participants, without conducting an immediate test of free recall, took tests of source memory for all encoded words both immediately and 24 h after learning. Experiment 1 showed that negative emotion enhanced consolidation of item memory (as measured by retention ratio of free recall) regardless of delay of emotion elicitation and that negative emotion enhanced consolidation of source memory when it was elicited at a 5 min delay but reduced consolidation of source memory when it was elicited at a 30 min delay; when elicited at a 45 min delay, negative emotion had little effect. Furthermore, Experiment 2 replicated the enhancement effect on source memory in the 5 min delay even when participants were tested on all the encoded words. The current study partially replicated prior studies on item memory and extends the literature by providing evidence for a time-dependent effect of negative emotion on consolidation of source memory based on internal monitoring. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Learning Time and Educational Effectiveness.

    Science.gov (United States)

    Anderson, Lorin W.

    1980-01-01

    To explore the relationship between time and school learning, this paper defines the three kinds of learning time identified by researchers--allocated time, time-on-task, and academic learning time--and relates them to curriculum development. The author cites evidence that time-on-task is related to student achievement and describes two…

  11. Prime Time for Learning.

    Science.gov (United States)

    Leidy, Vivian; And Others

    1981-01-01

    Five elementary teachers explain how they orient pupils and get learning started on the first day of school--whether or not their supplies or textbooks have arrived--by building learning activities around a common interest like dogs, earthworms, football, or the Statue of Liberty. (Editor/SJL)

  12. Time and Associative Learning.

    Science.gov (United States)

    Balsam, Peter D; Drew, Michael R; Gallistel, C R

    2010-01-01

    In a basic associative learning paradigm, learning is said to have occurred when the conditioned stimulus evokes an anticipatory response. This learning is widely believed to depend on the contiguous presentation of conditioned and unconditioned stimulus. However, what it means to be contiguous has not been rigorously defined. Here we examine the empirical bases for these beliefs and suggest an alternative view based on the hypothesis that learning about the temporal relationships between events determines the speed of emergence, vigor and form of conditioned behavior. This temporal learning occurs very rapidly and prior to the appearance of the anticipatory response. The temporal relations are learned even when no anticipatory response is evoked. The speed with which an anticipatory response emerges is proportional to the informativeness of the predictive cue (CS) regarding the rate of occurrence of the predicted event (US). This analysis gives an account of what we mean by "temporal pairing" and is in accord with the data on speed of acquisition and basic findings in the cue competition literature. In this account, learning depends on perceiving and encoding temporal regularities rather than stimulus contiguities.

  13. Establishing Time for Professional Learning

    Science.gov (United States)

    Journal of Staff Development, 2013

    2013-01-01

    Time for collaborative learning is an essential resource for educators working to implement college- and career-ready standards. The pages in this article include tools from the workbook "Establishing Time for Professional Learning." The tools support a complete process to help educators effectively find and use time. The following…

  14. A real time monitoring system

    International Nuclear Information System (INIS)

    Fontanini, Horacio; Galdoz, Erwin

    1989-01-01

    A real time monitoring system is described. It was initially developed to be used as a man-machine interface between a basic principles simulator of the Embalse Nuclear Power Plant and the operators. This simulator is under construction at the Bariloche Atomic Center's Process Control Division. Due to great design flexibility, this system can also be used in real plants. The system is designed to be run on a PC XT or AT personal computer with high resolution graphics capabilities. Three interrelated programs compose the system: 1) Graphics Editor, to build static image to be used as a reference frame where to show dynamically updated data. 2) Data acquisition and storage module. It is a memory resident module to acquire and store data in background. Data can be acquired and stored without interference with the operating system, via serial port or through analog-to-digital converter attached to the personal computer. 3) Display module. It shows the acquired data according to commands received from configuration files prepared by the operator. (Author) [es

  15. Time will tell: The role of mobile learning analytics in self-regulated learning

    NARCIS (Netherlands)

    Tabuenca, Bernardo; Kalz, Marco; Drachsler, Hendrik; Specht, Marcus

    2015-01-01

    This longitudinal study explores the effects of tracking and monitoring time devoted to learn with a mobile tool, on self-regulated learning. Graduate students (n = 36) from three different online courses used their own mobile devices to track how much time they devoted to learn over a period of

  16. A Deep Learning Approach to Drone Monitoring

    OpenAIRE

    Chen, Yueru; Aggarwal, Pranav; Choi, Jongmoo; Kuo, C. -C. Jay

    2017-01-01

    A drone monitoring system that integrates deep-learning-based detection and tracking modules is proposed in this work. The biggest challenge in adopting deep learning methods for drone detection is the limited amount of training drone images. To address this issue, we develop a model-based drone augmentation technique that automatically generates drone images with a bounding box label on drone's location. To track a small flying drone, we utilize the residual information between consecutive i...

  17. Real time monitoring of electron processors

    International Nuclear Information System (INIS)

    Nablo, S.V.; Kneeland, D.R.; McLaughlin, W.L.

    1995-01-01

    A real time radiation monitor (RTRM) has been developed for monitoring the dose rate (current density) of electron beam processors. The system provides continuous monitoring of processor output, electron beam uniformity, and an independent measure of operating voltage or electron energy. In view of the device's ability to replace labor-intensive dosimetry in verification of machine performance on a real-time basis, its application to providing archival performance data for in-line processing is discussed. (author)

  18. Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis

    NARCIS (Netherlands)

    Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

    2016-01-01

    Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require

  19. Establishing monitoring programs for travel time reliability.

    Science.gov (United States)

    2014-01-01

    Within the second Strategic Highway Research Program (SHRP 2), Project L02 focused on creating a suite of methods by which transportation agencies could monitor and evaluate travel time reliability. Creation of the methods also produced an improved u...

  20. Indirect Tire Monitoring System - Machine Learning Approach

    Science.gov (United States)

    Svensson, O.; Thelin, S.; Byttner, S.; Fan, Y.

    2017-10-01

    The heavy vehicle industry has today no requirement to provide a tire pressure monitoring system by law. This has created issues surrounding unknown tire pressure and thread depth during active service. There is also no standardization for these kind of systems which means that different manufacturers and third party solutions work after their own principles and it can be hard to know what works for a given vehicle type. The objective is to create an indirect tire monitoring system that can generalize a method that detect both incorrect tire pressure and thread depth for different type of vehicles within a fleet without the need for additional physical sensors or vehicle specific parameters. The existing sensors that are connected communicate through CAN and are interpreted by the Drivec Bridge hardware that exist in the fleet. By using supervised machine learning a classifier was created for each axle where the main focus was the front axle which had the most issues. The classifier will classify the vehicles tires condition and will be implemented in Drivecs cloud service where it will receive its data. The resulting classifier is a random forest implemented in Python. The result from the front axle with a data set consisting of 9767 samples of buses with correct tire condition and 1909 samples of buses with incorrect tire condition it has an accuracy of 90.54% (0.96%). The data sets are created from 34 unique measurements from buses between January and May 2017. This classifier has been exported and is used inside a Node.js module created for Drivecs cloud service which is the result of the whole implementation. The developed solution is called Indirect Tire Monitoring System (ITMS) and is seen as a process. This process will predict bad classes in the cloud which will lead to warnings. The warnings are defined as incidents. They contain only the information needed and the bandwidth of the incidents are also controlled so incidents are created within an

  1. Monitoring REDD+: From Social Safeguards to Social Learning

    Science.gov (United States)

    Ravikumar, A.; Andersson, K.

    2010-12-01

    Krister Andersson 1 and Ashwin Ravikumar 1 The UNFCCC requires countries that participate in the REDD+ (Reducing Emissions from Deforestation and Forest Degradation in Developing Countries) program to monitor both forest carbon inventories as well as the governance of REDD+ activities and their social consequences. Exactly how this should be done, however, remains an open question. This paper addresses this question by drawing on existing research on social-ecological systems and new institutional economics. We make the case for a monitoring system that goes beyond a narrow focus of qualitative indicators of REDD+ governance that seek to provide social safeguards for international investors to create a more comprehensive monitoring system that is useful for social learning about how policies affect a variety of forest outcomes. We describe the defining characteristics of five existing approaches to monitoring REDD+ governance. Applying evaluative criteria of affordability, comprehensiveness, transparency, uncertainty specification, and explanatory potential, we analyze the extent to which each of the programs contribute to broader social learning processes in participating countries. Our analysis finds that it makes sense to move from the current narrow focus of monitoring for control to monitoring for social learning. Particularly valuable to participating REDD+ actors would be the creation of learning systems that can help policy makers to identify opportunities for policy improvements, with the ultimate goal of making REDD+ more effective, efficient, and equitable. Such learning is not possible, however, without timely and systematic collection of data on the relationships between forests and forest users. 1University of Colorado at Boulder, Environmental Studies Program, Boulder, CO 80309-0397

  2. Space Weather and Real-Time Monitoring

    Directory of Open Access Journals (Sweden)

    S Watari

    2009-04-01

    Full Text Available Recent advance of information and communications technology enables to collect a large amount of ground-based and space-based observation data in real-time. The real-time data realize nowcast of space weather. This paper reports a history of space weather by the International Space Environment Service (ISES in association with the International Geophysical Year (IGY and importance of real-time monitoring in space weather.

  3. Tool Wear Monitoring Using Time Series Analysis

    Science.gov (United States)

    Song, Dong Yeul; Ohara, Yasuhiro; Tamaki, Haruo; Suga, Masanobu

    A tool wear monitoring approach considering the nonlinear behavior of cutting mechanism caused by tool wear and/or localized chipping is proposed, and its effectiveness is verified through the cutting experiment and actual turning machining. Moreover, the variation in the surface roughness of the machined workpiece is also discussed using this approach. In this approach, the residual error between the actually measured vibration signal and the estimated signal obtained from the time series model corresponding to dynamic model of cutting is introduced as the feature of diagnosis. Consequently, it is found that the early tool wear state (i.e. flank wear under 40µm) can be monitored, and also the optimal tool exchange time and the tool wear state for actual turning machining can be judged by this change in the residual error. Moreover, the variation of surface roughness Pz in the range of 3 to 8µm can be estimated by the monitoring of the residual error.

  4. Gravitational Lens Time Delays Using Polarization Monitoring

    Directory of Open Access Journals (Sweden)

    Andrew Biggs

    2017-11-01

    Full Text Available Gravitational lens time delays provide a means of measuring the expansion of the Universe at high redshift (and therefore in the ‘Hubble flow’ that is independent of local calibrations. It was hoped that many of the radio lenses found in the JVAS/CLASS survey would yield time delays as these were selected to have flat spectra and are dominated by multiple compact components. However, despite extensive monitoring with the Very Large Array (VLA, time delays have only been measured for three of these systems (out of 22. We have begun a programme to reanalyse the existing VLA monitoring data with the goal of producing light curves in polarized flux and polarization position angle, either to improve delay measurements or to find delays for new sources. Here, we present preliminary results on the lens system B1600+434 which demonstrate the presence of correlated and substantial polarization variability in each image.

  5. Timepiece: Extending and Enhancing Learning Time.

    Science.gov (United States)

    Anderson, Lorin W., Ed.; Walberg, Herbert J., Ed.

    This publication offers suggestions for making more productive use of time, a scarce and valued educational resource. The chapter authors, authorities on the use of educational time, write about how to extend and enhance learning time within and outside schools. In "Productive Use of Time," Herbert Walberg describes how learning time can be…

  6. Application of Machine Learning to Rotorcraft Health Monitoring

    Science.gov (United States)

    Cody, Tyler; Dempsey, Paula J.

    2017-01-01

    Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

  7. Timed Runtime Monitoring for Multiparty Conversations

    Directory of Open Access Journals (Sweden)

    Rumyana Neykova

    2014-08-01

    Full Text Available We propose a dynamic verification framework for protocols in real-time distributed systems. The framework is based on Scribble, a tool-chain for design and verification of choreographies based on multiparty session types, developed with our industrial partners. Drawing from recent work on multiparty session types for real-time interactions, we extend Scribble with clocks, resets, and clock predicates constraining the times in which interactions should occur. We present a timed API for Python to program distributed implementations of Scribble specifications. A dynamic verification framework ensures the safe execution of applications written with our timed API: we have implemented dedicated runtime monitors that check that each interaction occurs at a correct timing with respect to the corresponding Scribble specification. The performance of our implementation and its practicability are analysed via benchmarking.

  8. Real-time video quality monitoring

    Science.gov (United States)

    Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

    2011-12-01

    The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

  9. Real Time Radiation Monitoring Using Nanotechnology

    Science.gov (United States)

    Li, Jing (Inventor); Hanratty, James J. (Inventor); Wilkins, Richard T. (Inventor); Lu, Yijiang (Inventor)

    2016-01-01

    System and method for monitoring receipt and estimating flux value, in real time, of incident radiation, using two or more nanostructures (NSs) and associated terminals to provide closed electrical paths and to measure one or more electrical property change values .DELTA.EPV, associated with irradiated NSs, during a sequence of irradiation time intervals. Effects of irradiation, without healing and with healing, of the NSs, are separately modeled for first order and second order healing. Change values.DELTA.EPV are related to flux, to cumulative dose received by NSs, and to radiation and healing effectivity parameters and/or.mu., associated with the NS material and to the flux. Flux and/or dose are estimated in real time, based on EPV change values, using measured .DELTA.EPV values. Threshold dose for specified changes of biological origin (usually undesired) can be estimated. Effects of time-dependent radiation flux are analyzed in pre-healing and healing regimes.

  10. E-Learning, Time and Unconscious Thinking

    Science.gov (United States)

    Mathew, David

    2014-01-01

    This article views the temporal dimensions of e-learning through a psychoanalytic lens, and asks the reader to consider links between online learning and psychoanalysis. It argues that time and its associated philosophical puzzles impinge on both psychoanalytic theory and on e-learning at two specific points. The first is in the distinction…

  11. Communication, timing, and common learning

    Czech Academy of Sciences Publication Activity Database

    Steiner, Jakub; Stewart, C.

    2011-01-01

    Roč. 146, č. 1 (2011), s. 230-247 ISSN 0022-0531 Institutional research plan: CEZ:AV0Z70850503 Keywords : common knowledge * learning * communication Subject RIV: AH - Economics Impact factor: 1.235, year: 2011

  12. Self-learning health monitoring algorithm in composite structures

    Science.gov (United States)

    Grassia, Luigi; Iannone, Michele; Califano, America; D'Amore, Alberto

    2018-02-01

    The paper describes a system that it is able of monitoring the health state of a composite structure in real time. The hardware of the system consists of a wire of strain sensors connected to a control unit. The software of the system elaborates the strain data and in real time is able to detect the presence of an eventual damage of the structures monitored with the strain sensors. The algorithm requires as input only the strains of the monitored structured measured on real time, i.e. those strains coming from the deformations of the composite structure due to the working loads. The health monitoring system does not require any additional device to interrogate the structure as often used in the literature, instead it is based on a self-learning procedure. The strain data acquired when the structure is healthy are used to set up the correlations between the strain in different positions of structure by means of neural network. Once the correlations between the strains in different position have been set up, these correlations act as a fingerprint of the healthy structure. In case of damage the correlation between the strains in the position of the structure near the damage will change due to the change of the stiffness of the structure caused by the damage. The developed software is able to recognize the change of the transfer function between the strains and consequently is able to detect the damage.

  13. Real time water chemistry monitoring and diagnostics

    International Nuclear Information System (INIS)

    Gaudreau, T.M.; Choi, S.S.

    2002-01-01

    EPRI has produced a real time water chemistry monitoring and diagnostic system. This system is called SMART ChemWorks and is based on the EPRI ChemWorks codes. System models, chemistry parameter relationships and diagnostic approaches from these codes are integrated with real time data collection, an intelligence engine and Internet technologies to allow for automated analysis of system chemistry. Significant data management capabilities are also included which allow the user to evaluate data and create automated reporting. Additional features have been added to the system in recent years including tracking and evaluation of primary chemistry as well as the calculation and tracking of primary to secondary leakage in PWRs. This system performs virtual sensing, identifies normal and upset conditions, and evaluates the consistency of on-line monitor and grab sample readings. The system also makes use of virtual fingerprinting to identify the cause of any chemistry upsets. This technology employs plant-specific data and models to determine the chemical state of the steam cycle. (authors)

  14. Leading Learning in Our Times

    Science.gov (United States)

    Trilling, Bernie

    2010-01-01

    Important tools that schools need to support a 21st century approach to teaching and learning include the usual suspects: the Internet, pen and paper, cell phones, educational games, tests and quizzes, good teachers, caring communities, educational funding, and loving parents. All of these items and more contribute to a 21st century education, but…

  15. Development of the real time monitor system

    Energy Technology Data Exchange (ETDEWEB)

    Kato, Katsumi [Research Organization for Information Science and Technology, Tokai, Ibaraki (Japan); Watanabe, Tadashi; Kaburaki, Hideo

    1996-10-01

    Large-scale simulation technique is studied at the Center for Promotion of Computational Science and Engineering (CCSE) for the computational science research in nuclear fields. Visualization and animation processing technique are studied and developed for efficient understanding of simulation results. The real time monitor system, in which on-going simulation results are transferred from a supercomputer or workstation to a graphic workstation and are visualized and recorded, is described in this report. This system is composed of the graphic workstation and the video equipment connected to the network. The control shell programs are the job-execution shell for simulations on supercomputers, the file-transfer shell for output files for visualization, and the shell for starting visualization tools. Special image processing technique and hardware are not necessary in this system and the standard visualization tool AVS and the UNIX commands are used, so that this system can be implemented and applied in various computer environments. (author)

  16. Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis.

    Science.gov (United States)

    Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

    2016-05-15

    Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require reverse inference, which presupposes specificity of brain activity for the hidden cognitive processes. We investigated whether multivariate pattern classification can provide this specificity. We used a word recall task to create single trial examples of immediate and long term retrieval and trained a learning algorithm to discriminate them. Next, participants performed a similar task involving monitoring instead of recall. The recall-trained classifier recognized the retrieval patterns underlying immediate and long term monitoring and classified delayed monitoring examples as long-term retrieval. This result demonstrates the feasibility of decoding cognitive processes, instead of their content. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Real Time Monitor of Grid job executions

    International Nuclear Information System (INIS)

    Colling, D J; Martyniak, J; McGough, A S; Krenek, A; Sitera, J; Mulac, M; Dvorak, F

    2010-01-01

    In this paper we describe the architecture and operation of the Real Time Monitor (RTM), developed by the Grid team in the HEP group at Imperial College London. This is arguably the most popular dissemination tool within the EGEE [1] Grid. Having been used, on many occasions including GridFest and LHC inauguration events held at CERN in October 2008. The RTM gathers information from EGEE sites hosting Logging and Bookkeeping (LB) services. Information is cached locally at a dedicated server at Imperial College London and made available for clients to use in near real time. The system consists of three main components: the RTM server, enquirer and an apache Web Server which is queried by clients. The RTM server queries the LB servers at fixed time intervals, collecting job related information and storing this in a local database. Job related data includes not only job state (i.e. Scheduled, Waiting, Running or Done) along with timing information but also other attributes such as Virtual Organization and Computing Element (CE) queue - if known. The job data stored in the RTM database is read by the enquirer every minute and converted to an XML format which is stored on a Web Server. This decouples the RTM server database from the client removing the bottleneck problem caused by many clients simultaneously accessing the database. This information can be visualized through either a 2D or 3D Java based client with live job data either being overlaid on to a 2 dimensional map of the world or rendered in 3 dimensions over a globe map using OpenGL.

  18. Real-time bioacoustics monitoring and automated species identification

    Directory of Open Access Journals (Sweden)

    T. Mitchell Aide

    2013-07-01

    Full Text Available Traditionally, animal species diversity and abundance is assessed using a variety of methods that are generally costly, limited in space and time, and most importantly, they rarely include a permanent record. Given the urgency of climate change and the loss of habitat, it is vital that we use new technologies to improve and expand global biodiversity monitoring to thousands of sites around the world. In this article, we describe the acoustical component of the Automated Remote Biodiversity Monitoring Network (ARBIMON, a novel combination of hardware and software for automating data acquisition, data management, and species identification based on audio recordings. The major components of the cyberinfrastructure include: a solar powered remote monitoring station that sends 1-min recordings every 10 min to a base station, which relays the recordings in real-time to the project server, where the recordings are processed and uploaded to the project website (arbimon.net. Along with a module for viewing, listening, and annotating recordings, the website includes a species identification interface to help users create machine learning algorithms to automate species identification. To demonstrate the system we present data on the vocal activity patterns of birds, frogs, insects, and mammals from Puerto Rico and Costa Rica.

  19. Instrumentation development for real time brainwave monitoring.

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Lawrence Frederick; Clough, Benjamin W.

    2005-12-01

    The human brain functions through a chemically-induced biological process which operates in a manner similar to electrical systems. The signal resulting from this biochemical process can actually be monitored and read using tools and having patterns similar to those found in electrical and electronics engineering. The primary signature of this electrical activity is the ''brain wave'', which looks remarkably similar to the output of many electrical systems. Likewise, the device currently used in medical arenas to read brain electrical activity is the electroencephalogram (EEG) which is synonymous with a multi-channel oscilloscope reading. Brain wave readings and recordings for medical purposes are traditionally taken in clinical settings such as hospitals, laboratories or diagnostic clinics. The signal is captured via externally applied scalp electrodes using semi-viscous gel to reduce impedance. The signal will be in the 10 to 100 microvolt range. In other instances, where surgeons are attempting to isolate particular types of minute brain signals, the electrodes may actually be temporarily implanted in the brain during a preliminary procedure. The current configurations of equipment required for EEGs involve large recording instruments, many electrodes, wires, and large amounts of hard disk space devoted to storing large files of brain wave data which are then eventually analyzed for patterns of concern. Advances in sensors, signal processing, data storage and microelectronics over the last decade would seem to have paved the way for the realization of devices capable of ''real time'' external monitoring, and possible assessment, of brain activity. A myriad of applications for such a capability are likewise presenting themselves, including the ability to assess brain functioning, level of functioning and malfunctioning. Our plan is to develop the sensors, signal processing, and portable instrumentation package which could

  20. Learned Interval Time Facilitates Associate Memory Retrieval

    Science.gov (United States)

    van de Ven, Vincent; Kochs, Sarah; Smulders, Fren; De Weerd, Peter

    2017-01-01

    The extent to which time is represented in memory remains underinvestigated. We designed a time paired associate task (TPAT) in which participants implicitly learned cue-time-target associations between cue-target pairs and specific cue-target intervals. During subsequent memory testing, participants showed increased accuracy of identifying…

  1. Learning about Learning: Action Learning in Times of Organisational Change

    Science.gov (United States)

    Hill, Robyn

    2009-01-01

    This paper explores the conduct and outcomes of an action learning activity during a period of intense organisational change in a medium-sized vocational education and training organisation in Victoria, Australia. This organisation was the subject of significant change due to government-driven and statewide amalgamation, downsizing and sector…

  2. Real-time well condition monitoring in extended reach wells

    Energy Technology Data Exchange (ETDEWEB)

    Kucs, R.; Spoerker, H.F. [OMV Austria Exploration and Production GmbH, Gaenserndorf (Austria); Thonhauser, G. [Montanuniversitaet Leoben (Austria)

    2008-10-23

    Ever rising daily operating cost for offshore operations make the risk of running into drilling problems due to torque and drag developments in extended reach applications a growing concern. One option to reduce cost related to torque and drag problems can be to monitor torque and drag trends in real time without additional workload on the platform drilling team. To evaluate observed torque or drag trends it is necessary to automatically recognize operations and to have a 'standard value' to compare the measurements to. The presented systematic approach features both options - fully automated operations recognition and real time analysis. Trends can be discussed between rig- and shore-based teams, and decisions can be based on up to date information. Since the system is focused on visualization of real-time torque and drag trends, instead of highly complex and repeated simulations, calculation time is reduced by comparing the real-time rig data against predictions imported from a commercial drilling engineering application. The system allows reacting to emerging stuck pipe situations or developing cuttings beds long before the situations become severe enough to result in substantial lost time. The ability to compare real-time data with historical data from the same or other wells makes the system a valuable tool in supporting a learning organization. The system has been developed in a joint research initiative for field application on the development of an offshore heavy oil field in New Zealand. (orig.)

  3. Designing monitoring arrangements for collaborative learning about adaptation pathways

    NARCIS (Netherlands)

    Hermans, L.M.; Haasnoot, M.; ter Maat, Judith; Kwakkel, J.H.

    2017-01-01

    Adaptation pathways approaches support long-term planning under uncertainty. The use of adaptation pathways implies a systematic monitoring effort to inform future adaptation decisions. Such monitoring should feed into a long-term collaborative learning process between multiple actors at various

  4. Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin

    2016-05-16

    Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically request user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.

  5. Hard Times for HRD, Lean Times for Learning?: Workplace Participatory Practices as Enablers of Learning

    Science.gov (United States)

    Warhurst, Russell

    2013-01-01

    Purpose: This article aims to show how in times of austerity when formal HRD activity is curtailed and yet the need for learning is greatest, non-formal learning methods such as workplace involvement and participation initiated by line managers can compensate by enabling the required learning and change. Design/methodology/approach: A qualitative…

  6. Wide-area, real-time monitoring and visualization system

    Science.gov (United States)

    Budhraja, Vikram S.; Dyer, James D.; Martinez Morales, Carlos A.

    2013-03-19

    A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

  7. Real-time performance monitoring and management system

    Science.gov (United States)

    Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

    2007-06-19

    A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

  8. Monitoring and regulation of learning in medical education: the need for predictive cues.

    Science.gov (United States)

    de Bruin, Anique B H; Dunlosky, John; Cavalcanti, Rodrigo B

    2017-06-01

    Being able to accurately monitor learning activities is a key element in self-regulated learning in all settings, including medical schools. Yet students' ability to monitor their progress is often limited, leading to inefficient use of study time. Interventions that improve the accuracy of students' monitoring can optimise self-regulated learning, leading to higher achievement. This paper reviews findings from cognitive psychology and explores potential applications in medical education, as well as areas for future research. Effective monitoring depends on students' ability to generate information ('cues') that accurately reflects their knowledge and skills. The ability of these 'cues' to predict achievement is referred to as 'cue diagnosticity'. Interventions that improve the ability of students to elicit predictive cues typically fall into two categories: (i) self-generation of cues and (ii) generation of cues that is delayed after self-study. Providing feedback and support is useful when cues are predictive but may be too complex to be readily used. Limited evidence exists about interventions to improve the accuracy of self-monitoring among medical students or trainees. Developing interventions that foster use of predictive cues can enhance the accuracy of self-monitoring, thereby improving self-study and clinical reasoning. First, insight should be gained into the characteristics of predictive cues used by medical students and trainees. Next, predictive cue prompts should be designed and tested to improve monitoring and regulation of learning. Finally, the use of predictive cues should be explored in relation to teaching and learning clinical reasoning. Improving self-regulated learning is important to help medical students and trainees efficiently acquire knowledge and skills necessary for clinical practice. Interventions that help students generate and use predictive cues hold the promise of improved self-regulated learning and achievement. This framework is

  9. Monitoring Travel Time Reliability on Freeways

    NARCIS (Netherlands)

    Tu, Huizhao

    2008-01-01

    Travel time and travel time reliability are important attributes of a trip. The current measures of reliability have in common that in general they all relate to the variability of travel times. However, travel time reliability does not only rely on variability but also on the stability of travel

  10. Air quality monitoring using mobile microscopy and machine learning

    KAUST Repository

    Wu, Yi-Chen; Shiledar, Ashutosh; Li, Yi-Cheng; Wong, Jeffrey; Feng, Steve; Chen, Xuan; Chen, Christine; Jin, Kevin; Janamian, Saba; Yang, Zhe; Ballard, Zachary Scott; Gö rö cs, Zoltá n; Feizi, Alborz; Ozcan, Aydogan

    2017-01-01

    Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. In fact, particles in air with a diameter of ≤2.5 μm have been classified as carcinogenic by the World Health Organization. Here we present a field-portable cost-effective platform for high-throughput quantification of particulate matter using computational lens-free microscopy and machine-learning. This platform, termed c-Air, is also integrated with a smartphone application for device control and display of results. This mobile device rapidly screens 6.5 L of air in 30 s and generates microscopic images of the aerosols in air. It provides statistics of the particle size and density distribution with a sizing accuracy of ~93%. We tested this mobile platform by measuring the air quality at different indoor and outdoor environments and measurement times, and compared our results to those of an Environmental Protection Agency–approved device based on beta-attenuation monitoring, which showed strong correlation to c-Air measurements. Furthermore, we used c-Air to map the air quality around Los Angeles International Airport (LAX) over 24 h to confirm that the impact of LAX on increased PM concentration was present even at >7 km away from the airport, especially along the direction of landing flights. With its machine-learning-based computational microscopy interface, c-Air can be adaptively tailored to detect specific particles in air, for example, various types of pollen and mold and provide a cost-effective mobile solution for highly accurate and distributed sensing of air quality.

  11. Air quality monitoring using mobile microscopy and machine learning

    KAUST Repository

    Wu, Yi-Chen

    2017-09-08

    Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. In fact, particles in air with a diameter of ≤2.5 μm have been classified as carcinogenic by the World Health Organization. Here we present a field-portable cost-effective platform for high-throughput quantification of particulate matter using computational lens-free microscopy and machine-learning. This platform, termed c-Air, is also integrated with a smartphone application for device control and display of results. This mobile device rapidly screens 6.5 L of air in 30 s and generates microscopic images of the aerosols in air. It provides statistics of the particle size and density distribution with a sizing accuracy of ~93%. We tested this mobile platform by measuring the air quality at different indoor and outdoor environments and measurement times, and compared our results to those of an Environmental Protection Agency–approved device based on beta-attenuation monitoring, which showed strong correlation to c-Air measurements. Furthermore, we used c-Air to map the air quality around Los Angeles International Airport (LAX) over 24 h to confirm that the impact of LAX on increased PM concentration was present even at >7 km away from the airport, especially along the direction of landing flights. With its machine-learning-based computational microscopy interface, c-Air can be adaptively tailored to detect specific particles in air, for example, various types of pollen and mold and provide a cost-effective mobile solution for highly accurate and distributed sensing of air quality.

  12. Students' Pressure, Time Management and Effective Learning

    Science.gov (United States)

    Sun, Hechuan; Yang, Xiaolin

    2009-01-01

    Purpose: This paper aims to survey the status quo of the student pressure and the relationship between their daily time management and their learning outcomes in three different types of higher secondary schools at Shenyang, the capital city of Liaoning Province in mainland China. Design/methodology/approach: An investigation was carried out in 14…

  13. Modeling Time Series Data for Supervised Learning

    Science.gov (United States)

    Baydogan, Mustafa Gokce

    2012-01-01

    Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

  14. Unsupervised process monitoring and fault diagnosis with machine learning methods

    CERN Document Server

    Aldrich, Chris

    2013-01-01

    This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data

  15. Linear time relational prototype based learning.

    Science.gov (United States)

    Gisbrecht, Andrej; Mokbel, Bassam; Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara

    2012-10-01

    Prototype based learning offers an intuitive interface to inspect large quantities of electronic data in supervised or unsupervised settings. Recently, many techniques have been extended to data described by general dissimilarities rather than Euclidean vectors, so-called relational data settings. Unlike the Euclidean counterparts, the techniques have quadratic time complexity due to the underlying quadratic dissimilarity matrix. Thus, they are infeasible already for medium sized data sets. The contribution of this article is twofold: On the one hand we propose a novel supervised prototype based classification technique for dissimilarity data based on popular learning vector quantization (LVQ), on the other hand we transfer a linear time approximation technique, the Nyström approximation, to this algorithm and an unsupervised counterpart, the relational generative topographic mapping (GTM). This way, linear time and space methods result. We evaluate the techniques on three examples from the biomedical domain.

  16. Leisure time activities, parental monitoring and drunkenness in adolescents.

    Science.gov (United States)

    Tomcikova, Zuzana; Veselska, Zuzana; Madarasova Geckova, Andrea; van Dijk, Jitse P; Reijneveld, Sijmen A

    2013-01-01

    The aim of this cross-sectional study was to explore the association between adolescent drunkenness and participation in risky leisure time activities and parental monitoring. A sample of 3,694 Slovak elementary school students (mean age 14.5 years; 49.0% males) was assessed for drunkenness in the previous month, participation in risky leisure activities and parental monitoring. Participation in risky leisure time activities increased the probability of drunkenness among adolescents, while parental monitoring decreased it. The effect did not change after adding the mother's and father's monitoring into the models. Our results imply that adolescents involved in going out with friends, having parties with friends and/or visiting sporting events every day or several times a week are at a higher risk of drunkenness, as are those less monitored by their parents. These less monitored adolescents and their parents should become a target group in prevention. Copyright © 2012 S. Karger AG, Basel.

  17. Overcoming Learning Time And Space Constraints Through Technological Tool

    Directory of Open Access Journals (Sweden)

    Nafiseh Zarei

    2015-08-01

    Full Text Available Today the use of technological tools has become an evolution in language learning and language acquisition. Many instructors and lecturers believe that integrating Web-based learning tools into language courses allows pupils to become active learners during learning process. This study investigate how the Learning Management Blog (LMB overcomes the learning time and space constraints that contribute to students’ language learning and language acquisition processes. The participants were 30 ESL students at National University of Malaysia. A qualitative approach comprising an open-ended questionnaire and a semi-structured interview was used to collect data. The results of the study revealed that the students’ language learning and acquisition processes were enhanced. The students did not face any learning time and space limitations while being engaged in the learning process via the LMB. They learned and acquired knowledge using the language learning materials and forum at anytime and anywhere. Keywords: learning time, learning space, learning management blog

  18. Learning from case studies and monitoring of Dutch tunnel projects

    NARCIS (Netherlands)

    Korff, M.

    2017-01-01

    Individuals and project-based organisations in the construction industry can learn in a (more) systematic way from case studies and the monitoring of underground construction works. Underground construction projects such as tunnels and excavations suffer as much or more from failure costs

  19. Time Series Evaluation of Portal Monitor Data

    International Nuclear Information System (INIS)

    Robinson, Sean M.; Bender, Sarah E.; Lopresti, Charles A.; Woodring, Mitchell L.

    2008-01-01

    Radiation portal monitors screen cargo and personal vehicle traffic at international border crossings to detect and interdict illicit sources which may be present in the commerce stream. One difficulty faced by RPM systems is the prospect of false alarms, or undesired alarms due to background fluctuation, or Naturally-Occurring Radioactive Material (NORM) sources in the commerce stream. In general, NORM alarms represent a significant fraction of the nuisance alarms at international border crossings, particularly with Polyvinyl-Toluene (PVT) RPM detectors, which have only very weak spectral differentiation capability. With PVT detectors, the majority of detected photon events fall within the Compton continuum of the material, allowing for very little spectral information to be preserved (1). Previous work has shown that these detectors can be used for limited spectroscopy, utilizing around 8 spectral bins to further differentiate some NORM and other nuisance sources (2). NaI based systems achieve much more detailed spectral resolution from each measurement of a source, but still combine all measurements over a vehicle's occupancy in order to arrive at a spectrum to be analyzed

  20. Sensor response time monitoring using noise analysis

    International Nuclear Information System (INIS)

    Hashemian, H.M.; Thie, J.A.; Upadhyaya, B.R.; Holbert, K.E.

    1988-01-01

    Random noise techniques in nuclear power plants have been developed for system surveillance and for analysis of reactor core dynamics. The noise signals also contain information about sensor dynamics, and this can be extracted using frequency, amplitude and time domain analyses. Even though noise analysis has been used for sensor response time testing in some nuclear power plants, an adequate validation of this method has never been carried out. This paper presents the results of limited work recently performed to examine the validity of the noise analysis for sensor response time testing in nuclear power plants. The conclusion is that noise analysis has the potential for detecting gross changes in sensor response but it cannot be used for reliable measurement of response time until more laboratory and field experience is accumulated. The method is more advantageous for testing pressure sensors than it is for temperature sensors. This is because: 1) for temperature sensors, a method called Loop Current Step Response test is available which is quantitatively more exact than noise analysis, 2) no method currently exists for on-line testing of pressure transmitters other than the Power-Interrupt test which is applicable only to force balance pressure transmitters, and 3) pressure sensor response time is affected by sensing line degradation which is inherently taken into account by testing with noise analysis. (author)

  1. Expert systems for real-time monitoring and fault diagnosis

    Science.gov (United States)

    Edwards, S. J.; Caglayan, A. K.

    1989-01-01

    Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft.

  2. Novel Use of a Noninvasive Hemodynamic Monitor in a Personalized, Active Learning Simulation

    Science.gov (United States)

    Zoller, Jonathan K.; He, Jianghua; Ballew, Angela T.; Orr, Walter N.; Flynn, Brigid C.

    2017-01-01

    The present study furthered the concept of simulation-based medical education by applying a personalized active learning component. We tested this novel approach utilizing a noninvasive hemodynamic monitor with the capability to measure and display in real time numerous hemodynamic parameters in the exercising participant. Changes in medical…

  3. Timing and control monitor system upgrade design document. Version 4

    International Nuclear Information System (INIS)

    Brandt, J.J.

    1984-01-01

    This is a design document for the Timing and Control Monitor System Upgrade Project. This project is intended to provide a replacement system for the existing user Encoder Monitor Systems and Varian 72 Control Room computer systems. All of these systems reside at the Nevada Test Site. The function of the T and C Monitor System is to gather real-time statistics and data on user defined key variables from control, communication, data acquistion systems, and from the monitoring system itself. The control, communication, and data acquisition systems each operate separately from the monitor system. The T and C Monitor System gathers this data in order to verify the readiness of an event to begin countdown. This includes setup, verification, calibration, and peripheral services, report any failures that may occur during the countdown, verify detonation and containment, and assist reentry activities after the event

  4. Telepositional portable real time radiation monitoring system

    International Nuclear Information System (INIS)

    Talpalariu, Jeni; Matei, Corina; Popescu, Oana

    2010-01-01

    Technology development for complex portable networks is on going to meet the area dosimetry challenge, improving the basic design using new telepositional GPS satellite methods and GSM terrestrial civil radio transmission networks. The system and devices proposed overcome the limitations of fixed and portable dosimeters, providing wireless real time radiations data and geospatial information's means, using many portable dosimeter stations and a mobile dosimeter computerised central console. (authors)

  5. Radiation environmental real-time monitoring and dispersion modelling

    International Nuclear Information System (INIS)

    Kovacik, Andrej; Bartokova, Ivana; Melicherova, Terezia; Omelka, Jozef

    2015-01-01

    The MicroStep-MIS system of real-time radiation monitoring, which provides a turn-key solution for measurement, acquisition, processing, reporting, archiving and displaying of various radiation data, is described and discussed in detail. The qualities, long-term stability of measurement and sensitivity of the RPSG-05 probe are illustrated on its use within the radiation monitoring network of the Slovak Hydrometeorological Institute and within the monitoring network in the United Arab Emirates. (orig.)

  6. "Internet of Things" Real-Time Free Flap Monitoring.

    Science.gov (United States)

    Kim, Sang Hun; Shin, Ho Seong; Lee, Sang Hwan

    2018-01-01

    Free flaps are a common treatment option for head and neck reconstruction in plastic reconstructive surgery, and monitoring of the free flap is the most important factor for flap survival. In this study, the authors performed real-time free flap monitoring based on an implanted Doppler system and "internet of things" (IoT)/wireless Wi-Fi, which is a convenient, accurate, and efficient approach for surgeons to monitor a free flap. Implanted Doppler signals were checked continuously until the patient was discharged by the surgeon and residents using their own cellular phone or personal computer. If the surgeon decided that a revision procedure or exploration was required, the authors checked the consumed time (positive signal-to-operating room time) from the first notification when the flap's status was questioned to the determination for revision surgery according to a chart review. To compare the efficacy of real-time monitoring, the authors paired the same number of free flaps performed by the same surgeon and monitored the flaps using conventional methods such as a physical examination. The total survival rate was greater in the real-time monitoring group (94.7% versus 89.5%). The average time for the real-time monitoring group was shorter than that for the conventional group (65 minutes versus 86 minutes). Based on this study, real-time free flap monitoring using IoT technology is a method that surgeon and reconstruction team can monitor simultaneously at any time in any situation.

  7. An Empirical Investigation of Individual Differences in Time to Learn

    Science.gov (United States)

    Anderson, Lorin W.

    1976-01-01

    Results show that student differences in time-on-task to learn to criterion are alterable and can be minimized over a sequence of learning units given appropriate adaptive learning strategies. (Author/DEP)

  8. Novel Real-Time Flight Envelope Monitoring System, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation is an aircraft flight envelope monitoring system that will provide real-time in-cockpit estimations of aircraft flight envelope boundaries....

  9. Algorithm Development for a Real-Time Military Noise Monitor

    National Research Council Canada - National Science Library

    Vipperman, Jeffrey S; Bucci, Brian

    2006-01-01

    The long-range goal of this 1-year SERDP Exploratory Development (SEED) project was to create an improved real-time, high-energy military impulse noise monitoring system that can detect events with peak levels (Lpk...

  10. RadNet Real-Time Monitoring Spectrometry Data Inventory

    Data.gov (United States)

    U.S. Environmental Protection Agency — The RadNet Real-Time Monitoring Spectrometry Data Inventory contains measured data used to identify and measure specific radioactive materials in the atmosphere at...

  11. Establishing monitoring programs for travel time reliability. [supporting datasets

    Science.gov (United States)

    2014-01-01

    The objective of this project was to develop system designs for programs to monitor travel time reliability and to prepare a guidebook that practitioners and others can use to design, build, operate, and maintain such systems. Generally, such travel ...

  12. Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

    2014-08-15

    The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

  13. Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

    International Nuclear Information System (INIS)

    Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

    2014-01-01

    The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

  14. Time factor in e-learning and assessment

    OpenAIRE

    Romero Velasco, Margarida

    2010-01-01

    Peer-reviewed Peer reviewed Time is probably one of the most polysemous words in education. In e-learning, characterization of the time factor is particularly relevant because of the high level of flexibility in the teaching and learning times, and the resulting responsibility of the e-learners in regulating their learning times.

  15. MONITORING OF UNIVERSITY ALUMNI: PERFORMANCE EVALUATION OF LEARNING

    Directory of Open Access Journals (Sweden)

    Mosienko N. L.

    2014-03-01

    Full Text Available The paper presents the methodology and results of graduates’ monitoring that solves the problem of the evaluation of higher education institutions. The goal of the present study is to develop methodology of the effectiveness of training estimation in high school and to test it on a sample of Department of Sociology’s graduates. The wide interpretation of learning outcomes, including objective and subjective indicators of employment of graduates of formation and professional, analytical and communication skills has been proposed. The result of monitoring information is the basis of informed decisions in the management of educational processes at the university. In scientific terms, the monitoring data allows us to estimate the impact of the various components of the learning outcomes (formed skills, acquired social capital, etc. at professional tracks. Information base of monitoring made by online alumni Sociology Department EF NSU survey, that’s materials revealed what analytical skills formed during study at the university, allow them to adapt to the diversified requirements of the labor market. Graduates sociologists are divided into two streams: a smaller consisting of working in the specialty, which is formed mainly through personalized contacts, and the bigger distributed to other segments of the labor market through a formal selection process.

  16. Blended learning pedagogy: the time is now!

    Science.gov (United States)

    Pizzi, Michael A

    2014-07-01

    Pedagogy is rapidly changing. To develop best practice in academia, it is important that we change with the changing needs of students. This article suggests that blended learning is one of the most important pedagogical formats that can enhance student learning, optimize the use of active learning strategies, and potentially improve student learning outcomes.

  17. Real-time optoacoustic monitoring of temperature in tissues

    International Nuclear Information System (INIS)

    Larina, Irina V; Larin, Kirill V; Esenaliev, Rinat O

    2005-01-01

    To improve the safety and efficacy of thermal therapy, it is necessary to map tissue temperature in real time with submillimetre spatial resolution. Accurate temperature maps may provide the necessary control of the boundaries of the heated regions and minimize thermal damage to surrounding normal tissues. Current imaging modalities fail to monitor tissue temperature in real time with high resolution and accuracy. We investigated a non-invasive optoacoustic method for accurate, real-time monitoring of tissue temperature during thermotherapy. In this study, we induced temperature gradients in tissue and tissue-like samples and monitored the temperature distribution using the optoacoustic technique. The fundamental harmonic of a Q-switched Nd : YAG laser (λ = 1064 nm) was used for optoacoustic wave generation and probing of tissue temperature. The tissue temperature was also monitored with a multi-sensor temperature probe inserted in the samples. Good agreement between optoacoustically measured and actual tissue temperatures was obtained. The accuracy of temperature monitoring was better than 1 0 C, while the spatial resolution was about 1 mm. These data suggest that the optoacoustic technique has the potential to be used for non-invasive, real-time temperature monitoring during thermotherapy

  18. Learning to stay ahead of time

    DEFF Research Database (Denmark)

    Staunæs, Dorthe; Raffnsøe, Sverre

    2014-01-01

    In the context of an ongoing change, management is required to take the form of a leadership that must be reignited over and over again. The article examines a new art of leadership that may be viewed as an attempt to keep up with these challenges and stay ahead of time. It emerges from...... a pilgrimage leadership learning laboratory on the road to Santiago de la Compostela. This moving lab creates situations of extraordinary intensity that border on hyperreality and force the leader to find him/herself anew on the verge of him/herself. Conceived as pilgrimage, leadership moves ahead of time...... as it reaches into and anticipates a future still unknown. In this setting, anticipatory affects and the virtual take up a predominant role. As it emerges here, leadership distinguishes itself not only from leadership in the traditional sense, but also from management and governmentality....

  19. Precarious Learning and Labour in Financialized Times

    Directory of Open Access Journals (Sweden)

    Jamie Magnusson

    2013-07-01

    Full Text Available Our current globalized economic regimes of financialized capital have systematically altered relations of learning and labour through the dynamics of precarity, debt, and the political economy of new wars. The risks of these regimes are absorbed unevenly across transnational landscapes, creating cartographies of violence and dispossession, particularly among youth, indigenous, working class, and racialized women. Presently there is surprisingly little discussion on the relevance of financialization for adult educators. Transnational resistances organizing against neoliberal restructuring, austerity policies, and debt crises are emerging at the same time that massive investments are being made into homeland security and the carceral state. This paper opens up discussion on the implications of financialized times for educators, and develops an analytic framework for examining how these global realities are best addressed at local sites of adult and higher education.

  20. Monitoring activities of satellite data processing services in real-time with SDDS Live Monitor

    Science.gov (United States)

    Duc Nguyen, Minh

    2017-10-01

    This work describes Live Monitor, the monitoring subsystem of SDDS - an automated system for space experiment data processing, storage, and distribution created at SINP MSU. Live Monitor allows operators and developers of satellite data centers to identify errors occurred in data processing quickly and to prevent further consequences caused by the errors. All activities of the whole data processing cycle are illustrated via a web interface in real-time. Notification messages are delivered to responsible people via emails and Telegram messenger service. The flexible monitoring mechanism implemented in Live Monitor allows us to dynamically change and control events being shown on the web interface on our demands. Physicists, whose space weather analysis models are functioning upon satellite data provided by SDDS, can use the developed RESTful API to monitor their own events and deliver customized notification messages by their needs.

  1. Monitoring activities of satellite data processing services in real-time with SDDS Live Monitor

    Directory of Open Access Journals (Sweden)

    Duc Nguyen Minh

    2017-01-01

    Full Text Available This work describes Live Monitor, the monitoring subsystem of SDDS – an automated system for space experiment data processing, storage, and distribution created at SINP MSU. Live Monitor allows operators and developers of satellite data centers to identify errors occurred in data processing quickly and to prevent further consequences caused by the errors. All activities of the whole data processing cycle are illustrated via a web interface in real-time. Notification messages are delivered to responsible people via emails and Telegram messenger service. The flexible monitoring mechanism implemented in Live Monitor allows us to dynamically change and control events being shown on the web interface on our demands. Physicists, whose space weather analysis models are functioning upon satellite data provided by SDDS, can use the developed RESTful API to monitor their own events and deliver customized notification messages by their needs.

  2. Real-time water quality monitoring and providing water quality ...

    Science.gov (United States)

    EPA and the U.S. Geological Survey (USGS) have initiated the “Village Blue” research project to provide real-time water quality monitoring data to the Baltimore community and increase public awareness about local water quality in Baltimore Harbor and the Chesapeake Bay. The Village Blue demonstration project complements work that a number of state and local organizations are doing to make Baltimore Harbor “swimmable and fishable” 2 by 2020. Village Blue is designed to build upon EPA’s “Village Green” project which provides real-time air quality information to communities in six locations across the country. The presentation, “Real-time water quality monitoring and providing water quality information to the Baltimore Community”, summarizes the Village Blue real-time water quality monitoring project being developed for the Baltimore Harbor.

  3. Progress and lessons learned from water-quality monitoring networks

    Science.gov (United States)

    Myers, Donna N.; Ludtke, Amy S.

    2017-01-01

    Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

  4. Real-time personal exposure and health condition monitoring system

    Energy Technology Data Exchange (ETDEWEB)

    Saitou, Isamu; Kanda, Hiroaki; Asai, Akio; Takeishi, Naoki; Ota, Yoshito [Hitachi Aloka Medical, Ltd., Measuring Systems Engineering Dept., Tokyo (Japan); Hanawa, Nobuhiro; Ueda, Hisao; Kusunoki, Tsuyoshi; Ishitsuka, Etsuo; Kawamura, Hiroshi [Japan Atomic Energy Agency, Oarai Research and Development Center, Oarai, Ibaraki (Japan)

    2012-03-15

    JAEA (Japan Atomic Energy Agency) and HAM (Hitachi Aloka Medical, Ltd) have proposed novel monitoring system for workers of nuclear facility. In these facilities, exposure management for workers is mainly used access control and personal exposure recordings. This system is currently only for reports management but is not confirmative for surveillance when work in progress. Therefore, JAEA and HAM integrate access control and personal exposure recordings and two real-time monitoring systems which are position sensing and vital sign monitor. Furthermore change personal exposure management to real-time management, this system integration prevents workers from risk of accidents, and makes possible take appropriate action quickly. This novel system is going to start for tentative operation, using position sensing and real-time personal dosimeter with database in Apr. 2012. (author)

  5. Task 1. Monitoring real time materials degradation. NRC extended In-situ and real-time Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Bakhtiari, Sasan [Argonne National Lab. (ANL), Argonne, IL (United States)

    2012-03-01

    The overall objective of this project was to perform a scoping study to identify, in concert with the nuclear industry, those sensors and techniques that have the most promising commercial viability and fill a critical inspection or monitoring need. Candidates to be considered include sensors to monitor real-time material degradation, characterize residual stress, monitor and inspect component fabrication, assess radionuclide and associated chemical species concentrations in ground water and soil, characterize fuel properties, and monitor severe accident conditions. Under Task 1—Monitoring Real-Time Materials Degradation—scoping studies were conducted to assess the feasibility of potential inspection and monitoring technologies (i.e., a combination of sensors, advanced signal processing techniques, and data analysis methods) that could be utilized in LWR and/or advanced reactor applications for continuous monitoring of degradation in-situ. The goal was to identify those techniques that appear to be the most promising, i.e., those that are closest to being both technically and commercially viable and that the nuclear industry is most likely to pursue. Current limitations and associated issues that must be overcome before commercial application of certain techniques have also been addressed.

  6. Forecasting air quality time series using deep learning.

    Science.gov (United States)

    Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

    2018-04-13

    This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution

  7. Real Time Physiological Status Monitoring (RT-PSM): Accomplishments, Requirements, and Research Roadmap

    Science.gov (United States)

    2016-03-01

    actionable information. With many lessons learned , the first implementation of real time physiological monitoring (RT-PSM) uses thermal-work strain... Bidirectional Inductive On-Body Network (BIONET) for WPSM Develop sensor links and processing nodes on-Soldier and non-RF links off-Soldier Elintrix...recent sleep watches (e.g., BASIS Peak, Intel Corp.) are attempting to parse sleep quality beyond duration and interruptions into deep and REM sleep

  8. In-Time On-Place Learning

    Science.gov (United States)

    Bauters, Merja; Purma, Jukka; Leinonen, Teemu

    2014-01-01

    The aim of this short paper is to look at how mobile video recording devices could support learning related to physical practices or places and situations at work. This paper discusses particular kind of workplace learning, namely learning using short video clips that are related to physical environment and tasks preformed in situ. The paper…

  9. Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

    Science.gov (United States)

    Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

    2013-09-01

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

  10. A tool for monitoring lecturers’ interactions with Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Magdalena Cantabella

    2016-12-01

    Full Text Available Learning Management Systems’ (LMS interaction mechanisms are mainly focused on the improvement of students’ experiences and academic results. However, special attention should also be given to the interaction between these LMS and other actors involved in the educational process. This paper specifically targets the interaction of degree coordinators with LMS when monitoring lecturers’ performance, especially in an online mode. The methodology is guided by the following three objectives: (1 analysis of the limitations of monitoring lecturers in current LMS; (2 development of software program to overcome such limitations; and (3 empirical evaluation of the proposed program. The results show that this type of tool helps coordinators to intuitively and efficiently analyze the status of the subjects taught in their degree programs.

  11. Application of real time spectrum measurement to radiation monitors

    International Nuclear Information System (INIS)

    Matsuno, K.; Watanabe, M.; Sakamaki, T.

    1996-01-01

    A multichannel analyzer (MCA) and two realtime spectrum monitoring methods have been developed for use in radiation monitors. The new MCA was designed to be installed at a local site as a component of a radiation monitor. The MCA repeats spectrum measurement at short intervals (Δt) and, after each measurement, transmits a spectrum datum to the operation console. The authors applied two methods to process Δt spectrum counts for each channel for longer time interval. One method of processing counts is the 'running average (RA) method'. The other method is the 'exponential smoothing (ES) method', which simulates RC rate meters by subtracting a fraction corresponding to the accumulated counts. Relative standard deviations for each channel can be made the same by selecting an appropriate value. The response with the 'ES' method is initially faster than that with the 'RA' method, but the 'RA' method allows a full response to be reached at a predictable time. (author)

  12. Leisure time activities, parental monitoring and drunkenness in adolescents

    NARCIS (Netherlands)

    Tomcikova, Z.; Veselska, Z.; Madarasova Geckova, A.; van Dijk, J.P.; Reijneveld, S.A.

    2012-01-01

    Background: The aim of this cross-sectional study was to explore the association between adolescent drunkenness and participation in risky leisure time activities and parental monitoring. Methods: A sample of 3,694 Slovak elementary school students (mean age 14.5 years; 49.0% males) was assessed for

  13. Leisure Time Activities, Parental Monitoring and Drunkenness in Adolescents

    NARCIS (Netherlands)

    Tomcikova, Zuzana; Veselska, Zuzana; Geckova, Andrea Madarasova; van Dijk, Jitse P.; Reijneveld, Sijmen A.

    2013-01-01

    Background: The aim of this cross-sectional study was to explore the association between adolescent drunkenness and participation in risky leisure time activities and parental monitoring. Methods: A sample of 3,694 Slovak elementary school students (mean age 14.5 years; 49.0% males) was assessed for

  14. Real-time earthquake monitoring: Early warning and rapid response

    Science.gov (United States)

    1991-01-01

    A panel was established to investigate the subject of real-time earthquake monitoring (RTEM) and suggest recommendations on the feasibility of using a real-time earthquake warning system to mitigate earthquake damage in regions of the United States. The findings of the investigation and the related recommendations are described in this report. A brief review of existing real-time seismic systems is presented with particular emphasis given to the current California seismic networks. Specific applications of a real-time monitoring system are discussed along with issues related to system deployment and technical feasibility. In addition, several non-technical considerations are addressed including cost-benefit analysis, public perceptions, safety, and liability.

  15. Geological storage of CO2 : time frames, monitoring and verification

    International Nuclear Information System (INIS)

    Chalaturnyk, R.; Gunter, W.D.

    2005-01-01

    In order to ensure that carbon dioxide (CO 2 ) injection and storage occurs in an environmentally sound and safe manner, many organizations pursuing the development of a CO 2 geological storage industry are initiating monitoring programs that include operational monitoring; verification monitoring; and environmental monitoring. Each represents an increase in the level of technology used and the intensity and duration of monitoring. For each potential site, the project conditions must be defined, the mechanisms that control the fluid flow must be predicted and technical questions must be addressed. This paper reviewed some of the relevant issues in establishing a monitoring framework for geological storage and defined terms that indicate the fate of injected CO 2 . Migration refers to movement of fluids within the injection formation, while leakage refers to movement of fluids outside the injection formation, and seepage refers to movement of fluids from the geosphere to the biosphere. Currently, regulatory agencies focus mostly on the time period approved for waste fluid injection, including CO 2 , into depleted hydrocarbon reservoirs or deep saline aquifers, which is in the order of 25 years. The lifetime of the injection operation is limited by reservoir capacity and the injection rate. Monitoring periods can be divided into periods based on risk during injection-operation (10 to 25 years), at the beginning of the storage period during pressure equilibration (up to 100 years), and over the long-term (from 100 to 1000 years). The 42 commercial acid gas injection projects currently in operation in western Canada can be used to validate the technology for the short term, while validation of long-term storage can be based on natural geological analogues. It was concluded that a monitored decision framework recognizes uncertainties in the geological storage system and allows design decisions to be made with the knowledge that planned long-term observations and their

  16. An algorithm for learning real-time automata

    NARCIS (Netherlands)

    Verwer, S.E.; De Weerdt, M.M.; Witteveen, C.

    2007-01-01

    We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe

  17. Quality of E-Learners’ Time and Learning Performance Beyond Quantitative Time-on-Task

    Directory of Open Access Journals (Sweden)

    Margarida Romero

    2011-06-01

    Full Text Available AbstractAlong with the amount of time spent learning (or time-on-task, the quality of learning time has a real influence on learning performance. Quality of time in online learning depends on students’ time availability and their willingness to devote quality cognitive time to learning activities. However, the quantity and quality of the time spent by adult e-learners on learning activities can be reduced by professional, family, and social commitments. Considering that the main time pattern followed by most adult e-learners is a professional one, it may be beneficial for online education programs to offer a certain degree of flexibility in instructional time that might allow adult learners to adjust their learning times to their professional constraints. However, using the time left over once professional and family requirements have been fulfilled could lead to a reduction in quality time for learning. This paper starts by introducing the concept of quality of learning time from an online student-centred perspective. The impact of students’ time-related variables (working hours, time-on-task engagement, time flexibility, time of day, day of week is then analyzed according to individual and collaborative grades achieved during an online master’s degree program. The data show that both students’ time flexibility (r = .98 and especially their availability to learn in the morning are related to better grades in individual (r = .93 and collaborative activities (r = .46.

  18. Real-time electron-beam dose monitoring

    International Nuclear Information System (INIS)

    McKeown, J.

    1995-01-01

    A new technique to monitor the integrated dose that a product receives in an irradiation facility is determined by collecting the charge that passes through the product. The technique allows the absorbed dose to be monitored as the irradiation is taking place, i.e. on-line and in real time. The procedure will also provide a means of directly measuring the electron energy, independent of the accelerator control system. The irradiation plant operator can immediately detect a problem of inadequate electron energy and take appropriate action. Examples taken on the IMPELA trademark accelerator at the Iotron Irradiation Facility in Vancouver are presented

  19. Real time monitoring of moment magnitude by waveform inversion

    Science.gov (United States)

    Lee, J.; Friederich, W.; Meier, T.

    2012-01-01

    An instantaneous measure of the moment magnitude (Mw) of an ongoing earthquake is estimated from the moment rate function (MRF) determined in real-time from available seismic data using waveform inversion. Integration of the MRF gives the moment function from which an instantaneous Mw is derived. By repeating the inversion procedure at regular intervals while seismic data are coming in we can monitor the evolution of seismic moment and Mw with time. The final size and duration of a strong earthquake can be obtained within 12 to 15 minutes after the origin time. We show examples of Mw monitoring for three large earthquakes at regional distances. The estimated Mw is only weakly sensitive to changes in the assumed source parameters. Depending on the availability of seismic stations close to the epicenter, a rapid estimation of the Mw as a prerequisite for the assessment of earthquake damage potential appears to be feasible.

  20. Conceptual design for real time monitoring of electron microbeam

    International Nuclear Information System (INIS)

    Kim, Ji Seok; Kim, Hyun Ki; Jang, Mee; Choi, Chang Woon; Sun, Gwang Min; Lee, Jai Ki

    2008-01-01

    It is recognized that the microbeam is powerful system to understand the interaction of ionizing radiation with cells. Especially, electron microbeam system is useful to investigate the effect of low-LET radiation for cells. Electron microbeam has been developed in KIRAMS. It can irradiate the small volume in cell level by collimator and electromagnetic field and give local dose to individual cell by controlling the number of electrons. When the electron microbeam irradiates the individual cell, however, there is a possibility to change the current and intended trajectory of electron beam. Because this possibility introduces the uncertainty of dose, it is necessary to monitor the trajectory and current of electron beam. This study deals with development of real time monitoring device to confirm beam quality and to control if necessary during experiment. Consequently we designed dual monitoring device to solve various factors. And we optimize the design by simulation. (author)

  1. Real-Time Monitoring of Psychotherapeutic Processes: Concept and Compliance

    Directory of Open Access Journals (Sweden)

    Guenter Karl Schiepek

    2016-05-01

    Full Text Available AbstractObjective. The feasibility of a high-frequency real-time monitoring approach to psychotherapy is outlined and tested for patients’ compliance to evaluate its integration to everyday practice. Criteria concern the ecological momentary assessment, the assessment of therapy-related cognitions and emotions, equidistant time sampling, real-time nonlinear time series analysis, continuous participative process control by client and therapist, and the application of idiographic (person-specific surveys. Methods. The process-outcome monitoring is technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System. Its feasibility is documented by a compliance study on 151 clients treated in an inpatient and a day-treatment clinic. Results. We found high compliance rates (mean: 78.3%, median: 89.4% amongst the respondents, independent of the severity of symptoms or the degree of impairment. Compared to other diagnoses, the compliance rate was lower in the group diagnosed with personality disorders. Conclusion. The results support the feasibility of high-frequency monitoring in routine psychotherapy settings. Daily collection of psychological surveys allows for assessment of highly resolved, equidistant time series data which gives insight into the nonlinear qualities of therapeutic change processes (e.g., pattern transitions, critical instabilities.

  2. Real-Time Monitoring of Psychotherapeutic Processes: Concept and Compliance

    Science.gov (United States)

    Schiepek, Günter; Aichhorn, Wolfgang; Gruber, Martin; Strunk, Guido; Bachler, Egon; Aas, Benjamin

    2016-01-01

    Objective: The feasibility of a high-frequency real-time monitoring approach to psychotherapy is outlined and tested for patients' compliance to evaluate its integration to everyday practice. Criteria concern the ecological momentary assessment, the assessment of therapy-related cognitions and emotions, equidistant time sampling, real-time nonlinear time series analysis, continuous participative process control by client and therapist, and the application of idiographic (person-specific) surveys. Methods: The process-outcome monitoring is technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System. Its feasibility is documented by a compliance study on 151 clients treated in an inpatient and a day-treatment clinic. Results: We found high compliance rates (mean: 78.3%, median: 89.4%) amongst the respondents, independent of the severity of symptoms or the degree of impairment. Compared to other diagnoses, the compliance rate was lower in the group diagnosed with personality disorders. Conclusion: The results support the feasibility of high-frequency monitoring in routine psychotherapy settings. Daily collection of psychological surveys allows for the assessment of highly resolved, equidistant time series data which gives insight into the nonlinear qualities of therapeutic change processes (e.g., pattern transitions, critical instabilities). PMID:27199837

  3. Radiation environmental real-time monitoring and dispersion modeling

    International Nuclear Information System (INIS)

    Kovacik, A.; Bartokova, I.; Omelka, J.; Melicherova, T.

    2014-01-01

    The system of real-time radiation monitoring provided by MicroStep-MIS is a turn-key solution for measurement, acquisition, processing, reporting, archiving and displaying of various radiation data. At the level of measurements, the monitoring stations can be equipped with various devices from radiation probes, measuring the actual ambient gamma dose rate, to fully automated aerosol monitors, returning analysis results of natural and manmade radionuclides concentrations in the air. Using data gathered by our radiation probes RPSG-05 integrated into monitoring network of Crisis Management of the Slovak Republic and into monitoring network of Slovak Hydrometeorological Institute, we demonstrate its reliability and long-term stability of measurements. Data from RPSG-05 probes and GammaTracer probes, both of these types are used in the SHI network, are compared. The sensitivity of RPSG-05 is documented on data where changes of dose rate are caused by precipitation. Qualities of RPSG-05 probe are illustrated also on example of its use in radiation monitoring network in the United Arab Emirates. A more detailed information about radioactivity of the atmosphere can be obtained by using spectrometric detectors (e.g. scintillation detectors) which, besides gamma dose rate values, offer also a possibility to identify different radionuclides. However, this possibility is limited by technical parameters of detector like energetic resolution and detection efficiency in given geometry of measurement. A clearer information with less doubts can be obtained from aerosol monitors with a built-in silicon detector of alpha and beta particles and with an electrically cooled HPGe detector dedicated for gamma-ray spectrometry, which is performed during the sampling. Data from a complex radiation monitoring network can be used, together with meteorological data, in radiation dispersion model by MicroStep-MIS. This model serves for simulation of atmospheric propagation of radionuclides

  4. Working and Learning in Times of Uncertainty

    DEFF Research Database (Denmark)

    This book analyses the challenges of globalisation and uncertainty impacting on working and learning at individual, organisational and societal levels. Each of the contributions addresses two overall questions: How is working and learning affected by uncertainty and globalisation? And, in what ways...... do individuals, organisations, political actors and education systems respond to these challenges? Part 1 focuses on the micro level of working and learning for understanding the learning processes from an individual point of view by reflecting on learners’ needs and situations at work and in school......). Finally, Part 3 addresses the macro level of working and learning by analysing how to govern, structure and organise vocational, professional and adult education at the boundaries of work, education and policy making....

  5. Learning Styles of Medical Students Change in Relation to Time

    Science.gov (United States)

    Gurpinar, Erol; Bati, Hilal; Tetik, Cihat

    2011-01-01

    The aim of the present study was to investigate if any changes exist in the learning styles of medical students over time and in relation to different curriculum models with these learning styles. This prospective cohort study was conducted in three different medical faculties, which implement problem-based learning (PBL), hybrid, and integrated…

  6. Real-time beam monitoring in scanned proton therapy

    Science.gov (United States)

    Klimpki, G.; Eichin, M.; Bula, C.; Rechsteiner, U.; Psoroulas, S.; Weber, D. C.; Lomax, A.; Meer, D.

    2018-05-01

    When treating cancerous tissues with protons beams, many centers make use of a step-and-shoot irradiation technique, in which the beam is steered to discrete grid points in the tumor volume. For safety reasons, the irradiation is supervised by an independent monitoring system validating cyclically that the correct amount of protons has been delivered to the correct position in the patient. Whenever unacceptable inaccuracies are detected, the irradiation can be interrupted to reinforce a high degree of radiation protection. At the Paul Scherrer Institute, we plan to irradiate tumors continuously. By giving up the idea of discrete grid points, we aim to be faster and more flexible in the irradiation. But the increase in speed and dynamics necessitates a highly responsive monitoring system to guarantee the same level of patient safety as for conventional step-and-shoot irradiations. Hence, we developed and implemented real-time monitoring of the proton beam current and position. As such, we read out diagnostic devices with 100 kHz and compare their signals against safety tolerances in an FPGA. In this paper, we report on necessary software and firmware enhancements of our control system and test their functionality based on three exemplary error scenarios. We demonstrate successful implementation of real-time beam monitoring and, consequently, compliance with international patient safety regulations.

  7. Genetic association studies of performance monitoring and learning from feedback: The role of dopamine and serotonin

    NARCIS (Netherlands)

    Ullsperger, M.

    2010-01-01

    Performance monitoring is essential for optimization of action outcomes. Research consistently implicates the posterior medial frontal cortex, particularly the rostral cingulate zone, in monitoring for unfavorable action outcomes, signaling the need for adjustments and learning from feedback.

  8. Real-time Data Access Monitoring in Distributed, Multi-petabyte Systems

    Energy Technology Data Exchange (ETDEWEB)

    Azemoon, Tofigh; Becla, Jacek, a=Hanushevsky, Andrew; Turri, Massimiliano; /SLAC

    2008-04-22

    Petascale systems are in existence today and will become common in the next few years. Such systems are inevitably very complex, highly distributed and heterogeneous. Monitoring a petascale system in real-time and understanding its status at any given moment without impacting its performance is a highly intricate task. Common approaches and off-the-shelf tools are either unusable, do not scale, or severely impact the performance of the monitored servers. This paper describes unobtrusive monitoring software developed at Stanford Linear Accelerator Center (SLAC) for a highly distributed petascale production data set. The paper describes the employed solutions, the lessons learned, the problems still to be addressed, and explains how the system can be reused elsewhere.

  9. Real-time Color Codes for Assessing Learning Process

    OpenAIRE

    Dzelzkalēja, L; Kapenieks, J

    2016-01-01

    Effective assessment is an important way for improving the learning process. There are existing guidelines for assessing the learning process, but they lack holistic digital knowledge society considerations. In this paper the authors propose a method for real-time evaluation of students’ learning process and, consequently, for quality evaluation of teaching materials both in the classroom and in the distance learning environment. The main idea of the proposed Color code method (CCM) is to use...

  10. Monitor of dynamic parameters in real time; Monitor de parametros dinamicos en tiempo real

    Energy Technology Data Exchange (ETDEWEB)

    Rojas S, A.S.; Ruiz E, J.A. [ININ, 52750 La Marquesa, Estado de Mexico (Mexico)

    2008-07-01

    In the complex physical systems exist parameters that are necessary for monitoring in real time. In the nuclear industry, particularly in a reactor this surveillance is important, where the times of the reactions are almost instantaneous. Although many of these parameters are monitored, given the advance of the computer systems the monitoring could either be enlarged direct or indirect of other parameters. The analysis of the neutron noise in the nuclear reactors, plays an important role, the noise signal it contains information about the operation conditions of a system, when analyzing it with analysis methodologies of analogical signals to provide important information for the early detection of possible flaws and to indicate the permissible operation levels. To show the characteristics of the operation of the system of Monitoring of Dynamic Parameters in Real Time, oscillations of neutron noise of the TRIGA Mark III of the ININ were analyzed, these were caused with the control bar to a power of 10 Watts, the oscillations were carried out to a frequency of 1Hz, signal of low frequency. In this work a virtual instrument that allows by means of the spectral analysis method in frequency point by point is presented, to indicate in real time periodic variations that could be presented in the neutron noise signal, visualizing in advance the dynamic behavior of the system or nuclear plant. Another of the tests of the monitoring system presented is that of the oscillatory event happened in the reactor of Laguna Verde Nucleo electric Central, would be convenient to have an instrument of surveillance for monitoring through the neutron noise signal the behavior of some important parameter to predict and to indicate in an immediate way an abnormal condition in the reactor operation or in the plant system. These parameters can be the power, the recirculation water flow, etc. The monitor is based on a personal computer (PC), a data acquisition card (ADC) and a computer program

  11. GSM based real time remote radiation monitoring and mapping system

    International Nuclear Information System (INIS)

    Dodiya, Kamal; Gupta, Ashutosh; Padmanabhan, N.; Chaudhury, Probal; Pradeepkumar, K.S.

    2014-01-01

    Mobile Radiological Impact Assessment Laboratory (M-RIAL) has been developed in Radiation Safety Systems Division, Bhabha Atomic Research Centre for carrying out assessment of radioactive contamination following a nuclear or radiological emergency in a nuclear facility or in public domain. During such situations a large area is to be monitored for radiological impact assessment and availability of the monitored data in real-time to a control centre is a great advantage for the decision makers. Development and application of such a system has been described in this paper. The system can transmit real-time radiological data, acquired by the universal counting system of M-RIAL and tagged with positional information, wirelessly to an Emergency Response Centre (ERC) using Global System for Mobile (GSM) communication. The radiological profile of the affected area is then superimposed on Geographical Information System (GIS) at the ERC and which can be used for the generation of radiological impact maps for use as decision support

  12. Real-time trend monitoring of gas compressor stations

    Energy Technology Data Exchange (ETDEWEB)

    Van Hardeveld, T. (Nova, an Alberta Corp., AB (Canada))

    1991-02-01

    The authors' company has developed a machinery health monitoring system (MHealth) for short-term and long-term historical trending and analysis of data from its 40 gas compressor stations. The author discusses the benefits of real-time trending in troubleshooting operations, in preventative maintenance scheduling and cites specific applications in the startup operations of several new gas compressor/centrifugal compressor units.

  13. Real-time flood monitoring and warning system

    Directory of Open Access Journals (Sweden)

    Jirapon Sunkpho

    2011-04-01

    Full Text Available Flooding is one of the major disasters occurring in various parts of the world. The system for real-time monitoring ofwater conditions: water level; flow; and precipitation level, was developed to be employed in monitoring flood in Nakhon SiThammarat, a southern province in Thailand. The two main objectives of the developed system is to serve 1 as informationchannel for flooding between the involved authorities and experts to enhance their responsibilities and collaboration and2 as a web based information source for the public, responding to their need for information on water condition and flooding.The developed system is composed of three major components: sensor network, processing/transmission unit, and database/application server. These real-time data of water condition can be monitored remotely by utilizing wireless sensors networkthat utilizes the mobile General Packet Radio Service (GPRS communication in order to transmit measured data to theapplication server. We implemented a so-called VirtualCOM, a middleware that enables application server to communicatewith the remote sensors connected to a GPRS data unit (GDU. With VirtualCOM, a GDU behaves as if it is a cable directlyconnected the remote sensors to the application server. The application server is a web-based system implemented usingPHP and JAVA as the web application and MySQL as its relational database. Users can view real-time water conditionas well as the forecasting of the water condition directly from the web via web browser or via WAP. The developed systemhas demonstrated the applicability of today’s sensors in wirelessly monitor real-time water conditions.

  14. Simultaneous real-time monitoring of multiple cortical systems.

    Science.gov (United States)

    Gupta, Disha; Jeremy Hill, N; Brunner, Peter; Gunduz, Aysegul; Ritaccio, Anthony L; Schalk, Gerwin

    2014-10-01

    Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance. We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time. This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our

  15. Embedded Triboelectric Active Sensors for Real-Time Pneumatic Monitoring.

    Science.gov (United States)

    Fu, Xian Peng; Bu, Tian Zhao; Xi, Feng Ben; Cheng, Ting Hai; Zhang, Chi; Wang, Zhong Lin

    2017-09-20

    Pneumatic monitoring sensors have great demands for power supply in cylinder systems. Here, we present an embedded sliding triboelectric nanogenerator (TENG) in air cylinder as active sensors for position and velocity monitoring. The embedded TENG is composed of a circular poly(tetrafluoroethylene) polymer and a triangular copper electrode. The working mechanism as triboelectric active sensors and electric output performance are systematically investigated. By integrating into the pneumatic system, the embedded triboelectric active sensors have been used for real-time air pressure/flow monitoring and energy storage. Air pressures are measured from 0.04 to 0.12 MPa at a step of 0.02 MPa with a sensitivity of 49.235 V/MPa, as well as airflow from 50 to 250 L/min at a step of 50 L/min with a sensitivity of 0.002 μA·min/L. This work has first demonstrated triboelectric active sensors for pneumatic monitoring and may promote the development of TENG in intelligent pneumatic system.

  16. Integrated active sensor system for real time vibration monitoring.

    Science.gov (United States)

    Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

    2015-11-05

    We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0-60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.

  17. Intelligent data management for real-time spacecraft monitoring

    Science.gov (United States)

    Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

    1992-01-01

    Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

  18. ATLAS Tile Calorimeter time calibration, monitoring and performance

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00075913; The ATLAS collaboration

    2016-01-01

    The Tile Calorimeter (TileCal) is the hadronic calorimeter covering the central region of the ATLAS experiment at the LHC. This sampling device is made of plastic scintillating tiles alternated with iron plates and its response is calibrated to electromagnetic scale by means of several dedicated calibration systems. The accurate time calibration is important for the energy reconstruction, non-collision background removal as well as for specific physics analyses. The initial time calibration with so-called splash events and subsequent fine-tuning with collision data are presented. The monitoring of the time calibration with laser system and physics collision data is discussed as well as the corrections for sudden changes performed still before the recorded data are processed for physics analyses. Finally, the time resolution as measured with jets and isolated muons particles is presented.

  19. Lessons Learned In Aerosol Monitoring With The RASA

    International Nuclear Information System (INIS)

    Forrester, Joel B.; Bowyer, Ted W.; Carty, Fitz; Comes, Laura; Eslinger, Paul W.; Greenwood, Lawrence R.; Haas, Derek A.; Hayes, James C.; Kirkham, Randy R.; Lepel, Elwood A.; Litke, Kevin E.; Miley, Harry S.; Morris, Scott J.; Schrom, Brian T.; Van Davelaar, Peter; Woods, Vincent T.

    2011-01-01

    The Radionuclide Aerosol Sampler/Analyzer (RASA) is an automated aerosol collection and analysis system designed by Pacific Northwest National Laboratory (PNNL) in the 1990's and is deployed in several locations around the world as part of the International Monitoring System (IMS) required under the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The RASA operates unattended, save for regularly scheduled maintenance, iterating samples through a three-step process on a 24-hour interval. In its 15-year history, much has been learned from the operation and maintenance of the RASA that can benefit engineering updates or future aerosol systems. On 11 March 2011, a 9.0 magnitude earthquake and tsunami rocked the eastern coast of Japan, resulting in power loss and cooling failures at the Daiichi nuclear power plants in Fukushima Prefecture. Aerosol collections were conducted with the RASA in Richland, WA. We present a summary of the lessons learned over the history of the RASA, including lessons taken from the Fukushima incident, regarding the RASA IMS stations operated by the United States.

  20. Development of a real time chemistry monitoring and diagnostic system

    International Nuclear Information System (INIS)

    Gaudreau, T.M.; Millett, P.J.; Bates, J.; Burns, G.

    1998-01-01

    EPRI has developed SMART chem WORKS, which is capable of operating as a real time chemistry diagnostic and monitoring system. A high degree of plant-specific customization is possible which allows discrimination between normal chemistry and off-normal conditions. The initial implementation of the system has been very successful. State of the art technology has been employed which allows remote administration of the system, a flexible, web page display of the output from the system and instant notification of excursions using email and pagers. The second installation of SMART chem WORKS is currently underway at a BWR plant, Grand Gulf. The SMART chem WORKS techniques can be applied to monitor PWR Primary Chemistry, PWR Secondary Chemistry and BWR steam cycle chemistry. A fossil steam cycle simulator will also be developed for application to fossil plants. (J.P.N.)

  1. Expert system and process optimization techniques for real-time monitoring and control of plasma processes

    Science.gov (United States)

    Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

    1991-03-01

    To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

  2. Precarious Learning and Labour in Financialized Times

    Science.gov (United States)

    Magnusson, Jamie

    2013-01-01

    Our current globalized economic regimes of financialized capital have systematically altered relations of learning and labour through the dynamics of precarity, debt, and the political economy of new wars. The risks of these regimes are absorbed unevenly across transnational landscapes, creating cartographies of violence and dispossession,…

  3. Learning to trust : network effects through time.

    NARCIS (Netherlands)

    Barrera, D.; Bunt, G. van de

    2009-01-01

    This article investigates the effects of information originating from social networks on the development of interpersonal trust relations in the context of a dialysis department of a Dutch medium-sized hospital. Hypotheses on learning effects are developed from existing theories and tested using

  4. Learning to trust: network effects through time

    NARCIS (Netherlands)

    Barrera, D.; van de Bunt, G

    2009-01-01

    This article investigates the effects of information originating from social networks on the development of interpersonal trust relations in the context of a dialysis department of a Dutch medium-sized hospital. Hypotheses on learning effects are developed from existing theories and tested using

  5. Real-time database for high resolution neutron monitor measurements

    Energy Technology Data Exchange (ETDEWEB)

    Steigies, Christian T.; Rother, Oliver M.; Wimmer-Schweingruber, Robert F.; Heber, Bernd [IEAP, Christian-Albrechts-Universitaet zu Kiel (Germany)

    2008-07-01

    The worldwide network of standardised neutron monitors is, after 50 years, still the state-of-the-art instrumentation to measure spectral variations of the primary cosmic ray component. These measurements are an ideal complement to space based cosmic ray measurements. Data from the approximately 50 IGY and NM64 neutron monitors is stored locally but also available through data collections sites like the World Data Center (WDC) or the IZMIRAN ftp server. The data from the WDC is in a standard format, but only hourly values are available. IZMIRAN collects the data in the best available time resolution, but the data arrives on the ftp server only hours, sometimes days, after the measurements. Also, the high time-resolution measurements of the different stations do not have a common format, a conversion routine for each station is needed before they can be used for scientific analysis. Supported by the 7th framework program of the European Commission, we are setting up a real-time database where high resolution cosmic ray measurements will be stored and accessible immediately after the measurement. Stations that do not have 1-minute resolution measurements will be upgraded to 1-minute or better resolution with an affordable standard registration system, that will submit the measurements to the database via the internet in real-time.

  6. PBL on Line: A Proposal for the Organization, Part-Time Monitoring and Assessment of PBL Group Activities

    Science.gov (United States)

    Marti, Enric; Gil, Debora; Gurguí, Antoni; Hernández-Sabaté, Aura; Rocarías, Jaume; Poveda, Ferran

    2015-01-01

    This report presents the organisation of PBL (Project Based Learning) for a subject included in the IT engineering degree course. It is the result of 10 years of experience of the implantation and continuous improvement of the PBL class structure. The latest innovations include the experience of part-time monitoring with PBL groups using the Open…

  7. Correction of time resolution of an ambulatory cardiac monitor (VEST)

    International Nuclear Information System (INIS)

    Kumita, Shin-ichiro; Nishimura, Tsunehiko; Hayashida, Kohei; Uehara, Toshiisa

    1990-01-01

    Using ambulatory cardiac monitor (VEST) at exercise study, its time resolution is very important factor. We evaluated the time resolution of VEST using pulsate cardiac baloon phantom. Four analysis were carried out; no smoothing (NS) method, 3 points smoothing (3S) method, short sampling interval (SS) method, and digital filter (DF) method. By comparison of |ΔEF| (|EF:HR120-EF: HR60|) among 4 analysis methods, |ΔEF| by DF method was significant small (NS:3.58±3.01, 3S: 4.46±0.95, SS: 3.35±3.26, DF: 1.11±1.28%). We conclude that correction of time resolution by digital filter is necessary when we use VEST during exercise. (author)

  8. Time domain spectroscopy to monitor the condition of cable insulation

    International Nuclear Information System (INIS)

    Mopsik, F.I.; Martzloff, F.D.

    1989-01-01

    The use of Time Domain Spectroscopy, the measurement of dielectric constant and loss using time-domain response, the monitoring the aging of reactor cable insulation is examined. The method is presented, showing its sensitivity, accuracy and wide frequency range. The method's ability to acquire a great deal of information in a short time and its superiority to conventional single frequency data is shown. Different cable samples are examined before and after exposure to radiation and changes with exposure are clearly seen to occur. Also it is shown that a wide range of behavior can be found in different insulation systems. The requirements for performing valid measurements is presented. The need for controlled samples and correlation with other criteria for aging is discussed. 14 refs., 9 figs

  9. Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems.

    Science.gov (United States)

    Tulsyan, Aditya; Garvin, Christopher; Ündey, Cenk

    2018-04-06

    Biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. The state-of-the-art real-time multivariate statistical batch process monitoring (BPM) platforms have been in use in recent years to ensure comprehensive monitoring is in place as a complementary tool for continued process verification to detect weak signals. This article addresses a longstanding, industry-wide problem in BPM, referred to as the "Low-N" problem, wherein a product has a limited production history. The current best industrial practice to address the Low-N problem is to switch from a multivariate to a univariate BPM, until sufficient product history is available to build and deploy a multivariate BPM platform. Every batch run without a robust multivariate BPM platform poses risk of not detecting potential weak signals developing in the process that might have an impact on process and product performance. In this article, we propose an approach to solve the Low-N problem by generating an arbitrarily large number of in silico batches through a combination of hardware exploitation and machine-learning methods. To the best of authors' knowledge, this is the first article to provide a solution to the Low-N problem in biopharmaceutical manufacturing using machine-learning methods. Several industrial case studies from bulk drug substance manufacturing are presented to demonstrate the efficacy of the proposed approach for BPM under various Low-N scenarios. © 2018 Wiley Periodicals, Inc.

  10. Radiographic apparatus and method for monitoring film exposure time

    International Nuclear Information System (INIS)

    Vatne, R.S.; Woodmansee, W.E.

    1981-01-01

    In connection with radiographic inspection of structural and industrial materials, method and apparatus are disclosed for automatically determining and displaying the time required to expose a radiographic film positioned to receive radiation passed by a test specimen, so that the finished film is exposed to an optimum blackening (density) for maximum film contrast. A plot is made of the variations in a total exposure parameter (representing the product of detected radiation rate and time needed to cause optimum film blackening) as a function of the voltage level applied to an X-ray tube. An electronic function generator storing the shape of this plot is incorporated into an exposure monitoring apparatus, such that for a selected tube voltage setting, the function generator produces an electrical analog signal of the corresponding exposure parameter. During the exposure, another signal is produced representing the rate of radiation as monitored by a diode detector positioned so as to receive the same radiation that is incident on the film. The signal representing the detected radiation rate is divided, by an electrical divider circuit into the signal representing total exposure, and the resulting quotient is an electrical signal representing the required exposure time. (author)

  11. Selection of monitoring times to assess remediation performance

    Energy Technology Data Exchange (ETDEWEB)

    Kueper, B.H.; Mundle, K. [Queen' s Univ., Kingston, ON (Canada). Dept. of Civil Engineering, Geoengineering Centre

    2007-07-01

    Several factors determine the time needed for a plume to respond to non-aqueous phase liquid (NAPL) source zone remediation. Most spills of NAPLs (fuels, chlorinated solvents, PCB oils, creosote and coal tar) require mass removal in order to implement remediation technologies such as chemical oxidation, thermal treatments, alcohol flushing, surfactant flushing and hydraulic displacement. While much attention has been given to the development of these remediation technologies, little attention has been given to the response of the plume downstream of the treatment zone and selection of an appropriate monitoring time scale to adequately evaluate the impacts of remediation. For that reason, this study focused on the prevalence of diffusive sinks, the mobility of the contaminant and the hydraulic conductivity of subsurface materials. Typically, plumes in subsurface environments dominated by diffusive sinks or low permeability materials need long periods of time to detach after source removal. This paper presented generic plume response model simulations that illustrated concentration rebound following the use of in-situ chemical oxidation in fractured clay containing trichloroethylene. It was determined that approximately 2 years are needed to reach peak rebound concentration after cessation remedial action. It was concluded that downgradient monitoring well concentrations may be greatly reduced during remedial action due to the fact that oxidant occupies the fracture and because oxidant diffuses into the clay matrix, creating a short period of contaminant reduction in the area of flowing groundwater. 9 refs., 2 tabs., 7 figs.

  12. Selection of monitoring times to assess remediation performance

    International Nuclear Information System (INIS)

    Kueper, B.H.; Mundle, K.

    2007-01-01

    Several factors determine the time needed for a plume to respond to non-aqueous phase liquid (NAPL) source zone remediation. Most spills of NAPLs (fuels, chlorinated solvents, PCB oils, creosote and coal tar) require mass removal in order to implement remediation technologies such as chemical oxidation, thermal treatments, alcohol flushing, surfactant flushing and hydraulic displacement. While much attention has been given to the development of these remediation technologies, little attention has been given to the response of the plume downstream of the treatment zone and selection of an appropriate monitoring time scale to adequately evaluate the impacts of remediation. For that reason, this study focused on the prevalence of diffusive sinks, the mobility of the contaminant and the hydraulic conductivity of subsurface materials. Typically, plumes in subsurface environments dominated by diffusive sinks or low permeability materials need long periods of time to detach after source removal. This paper presented generic plume response model simulations that illustrated concentration rebound following the use of in-situ chemical oxidation in fractured clay containing trichloroethylene. It was determined that approximately 2 years are needed to reach peak rebound concentration after cessation remedial action. It was concluded that downgradient monitoring well concentrations may be greatly reduced during remedial action due to the fact that oxidant occupies the fracture and because oxidant diffuses into the clay matrix, creating a short period of contaminant reduction in the area of flowing groundwater. 9 refs., 2 tabs., 7 figs

  13. Distributed computing for real-time petroleum reservoir monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Ayodele, O. R. [University of Alberta, Edmonton, AB (Canada)

    2004-05-01

    Computer software architecture is presented to illustrate how the concept of distributed computing can be applied to real-time reservoir monitoring processes, permitting the continuous monitoring of the dynamic behaviour of petroleum reservoirs at much shorter intervals. The paper describes the fundamental technologies driving distributed computing, namely Java 2 Platform Enterprise edition (J2EE) by Sun Microsystems, and the Microsoft Dot-Net (Microsoft.Net) initiative, and explains the challenges involved in distributed computing. These are: (1) availability of permanently placed downhole equipment to acquire and transmit seismic data; (2) availability of high bandwidth to transmit the data; (3) security considerations; (4) adaptation of existing legacy codes to run on networks as downloads on demand; and (5) credibility issues concerning data security over the Internet. Other applications of distributed computing in the petroleum industry are also considered, specifically MWD, LWD and SWD (measurement-while-drilling, logging-while-drilling, and simulation-while-drilling), and drill-string vibration monitoring. 23 refs., 1 fig.

  14. Real Time Environmental Radiation Monitoring System in the Philippines

    International Nuclear Information System (INIS)

    Garcia, Teofilo Y.

    2015-01-01

    The widespread release of radioactive materials caused by the Fukushima Daiichi Nuclear Power Plant Accident that occurred on 11 March 2011 raised concerns on the environmental radiation monitoring Presently, the Philippine Nuclear Research Institute (PNRI) can only perform limited incident. Country-wide radiation measurements by carrying out field-works in the different provinces of the country. This is due to limitation in the availability of appropriate equipment to carry-out the task of conducting radiation measurements, especially in remote and hart to access areas of the country. Although no nuclear reactor is currently operating in the Philippines, it is situated in a region surrounded by neighboring countries with several existing or planned nuclear power plants. While nuclear power has tremendous benefits in meeting the electricity needs of growing populations, and does not have the adverse environmental effects associated with burning of fossil fuels, there are potential risks from releases of radio nuclides into the environment. The PNRI, through the support of the International Atomic Energy Agency (IAEA), is establishing an on-line environmental radiation monitoring system that can provide real-time environmental during emergencies that lead to extensive spread of radioactive materials, such as nuclear power plant accidents, an on-line radiation monitoring system will enable the immediate detection of radiological emergencies affecting the country and will provide important information of authorities for appropriate emergency response. (author)

  15. Real-time monitoring of seismic data using satellite telemetry

    Directory of Open Access Journals (Sweden)

    L. Merucci

    1997-06-01

    Full Text Available This article describes the ARGO Satellite Seismic Network (ARGO SSN as a reliable system for monitoring, collection, visualisation and analysis of seismic and geophysical low-frequency data, The satellite digital telemetry system is composed of peripheral geophysical stations, a centraI communications node (master sta- tion located in CentraI Italy, and a data collection and processing centre located at ING (Istituto Nazionale di Geofisica, Rome. The task of the peripheral stations is to digitalise and send via satellite the geophysical data collected by the various sensors to the master station. The master station receives the data and forwards them via satellite to the ING in Rome; it also performs alI the monitoring functions of satellite communications. At the data collection and processing centre of ING, the data are received and analysed in real time, the seismic events are identified and recorded, the low-frequency geophysical data are stored. In addition, the generaI sta- tus of the satellite network and of each peripheral station connected, is monitored. The procedure for analysjs of acquired seismic signals allows the automatic calculation of local magnitude and duration magnitude The communication and data exchange between the seismic networks of Greece, Spain and Italy is the fruit of a recent development in the field of technology of satellite transmission of ARGO SSN (project of European Community "Southern Europe Network for Analysis of Seismic Data"

  16. Search route decision of environmental monitoring at emergency time

    International Nuclear Information System (INIS)

    Aoyama, Isao

    1979-01-01

    The search route decision method is reviewed, especially the adequate arrangement of monitors in view of time in the information-gathering activity by transferring the monitors on the horizontal space after the confirmation of the abnormal release of radioactive material. As for the field of the theory of search, the developmental history is explained, namely the experiences of the naval anti submarine operation in WW-2, the salvage activities and the search problem on the sea. The kinematics for search, the probability theory for detection and the optimum distribution for search are the most important contents of the application of theory of search relating to the environmental monitoring at emergency condition. The combination of a search model consists of the peculiarity of targets, the peculiarity of observers and the standard of optimality. The peculiarity of targets is divided into the space of search, the number of targets, the way of appearance of targets and the motion of targets. The peculiarity of observers is divided into the number of observers, the divisibility of efforts for search, the credibility of search information and the search process. The standard of optimality is divided into the maximum probability of detection, the minimum risk expected and the others. Each item written above of search model is explained. Concerning the formulation of the search model, the theoretical equations for detection probability, discovery potential and instantaneous detection probability, density are derived, and these equations are evaluated and explained. The future plan is to advance the search technology so as to evaluate the detection potential to decide the route of running a monitoring car for a nuclear power plant at accidental condition. (Nakai, Y.)

  17. SCALABLE TIME SERIES CHANGE DETECTION FOR BIOMASS MONITORING USING GAUSSIAN PROCESS

    Data.gov (United States)

    National Aeronautics and Space Administration — SCALABLE TIME SERIES CHANGE DETECTION FOR BIOMASS MONITORING USING GAUSSIAN PROCESS VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Biomass monitoring,...

  18. REVIEW OF MONITORING TOOLS FOR E-LEARNING PLATFORMS

    OpenAIRE

    Ali Alowayr; Atta Badii

    2014-01-01

    The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The...

  19. Monitoring transcranial direct current stimulation induced changes in cortical excitability during the serial reaction time task.

    Science.gov (United States)

    Ambrus, Géza Gergely; Chaieb, Leila; Stilling, Roman; Rothkegel, Holger; Antal, Andrea; Paulus, Walter

    2016-03-11

    The measurement of the motor evoked potential (MEP) amplitudes using single pulse transcranial magnetic stimulation (TMS) is a common method to observe changes in motor cortical excitability. The level of cortical excitability has been shown to change during motor learning. Conversely, motor learning can be improved by using anodal transcranial direct current stimulation (tDCS). In the present study, we aimed to monitor cortical excitability changes during an implicit motor learning paradigm, a version of the serial reaction time task (SRTT). Responses from the first dorsal interosseous (FDI) and forearm flexor (FLEX) muscles were recorded before, during and after the performance of the SRTT. Online measurements were combined with anodal, cathodal or sham tDCS for the duration of the SRTT. Negative correlations between the amplitude of online FDI MEPs and SRTT reaction times (RTs) were observed across the learning blocks in the cathodal condition (higher average MEP amplitudes associated with lower RTs) but no significant differences in the anodal and sham conditions. tDCS did not have an impact on SRTT performance, as would be predicted based on previous studies. The offline before-after SRTT MEP amplitudes showed an increase after anodal and a tendency to decrease after cathodal stimulation, but these changes were not significant. The combination of different interventions during tDCS might result in reduced efficacy of the stimulation that in future studies need further attention. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  20. Real-time monitoring of cisplatin-induced cell death.

    Directory of Open Access Journals (Sweden)

    Hamed Alborzinia

    Full Text Available Since the discovery of cisplatin more than 40 years ago and its clinical introduction in the 1970s an enormous amount of research has gone into elucidating the mechanism of action of cisplatin on tumor cells. With a novel cell biosensor chip system allowing continuous monitoring of respiration, glycolysis, and impedance we followed cisplatin treatment of different cancer cell lines in real-time. Our measurements reveal a first effect on respiration, in all cisplatin treated cell lines, followed with a significant delay by interference with glycolysis in HT-29, HCT-116, HepG2, and MCF-7 cells but not in the cisplatin-resistant cell line MDA-MB-231. Most strikingly, cell death started in all cisplatin-sensitive cell lines within 8 to 11 h of treatment, indicating a clear time frame from exposure, first response to cisplatin lesions, to cell fate decision. The time points of most significant changes were selected for more detailed analysis of cisplatin response in the breast cancer cell line MCF-7. Phosphorylation of selected signal transduction mediators connected with cellular proliferation, as well as changes in gene expression, were analyzed in samples obtained directly from sensor chips at the time points when changes in glycolysis and impedance occurred. Our online cell biosensor measurements reveal for the first time the time scale of metabolic response until onset of cell death under cisplatin treatment, which is in good agreement with models of p53-mediated cell fate decision.

  1. A real-time monitoring system for night glare protection

    Science.gov (United States)

    Ma, Jun; Ni, Xuxiang

    2010-11-01

    When capturing a dark scene with a high bright object, the monitoring camera will be saturated in some regions and the details will be lost in and near these saturated regions because of the glare vision. This work aims at developing a real-time night monitoring system. The system can decrease the influence of the glare vision and gain more details from the ordinary camera when exposing a high-contrast scene like a car with its headlight on during night. The system is made up of spatial light modulator (The liquid crystal on silicon: LCoS), image sensor (CCD), imaging lens and DSP. LCoS, a reflective liquid crystal, can modular the intensity of reflective light at every pixel as a digital device. Through modulation function of LCoS, CCD is exposed with sub-region. With the control of DSP, the light intensity is decreased to minimum in the glare regions, and the light intensity is negative feedback modulated based on PID theory in other regions. So that more details of the object will be imaging on CCD and the glare protection of monitoring system is achieved. In experiments, the feedback is controlled by the embedded system based on TI DM642. Experiments shows: this feedback modulation method not only reduces the glare vision to improve image quality, but also enhances the dynamic range of image. The high-quality and high dynamic range image is real-time captured at 30hz. The modulation depth of LCoS determines how strong the glare can be removed.

  2. Active learning reduces annotation time for clinical concept extraction.

    Science.gov (United States)

    Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

    2017-10-01

    To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Monitoring external beam radiotherapy using real-time beam visualization

    Energy Technology Data Exchange (ETDEWEB)

    Jenkins, Cesare H. [Department of Mechanical Engineering and Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Naczynski, Dominik J.; Yu, Shu-Jung S.; Xing, Lei, E-mail: lei@stanford.edu [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305 (United States)

    2015-01-15

    Purpose: To characterize the performance of a novel radiation therapy monitoring technique that utilizes a flexible scintillating film, common optical detectors, and image processing algorithms for real-time beam visualization (RT-BV). Methods: Scintillating films were formed by mixing Gd{sub 2}O{sub 2}S:Tb (GOS) with silicone and casting the mixture at room temperature. The films were placed in the path of therapeutic beams generated by medical linear accelerators (LINAC). The emitted light was subsequently captured using a CMOS digital camera. Image processing algorithms were used to extract the intensity, shape, and location of the radiation field at various beam energies, dose rates, and collimator locations. The measurement results were compared with known collimator settings to validate the performance of the imaging system. Results: The RT-BV system achieved a sufficient contrast-to-noise ratio to enable real-time monitoring of the LINAC beam at 20 fps with normal ambient lighting in the LINAC room. The RT-BV system successfully identified collimator movements with sub-millimeter resolution. Conclusions: The RT-BV system is capable of localizing radiation therapy beams with sub-millimeter precision and tracking beam movement at video-rate exposure.

  4. Satellite image time series simulation for environmental monitoring

    Science.gov (United States)

    Guo, Tao

    2014-11-01

    The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

  5. Real Time Monitoring and Wear Out of Power Modules

    DEFF Research Database (Denmark)

    Ghimire, Pramod

    the expected lifetime of converters. Real time monitoring of power modules is very important together with a smart control and a driving technique in a converter. This ensures to operate the device within a safe operating area and also to protect from a catastrophic failure. Furthermore, the inherent physical...... and in a mission-profile oriented advanced power cycling test. The measurement technique is implemented in a full scale converter under field oriented test conditions. Initially, a real time measurement technique and it's implementation in a converter are introduced. A full scale converter is also used......Power electronic devices have a wide range of applications from very low to high power at constantly varying load conditions. Irrespective of the harsh operating loads, including both internal and external, an improvement in a performance such as efficiency, power density, reliability and cost...

  6. Time-Frequency Methods for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Alexander L. Pyayt

    2014-03-01

    Full Text Available Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM of flood protection systems (levees, earthen dikes and concrete dams using sensor data. We present a robust data-driven anomaly detection method that combines time-frequency feature extraction, using wavelet analysis and phase shift, with one-sided classification techniques to identify the onset of failure anomalies in real-time sensor measurements. The methodology has been successfully tested at three operational levees. We detected a dam leakage in the retaining dam (Germany and “strange” behaviour of sensors installed in a Boston levee (UK and a Rhine levee (Germany.

  7. Novel use of a noninvasive hemodynamic monitor in a personalized, active learning simulation.

    Science.gov (United States)

    Zoller, Jonathan K; He, Jianghua; Ballew, Angela T; Orr, Walter N; Flynn, Brigid C

    2017-06-01

    The present study furthered the concept of simulation-based medical education by applying a personalized active learning component. We tested this novel approach utilizing a noninvasive hemodynamic monitor with the capability to measure and display in real time numerous hemodynamic parameters in the exercising participant. Changes in medical knowledge concerning physiology were examined with a pre-and posttest. Simply by observation of one's own hemodynamic variables, the understanding of complex physiological concepts was significantly enhanced. Copyright © 2017 the American Physiological Society.

  8. Time Analyzer for Time Synchronization and Monitor of the Deep Space Network

    Science.gov (United States)

    Cole, Steven; Gonzalez, Jorge, Jr.; Calhoun, Malcolm; Tjoelker, Robert

    2003-01-01

    A software package has been developed to measure, monitor, and archive the performance of timing signals distributed in the NASA Deep Space Network. Timing signals are generated from a central master clock and distributed to over 100 users at distances up to 30 kilometers. The time offset due to internal distribution delays and time jitter with respect to the central master clock are critical for successful spacecraft navigation, radio science, and very long baseline interferometry (VLBI) applications. The instrument controller and operator interface software is written in LabView and runs on the Linux operating system. The software controls a commercial multiplexer to switch 120 separate timing signals to measure offset and jitter with a time-interval counter referenced to the master clock. The offset of each channel is displayed in histogram form, and "out of specification" alarms are sent to a central complex monitor and control system. At any time, the measurement cycle of 120 signals can be interrupted for diagnostic tests on an individual channel. The instrument also routinely monitors and archives the long-term stability of all frequency standards or any other 1-pps source compared against the master clock. All data is stored and made available for

  9. Time to rethink the neural mechanisms of learning and memory.

    Science.gov (United States)

    Gallistel, Charles R; Balsam, Peter D

    2014-02-01

    Most studies in the neurobiology of learning assume that the underlying learning process is a pairing - dependent change in synaptic strength that requires repeated experience of events presented in close temporal contiguity. However, much learning is rapid and does not depend on temporal contiguity, which has never been precisely defined. These points are well illustrated by studies showing that the temporal relations between events are rapidly learned- even over long delays- and that this knowledge governs the form and timing of behavior. The speed with which anticipatory responses emerge in conditioning paradigms is determined by the information that cues provide about the timing of rewards. The challenge for understanding the neurobiology of learning is to understand the mechanisms in the nervous system that encode information from even a single experience, the nature of the memory mechanisms that can encode quantities such as time, and how the brain can flexibly perform computations based on this information. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Semireal Time Monitoring Of The Functional Movements Of The Mandible

    Science.gov (United States)

    Isaacson, Robert J.; Baumrind, Sheldon; Curry, Sean; Molthen, Robert A.

    1983-07-01

    Many branches of dental practice would benefit from the availability of a relatively accurate, precise, and efficient method for monitoring the movements of the human mandible during function. Mechanical analog systems have been utilized in the past but these are difficult to quantify, have limited accuracy due to frictional resistance of the components, and contain information only on the borders of the envelopes of possible movement of the landmarks measured (rather than on the functional paths of the landmarks which lie within their envelopes). Those electronic solutions which have been attempted thus far have been prohibitively expensive and time consuming for clinical use, have had lag times between data acquisition and display, or have involved such restrictions of freedom of motion as to render ambiguous the meaning of the data obtained. We report work aimed at developing a relatively non-restrictive semi-real time acoustical system for monitoring the functional movement of the mandible relative to the rest of the head. A set of three sparking devices is mounted to the mandibular component of a light, relatively non-constraining extra-oral harness and another set of three sparkers is attached to the harness' cranial or skull component. The sparkers are fired sequentially by a multiplexer and the sound associated with each firing is recorded by an array of three or more microphones. Computations based on the known speed of sound are used to evaluate the distances between the sparkers and the microphones. These data can then be transformed by computer to provide numeric or graphic information on the movement of selected mandibular landmarks with respect to the skull. Total elapsed time between the firing of the sparkers and the display of graphic information need not exceed 30-60 seconds using even a relatively modest modern computer.

  11. Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

    Science.gov (United States)

    McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

    2008-01-01

    The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

  12. Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series

    Directory of Open Access Journals (Sweden)

    Valerie J. Pasquarella

    2017-07-01

    Full Text Available Introduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a significant challenge due to the ephemeral nature of defoliation events. Using the 2016 gypsy moth (Lymantria dispar outbreak in Southern New England as a case study, we present a new approach for near-real-time defoliation monitoring using synthetic images produced from Landsat time series. By comparing predicted and observed images, we assessed changes in vegetation condition multiple times over the course of an outbreak. Initial measures can be made as imagery becomes available, and season-integrated products provide a wall-to-wall assessment of potential defoliation at 30 m resolution. Qualitative and quantitative comparisons suggest our Landsat Time Series (LTS products improve identification of defoliation events relative to existing products and provide a repeatable metric of change in condition. Our synthetic-image approach is an important step toward using the full temporal potential of the Landsat archive for operational monitoring of forest health over large extents, and provides an important new tool for understanding spatial and temporal dynamics of insect defoliators.

  13. Professional Learning in Part-time University Study

    DEFF Research Database (Denmark)

    Rasmussen, Palle

    2007-01-01

    The theme of this article is adult students' learning in part-time studies at university level in Denmark. One issue discussed is the interplay of research and teaching in this kind of study programme. Examples are presented from the Master of Learning Processes study programme at Aalborg...

  14. Radiologists' preferences for just-in-time learning.

    Science.gov (United States)

    Kahn, Charles E; Ehlers, Kevin C; Wood, Beverly P

    2006-09-01

    Effective learning can occur at the point of care, when opportunities arise to acquire information and apply it to a clinical problem. To assess interest in point-of-care learning, we conducted a survey to explore radiologists' attitudes and preferences regarding the use of just-in-time learning (JITL) in radiology. Following Institutional Review Board approval, we invited 104 current radiology residents and 86 radiologists in practice to participate in a 12-item Internet-based survey to assess their attitudes toward just-in-time learning. Voluntary participation in the survey was solicited by e-mail; respondents completed the survey on a web-based form. Seventy-nine physicians completed the questionnaire, including 47 radiology residents and 32 radiologists in practice; the overall response rate was 42%. Respondents generally expressed a strong interest for JITL: 96% indicated a willingness to try such a system, and 38% indicated that they definitely would use a JITL system. They expressed a preference for learning interventions of 5-10 min in length. Current and recent radiology trainees have expressed a strong interest in just-in-time learning. The information from this survey should be useful in pursuing the design of learning interventions and systems for delivering just-in-time learning to radiologists.

  15. Real-time Environmental Monitoring Data on the internet

    International Nuclear Information System (INIS)

    Nakashima, N.I.; Maruo, Y.; Tobita, K.; Takeyasu, M.

    2000-01-01

    Japan Nuclear Cycle Development Institute (JNC) places great emphasis on safety, information disclosure and communication with the local community. The Real-time Environmental Monitoring Data (REMD) was made to provide to the public on the JNC web-site (http://www.jnc.go.jp/). It is the first organization having nuclear facilities in Japan to open REMD on the Internet web-site. JNC Tokai Works included Tokai Reprocessing Plant (TRP) started to open REMD in Oct. 1998. O-arai Engineering Center (OEC) included the Experimental Fast Reactor JOYO opened in April 1999. OEC produced this web-site in both Japanese and English (http://www.jnc.go.jp/zooarai/Oantai_e/html/index.html). REMD means airborne gamma radiation dose rate, and Meteorological Observation Data. Tokai Works has 13 Monitoring Posts/Stations and OEC has 8 Monitoring Posts to measure airborne gamma radiation dose. The data from these Monitoring Posts/Stations are shown on the web-site. The Meteorological Observation Data in this web-site are wind direction, wind speed, temperature, humidity, precipitation, and atmospheric stability. Atmospheric stability provides information on the state of the atmosphere concerned with air diffusion. REMD web-site provides all these data mentioned above as current data, data tables, trend graphs, and additional information. They are updated every hour. The current data are shown with a graphical map around the JNC site. Data tables are shown within 7 days. Daily highest and lowest temperature and precipitation are also shown as a table. There are three kinds of trend graphs of airborne radiation dose rate, the latest 24 hours trend graph, 48 hours, and 7 days. Each graph is shown with a graph of precipitation, so that variation of airborne gamma radiation with rainfall can be seen. Some explanations of this web-site are expressed as additional information. The topics of them are airborne Radiation, Meteorology, Radioactivity and Radiation, and Rainfall and Radiation. A set

  16. Smartphone-Based Patients' Activity Recognition by Using a Self-Learning Scheme for Medical Monitoring.

    Science.gov (United States)

    Guo, Junqi; Zhou, Xi; Sun, Yunchuan; Ping, Gong; Zhao, Guoxing; Li, Zhuorong

    2016-06-01

    Smartphone based activity recognition has recently received remarkable attention in various applications of mobile health such as safety monitoring, fitness tracking, and disease prediction. To achieve more accurate and simplified medical monitoring, this paper proposes a self-learning scheme for patients' activity recognition, in which a patient only needs to carry an ordinary smartphone that contains common motion sensors. After the real-time data collection though this smartphone, we preprocess the data using coordinate system transformation to eliminate phone orientation influence. A set of robust and effective features are then extracted from the preprocessed data. Because a patient may inevitably perform various unpredictable activities that have no apriori knowledge in the training dataset, we propose a self-learning activity recognition scheme. The scheme determines whether there are apriori training samples and labeled categories in training pools that well match with unpredictable activity data. If not, it automatically assembles these unpredictable samples into different clusters and gives them new category labels. These clustered samples combined with the acquired new category labels are then merged into the training dataset to reinforce recognition ability of the self-learning model. In experiments, we evaluate our scheme using the data collected from two postoperative patient volunteers, including six labeled daily activities as the initial apriori categories in the training pool. Experimental results demonstrate that the proposed self-learning scheme for activity recognition works very well for most cases. When there exist several types of unseen activities without any apriori information, the accuracy reaches above 80 % after the self-learning process converges.

  17. Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

    Science.gov (United States)

    Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

    2013-07-01

    Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

  18. Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

    International Nuclear Information System (INIS)

    Gueth, P; Freud, N; Létang, J M; Sarrut, D; Dauvergne, D; Ray, C; Testa, E

    2013-01-01

    Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations. (paper)

  19. Learned Compact Local Feature Descriptor for Tls-Based Geodetic Monitoring of Natural Outdoor Scenes

    Science.gov (United States)

    Gojcic, Z.; Zhou, C.; Wieser, A.

    2018-05-01

    The advantages of terrestrial laser scanning (TLS) for geodetic monitoring of man-made and natural objects are not yet fully exploited. Herein we address one of the open challenges by proposing feature-based methods for identification of corresponding points in point clouds of two or more epochs. We propose a learned compact feature descriptor tailored for point clouds of natural outdoor scenes obtained using TLS. We evaluate our method both on a benchmark data set and on a specially acquired outdoor dataset resembling a simplified monitoring scenario where we successfully estimate 3D displacement vectors of a rock that has been displaced between the scans. We show that the proposed descriptor has the capacity to generalize to unseen data and achieves state-of-the-art performance while being time efficient at the matching step due the low dimension.

  20. Monitoring Forest Regrowth Using a Multi-Platform Time Series

    Science.gov (United States)

    Sabol, Donald E., Jr.; Smith, Milton O.; Adams, John B.; Gillespie, Alan R.; Tucker, Compton J.

    1996-01-01

    Over the past 50 years, the forests of western Washington and Oregon have been extensively harvested for timber. This has resulted in a heterogeneous mosaic of remaining mature forests, clear-cuts, new plantations, and second-growth stands that now occur in areas that formerly were dominated by extensive old-growth forests and younger forests resulting from fire disturbance. Traditionally, determination of seral stage and stand condition have been made using aerial photography and spot field observations, a methodology that is not only time- and resource-intensive, but falls short of providing current information on a regional scale. These limitations may be solved, in part, through the use of multispectral images which can cover large areas at spatial resolutions in the order of tens of meters. The use of multiple images comprising a time series potentially can be used to monitor land use (e.g. cutting and replanting), and to observe natural processes such as regeneration, maturation and phenologic change. These processes are more likely to be spectrally observed in a time series composed of images taken during different seasons over a long period of time. Therefore, for many areas, it may be necessary to use a variety of images taken with different imaging systems. A common framework for interpretation is needed that reduces topographic, atmospheric, instrumental, effects as well as differences in lighting geometry between images. The present state of remote-sensing technology in general use does not realize the full potential of the multispectral data in areas of high topographic relief. For example, the primary method for analyzing images of forested landscapes in the Northwest has been with statistical classifiers (e.g. parallelepiped, nearest-neighbor, maximum likelihood, etc.), often applied to uncalibrated multispectral data. Although this approach has produced useful information from individual images in some areas, landcover classes defined by these

  1. Multi-Isotope Process (MIP) Monitor: A Near-Real-Time Monitor For Reprocessing Facilities

    International Nuclear Information System (INIS)

    Schwantes, Jon M.; Douglas, Matthew; Orton, Christopher R.; Fraga, Carlos G.; Christensen, Richard

    2008-01-01

    The threat of protracted diversion of Pu from commercial reprocessing operations is perhaps the greatest concern to national and international agencies tasked with safeguarding these facilities. While it is generally understood that a method for direct monitoring of process on-line and in near-real time (NRT) would be the best defense against protracted diversion scenarios, an effective method with these qualities has yet to be developed. Here, we attempt to bridge this gap by proposing an on-line NRT process monitoring method that should be sensitive to minor alterations in process conditions and compatible with small, easily deployable, detection systems. This Approach is known as the Multi-Isotope Process (MIP) Monitor and involves the determination and recognition of the contaminant pattern within a process stream for a suite of indicator (radioactive) elements present in the spent fuel as a function of process variables. Utilization of a suite of radio-elements, including ones with multiple oxidation states, decreases the likelihood that attempts to divert Pu by altering the ReDox environment within the process would go undetected. In addition, by identifying gamma-emitting indicator isotopes, this Approach might eliminate the need for bulky neutron detection systems, relying instead on small, portable, high-resolution gamma detectors easily deployable throughout the facility

  2. Learning neuroendoscopy with an exoscope system (video telescopic operating monitor): Early clinical results.

    Science.gov (United States)

    Parihar, Vijay; Yadav, Y R; Kher, Yatin; Ratre, Shailendra; Sethi, Ashish; Sharma, Dhananjaya

    2016-01-01

    Steep learning curve is found initially in pure endoscopic procedures. Video telescopic operating monitor (VITOM) is an advance in rigid-lens telescope systems provides an alternative method for learning basics of neuroendoscopy with the help of the familiar principle of microneurosurgery. The aim was to evaluate the clinical utility of VITOM as a learning tool for neuroendoscopy. Video telescopic operating monitor was used 39 cranial and spinal procedures and its utility as a tool for minimally invasive neurosurgery and neuroendoscopy for initial learning curve was studied. Video telescopic operating monitor was used in 25 cranial and 14 spinal procedures. Image quality is comparable to endoscope and microscope. Surgeons comfort improved with VITOM. Frequent repositioning of scope holder and lack of stereopsis is initial limiting factor was compensated for with repeated procedures. Video telescopic operating monitor is found useful to reduce initial learning curve of neuroendoscopy.

  3. Landfill cover performance monitoring using time domain reflectometry

    International Nuclear Information System (INIS)

    Neher, E.R.; Cotten, G.B.; McElroy, D.

    1998-01-01

    Time domain reflectometry (TDR) systems were installed to monitor soil moisture in two newly constructed landfill covers at the Idaho National Engineering and Environmental Laboratory. Each TDR system includes four vertical arrays with each array consisting of four TDR probes located at depths of 15, 30, 45, and 60 cm. The deepest probes at 60 cm were installed beneath a compacted soil layer to analyze infiltration through the compacted layer. Based on the TDR data, infiltration through the two covers between March and October, 1997 ranged from less than measurable to 1.5 cm. However, due to a prohibition on penetrating the buried waste and resulting limits on probe placement depths, deeper percolation was not evaluated. Some of the advantages found in the application of TDR for infiltration monitoring at this site are the relative low cost and rugged nature of the equipment. Also, of particular importance, the ability to collect frequent moisture measurements allows the capture and evaluation of soil moisture changes resulting from episodic precipitation events. Disadvantages include the inability to install the probes into the waste, difficulties in interpretation of infiltration during freeze/thaw periods, and some excessive noise in the data

  4. Integrated Monitoring of Mola mola Behaviour in Space and Time.

    Science.gov (United States)

    Sousa, Lara L; López-Castejón, Francisco; Gilabert, Javier; Relvas, Paulo; Couto, Ana; Queiroz, Nuno; Caldas, Renato; Dias, Paulo Sousa; Dias, Hugo; Faria, Margarida; Ferreira, Filipe; Ferreira, António Sérgio; Fortuna, João; Gomes, Ricardo Joel; Loureiro, Bruno; Martins, Ricardo; Madureira, Luis; Neiva, Jorge; Oliveira, Marina; Pereira, João; Pinto, José; Py, Frederic; Queirós, Hugo; Silva, Daniel; Sujit, P B; Zolich, Artur; Johansen, Tor Arne; de Sousa, João Borges; Rajan, Kanna

    2016-01-01

    Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, pstructure provide a rationale for a predator's fine-scale behaviour observed over a two weeks in May 2014.

  5. Integrated Monitoring of Mola mola Behaviour in Space and Time

    Science.gov (United States)

    Sousa, Lara L.; López-Castejón, Francisco; Gilabert, Javier; Relvas, Paulo; Couto, Ana; Queiroz, Nuno; Caldas, Renato; Dias, Paulo Sousa; Dias, Hugo; Faria, Margarida; Ferreira, Filipe; Ferreira, António Sérgio; Fortuna, João; Gomes, Ricardo Joel; Loureiro, Bruno; Martins, Ricardo; Madureira, Luis; Neiva, Jorge; Oliveira, Marina; Pereira, João; Pinto, José; Py, Frederic; Queirós, Hugo; Silva, Daniel; Sujit, P. B.; Zolich, Artur; Johansen, Tor Arne; de Sousa, João Borges; Rajan, Kanna

    2016-01-01

    Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, pbehaviour observed over a two weeks in May 2014. PMID:27494028

  6. A Simple Approach for Monitoring Business Service Time Variation

    Directory of Open Access Journals (Sweden)

    Su-Fen Yang

    2014-01-01

    Full Text Available Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA variance chart (EWMA-AV chart and an asymmetric EWMA mean chart (EWMA-AM chart based on two simple statistics to monitor process variance and mean shifts simultaneously. Further, we explore the sampling properties of the new monitoring statistics and calculate the average run lengths when using both the EWMA-AV chart and the EWMA-AM chart. The performance of the EWMA-AV and EWMA-AM charts and that of some existing variance and mean charts are compared. A numerical example involving nonnormal service times from the service system of a bank branch in Taiwan is used to illustrate the applications of the EWMA-AV and EWMA-AM charts and to compare them with the existing variance (or standard deviation and mean charts. The proposed EWMA-AV chart and EWMA-AM charts show superior detection performance compared to the existing variance and mean charts. The EWMA-AV chart and EWMA-AM chart are thus recommended.

  7. A simple approach for monitoring business service time variation.

    Science.gov (United States)

    Yang, Su-Fen; Arnold, Barry C

    2014-01-01

    Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA variance chart (EWMA-AV chart) and an asymmetric EWMA mean chart (EWMA-AM chart) based on two simple statistics to monitor process variance and mean shifts simultaneously. Further, we explore the sampling properties of the new monitoring statistics and calculate the average run lengths when using both the EWMA-AV chart and the EWMA-AM chart. The performance of the EWMA-AV and EWMA-AM charts and that of some existing variance and mean charts are compared. A numerical example involving nonnormal service times from the service system of a bank branch in Taiwan is used to illustrate the applications of the EWMA-AV and EWMA-AM charts and to compare them with the existing variance (or standard deviation) and mean charts. The proposed EWMA-AV chart and EWMA-AM charts show superior detection performance compared to the existing variance and mean charts. The EWMA-AV chart and EWMA-AM chart are thus recommended.

  8. Real-time personal dose monitoring and management system

    International Nuclear Information System (INIS)

    Zhang Zhiyong; Cheng Chang; Yang Huating; Liu Zhengshan; Deng Changming; Li Mei

    2000-01-01

    This paper mainly describes a real-time personal dose monitoring and management system. The system is composed of three parts that include SDM-98 semiconductor detector personal dosimeters, Data Readers and a Management System Software. It can be used for personal dose monitoring and management and other controlling actions in a radioactive controlled area. Adopting semiconductor detector and microcontroller, SDM-98 Personal Dosimeter is used to measure personal accumulated dose equivalent and dose rate caused by X-ray and Gamma ray. The results can be read directly on LCD. All the data stored in dosimeter can be transmitted into a data reader by infrared optical link. The alarm threshold can be adjusted successively in whole range of dose or dose rate. The Data Reader is an intelligent interface between the dosimeter and master computer. The data received from dosimeter will be sent to a master computer through RS-232 serial interface. According to the master computer's order, the Data Reader can turn on the dosimeter's power at entrance and shutdown it at exit. The Management System Software which written by Visual BASIC 5.0 runs on MS Win95. All the measuring data from dosimeters can be analyzed and treated according to requirements and stored in database. Therefore, some figures and tables relative to dose or rate can be shown on screen or printed out. (author)

  9. Increasing instruction time in school does increase learning

    DEFF Research Database (Denmark)

    Andersen, Simon Calmar; Humlum, Maria; Nandrup, Anne Brink

    2016-01-01

    Increasing instruction time in school is a central element in the attempts of many governments to improve student learning, but prior research—mainly based on observational data—disputes the effect of this approach and points out the potential negative effects on student behavior. Based on a large......-scale, cluster-randomized trial, we find that increasing instruction time increases student learning and that a general increase in instruction time is at least as efficient as an expert-developed, detailed teaching program that increases instruction with the same amount of time. These findings support the value...... of increased instruction time....

  10. NASDA technician test real-time radiation monitoring device

    Science.gov (United States)

    1997-01-01

    A technician from the National Space Development Agency of Japan (NASDA) tests the real-time radiation monitoring device on SPACEHAB at Kennedy Space Center in preparation for the STS-89 mission, slated to be the first Shuttle launch of 1998. STS-89 will be the eighth of nine scheduled Mir dockings and will include a double module of SPACEHAB, used mainly as a large pressurized cargo container for science, logistical equipment and supplies to be exchanged between the orbiter Endeavour and the Russian Space Station Mir. The nine-day flight of STS-89 also is scheduled to include the transfer of the seventh American to live and work aboard the Russian orbiting outpost. Liftoff of Endeavour and its seven-member crew is targeted for Jan. 15, 1998, at 1:03 a.m. EDT from Launch Pad 39A.

  11. Smart sensors for real-time water quality monitoring

    CERN Document Server

    Mason, Alex

    2013-01-01

    Sensors are being utilised to increasing degrees in all forms of industry.  Researchers and industrial practitioners in all fields seek to obtain a better understanding of appropriate processes so as to improve quality of service and efficiency.  The quality of water is no exception, and the water industry is faced with a wide array of water quality issues being present world-wide.  Thus, the need for sensors to tackle this diverse subject is paramount.  The aim of this book is to combine, for the first time, international expertise in the area of water quality monitoring using smart sensors and systems in order that a better understanding of the challenges faced and solutions posed may be available to all in a single text.

  12. Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

    Science.gov (United States)

    Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina

    2015-01-01

    Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.

  13. Real-time monitoring of drowsiness through wireless nanosensor systems

    Science.gov (United States)

    Ramasamy, Mouli; Varadan, Vijay K.

    2016-04-01

    Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Generally, the bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper reviews the design aspects of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the textile based nanosensors mounted on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through ZigBee communication. This system is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the fatigue level. This approach of using a wireless, real time, dry sensor on a flexible substrate mitigates obtrusiveness that is expected from a wearable system. We have previously presented the results of the aforementioned wearable systems. This paper aims to extend our work conceptually through a review of engineering and medical techniques involved in wearable systems to detect drowsiness.

  14. Online Quiz Time Limits and Learning Outcomes in Economics

    Science.gov (United States)

    Evans, Brent; Culp, Robert

    2015-01-01

    In an effort to better understand the impact of timing limits, the authors compare the learning outcomes of students who completed timed quizzes with students who took untimed quizzes in economics principles courses. Students were assigned two online quizzes--one timed and one untimed--and re-tested on the material the following class day. Our…

  15. Time for Learning: An Exploratory Analysis of NAEP Data

    Science.gov (United States)

    Ginsburg, Alan; Chudowsky, Naomi

    2012-01-01

    This report uses NAEP background data to track time and learning since the mid-1990s in three areas: student absenteeism; classroom instructional time in mathematics, reading, music and the visual arts; and homework time expected by teachers. Key report findings are: (1) Students with higher rates of "monthly absenteeism" score…

  16. A Model for Learning Over Time: The Big Picture

    Science.gov (United States)

    Amato, Herbert K.; Konin, Jeff G.; Brader, Holly

    2002-01-01

    Objective: To present a method of describing the concept of “learning over time” with respect to its implementation into an athletic training education program curriculum. Background: The formal process of learning over time has recently been introduced as a required way for athletic training educational competencies and clinical proficiencies to be delivered and mastered. Learning over time incorporates the documented cognitive, psychomotor, and affective skills associated with the acquisition, progression, and reflection of information. This method of academic preparation represents a move away from a quantitative-based learning module toward a proficiency-based mastery of learning. Little research or documentation can be found demonstrating either the specificity of this concept or suggestions for its application. Description: We present a model for learning over time that encompasses multiple indicators for assessment in a successive format. Based on a continuum approach, cognitive, psychomotor, and affective characteristics are assessed at different levels in classroom and clinical environments. Clinical proficiencies are a common set of entry-level skills that need to be integrated into the athletic training educational domains. Objective documentation is presented, including the skill breakdown of a task and a matrix to identify a timeline of competency and proficiency delivery. Clinical Advantages: The advantages of learning over time pertain to the integration of cognitive knowledge into clinical skill acquisition. Given the fact that learning over time has been implemented as a required concept for athletic training education programs, this model may serve to assist those program faculty who have not yet developed, or are in the process of developing, a method of administering this approach to learning. PMID:12937551

  17. Timing of quizzes during learning: Effects on motivation and retention.

    Science.gov (United States)

    Healy, Alice F; Jones, Matt; Lalchandani, Lakshmi A; Tack, Lindsay Anderson

    2017-06-01

    This article investigates how the timing of quizzes given during learning impacts retention of studied material. We investigated the hypothesis that interspersing quizzes among study blocks increases student engagement, thus improving learning. Participants learned 8 artificial facts about each of 8 plant categories, with the categories blocked during learning. Quizzes about 4 of the 8 facts from each category occurred either immediately after studying the facts for that category (standard) or after studying the facts from all 8 categories (postponed). In Experiment 1, participants were given tests shortly after learning and several days later, including both the initially quizzed and unquizzed facts. Test performance was better in the standard than in the postponed condition, especially for categories learned later in the sequence. This result held even for the facts not quizzed during learning, suggesting that the advantage cannot be due to any direct testing effects. Instead the results support the hypothesis that interrupting learning with quiz questions is beneficial because it can enhance learner engagement. Experiment 2 provided further support for this hypothesis, based on participants' retrospective ratings of their task engagement during the learning phase. These findings have practical implications for when to introduce quizzes in the classroom. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  18. Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)

    2006-11-01

    survivability issues. Our findings indicate that packaging represents the most significant technical challenge associated with application of sensors in the downhole environment for long periods (5+ years) of time. These issues are described in detail within the report. The impact of successful reservoir monitoring programs and coincident improved reservoir management is measured by the production of additional oil and gas volumes from existing reservoirs, revitalization of nearly depleted reservoirs, possible re-establishment of already abandoned reservoirs, and improved economics for all cases. Smart Well monitoring provides the means to understand how a reservoir process is developing and to provide active reservoir management. At the same time it also provides data for developing high-fidelity simulation models. This work has been a joint effort with Sandia National Laboratories and UT-Austin's Bureau of Economic Geology, Department of Petroleum and Geosystems Engineering, and the Institute of Computational and Engineering Mathematics.

  19. Human learning: Power laws or multiple characteristic time scales?

    Directory of Open Access Journals (Sweden)

    Gottfried Mayer-Kress

    2006-09-01

    Full Text Available The central proposal of A. Newell and Rosenbloom (1981 was that the power law is the ubiquitous law of learning. This proposition is discussed in the context of the key factors that led to the acceptance of the power law as the function of learning. We then outline the principles of an epigenetic landscape framework for considering the role of the characteristic time scales of learning and an approach to system identification of the processes of performance dynamics. In this view, the change of performance over time is the product of a superposition of characteristic exponential time scales that reflect the influence of different processes. This theoretical approach can reproduce the traditional power law of practice – within the experimental resolution of performance data sets - but we hypothesize that this function may prove to be a special and perhaps idealized case of learning.

  20. Real-Time Spatial Monitoring of Vehicle Vibration Data as a Model for TeleGeoMonitoring Systems

    OpenAIRE

    Robidoux, Jeff

    2005-01-01

    This research presents the development and proof of concept of a TeleGeoMonitoring (TGM) system for spatially monitoring and analyzing, in real-time, data derived from vehicle-mounted sensors. In response to the concern for vibration related injuries experienced by equipment operators in surface mining and construction operations, the prototype TGM system focuses on spatially monitoring vehicle vibration in real-time. The TGM vibration system consists of 3 components: (1) Data Acquisition ...

  1. Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

    Science.gov (United States)

    Ammenwerth, Elske; Hackl, Werner O

    2017-01-01

    Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

  2. Evaluating Stream Restoration Projects: What Do We Learn from Monitoring?

    Directory of Open Access Journals (Sweden)

    Zan Rubin

    2017-02-01

    Full Text Available Two decades since calls for stream restoration projects to be scientifically assessed, most projects are still unevaluated, and conducted evaluations yield ambiguous results. Even after these decades of investigation, do we know how to define and measure success? We systematically reviewed 26 studies of stream restoration projects that used macroinvertebrate indicators to assess the success of habitat heterogeneity restoration projects. All 26 studies were previously included in two meta-analyses that sought to assess whether restoration programs were succeeding. By contrast, our review focuses on the evaluations themselves, and asks what exactly we are measuring and learning from these evaluations. All 26 studies used taxonomic diversity, richness, or abundance of invertebrates as biological measures of success, but none presented explicit arguments why those metrics were relevant measures of success for the restoration projects. Although changes in biodiversity may reflect overall ecological condition at the regional or global scale, in the context of reach-scale habitat restoration, more abundance and diversity may not necessarily be better. While all 26 studies sought to evaluate the biotic response to habitat heterogeneity enhancement projects, about half of the studies (46% explicitly measured habitat alteration, and 31% used visual estimates of grain size or subjectively judged ‘habitat quality’ from protocols ill-suited for the purpose. Although the goal of all 26 projects was to increase habitat heterogeneity, 31% of the studies either sampled only riffles or did not specify the habitats sampled. One-third of the studies (35% used reference ecosystems to define target conditions. After 20 years of stream restoration evaluation, more work remains for the restoration community to identify appropriate measures of success and to coordinate monitoring so that evaluations are at a scale capable of detecting ecosystem change.

  3. Monitoring risk-adjusted medical outcomes allowing for changes over time.

    Science.gov (United States)

    Steiner, Stefan H; Mackay, R Jock

    2014-10-01

    We consider the problem of monitoring and comparing medical outcomes, such as surgical performance, over time. Performance is subject to change due to a variety of reasons including patient heterogeneity, learning, deteriorating skills due to aging, etc. For instance, we expect inexperienced surgeons to improve their skills with practice. We propose a graphical method to monitor surgical performance that incorporates risk adjustment to account for patient heterogeneity. The procedure gives more weight to recent outcomes and down-weights the influence of outcomes further in the past. The chart is clinically interpretable as it plots an estimate of the failure rate for a "standard" patient. The chart also includes a measure of uncertainty in this estimate. We can implement the method using historical data or start from scratch. As the monitoring proceeds, we can base the estimated failure rate on a known risk model or use the observed outcomes to update the risk model as time passes. We illustrate the proposed method with an example from cardiac surgery. © The Author 2013. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  4. Time representation in reinforcement learning models of the basal ganglia

    Directory of Open Access Journals (Sweden)

    Samuel Joseph Gershman

    2014-01-01

    Full Text Available Reinforcement learning models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between reinforcement learning models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both reinforcement learning and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired.

  5. Multisensor Instrument for Real-Time Biological Monitoring

    Science.gov (United States)

    Zhang, Sean (Zhanxiang); Xu, Guoda; Qiu, Wei; Lin, Freddie

    2004-01-01

    The figure schematically depicts an instrumentation system, called a fiber optic-based integration system (FOBIS), that is undergoing development to enable real-time monitoring of fluid cell cultures, bioprocess flows, and the like. The FOBIS design combines a micro flow cytometer (MFC), a microphotometer (MP), and a fluorescence-spectrum- or binding-force-measuring micro-sensor (MS) in a single instrument that is capable of measuring multiple biological parameters simultaneously or sequentially. The fiber-optic-based integration system is so named because the MFC, the MP, and the MS are integrated into a single optical system that is coupled to light sources and photometric equipment via optical fibers. The optical coupling components also include a wavelength-division multiplexer and diffractive optical elements. The FOBIS includes a laserdiode- and fiber-optic-based optical trapping subsystem (optical tweezers ) with microphotometric and micro-sensing capabilities for noninvasive confinement and optical measurement of relevant parameters of a single cell or other particle. Some of the measurement techniques implemented together by the FOBIS have long been used separately to obtain basic understanding of the optical properties of individual cells and other organisms, the optical properties of populations of organisms, and the interrelationships among these properties, physiology of the organisms, and physical processes that govern the media that surround the organisms. For example, flow cytometry yields information on numerical concentrations, cross-sectional areas, and types of cells or other particles. Micro-sensing can be used to measure pH and concentrations of oxygen, carbon dioxide, glucose, metabolites, calcium, and antigens in a cell-culture fluid, thereby providing feedback that can be helpful in improving control over a bioprocess. Microphotometry (including measurements of scattering and fluorescence) can yield further information about optically

  6. Experiments with Online Reinforcement Learning in Real-Time Strategy Games

    DEFF Research Database (Denmark)

    Toftgaard Andersen, Kresten; Zeng, Yifeng; Dahl Christensen, Dennis

    2009-01-01

    Real-time strategy (RTS) games provide a challenging platform to implement online reinforcement learning (RL) techniques in a real application. Computer, as one game player, monitors opponents' (human or other computers) strategies and then updates its own policy using RL methods. In this article......, we first examine the suitability of applying the online RL in various computer games. Reinforcement learning application depends on both RL complexity and the game features. We then propose a multi-layer framework for implementing online RL in an RTS game. The framework significantly reduces RL...... the effectiveness of our proposed framework and shed light on relevant issues in using online RL in RTS games....

  7. Real-time monitoring of Hanford nuclear waste

    International Nuclear Information System (INIS)

    McNeece, S.G.; Glasscock, J.A.; Rosnick, C.K.

    1979-10-01

    Two minicomputers are used to perform real time monitoring of radioactive waste storage tanks on the Hanford Nuclear Reservation. The Computer Automated Surveillance System, CASS, consists of a network of six field microprocessors, a central microprocessor and two central Eclipse minicomputers. The field microprocessors are each responsible for monitoring alarm sensors, liquid levels and temperatures. The field microprocessors report alarm conditions immediately to the central microprocessor. The central minicomputer reports all alarm conditions to the user terminals, requests data from the field on a scheduled and requested basis, and generates reports. It handles all requests for information from the user and stores all incoming data for historical purposes. The CASS software consists of five major segments: (1) process creation, (2) report generation, (3) file updating, (4) terminal communication, and (5) microprocessor communication. Since CASS must operate 24 hours a day, 7 days a week, the system cannot be allowed to abnormally terminate. For this reason all processes are started by the creation process. Having a single process responsible for creating all other processes provides the ability to detect a failure of a subordinate process and to automatically restart the failed process. The report generation process schedules reports, requests the data to be gathered to produce the reports, forms the reports, and distributes the reports to the user terminals. The file updating process handles all data file modifications. There is a terminal communication process for each user terminal which is responsible for printing scheduled reports and for allowing the user to request information from the CASS system. The microprocessor communication process handles all communication with the central microprocessor

  8. Integrated Monitoring of Mola mola Behaviour in Space and Time.

    Directory of Open Access Journals (Sweden)

    Lara L Sousa

    Full Text Available Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS, which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001. The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator's fine-scale behaviour observed over a two weeks in May 2014.

  9. Implantable Biosensors for Real-time Strain and Pressure Monitoring

    Directory of Open Access Journals (Sweden)

    Keat Ghee Ong

    2008-10-01

    Full Text Available Implantable biosensors were developed for real-time monitoring of pressure and strain in the human body. The sensors, which are wireless and passive, consisted of a soft magnetic material and a permanent magnet. When exposed to a low frequency AC magnetic field, the soft magnetic material generated secondary magnetic fields that also included the higher-order harmonic modes. Parameters of interest were determined by measuring the changes in the pattern of these higher-order harmonic fields, which was achieved by changing the intensity of a DC magnetic field generated by a permanent magnet. The DC magnetic field, or the biasing field, was altered by changing the separation distance between the soft magnetic material and the permanent magnet. For pressure monitoring, the permanent magnet was placed on the membrane of an airtight chamber. Changes in the ambient pressure deflected the membrane, altering the separation distance between the two magnetic elements and thus the higher-order harmonic fields. Similarly, the soft magnetic material and the permanent magnet were separated by a flexible substrate in the stress/strain sensor. Compressive and tensile forces flexed the substrate, changing the separation distance between the two elements and the higher-order harmonic fields. In the current study, both stress/strain and pressure sensors were fabricated and characterized. Good stability, linearity and repeatability of the sensors were demonstrated. This passive and wireless sensor technology may be useful for long term detection of physical quantities within the human body as a part of treatment assessment, disease diagnosis, or detection of biomedical implant failures.

  10. Real time speckle monitoring to control retinal photocoagulation

    Science.gov (United States)

    Bliedtner, Katharina; Seifert, Eric; Brinkmann, Ralf

    2017-07-01

    Photocoagulation is a treatment modality for several retinal diseases. Intra- and inter-individual variations of the retinal absorption as well as ocular transmission and light scattering makes it impossible to achieve a uniform effective exposure with one set of laser parameters. To guarantee a uniform damage throughout the therapy a real-time control is highly requested. Here, an approach to realize a real-time optical feedback using dynamic speckle analysis in-vivo is presented. A 532 nm continuous wave Nd:YAG laser is used for coagulation. During coagulation, speckle dynamics are monitored by a coherent object illumination using a 633 nm diode laser and analyzed by a CMOS camera with a frame rate up to 1 kHz. An algorithm is presented that can discriminate between different categories of retinal pigment epithelial damage ex-vivo in enucleated porcine eyes and that seems to be robust to noise in-vivo. Tissue changes in rabbits during retinal coagulation could be observed for different lesion strengths. This algorithm can run on a FPGA and is able to calculate a feedback value which is correlated to the thermal and coagulation induced tissue motion and thus the achieved damage.

  11. E-learning for Part-Time Medical Studies

    Directory of Open Access Journals (Sweden)

    Półjanowicz Wiesław

    2016-12-01

    Full Text Available Distance education undoubtedly has many advantages, such as individualization of the learning process, unified transmission of teaching materials, the opportunity to study at any place and any time, reduction of financial costs for commuting to classes or accommodation of participants, etc. Adequate working conditions on the e-learning portal must also be present, eg. well-prepared, substantive courses and good communication between the participants. Therefore, an important element in the process of conducting e-learning courses is to measure the increase of knowledge and satisfaction of participants with distance learning. It allows for fine-tuning the content of the course and for classes to be properly organized. This paper presents the results of teaching and assessment of satisfaction with e-learning courses in “Problems of multiculturalism in medicine”, “Selected issues of visual rehabilitation” and “Ophthalmology and Ophthalmic Nursing”, which were carried out experimentally at the Faculty of Health Sciences at the Medical University of Bialystok for nursing students for the 2010/2011 academic year. The study group consisted of 72 part-time students who learnt in e-learning mode and the control group of 87 students who learnt in the traditional way. The students’ opinions about the teaching process and final exam scores were analyzed based on a specially prepared survey questionnaire. Organization of e-learning classes was rated positively by 90% of students. The average result on the final exams for all distance learning subjects was at the level of 82%, while for classes taught in the traditional form it was 81%. Based on these results, we conclude that distance learning is as effective as learning according to the traditional form in medical education studies.

  12. A novel time series link prediction method: Learning automata approach

    Science.gov (United States)

    Moradabadi, Behnaz; Meybodi, Mohammad Reza

    2017-09-01

    Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

  13. NEW MATERIALS FOR PEDAGOGICAL TEACHING-LEARNING IN BIOCHEMISTRY: MONITORING PARTICIPATION

    OpenAIRE

    Campos, R. S.; Fernandes, I. L.; Andrade, G. P.V.; Matta, L. D.M.; Filgueira, L. G.A.

    2015-01-01

    This summary consists of an experience report about actions taken by biochemical monitors with pharmacy students. The reason of our work was the intention to both improve the process of teaching and also learning and invalidate the labels owned by biochemistry of hard and high-level-failure subject. The three actors: teachers, students and monitor could act on an integrated basis for the construction of an articulated  pedagogical process between theory/practice and learning signification. Ou...

  14. Learning to drive: developing a workable awareness plan for monitoring new technology.

    Science.gov (United States)

    Berryman, Donna R

    2010-04-01

    Technology is constantly driving forward, and information professionals need to be informed about developments in order to work more effectively, provide new services, understand what users need and want, and to develop professionally. Learning how to monitor these developments in technology is a skill, just like learning to drive. This article provides information about developing a workable awareness plan and provides some suggested sites to monitor and tools to use.

  15. Tensorial dynamic time warping with articulation index representation for efficient audio-template learning.

    Science.gov (United States)

    Le, Long N; Jones, Douglas L

    2018-03-01

    Audio classification techniques often depend on the availability of a large labeled training dataset for successful performance. However, in many application domains of audio classification (e.g., wildlife monitoring), obtaining labeled data is still a costly and laborious process. Motivated by this observation, a technique is proposed to efficiently learn a clean template from a few labeled, but likely corrupted (by noise and interferences), data samples. This learning can be done efficiently via tensorial dynamic time warping on the articulation index-based time-frequency representations of audio data. The learned template can then be used in audio classification following the standard template-based approach. Experimental results show that the proposed approach outperforms both (1) the recurrent neural network approach and (2) the state-of-the-art in the template-based approach on a wildlife detection application with few training samples.

  16. Enhancements and Evolution of the Real Time Mission Monitor

    Science.gov (United States)

    Goodman, M.; Blakeslee, R.; Hardin, D.; Hall, J.; He, Y.; Regner, K.

    2008-12-01

    The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual earth application. RTMM has proven extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, mission scientists, instrument scientists and program managers alike appreciate the contributions that RTMM makes to their flight projects. RTMM has received numerous plaudits from a wide variety of scientists who used RTMM during recent field campaigns including the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) missions, the 2007-2008 NOAA-NASA Aerosonde Hurricane flights and the 2008 Soil Moisture Active-Passive Validation Experiment (SMAP-VEX). Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated for altitude, latitude, longitude, flight leg distance, cumulative distance, flight leg time, cumulative time, and

  17. Enrichment in Massachusetts Expanded Learning Time (ELT) Schools. Issue Brief

    Science.gov (United States)

    Caven, Meghan; Checkoway, Amy; Gamse, Beth; Luck, Rachel; Wu, Sally

    2012-01-01

    This brief highlights key information about enrichment activities, which represent one of the main components of the Massachusetts Expanded Learning Time (ELT) initiative. Over time, the ELT initiative has supported over two dozen schools across the Commonwealth. A comprehensive evaluation of the ELT initiative found that implementation of the…

  18. Learning and Teaching Problems in Part-Time Higher Education.

    Science.gov (United States)

    Trotman-Dickenson, D. I.

    1988-01-01

    Results of a British survey of the administrations of six universities and six public colleges, employers, and employees who were part-time students are reported and discussed. The survey assessed the perceptions of those groups concerning problems in the instruction and learning of part-time students. (MSE)

  19. Investigating General Chemistry Students' Metacognitive Monitoring of Their Exam Performance by Measuring Postdiction Accuracies over Time

    Science.gov (United States)

    Hawker, Morgan J.; Dysleski, Lisa; Rickey, Dawn

    2016-01-01

    Metacognitive monitoring of one's own understanding plays a key role in learning. An aspect of metacognitive monitoring can be measured by comparing a student's prediction or postdiction of performance (a judgment made before or after completing the relevant task) with the student's actual performance. In this study, we investigated students'…

  20. Monitoring Distributed Real-Time Systems: A Survey and Future Directions

    Science.gov (United States)

    Goodloe, Alwyn E.; Pike, Lee

    2010-01-01

    Runtime monitors have been proposed as a means to increase the reliability of safety-critical systems. In particular, this report addresses runtime monitors for distributed hard real-time systems. This class of systems has had little attention from the monitoring community. The need for monitors is shown by discussing examples of avionic systems failure. We survey related work in the field of runtime monitoring. Several potential monitoring architectures for distributed real-time systems are presented along with a discussion of how they might be used to monitor properties of interest.

  1. Monitoring and calibration of the ALICE time projection chamber

    CERN Document Server

    Larsen, Dag Toppe

    The aim of the A Large Ion Collider Experiment (ALICE) experiment at CERN is to study the properties of the Quark–Gluon Plasma (QGP). With energies up to 5.5 A T eV for Pb+Pb collisions, the Large Hadron Collider (LHC) sets a new benchmark for heavy- ion collisions, and opens the door to a so far unexplored energy domain. A closer look at some of the physics topics of ALICE is given in Chapter 1. ALICE consists of several sub-detectors and other sub-systems. The various sub- detectors are designed for exploring different aspects of the particle production of an heavy-ion collision. Chapter 2 gives some insight into the design. The main tracking detector is the Time Projection Chamber (TPC). It has more than half million read-out channels, divided into 216 Read-out Partitions (RPs). Each RP is a separate Front-End Electronics (FEE) entity, as described in Chapter 3. A complex Detector Control System (DCS) is needed for configuration, monitoring and control. The heart of it on the RP side is a small embedded ...

  2. Real time kernel performance monitoring with SystemTap

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    SystemTap is a dynamic method of monitoring and tracing the operation of a running Linux kernel. In this talk I will present a few practical use cases where SystemTap allowed me to turn otherwise complex userland monitoring tasks in simple kernel probes.

  3. An integrated framework for SAGD real-time monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Mohajer, M.; Perez-Damas, C.; Berbin, A.; Al-kinani, A. [Schlumberger, Calgary, AB (Canada)

    2009-07-01

    This study examined the technologies and workflows for real-time optimization (RTO) of the steam assisted gravity drainage (SAGD) process. Although SAGD operators have tried to control the reservoir's steam chamber distribution to optimize bitumen recovery and minimize steam oil ratios, a true optimization can only be accomplished by implementing RTO workflows. In order for these workflows to be successful, some elements must be properly designed and introduced into the system. Most notably, well completions must ensure the integrity of downhole sensors; the appropriate measuring instruments must be selected; and surface and downhole measurements must be obtained. Operators have not been early adopters of RTO workflows for SAGD because of the numerous parameters that must be monitored, harsh operating conditions, the lack of integration between the different data acquisition systems, and the complex criteria required to optimize SAGD performance. This paper discussed the first stage in the development of a fully integrated RTO workflow for SAGD. An experimental apparatus with fiber optics distributed temperature sensing (DTS) was connected to a data acquisition system, and intra-minute data was streamed directly into an engineering desktop. The paper showed how subcool calculations can be effectively performed along the length of the horizontal well in real time and the results used to improve SAGD operation. Observations were compared against simulated predictions. In the next stage, a more complex set of criteria will be derived and additional data will be incorporated, such as surface heave, cross-well microseismic, multiphase flowmeter, and observation wells. 9 refs., 9 tabs., 13 figs.

  4. Embryo selection: the role of time-lapse monitoring.

    Science.gov (United States)

    Kovacs, Peter

    2014-12-15

    In vitro fertilization has been available for over 3 decades. Its use is becoming more widespread worldwide, and in the developed world, up to 5% of children have been born following IVF. It is estimated that over 5 million children have been conceived in vitro. In addition to giving hope to infertile couples to have their own family, in vitro fertilization has also introduced risks as well. The risk of multiple gestation and the associated maternal and neonatal morbidity/mortality has increased significantly over the past few decades. While stricter transfer policies have eliminated the majority of the high-order multiples, these changes have not yet had much of an impact on the incidence of twins. A twin pregnancy can be avoided by the transfer of a single embryo only. However, the traditionally used method of morphologic embryo selection is not predictive enough to allow routine single embryo transfer; therefore, new screening tools are needed. Time-lapse embryo monitoring allows continuous, non-invasive embryo observation without the need to remove the embryo from optimal culturing conditions. The extra information on the cleavage pattern, morphologic changes and embryo development dynamics could help us identify embryos with a higher implantation potential. These technologic improvements enable us to objectively select the embryo(s) for transfer based on certain algorithms. In the past 5-6 years, numerous studies have been published that confirmed the safety of time-lapse technology. In addition, various markers have already been identified that are associated with the minimal likelihood of implantation and others that are predictive of blastocyst development, implantation potential, genetic health and pregnancy. Various groups have proposed different algorithms for embryo selection based on mostly retrospective data analysis. However, large prospective trials are needed to study the full benefit of these (and potentially new) algorithms before their

  5. The 2nd Generation Real Time Mission Monitor (RTMM) Development

    Science.gov (United States)

    Blakeslee, Richard; Goodman, Michael; Meyer, Paul; Hardin, Danny; Hall, John; He, Yubin; Regner, Kathryn; Conover, Helen; Smith, Tammy; Lu, Jessica; hide

    2009-01-01

    The NASA Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decisionmaking for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery and orbit data, radar and other surface observations (e.g., lightning location network data), airborne navigation and instrument data sets, model output parameters, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. In order to improve the usefulness and efficiency of the RTMM system, capabilities are being developed to allow the end-user to easily configure RTMM applications based on their mission-specific requirements and objectives. This second generation RTMM is being redesigned to take advantage of the Google plug-in capabilities to run multiple applications in a web browser rather than the original single application Google Earth approach. Currently RTMM employs a limited Service Oriented Architecture approach to enable discovery of mission specific resources. We are expanding the RTMM architecture such that it will more effectively utilize the Open Geospatial Consortium Sensor Web Enablement services and other new technology software tools and components. These modifications and extensions will result in a robust, versatile RTMM system that will greatly increase flexibility of the user to choose which science data sets and support applications to view and/or use. The improvements brought about by RTMM 2nd generation system will provide mission planners and airborne scientists with enhanced decision-making tools and capabilities to more

  6. Monitoring and Depth of Strategy Use in Computer-Based Learning Environments for Science and History

    Science.gov (United States)

    Deekens, Victor M.; Greene, Jeffrey A.; Lobczowski, Nikki G.

    2018-01-01

    Background: Self-regulated learning (SRL) models position metacognitive monitoring as central to SRL processing and predictive of student learning outcomes (Winne & Hadwin, 2008; Zimmerman, 2000). A body of research evidence also indicates that depth of strategy use, ranging from surface to deep processing, is predictive of learning…

  7. Impact of Video Self-Monitoring with Graduated Training on Implementation of Embedded Instructional Learning Trials

    Science.gov (United States)

    Bishop, Crystal D.; Snyder, Patricia A.; Crow, Robert E.

    2015-01-01

    We used a multi-component single-subject experimental design across three preschool teachers to examine the effects of video self-monitoring with graduated training and feedback on the accuracy with which teachers monitored their implementation of embedded instructional learning trials. We also examined changes in teachers' implementation of…

  8. Soil Monitor: an open source web application for real-time soil sealing monitoring and assessment

    Science.gov (United States)

    Langella, Giuliano; Basile, Angelo; Giannecchini, Simone; Iamarino, Michela; Munafò, Michele; Terribile, Fabio

    2016-04-01

    Soil sealing is one of the most important causes of land degradation and desertification. In Europe, soil covered by impermeable materials has increased by about 80% from the Second World War till nowadays, while population has only grown by one third. There is an increasing concern at the high political levels about the need to attenuate imperviousness itself and its effects on soil functions. European Commission promulgated a roadmap (COM(2011) 571) by which the net land take would be zero by 2050. Furthermore, European Commission also published a report in 2011 providing best practices and guidelines for limiting soil sealing and imperviousness. In this scenario, we developed an open source and an open source based Soil Sealing Geospatial Cyber Infrastructure (SS-GCI) named as "Soil Monitor". This tool merges a webGIS with parallel geospatial computation in a fast and dynamic fashion in order to provide real-time assessments of soil sealing at high spatial resolution (20 meters and below) over the whole Italy. Common open source webGIS packages are used to implement both the data management and visualization infrastructures, such as GeoServer and MapStore. The high-speed geospatial computation is ensured by a GPU parallelism using the CUDA (Computing Unified Device Architecture) framework by NVIDIA®. This kind of parallelism required the writing - from scratch - all codes needed to fulfil the geospatial computation built behind the soil sealing toolbox. The combination of GPU computing with webGIS infrastructures is relatively novel and required particular attention at the Java-CUDA programming interface. As a result, Soil Monitor is smart because it can perform very high time-consuming calculations (querying for instance an Italian administrative region as area of interest) in less than one minute. The web application is embedded in a web browser and nothing must be installed before using it. Potentially everybody can use it, but the main targets are the

  9. Active controllers and the time duration to learn a task

    Science.gov (United States)

    Repperger, D. W.; Goodyear, C.

    1986-01-01

    An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.

  10. Seeking surprise : rethinking monitoring for collective learning in rural resource management

    OpenAIRE

    Guijt, I.M.

    2008-01-01

    Commonsense says that monitoring systems should be able to provide feedback that can help correct ineffective actions. But practice shows that when dealing with complex rural development issues that involve collaborative action by a changing configuration of stakeholders, monitoring practice often falls short of its potential. In this thesis, I describe my search to understand why practice is so limited and what might be needed to design monitoring processes that foster learning in concerted ...

  11. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Årup; Frutiger, Sally A.

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15...

  12. Environmental monitoring, restoration and assessment: What have we learned

    Energy Technology Data Exchange (ETDEWEB)

    Gray, R.H. (ed.)

    1990-01-01

    The Twenty-Eighth Hanford Symposium on Health and the Environment was held in Richland, Washington, October 16--19, 1989. The symposium was sponsored by the US Department of Energy and the Pacific Northwest Laboratory, operated by Battelle Memorial Institute. The symposium was organized to review and evaluate some of the monitoring and assessment programs that have been conducted or are currently in place. Potential health and environmental effects of energy-related and other industrial activities have been monitored and assessed at various government and private facilities for over three decades. Most monitoring is required under government regulations; some monitoring is implemented because facility operators consider it prudent practice. As a result of these activities, there is now a substantial radiological, physical, and chemical data base for various environmental components, both in the United States and abroad. Symposium participants, both platform and poster presenters, were asked to consider, among other topics, the following: Has the expenditure of millions of dollars for radiological monitoring and assessment activities been worth the effort How do we decide when enough monitoring is enough Can we adequately assess the impacts of nonradiological components -- both inorganic and organic -- of wastes Are current regulatory requirements too restrictive or too lenient Can monitoring and assessment be made more cost effective Papers were solicited in the areas of environmental monitoring; environmental regulations; remediation, restoration, and decommissioning; modeling and dose assessment; uncertainty, design, and data analysis; and data management and quality assurance. Individual reports are processed separately for the databases.

  13. Environmental monitoring, restoration and assessment: What have we learned?

    International Nuclear Information System (INIS)

    Gray, R.H.

    1990-01-01

    The Twenty-Eighth Hanford Symposium on Health and the Environment was held in Richland, Washington, October 16--19, 1989. The symposium was sponsored by the US Department of Energy and the Pacific Northwest Laboratory, operated by Battelle Memorial Institute. The symposium was organized to review and evaluate some of the monitoring and assessment programs that have been conducted or are currently in place. Potential health and environmental effects of energy-related and other industrial activities have been monitored and assessed at various government and private facilities for over three decades. Most monitoring is required under government regulations; some monitoring is implemented because facility operators consider it prudent practice. As a result of these activities, there is now a substantial radiological, physical, and chemical data base for various environmental components, both in the United States and abroad. Symposium participants, both platform and poster presenters, were asked to consider, among other topics, the following: Has the expenditure of millions of dollars for radiological monitoring and assessment activities been worth the effort? How do we decide when enough monitoring is enough? Can we adequately assess the impacts of nonradiological components -- both inorganic and organic -- of wastes? Are current regulatory requirements too restrictive or too lenient? Can monitoring and assessment be made more cost effective? Papers were solicited in the areas of environmental monitoring; environmental regulations; remediation, restoration, and decommissioning; modeling and dose assessment; uncertainty, design, and data analysis; and data management and quality assurance. Individual reports are processed separately for the databases

  14. Real time nanogravimetric monitoring of corrosion in radioactive environments

    OpenAIRE

    Tzagkaroulakis, Ioannis; Boxall, Colin

    2017-01-01

    Monitoring and understanding the mechanism of metal corrosion throughout the nuclear fuel cycle play a key role in the safe asset management of facilities. They also provide information essential for making an informed choice regarding the selection of decontamination methods for steel plant and equipment scheduled for decommissioning. Recent advances in Quartz Crystal Nanobalance (QCN) technology offer the means of monitoring corrosion in-situ, in radiologically harsh environments, in real t...

  15. Cooperating Expert Systems for the Next Generation of Real-time Monitoring Applications

    Science.gov (United States)

    Schwuttke, U.; Veregge, J.; Quan, A.

    1995-01-01

    A distributed monitoring and diagnosis system has been developed and successfully applied to real-time monitoring of interplanetary spacecraft at NASA's Jet Propulsion Laboratory. This system uses a combination of conventional processing and artificial intelligence.

  16. Robot-assisted motor activation monitored by time-domain optical brain imaging

    Science.gov (United States)

    Steinkellner, O.; Wabnitz, H.; Schmid, S.; Steingräber, R.; Schmidt, H.; Krüger, J.; Macdonald, R.

    2011-07-01

    Robot-assisted motor rehabilitation proved to be an effective supplement to conventional hand-to-hand therapy in stroke patients. In order to analyze and understand motor learning and performance during rehabilitation it is desirable to develop a monitor to provide objective measures of the corresponding brain activity at the rehabilitation progress. We used a portable time-domain near-infrared reflectometer to monitor the hemodynamic brain response to distal upper extremity activities. Four healthy volunteers performed two different robot-assisted wrist/forearm movements, flexion-extension and pronation-supination in comparison with an unassisted squeeze ball exercise. A special headgear with four optical measurement positions to include parts of the pre- and postcentral gyrus provided a good overlap with the expected activation areas. Data analysis based on variance of time-of-flight distributions of photons through tissue was chosen to provide a suitable representation of intracerebral signals. In all subjects several of the four detection channels showed a response. In some cases indications were found of differences in localization of the activated areas for the various tasks.

  17. Development of a real time activity monitoring Android application utilizing SmartStep.

    Science.gov (United States)

    Hegde, Nagaraj; Melanson, Edward; Sazonov, Edward

    2016-08-01

    Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback. The development of activity classification methods was based on the the data from a human study involving 4 participants. Participants were asked to perform activities of sitting, standing, walking, and cycling while they wore SmartStep insole system. Multinomial Logistic Discrimination (MLD) was utilized in the development of machine learning model for activity prediction. The resulting classification model was implemented in an Android Smartphone. The Android application was benchmarked for power consumption and CPU loading. Leave one out cross validation resulted in average accuracy of 96.9% during model training phase. The Android application for real time activity classification was tested on a human subject wearing SmartStep resulting in testing accuracy of 95.4%.

  18. A machine learning approach to the accurate prediction of monitor units for a compact proton machine.

    Science.gov (United States)

    Sun, Baozhou; Lam, Dao; Yang, Deshan; Grantham, Kevin; Zhang, Tiezhi; Mutic, Sasa; Zhao, Tianyu

    2018-05-01

    Clinical treatment planning systems for proton therapy currently do not calculate monitor units (MUs) in passive scatter proton therapy due to the complexity of the beam delivery systems. Physical phantom measurements are commonly employed to determine the field-specific output factors (OFs) but are often subject to limited machine time, measurement uncertainties and intensive labor. In this study, a machine learning-based approach was developed to predict output (cGy/MU) and derive MUs, incorporating the dependencies on gantry angle and field size for a single-room proton therapy system. The goal of this study was to develop a secondary check tool for OF measurements and eventually eliminate patient-specific OF measurements. The OFs of 1754 fields previously measured in a water phantom with calibrated ionization chambers and electrometers for patient-specific fields with various range and modulation width combinations for 23 options were included in this study. The training data sets for machine learning models in three different methods (Random Forest, XGBoost and Cubist) included 1431 (~81%) OFs. Ten-fold cross-validation was used to prevent "overfitting" and to validate each model. The remaining 323 (~19%) OFs were used to test the trained models. The difference between the measured and predicted values from machine learning models was analyzed. Model prediction accuracy was also compared with that of the semi-empirical model developed by Kooy (Phys. Med. Biol. 50, 2005). Additionally, gantry angle dependence of OFs was measured for three groups of options categorized on the selection of the second scatters. Field size dependence of OFs was investigated for the measurements with and without patient-specific apertures. All three machine learning methods showed higher accuracy than the semi-empirical model which shows considerably large discrepancy of up to 7.7% for the treatment fields with full range and full modulation width. The Cubist-based solution

  19. Lessons learned from post-construction bird and bat monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Stephenson, D.E. [Natural Resource Solutions, Waterloo, ON (Canada)

    2010-07-01

    This PowerPoint presentation presented recommendations for a successful post-construction bat mortality monitoring strategy. A range of metrics are offered in the literature for establishing a search radius from the base of wind turbines, and changes in radius can have a significant impact on the outcomes of bat monitoring programs. Changes in ground-cover or areas with agricultural crops can obscure bat carcasses. Scavengers can also remove carcasses. Frequent scavenger tests are required to ensure that bat mortality rates are accurately represented. The full area under wind turbines must be regularly monitored instead of radial subsamples. A search radius must be established as part of an accurate strategy. Monitoring crews must be trained to look for carcasses in varied terrains, including under foliage, plants, and crops. Turbine operators must also consider that the presence of a single bat carcass may, after applying adjustments, represent 5 dead animals. Conservative adjustment assumptions may overwhelm the collected data. tabs., figs.

  20. Promoting Stakeholder Participation in a Learning-Based Monitoring ...

    African Journals Online (AJOL)

    Southern African Journal of Environmental Education ... This research analysed monitoring and evaluation activities based on the Outcome Mapping ... Development, Cooperation and Technical Assistance), have perceived the performance of ...

  1. Polysynchronous: Dialogic Construction of Time in Online Learning

    Science.gov (United States)

    Oztok, Murat; Wilton, Lesley; Zingaro, Daniel; Mackinnon, Kim; Makos, Alexandra; Phirangee, Krystle; Brett, Clare; Hewitt, Jim

    2014-01-01

    Online learning has been conceptualized for decades as being delivered in one of two modes: synchronous or asynchronous. Technological determinism falls short in describing the role that the individuals' psychological, social and pedagogical factors play in their perception, experience and understanding of time online. This article explores…

  2. Probability Learning: Changes in Behavior across Time and Development

    Science.gov (United States)

    Plate, Rista C.; Fulvio, Jacqueline M.; Shutts, Kristin; Green, C. Shawn; Pollak, Seth D.

    2018-01-01

    Individuals track probabilities, such as associations between events in their environments, but less is known about the degree to which experience--within a learning session and over development--influences people's use of incoming probabilistic information to guide behavior in real time. In two experiments, children (4-11 years) and adults…

  3. Instructional Advice, Time Advice and Learning Questions in Computer Simulations

    Science.gov (United States)

    Rey, Gunter Daniel

    2010-01-01

    Undergraduate students (N = 97) used an introductory text and a computer simulation to learn fundamental concepts about statistical analyses (e.g., analysis of variance, regression analysis and General Linear Model). Each learner was randomly assigned to one cell of a 2 (with or without instructional advice) x 2 (with or without time advice) x 2…

  4. Adaptation and learning: characteristic time scales of performance dynamics.

    Science.gov (United States)

    Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

    2009-12-01

    A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

  5. Online gaming for learning optimal team strategies in real time

    Science.gov (United States)

    Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

    2010-04-01

    This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

  6. Remote real-time monitoring of subsurface landfill gas migration.

    Science.gov (United States)

    Fay, Cormac; Doherty, Aiden R; Beirne, Stephen; Collins, Fiachra; Foley, Colum; Healy, John; Kiernan, Breda M; Lee, Hyowon; Maher, Damien; Orpen, Dylan; Phelan, Thomas; Qiu, Zhengwei; Zhang, Kirk; Gurrin, Cathal; Corcoran, Brian; O'Connor, Noel E; Smeaton, Alan F; Diamond, Dermot

    2011-01-01

    The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months.

  7. Explosion Monitoring with Machine Learning: A LSTM Approach to Seismic Event Discrimination

    Science.gov (United States)

    Magana-Zook, S. A.; Ruppert, S. D.

    2017-12-01

    The streams of seismic data that analysts look at to discriminate natural from man- made events will soon grow from gigabytes of data per day to exponentially larger rates. This is an interesting problem as the requirement for real-time answers to questions of non-proliferation will remain the same, and the analyst pool cannot grow as fast as the data volume and velocity will. Machine learning is a tool that can solve the problem of seismic explosion monitoring at scale. Using machine learning, and Long Short-term Memory (LSTM) models in particular, analysts can become more efficient by focusing their attention on signals of interest. From a global dataset of earthquake and explosion events, a model was trained to recognize the different classes of events, given their spectrograms. Optimal recurrent node count and training iterations were found, and cross validation was performed to evaluate model performance. A 10-fold mean accuracy of 96.92% was achieved on a balanced dataset of 30,002 instances. Given that the model is 446.52 MB it can be used to simultaneously characterize all incoming signals by researchers looking at events in isolation on desktop machines, as well as at scale on all of the nodes of a real-time streaming platform. LLNL-ABS-735911

  8. Time-sensitive Customer Churn Prediction based on PU Learning

    OpenAIRE

    Wang, Li; Chen, Chaochao; Zhou, Jun; Li, Xiaolong

    2018-01-01

    With the fast development of Internet companies throughout the world, customer churn has become a serious concern. To better help the companies retain their customers, it is important to build a customer churn prediction model to identify the customers who are most likely to churn ahead of time. In this paper, we propose a Time-sensitive Customer Churn Prediction (TCCP) framework based on Positive and Unlabeled (PU) learning technique. Specifically, we obtain the recent data by shortening the...

  9. Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

    Science.gov (United States)

    Parsa, Maryam; Panda, Priyadarshini; Sen, Shreyas; Roy, Kaushik

    2017-07-01

    Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for analysis of the large pool of data generated by the wearable devices. Deep learning is among the promising methods for analyzing such data for healthcare applications and disease diagnosis. However, the conventional deep neural networks are computationally intensive and it is impractical to use them in real-time diagnosis with low-powered on-body devices. We propose Staged Inference using Conditional Deep Learning (SICDL), as an energy efficient approach for creating healthcare monitoring systems. For smart diagnostics, we observe that all diagnoses are not equally challenging. The proposed approach thus decomposes the diagnoses into preliminary analysis (such as healthy vs unhealthy) and detailed analysis (such as identifying the specific type of cardio disease). The preliminary diagnosis is conducted real-time with a low complexity neural network realized on the resource-constrained on-body device. The detailed diagnosis requires a larger network that is implemented remotely in cloud and is conditionally activated only for detailed diagnosis (unhealthy individuals). We evaluated the proposed approach using available physiological sensor data from Physionet databases, and achieved 38% energy reduction in comparison to the conventional deep learning approach.

  10. Reflection in Learning through a Self-monitoring Device: Design Research on EEG Self-Monitoring during a Study Session

    Directory of Open Access Journals (Sweden)

    Eva Durall

    2017-04-01

    Full Text Available The increasing availability of self-monitoring technologies has created opportunities for gaining awareness about one’s own behavior and reflecting on it. In teaching and learning, there is interest in using self-monitoring technologies, but very few studies have explored the possibilities. In this paper, we present a design study that investigates a technology (called Feeler that guides students to follow a specific learning script, monitors changes in their electroencephalogram (EEG while studying, and later provides visualization of the EEG data. The results are two-fold: (1 the hardware/software prototype and (2 the conclusions from the proof-of-concept research conducted with the prototype and six participants. In the research, we collected qualitative data from interviews to identify whether the prototype supported students to develop their reflective skills. The thematic analysis of the interviews showed that the Feeler’s learning script and visualization of the EEG data supported greater levels of reflection by fostering students’ curiosity, puzzlement, and personal inquiry. The proof-of-concept research also provided insights into several factors, such as the value of personal experience, the challenge of assumptions, and the contextualization of the data that trigger reflective thinking. The results validate the design concept and the role of the prototype in supporting awareness of and reflection about students’ mental states when they perform academic tasks.

  11. Feasibility of a real-time hand hygiene notification machine learning system in outpatient clinics.

    Science.gov (United States)

    Geilleit, R; Hen, Z Q; Chong, C Y; Loh, A P; Pang, N L; Peterson, G M; Ng, K C; Huis, A; de Korne, D F

    2018-04-09

    Various technologies have been developed to improve hand hygiene (HH) compliance in inpatient settings; however, little is known about the feasibility of machine learning technology for this purpose in outpatient clinics. To assess the effectiveness, user experiences, and costs of implementing a real-time HH notification machine learning system in outpatient clinics. In our mixed methods study, a multi-disciplinary team co-created an infrared guided sensor system to automatically notify clinicians to perform HH just before first patient contact. Notification technology effects were measured by comparing HH compliance at baseline (without notifications) with real-time auditory notifications that continued till HH was performed (intervention I) or notifications lasting 15 s (intervention II). User experiences were collected during daily briefings and semi-structured interviews. Costs of implementation of the system were calculated and compared to the current observational auditing programme. Average baseline HH performance before first patient contact was 53.8%. With real-time auditory notifications that continued till HH was performed, overall HH performance increased to 100% (P machine learning system were estimated to be 46% lower than the observational auditing programme. Machine learning technology that enables real-time HH notification provides a promising cost-effective approach to both improving and monitoring HH, and deserves further development in outpatient settings. Copyright © 2018 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  12. Fiber Optics Deliver Real-Time Structural Monitoring

    Science.gov (United States)

    2013-01-01

    To alter the shape of aircraft wings during flight, researchers at Dryden Flight Research Center worked on a fiber optic sensor system with Austin-based 4DSP LLC. The company has since commercialized a new fiber optic system for monitoring applications in health and medicine, oil and gas, and transportation, increasing company revenues by 60 percent.

  13. Time-frequency Methods for Structural Health Monitoring

    NARCIS (Netherlands)

    Pyayt, A.L.; Kozionov, A.P.; Mokhov, I.I.; Lang, B.; Meijer, R.J.; Krzhizhanovskaya, V.V.; Sloot, P.M.A.

    2014-01-01

    Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM) of flood protection systems (levees, earthen dikes and

  14. Time-frequency methods for structural health monitoring

    NARCIS (Netherlands)

    Pyayt, A.L.; Kozionov, A.P.; Mokhov, I.I.; Lang, B.; Meijer, R.J.; Krzhizhanovskaya, V.V.; Sloot, P.M.A.

    2014-01-01

    Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM) of flood protection systems (levees, earthen dikes and

  15. Phonetic Accounts of Timed Responses in Syllable Monitoring Experiments

    NARCIS (Netherlands)

    Rietveld, A.C.M.; Schiller, N.O.; Caspers, J.; Chen, Y.; Heeren, W.; Pacilly, J.; Schiller, N.O.; Zanten, E. van

    2014-01-01

    This paper reports a syllable monitoring experiment that examines the role of segmental phonetic information in Dutch. Participants were presented with lists of spoken words and were required to detect auditorily specified targets that matched or did not match the initial syllable of the spoken

  16. Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study

    Directory of Open Access Journals (Sweden)

    Haoteng Zhao

    2018-03-01

    Full Text Available Quarry sites result from human activity, which includes the removal of original vegetation and the overlying soil to dig out stones for building use. Therefore, the dynamics of the quarry area provide a unique view of human mining activities. Actually, the topographic changes caused by mining activities are also a result of the development of the local economy. Thus, monitoring the quarry area can provide information about the policies of the economy and environmental protection. In this paper, we developed a combined method of machine learning classification and quarry region analysis to estimate the quarry area in a quarry region near Beijing. A temporal smoothing based on the classification results of all years was applied in post-processing to remove outliers and obtain gently changing sequences along the monitoring term. The method was applied to Landsat images to derive a quarry distribution map and quarry area time series from 1984 to 2017, revealing significant inter-annual variability. The time series revealed a five-stage development of the quarry area with different growth patterns. As the study region lies on two jurisdictions—Tianjin and Hebei—a comparison of the quarry area changes in the two jurisdictions was applied, which revealed that the different policies in the two regions could impose different impacts on the development of a quarry area. An analysis concerning the relationship between quarry area and gross regional product (GRP was performed to explore the potential application on socioeconomic studies, and we found a strong positive correlation between quarry area and GRP in Langfang City, Hebei Province. These results demonstrate the potential benefit of annual monitoring over the long-term for socioeconomic studies, which can be used for mining decision making.

  17. Spaced learning and innovative teaching: school time, pedagogy of attention and learning awareness

    Directory of Open Access Journals (Sweden)

    Garzia Maeca

    2016-06-01

    Full Text Available Currently, the ‘time’ variable has taken on the function of instructional and pedagogical innovation catalyst, after representing-over the years-a symbol of democratisation, learning opportunity and instruction quality, able to incorporate themes such as school dropout, personalisation and vocation into learning. Spaced Learning is a teaching methodology useful to quickly seize information in long-term memory based on a particular arrangement of the lesson time that comprises three input sessions and two intervals. Herein we refer to a teachers’ training initiative on Spaced Learning within the programme ‘DocentiInFormAzione’ in the EDOC@WORK3.0 Project in Apulia region in 2015. The training experience aimed at increasing teachers’ competencies in the Spaced Learning method implemented in a context of collaborative reflection and reciprocal enrichment. The intent of the article is to show how a process of rooting of the same culture of innovation, which opens to the discovery (or rediscovery of effective teaching practices sustained by scientific evidences, can be successfully implemented and to understand how or whether this innovation- based on the particular organisation of instructional time-links learning awareness to learning outcomes.

  18. Real time monitoring of rat liver energy state during ischemia.

    Science.gov (United States)

    Barbiro, E; Zurovsky, Y; Mayevsky, A

    1998-11-01

    Hepatic failure is one of the major problems developed during the posttransplantation period. A possible cause of hepatic failure is the prolonged ischemia induced during the implantation procedure. Hepatic ischemia leads to a reduction in oxygen supply, ATP level decline, liver metabolism impairment, and finally organ failure. The purpose of this study was to estimate the functional state of the liver by monitoring liver blood flow and the mitochondrial NADH redox state simultaneously and continuously during in situ liver ischemia followed by reperfusion. Measurements were performed using the multiprobe developed in our laboratory consisting of fibers for the measurement of relative liver blood flow (laser Doppler flowmetry) and mitochondrial redox state (NADH fluorescence). The experimental procedure included the temporary interruption of blood flow to the liver using three types of ischemia, hepatic artery occlusion, portal vein occlusion, and simultaneous occlusion of hepatic artery and portal vein, followed by a reperfusion period. These preliminary experiments showed a significant decrease in liver blood flow, following the three types of liver ischemia, and a significant increase in NADH levels. The probe used in this study incorporates the advantage of monitoring NADH and liver blood flow simultaneously and continuously from the same area on the surface of the liver. Since each of these two parameters is not calibrated in absolute units, the simultaneous monitoring decreases possible artifacts. Also, it will allow us to determine of the coupling between tissue blood flow and oxidative phosphorylation. It is believed that the measurements of respiratory chain dysfunction might predict organ viability in clinical organ transplantation situations. Using this probe may also help to decrease the variability in liver blood flow monitoring since liver blood flow monitoring is supported simultaneously with the mitochondrial redox state, which supplies the

  19. A Parametric Learning and Identification Based Robust Iterative Learning Control for Time Varying Delay Systems

    Directory of Open Access Journals (Sweden)

    Lun Zhai

    2014-01-01

    Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.

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

    Science.gov (United States)

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

    2012-01-01

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

  1. Learning of time series through neuron-to-neuron instruction

    Energy Technology Data Exchange (ETDEWEB)

    Miyazaki, Y [Department of Physics, Kyoto University, Kyoto 606-8502, (Japan); Kinzel, W [Institut fuer Theoretische Physik, Universitaet Wurzburg, 97074 Wurzburg (Germany); Shinomoto, S [Department of Physics, Kyoto University, Kyoto (Japan)

    2003-02-07

    A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space.

  2. Learning of time series through neuron-to-neuron instruction

    International Nuclear Information System (INIS)

    Miyazaki, Y; Kinzel, W; Shinomoto, S

    2003-01-01

    A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space

  3. Finite time convergent learning law for continuous neural networks.

    Science.gov (United States)

    Chairez, Isaac

    2014-02-01

    This paper addresses the design of a discontinuous finite time convergent learning law for neural networks with continuous dynamics. The neural network was used here to obtain a non-parametric model for uncertain systems described by a set of ordinary differential equations. The source of uncertainties was the presence of some external perturbations and poor knowledge of the nonlinear function describing the system dynamics. A new adaptive algorithm based on discontinuous algorithms was used to adjust the weights of the neural network. The adaptive algorithm was derived by means of a non-standard Lyapunov function that is lower semi-continuous and differentiable in almost the whole space. A compensator term was included in the identifier to reject some specific perturbations using a nonlinear robust algorithm. Two numerical examples demonstrated the improvements achieved by the learning algorithm introduced in this paper compared to classical schemes with continuous learning methods. The first one dealt with a benchmark problem used in the paper to explain how the discontinuous learning law works. The second one used the methane production model to show the benefits in engineering applications of the learning law proposed in this paper. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Promoting Stakeholder Participation in a Learning-Based Monitoring ...

    African Journals Online (AJOL)

    It is result-oriented and aims to enhance control and efficiency (Morgan, 2005). However ... Outcome Mapping as a Learning-Oriented Project Cycle Management Framework .... Therefore, a qualitative case-study design was selected as .... college and colleagues admitting embarrassment [for failing to do what was agreed.

  5. An LCD Monitor with Sufficiently Precise Timing for Research in Vision

    OpenAIRE

    Wang, Peng; Nikolić, Danko

    2011-01-01

    Until now, liquid crystal display (LCD) monitors have not been used widely for research in vision. Despite their main advantages of continuous illumination and low electromagnetic emission, these monitors had problems with timing and reliability. Here we report that there is at least one new inexpensive 120 Hz model, whose timing and stability is on a par with a benchmark cathode-ray tube monitor, or even better. The onset time was stable across repetitions, 95% confidence interval (the erro...

  6. Optimizing the De-Noise Neural Network Model for GPS Time-Series Monitoring of Structures

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2015-09-01

    Full Text Available The Global Positioning System (GPS is recently used widely in structures and other applications. Notwithstanding, the GPS accuracy still suffers from the errors afflicting the measurements, particularly the short-period displacement of structural components. Previously, the multi filter method is utilized to remove the displacement errors. This paper aims at using a novel application for the neural network prediction models to improve the GPS monitoring time series data. Four prediction models for the learning algorithms are applied and used with neural network solutions: back-propagation, Cascade-forward back-propagation, adaptive filter and extended Kalman filter, to estimate which model can be recommended. The noise simulation and bridge’s short-period GPS of the monitoring displacement component of one Hz sampling frequency are used to validate the four models and the previous method. The results show that the Adaptive neural networks filter is suggested for de-noising the observations, specifically for the GPS displacement components of structures. Also, this model is expected to have significant influence on the design of structures in the low frequency responses and measurements’ contents.

  7. Influence of learning strategy on response time during complex value-based learning and choice.

    Directory of Open Access Journals (Sweden)

    Shiva Farashahi

    Full Text Available Measurements of response time (RT have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning. Alternatively, they could learn reward values of options' features (e.g. color, shape and combine these values to estimate reward values for individual options (feature-based learning. We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.

  8. Real-time individualized training vectors for experiential learning.

    Energy Technology Data Exchange (ETDEWEB)

    Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie; Glickman, Matthew R.; Fabian, Nathan

    2011-01-01

    Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD) project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.

  9. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

  10. Representation Learning from Time Labelled Heterogeneous Data for Mobile Crowdsensing

    Directory of Open Access Journals (Sweden)

    Chunmei Ma

    2016-01-01

    Full Text Available Mobile crowdsensing is a new paradigm that can utilize pervasive smartphones to collect and analyze data to benefit users. However, sensory data gathered by smartphone usually involves different data types because of different granularity and multiple sensor sources. Besides, the data are also time labelled. The heterogeneous and time sequential data raise new challenges for data analyzing. Some existing solutions try to learn each type of data one by one and analyze them separately without considering time information. In addition, the traditional methods also have to determine phone orientation because some sensors equipped in smartphone are orientation related. In this paper, we think that a combination of multiple sensors can represent an invariant feature for a crowdsensing context. Therefore, we propose a new representation learning method of heterogeneous data with time labels to extract typical features using deep learning. We evaluate that our proposed method can adapt data generated by different orientations effectively. Furthermore, we test the performance of the proposed method by recognizing two group mobile activities, walking/cycling and driving/bus with smartphone sensors. It achieves precisions of 98.6% and 93.7% in distinguishing cycling from walking and bus from driving, respectively.

  11. NEW MATERIALS FOR PEDAGOGICAL TEACHING-LEARNING IN BIOCHEMISTRY: MONITORING PARTICIPATION

    Directory of Open Access Journals (Sweden)

    R. S. Campos

    2015-08-01

    Full Text Available This summary consists of an experience report about actions taken by biochemical monitors with pharmacy students. The reason of our work was the intention to both improve the process of teaching and also learning and invalidate the labels owned by biochemistry of hard and high-level-failure subject. The three actors: teachers, students and monitor could act on an integrated basis for the construction of an articulated  pedagogical process between theory/practice and learning signification. Our main objective was to initiate the monitors in teaching practice effected through educational projects aimed at improving the teaching and learning of undergraduate courses and encouraging teacher training, involving teachers and students the guiding condition and monitors, respectively. The methodology was applied in three stages: 1 preparation of teaching materials; 2nd application in class and 3rd students rating of the methodology applied by monitors. The teaching materials presented discussed several biochemistry's topics and students had the opportunity to scaffold their own knowledge actively. Almost 90% considered the tool applied as highly related to classes and 82% considered this way of learning more significant than dialogical lectures. The performance of the monitors, focused on students and their learning, was considered great by students who were more motivated, resulting in the excellent evaluation of the work (100% of acceptance. The failure rate of the subject reduced in the four groups wherein the pedagogical materials were applied. It can demonstrate that both the mastery of scientific content and the pedagogical process involved during the teaching and learning moments are important.

  12. Quasi Real Time Data Analysis for Air Quality Monitoring with an Electronic Nose

    Science.gov (United States)

    Zhou, Hanying; Shevade, Abhijit V.; Pelletier, Christine C.; Homer, Margie L.; Ryan, M. Amy

    2006-01-01

    Cabin Air Quality Monitoring: A) Functions; 1) Incident monitor for targeted contaminants exceeding targeted concentrations. Identify and quantify. 2) Monitor for presence of compounds associated with fires or overheating electronics. 3) Monitor clean-up process. B) Characteristics; 1) Low mass, low power device. 2) Requires little crew time for maintenance and calibration. 3) Detects, identifies and quantifies selected chemical species at or below 24 hour SMAC.

  13. The Real-Time Monitoring Service Platform for Land Supervision Based on Cloud Integration

    Science.gov (United States)

    Sun, J.; Mao, M.; Xiang, H.; Wang, G.; Liang, Y.

    2018-04-01

    Remote sensing monitoring has become the important means for land and resources departments to strengthen supervision. Aiming at the problems of low monitoring frequency and poor data currency in current remote sensing monitoring, this paper researched and developed the cloud-integrated real-time monitoring service platform for land supervision which enhanced the monitoring frequency by acquiring the domestic satellite image data overall and accelerated the remote sensing image data processing efficiency by exploiting the intelligent dynamic processing technology of multi-source images. Through the pilot application in Jinan Bureau of State Land Supervision, it has been proved that the real-time monitoring technical method for land supervision is feasible. In addition, the functions of real-time monitoring and early warning are carried out on illegal land use, permanent basic farmland protection and boundary breakthrough in urban development. The application has achieved remarkable results.

  14. Effect of chronotype and student learning time on mathematical ability based on self-regulated learning

    Science.gov (United States)

    Ratnaningsih, N.; El Akbar, R. R.; Hidayat, E.

    2018-05-01

    One of ways to improve students' learning ability is conduct a research, with purpose to obtain a method to improve students' ability. Research often carried out on the modification of teaching methods, uses of teaching media, motivation, interests and talents of students. Research related to the internal condition of students becomes very interesting to studied, including research on circadian rhythms. Every person in circadian rhythms has its own Chronotype, which divided into two types namely early type and night late type. Chronotype affects the comfort in activity, for example a person with Chronotype category of early type tends to be more comfort in daytime activities. The purpose of this study is to examine the conditions of students, related Chronotype suitable or appropriate for student learning time. This suitability then studied in relation to the ability of learning mathematics with self- regulated learning approach. This study consists of three stages; (i) student Chronotype measurement, (ii) data retrieval, and (iii) analysis of research results. The results show the relationship between the students' learning ability in mathematics to learning time corresponding to Chronotype.

  15. EXPERT-ANALITICAL MONITORING OF LEARNING PROCESS QUALITY IN HIGH SCHOOL

    Directory of Open Access Journals (Sweden)

    T. M. Korotun

    2010-10-01

    Full Text Available The technological model is proposed for monitoring process of learning process quality in high school compliant with current European and home standards. The mathematical methods are elaborated for diverse activities as to learning process objects quality determination unified support. They self-consistently combine: automatic expert evaluation with Bayesian net and Value tree models; Delphi technique enhancement; best practices for education quality assessment. Quality estimates’ consistency index is introduced for their choice and acceptability analysis. Its permanent increasing over monitoring stages is guaranteed. The tools for these stages’ automatic support are described.

  16. Fixation and escape times in stochastic game learning

    International Nuclear Information System (INIS)

    Realpe-Gomez, John; Szczesny, Bartosz; Galla, Tobias; Dall’Asta, Luca

    2012-01-01

    Evolutionary dynamics in finite populations is known to fixate eventually in the absence of mutation. We here show that a similar phenomenon can be found in stochastic game dynamical batch learning, and investigate fixation in learning processes in a simple 2×2 game, for two-player games with cyclic interaction, and in the context of the best-shot network game. The analogues of finite populations in evolution are here finite batches of observations between strategy updates. We study when and how such fixation can occur, and present results on the average time-to-fixation from numerical simulations. Simple cases are also amenable to analytical approaches and we provide estimates of the behaviour of so-called escape times as a function of the batch size. The differences and similarities with escape and fixation in evolutionary dynamics are discussed. (paper)

  17. A Mobile Full-Time Daily System for Fetal Monitoring

    Directory of Open Access Journals (Sweden)

    Bureev Artem

    2016-01-01

    Full Text Available The article describes a mobile hardware and software system designed for daily monitoring of the state of fetal and maternal cardiovascular systems. The assessment is carried out by means of recording and further online analysis of acoustic data, obtained from the abdominal surface of a pregnant woman’s body. The components and operating principles of the hardware and software system designed are described. The results of experimental studies aimed at assessing the applicability of a method of acoustic data analysis implemented in the system developed are shown. The results obtained have been compared with the results obtained using cardiotocography.

  18. The 3 R's of Learning Time: Rethink, Reshape, Reclaim

    Science.gov (United States)

    Sackey, Shera Carter

    2012-01-01

    The Learning School Alliance is a network of schools collaborating about professional practice. The network embodies Learning Forward's purpose to advance effective job-embedded professional learning that leads to student outcomes. A key component of Learning Forward's Standards for Professional Learning is a focus on collaborative learning,…

  19. Real time fish pond monitoring and automation using Arduino

    Science.gov (United States)

    Harun, Z.; Reda, E.; Hashim, H.

    2018-03-01

    Investment and operating costs are the biggest obstacles in modernizing fish ponds in an otherwise very lucrative industry i.e. food production, in this region. Small-scale farmers running on small ponds could not afford to hire workers to man daily operations which usually consists of monitoring water levels, temperature and feeding fish. Bigger scale enterprises usually have some kinds of automation for water monitoring and replacement. These entities have to consider employing pH and dissolved oxygen (DO) sensors to ensure the health and growth of fish, sooner or later as their farms grow. This project identifies one of the sites, located in Malacca. In this project, water, temperature, pH and DO levels are measured and integrated with aerating and water supply pumps using Arduino. User could receive information at predetermined intervals on preferred communication or display gadgets as long as they have internet. Since integrating devices are comparatively not expensive; it usually consists of Arduino board, internet and relay frames and display system, farmer could source these components easily. A sample of two days measurements of temperature, pH and DO levels show that this farm has a high-quality water. Oxygen levels increases in the day as sunshine supports photosynthesis in the pond. With this integration system, farmer need not hire worker at their site, consequently drive down operating costs and improve efficiency.

  20. Development of real time monitoring for ITER first wall erosion

    International Nuclear Information System (INIS)

    Berryman, Ian.; Pallaras, Luke; Thomson, Laura; Wang, Michael; Riley, Daniel P.

    2009-01-01

    Full text: This project aims to contribute to the current research on the first wall erosion diagnostic for the ITER fusion reactor. The plasma-facing first wall tiles of the ITER tokamak reactor are exposed to an expected neutron flux of O. 7 8 M W/m2 and a thermal load of O. 5M W/m 2 during operation. Instabilities in the magnetically confined plasma, such as edge-Iocalised modes, cause the plasma to come into direct contact with the first wall. The resulting thermal loads can vaporise and ablate the tile material. Moreover, a flux of high-energy neutrons produced during the fusion process results in a range of radiation effects. Therefore, a diagnostic is necessary to monitor the extent and rate of damage caused to the first wall. We have considered and critically assessed the viability of six alternative diagnostic methods, encompassing both established and novel concepts. From these, a design featuring embedded conducting elements was selected as the strongest candidate, as by monitoring electrical signals it has the potential to detect both bulk erosion and radiation damage.

  1. Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

    Science.gov (United States)

    Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

    2018-04-01

    Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

  2. The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

    Science.gov (United States)

    Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

    2011-06-01

    The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

  3. Oscillations, Timing, Plasticity, and Learning in the Cerebellum.

    Science.gov (United States)

    Cheron, G; Márquez-Ruiz, J; Dan, B

    2016-04-01

    The highly stereotyped, crystal-like architecture of the cerebellum has long served as a basis for hypotheses with regard to the function(s) that it subserves. Historically, most clinical observations and experimental work have focused on the involvement of the cerebellum in motor control, with particular emphasis on coordination and learning. Two main models have been suggested to account for cerebellar functioning. According to Llinás's theory, the cerebellum acts as a control machine that uses the rhythmic activity of the inferior olive to synchronize Purkinje cell populations for fine-tuning of coordination. In contrast, the Ito-Marr-Albus theory views the cerebellum as a motor learning machine that heuristically refines synaptic weights of the Purkinje cell based on error signals coming from the inferior olive. Here, we review the role of timing of neuronal events, oscillatory behavior, and synaptic and non-synaptic influences in functional plasticity that can be recorded in awake animals in various physiological and pathological models in a perspective that also includes non-motor aspects of cerebellar function. We discuss organizational levels from genes through intracellular signaling, synaptic network to system and behavior, as well as processes from signal production and processing to memory, delegation, and actual learning. We suggest an integrative concept for control and learning based on articulated oscillation templates.

  4. METHODS OF STATISTICAL MONITORING OF PROFESSIONAL ORIENTATION WORK OF SOCIAL EDUCATORS IN PERSONAL LEARNING ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    Oleksandr M. Korniiets

    2012-12-01

    Full Text Available The article deals with the application of social services WEB 2.0 for personal learning environment creation that is used for professional orientation work of social educator. The feedback is must be in personal learning environment for the effective professional orientation work. This feedback can be organized through statistical monitoring. The typical solution for organizing personal learning environment with built-in statistical surveys and statistical data processing is considered in the article. The possibilities of the statistical data collection and processing services on the example of Google Analytics are investigated.

  5. Telecontrol - Expert systems. Real-time monitoring and remote diagnostic

    Energy Technology Data Exchange (ETDEWEB)

    Lam, A.

    1996-09-01

    The role of expert systems in programming simple and complex tasks in utilities companies was discussed with examples from B.C. Hydro, where expert systems have been used in such diverse applications as an in-house programmable logic controller (PLC) training course, and a machine audit on a 150 MW steam turbine generating unit at their Burrard Thermal Generating Plant. The PLC tutoring program uses expert system technology for the air blast circuit breakers` air drier system, for individualized on-site training. The steam turbine audits (an eight-month long project) were performed remotely by dialing an on-site computer configured with customized expert software. Details of these, and other potential applications, such as transformer monitoring and diagnostics, circuit breaker performance analysis, and information management, were described.

  6. Real Time Flame Monitoring of Gasifier and Injectors

    Energy Technology Data Exchange (ETDEWEB)

    Zelepouga, Serguei; Saveliev, Alexei

    2011-12-31

    This project is a multistage effort with the final goal to develop a practical and reliable nonintrusive gasifier injector monitor to assess burner wear and need for replacement. The project team included the National Energy Technology Laboratory (NETL), Gas Technology Institute (GTI), North Carolina State University, and ConocoPhillips. This report presents the results of the sensor development and testing initially at GTI combustion laboratory with natural gas flames, then at the Canada Energy Technology Center (CANMET), Canada in the atmospheric coal combustor as well as in the pilot scale pressurized entrained flow gasifier, and finally the sensor capabilities were demonstrated at the Pratt and Whitney Rocketdyne (PWR) Gasifier and the Wabash River Repowering plant located in West Terre Haute, IN. The initial tests demonstrated that GTI gasifier sensor technology was capable of detecting shape and rich/lean properties of natural gas air/oxygen enriched air flames. The following testing at the Vertical Combustor Research Facility (VCRF) was a logical transition step from the atmospheric natural gas flames to pressurized coal gasification environment. The results of testing with atmospheric coal flames showed that light emitted by excited OH* and CH* radicals in coal/air flames can be detected and quantified. The maximum emission intensities of OH*, CH*, and black body (char combustion) occur at different axial positions along the flame length. Therefore, the excitation rates of CH* and OH* are distinct at different stages of coal combustion and can be utilized to identify and characterize processes which occur during coal combustion such as devolatilization, char heating and burning. To accomplish the goals set for Tasks 4 and 5, GTI utilized the CANMET Pressurized Entrained Flow Gasifier (PEFG). The testing parameters of the PEFG were selected to simulate optimum gasifier operation as well as gasifier conditions normally resulting from improper operation or

  7. Online, real-time corrosion monitoring in district heating systems

    DEFF Research Database (Denmark)

    Hilbert, Lisbeth Rischel; Thorarinsdottir, R.I.

    2005-01-01

    The corrosion control in district heating systems is today performed primarily with control of the water quality. The corrosion rate is kept low by assuring low dissolved oxygen concentration, high pH and low conductivity. Corrosion failures can occur, e.g. as a result of unknown oxygen ingress, ......, precipitation of deposits or crevices. The authors describe methods used for on-line monitoring of corrosion, cover the complications and the main results of a Nordic project.......The corrosion control in district heating systems is today performed primarily with control of the water quality. The corrosion rate is kept low by assuring low dissolved oxygen concentration, high pH and low conductivity. Corrosion failures can occur, e.g. as a result of unknown oxygen ingress...

  8. High-Cadence Transit Timing Variation Monitoring of Extrasolar Planets

    Directory of Open Access Journals (Sweden)

    Naef D.

    2011-02-01

    Full Text Available We report ground-based high-cadence transit timing observations of the extrasolar planet WASP-2b. We achieve a typical timing error of 15-30 sec. The data show no significant deviations from the predicted ephemeris.

  9. Advancing Continuous Predictive Analytics Monitoring: Moving from Implementation to Clinical Action in a Learning Health System.

    Science.gov (United States)

    Keim-Malpass, Jessica; Kitzmiller, Rebecca R; Skeeles-Worley, Angela; Lindberg, Curt; Clark, Matthew T; Tai, Robert; Calland, James Forrest; Sullivan, Kevin; Randall Moorman, J; Anderson, Ruth A

    2018-06-01

    In the intensive care unit, clinicians monitor a diverse array of data inputs to detect early signs of impending clinical demise or improvement. Continuous predictive analytics monitoring synthesizes data from a variety of inputs into a risk estimate that clinicians can observe in a streaming environment. For this to be useful, clinicians must engage with the data in a way that makes sense for their clinical workflow in the context of a learning health system (LHS). This article describes the processes needed to evoke clinical action after initiation of continuous predictive analytics monitoring in an LHS. Copyright © 2018 Elsevier Inc. All rights reserved.

  10. Long-term monitoring of western aspen--lessons learned.

    Science.gov (United States)

    Strand, E K; Bunting, S C; Starcevich, L A; Nahorniak, M T; Dicus, G; Garrett, L K

    2015-08-01

    Aspen woodland is an important ecosystem in the western United States. Aspen is currently declining in western mountains; stressors include conifer expansion due to fire suppression, drought, disease, heavy wildlife and livestock use, and human development. Forecasting of tree species distributions under future climate scenarios predicts severe losses of western aspen within the next 50 years. As a result, aspen has been selected as one of 14 vital signs for long-term monitoring by the National Park Service Upper Columbia Basin Network. This article describes the development of a monitoring protocol for aspen including inventory mapping, selection of sampling locations, statistical considerations, a method for accounting for spatial dependence, field sampling strategies, and data management. We emphasize the importance of collecting pilot data for use in statistical power analysis and semi-variogram analysis prior to protocol implementation. Given the spatial and temporal variability within aspen stem size classes, we recommend implementing permanent plots that are distributed spatially within and among stands. Because of our careful statistical design, we were able to detect change between sampling periods with desired confidence and power. Engaging a protocol development and implementation team with necessary and complementary knowledge and skills is critical for success. Besides the project leader, we engaged field sampling personnel, GIS specialists, statisticians, and a data management specialist. We underline the importance of frequent communication with park personnel and network coordinators.

  11. A Distance Learning Review--The Communicational Module "Learning on Demand--Anywhere at Any Time"

    Science.gov (United States)

    Tatkovic, Nevenka; Ruzic, Maja

    2004-01-01

    The society of knowledge refers to the society marked with the principle which requires that knowledge, information and life-time learning hold a key to success in the world of IT technology. Internet, World Wide Web, Web Based Education and ever so growing speed of IT and communicational technologies have enabled the application of new modes,…

  12. From feedback- to response-based performance monitoring in active and observational learning.

    Science.gov (United States)

    Bellebaum, Christian; Colosio, Marco

    2014-09-01

    Humans can adapt their behavior by learning from the consequences of their own actions or by observing others. Gradual active learning of action-outcome contingencies is accompanied by a shift from feedback- to response-based performance monitoring. This shift is reflected by complementary learning-related changes of two ACC-driven ERP components, the feedback-related negativity (FRN) and the error-related negativity (ERN), which have both been suggested to signal events "worse than expected," that is, a negative prediction error. Although recent research has identified comparable components for observed behavior and outcomes (observational ERN and FRN), it is as yet unknown, whether these components are similarly modulated by prediction errors and thus also reflect behavioral adaptation. In this study, two groups of 15 participants learned action-outcome contingencies either actively or by observation. In active learners, FRN amplitude for negative feedback decreased and ERN amplitude in response to erroneous actions increased with learning, whereas observational ERN and FRN in observational learners did not exhibit learning-related changes. Learning performance, assessed in test trials without feedback, was comparable between groups, as was the ERN following actively performed errors during test trials. In summary, the results show that action-outcome associations can be learned similarly well actively and by observation. The mechanisms involved appear to differ, with the FRN in active learning reflecting the integration of information about own actions and the accompanying outcomes.

  13. Connection with seismic networks and construction of real time earthquake monitoring system

    International Nuclear Information System (INIS)

    Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S.

    2000-12-01

    It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system

  14. Optical Real-Time Space Radiation Monitor, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Real-time dosimetry is needed to provide immediate feedback, so astronauts can minimize their exposure to ionizing radiation during periods of high solar activity....

  15. Electrophysiological Correlates of Error Monitoring and Feedback Processing in Second Language Learning.

    Science.gov (United States)

    Bultena, Sybrine; Danielmeier, Claudia; Bekkering, Harold; Lemhöfer, Kristin

    2017-01-01

    Humans monitor their behavior to optimize performance, which presumably relies on stable representations of correct responses. During second language (L2) learning, however, stable representations have yet to be formed while knowledge of the first language (L1) can interfere with learning, which in some cases results in persistent errors. In order to examine how correct L2 representations are stabilized, this study examined performance monitoring in the learning process of second language learners for a feature that conflicts with their first language. Using EEG, we investigated if L2 learners in a feedback-guided word gender assignment task showed signs of error detection in the form of an error-related negativity (ERN) before and after receiving feedback, and how feedback is processed. The results indicated that initially, response-locked negativities for correct (CRN) and incorrect (ERN) responses were of similar size, showing a lack of internal error detection when L2 representations are unstable. As behavioral performance improved following feedback, the ERN became larger than the CRN, pointing to the first signs of successful error detection. Additionally, we observed a second negativity following the ERN/CRN components, the amplitude of which followed a similar pattern as the previous negativities. Feedback-locked data indicated robust FRN and P300 effects in response to negative feedback across different rounds, demonstrating that feedback remained important in order to update memory representations during learning. We thus show that initially, L2 representations may often not be stable enough to warrant successful error monitoring, but can be stabilized through repeated feedback, which means that the brain is able to overcome L1 interference, and can learn to detect errors internally after a short training session. The results contribute a different perspective to the discussion on changes in ERN and FRN components in relation to learning, by extending the

  16. Data-driven strategies for robust forecast of continuous glucose monitoring time-series.

    Science.gov (United States)

    Fiorini, Samuele; Martini, Chiara; Malpassi, Davide; Cordera, Renzo; Maggi, Davide; Verri, Alessandro; Barla, Annalisa

    2017-07-01

    Over the past decade, continuous glucose monitoring (CGM) has proven to be a very resourceful tool for diabetes management. To date, CGM devices are employed for both retrospective and online applications. Their use allows to better describe the patients' pathology as well as to achieve a better control of patients' level of glycemia. The analysis of CGM sensor data makes possible to observe a wide range of metrics, such as the glycemic variability during the day or the amount of time spent below or above certain glycemic thresholds. However, due to the high variability of the glycemic signals among sensors and individuals, CGM data analysis is a non-trivial task. Standard signal filtering solutions fall short when an appropriate model personalization is not applied. State-of-the-art data-driven strategies for online CGM forecasting rely upon the use of recursive filters. Each time a new sample is collected, such models need to adjust their parameters in order to predict the next glycemic level. In this paper we aim at demonstrating that the problem of online CGM forecasting can be successfully tackled by personalized machine learning models, that do not need to recursively update their parameters.

  17. Assessment of Learners' Attention to E-Learning by Monitoring Facial Expressions for Computer Network Courses

    Science.gov (United States)

    Chen, Hong-Ren

    2012-01-01

    Recognition of students' facial expressions can be used to understand their level of attention. In a traditional classroom setting, teachers guide the classes and continuously monitor and engage the students to evaluate their understanding and progress. Given the current popularity of e-learning environments, it has become important to assess the…

  18. Lessons learned from nuclear power plant posttrip monitoring systems

    International Nuclear Information System (INIS)

    Barasa, W.A.

    1989-01-01

    This paper discusses a program to identify common causes of unit trips and cost-effective evaluation of the options for addressing the causes. The core of the program is a living historical data base of events, based on root-cause analysis of station-specific events, that provides a means of segregating common-cause failures from random failures. Once common-cause failures at a specific plant are identified, the payback periods of the options to address a specific unit trip cause - modification, procedural changes, or status quo - can be calculated by comparing the cost of the modifications with the cost of the lost electrical production, which is also determined from the historical data base. This paper describes how the information is developed and gives examples of how the lessons learned from previous trips can be applied to the elimination of the causes

  19. Overlay improvements using a real time machine learning algorithm

    Science.gov (United States)

    Schmitt-Weaver, Emil; Kubis, Michael; Henke, Wolfgang; Slotboom, Daan; Hoogenboom, Tom; Mulkens, Jan; Coogans, Martyn; ten Berge, Peter; Verkleij, Dick; van de Mast, Frank

    2014-04-01

    While semiconductor manufacturing is moving towards the 14nm node using immersion lithography, the overlay requirements are tightened to below 5nm. Next to improvements in the immersion scanner platform, enhancements in the overlay optimization and process control are needed to enable these low overlay numbers. Whereas conventional overlay control methods address wafer and lot variation autonomously with wafer pre exposure alignment metrology and post exposure overlay metrology, we see a need to reduce these variations by correlating more of the TWINSCAN system's sensor data directly to the post exposure YieldStar metrology in time. In this paper we will present the results of a study on applying a real time control algorithm based on machine learning technology. Machine learning methods use context and TWINSCAN system sensor data paired with post exposure YieldStar metrology to recognize generic behavior and train the control system to anticipate on this generic behavior. Specific for this study, the data concerns immersion scanner context, sensor data and on-wafer measured overlay data. By making the link between the scanner data and the wafer data we are able to establish a real time relationship. The result is an inline controller that accounts for small changes in scanner hardware performance in time while picking up subtle lot to lot and wafer to wafer deviations introduced by wafer processing.

  20. Effects of Online Synchronous Instruction with an Attention Monitoring and Alarm Mechanism on Sustained Attention and Learning Performance

    Science.gov (United States)

    Chen, Chih-Ming; Wang, Jung-Ying

    2018-01-01

    Many studies have shown that learners' sustained attention strongly affects e-learning performance, particularly during online synchronous instruction. This work thus develops a novel attention monitoring and alarm mechanism (AMAM) based on brainwave signals to improve learning performance via monitoring the attention state of individual learners…

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

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2014-11-01

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

  2. Real-Time and Secure Wireless Health Monitoring

    Science.gov (United States)

    Dağtaş, S.; Pekhteryev, G.; Şahinoğlu, Z.; Çam, H.; Challa, N.

    2008-01-01

    We present a framework for a wireless health monitoring system using wireless networks such as ZigBee. Vital signals are collected and processed using a 3-tiered architecture. The first stage is the mobile device carried on the body that runs a number of wired and wireless probes. This device is also designed to perform some basic processing such as the heart rate and fatal failure detection. At the second stage, further processing is performed by a local server using the raw data transmitted by the mobile device continuously. The raw data is also stored at this server. The processed data as well as the analysis results are then transmitted to the service provider center for diagnostic reviews as well as storage. The main advantages of the proposed framework are (1) the ability to detect signals wirelessly within a body sensor network (BSN), (2) low-power and reliable data transmission through ZigBee network nodes, (3) secure transmission of medical data over BSN, (4) efficient channel allocation for medical data transmission over wireless networks, and (5) optimized analysis of data using an adaptive architecture that maximizes the utility of processing and computational capacity at each platform. PMID:18497866

  3. [Design and implementation of real-time continuous glucose monitoring instrument].

    Science.gov (United States)

    Huang, Yonghong; Liu, Hongying; Tian, Senfu; Jia, Ziru; Wang, Zi; Pi, Xitian

    2017-12-01

    Real-time continuous glucose monitoring can help diabetics to control blood sugar levels within the normal range. However, in the process of practical monitoring, the output of real-time continuous glucose monitoring system is susceptible to glucose sensor and environment noise, which will influence the measurement accuracy of the system. Aiming at this problem, a dual-calibration algorithm for the moving-window double-layer filtering algorithm combined with real-time self-compensation calibration algorithm is proposed in this paper, which can realize the signal drift compensation for current data. And a real-time continuous glucose monitoring instrument based on this study was designed. This real-time continuous glucose monitoring instrument consisted of an adjustable excitation voltage module, a current-voltage converter module, a microprocessor and a wireless transceiver module. For portability, the size of the device was only 40 mm × 30 mm × 5 mm and its weight was only 30 g. In addition, a communication command code algorithm was designed to ensure the security and integrity of data transmission in this study. Results of experiments in vitro showed that current detection of the device worked effectively. A 5-hour monitoring of blood glucose level in vivo showed that the device could continuously monitor blood glucose in real time. The relative error of monitoring results of the designed device ranged from 2.22% to 7.17% when comparing to a portable blood meter.

  4. Analysis of Land Subsidence Monitoring in Mining Area with Time-Series Insar Technology

    Science.gov (United States)

    Sun, N.; Wang, Y. J.

    2018-04-01

    Time-series InSAR technology has become a popular land subsidence monitoring method in recent years, because of its advantages such as high accuracy, wide area, low expenditure, intensive monitoring points and free from accessibility restrictions. In this paper, we applied two kinds of satellite data, ALOS PALSAR and RADARSAT-2, to get the subsidence monitoring results of the study area in two time periods by time-series InSAR technology. By analyzing the deformation range, rate and amount, the time-series analysis of land subsidence in mining area was realized. The results show that InSAR technology could be used to monitor land subsidence in large area and meet the demand of subsidence monitoring in mining area.

  5. Real-time continuous nitrate monitoring in Illinois in 2013

    Science.gov (United States)

    Warner, Kelly L.; Terrio, Paul J.; Straub, Timothy D.; Roseboom, Donald; Johnson, Gary P.

    2013-01-01

    Many sources contribute to the nitrogen found in surface water in Illinois. Illinois is located in the most productive agricultural area in the country, and nitrogen fertilizer is commonly used to maximize corn production in this area. Additionally, septic/wastewater systems, industrial emissions, and lawn fertilizer are common sources of nitrogen in urban areas of Illinois. In agricultural areas, the use of fertilizer has increased grain production to meet the needs of a growing population, but also has resulted in increases in nitrogen concentrations in many streams and aquifers (Dubrovsky and others, 2010). The urban sources can increase nitrogen concentrations, too. The Federal limit for nitrate nitrogen in water that is safe to drink is 10 milligrams per liter (mg/L) (http://water.epa.gov/drink/contaminants/basicinformation/nitrate.cfm, accessed on May 24, 2013). In addition to the concern with nitrate nitrogen in drinking water, nitrogen, along with phosphorus, is an aquatic concern because it feeds the intensive growth of algae that are responsible for the hypoxic zone in the Gulf of Mexico. The largest nitrogen flux to the waters feeding the Gulf of Mexico is from Illinois (Alexander and others, 2008). Most studies of nitrogen in surface water and groundwater include samples for nitrate nitrogen collected weekly or monthly, but nitrate concentrations can change rapidly and these discrete samples may not capture rapid changes in nitrate concentrations that can affect human and aquatic health. Continuous monitoring for nitrate could inform scientists and water-resource managers of these changes and provide information on the transport of nitrate in surface water and groundwater.

  6. Combining monitoring with run-time assertion checking

    NARCIS (Netherlands)

    Gouw, Stijn de

    2013-01-01

    We develop a new technique for Run-time Checking for two object-oriented languages: Java and the Abstract Behavioral Specification language ABS. In object-oriented languages, objects communicate by sending each other messages. Assuming encapsulation, the behavior of objects is completely

  7. Real-time bus location monitoring using Arduino

    Science.gov (United States)

    Ibrahim, Mohammad Y. M.; Audah, Lukman

    2017-09-01

    The Internet of Things (IoT) is the network of objects, such as a vehicles, mobile devices, and buildings that have electronic components, software, and network connectivity that enable them to collect data, run commands, and be controlled through the Internet. Controlling physical items from the Internet will increase efficiency and save time. The growing number of devices used by people increases the practicality of having IoT devices on the market. The IoT is also an opportunity to develop products that can save money and time and increase work efficiency. Initially, they need more efficiency for real-time bus location systems, especially in university campuses. This system can easily find the accurate locations of and distances between each bus stop and the estimated time to reach a new location. This system has been separated into two parts, which are the hardware and the software. The hardware parts are the Arduino Uno and the Global Positioning System (GPS), while Google Earth and GpsGate are the software parts. The GPS continuously takes input data from the satellite and stores the latitude and longitude values in the Arduino Uno. If we want to track the vehicle, we need to send the longitude and latitude as a message to the Google Earth software to convert these into maps for navigation. Once the Arduino Uno is activated, it takes the last received latitude and longitude positions' values from GpsGate and sends a message to Google Earth. Once the message has been sent to Google Earth, the current location will be shown, and navigation will be activated automatically. Then it will be broadcast using ManyCam, Google+ Hangouts, and YouTube, as well as Facebook, and appear to users. The additional features use Google Forms for determining problems faced by students, who can also take immediate action against the responsible department. Then after several successful simulations, the results will be shown in real time on a map.

  8. The Negative Impact of Community Stressors on Learning Time: Examining Inequalities between California High Schools

    Science.gov (United States)

    Mirra, Nicole; Rogers, John

    2015-01-01

    Allocated classroom time is not the same as time available for learning--a host of economic and social stressors undermine learning time in schools serving low-income students. When time is limited, it is hard to meet rigorous learning standards. The challenge is compounded in high-poverty schools where community stressors place additional demands…

  9. Real-time alpha monitoring of a radioactive liquid waste stream at Los Alamos National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, J.D.; Whitley, C.R.; Rawool-Sullivan, M. [Los Alamos National Lab., NM (United States)

    1995-12-31

    This poster display concerns the development, installation, and testing of a real-time radioactive liquid waste monitor at Los Alamos National Laboratory (LANL). The detector system was designed for the LANL Radioactive Liquid Waste Treatment Facility so that influent to the plant could be monitored in real time. By knowing the activity of the influent, plant operators can better monitor treatment, better segregate waste (potentially), and monitor the regulatory compliance of users of the LANL Radioactive Liquid Waste Collection System. The detector system uses long-range alpha detection technology, which is a nonintrusive method of characterization that determines alpha activity on the liquid surface by measuring the ionization of ambient air. Extensive testing has been performed to ensure long-term use with a minimal amount of maintenance. The final design was a simple cost-effective alpha monitor that could be modified for monitoring influent waste streams at various points in the LANL Radioactive Liquid Waste Collection System.

  10. What time is it? Deep learning approaches for circadian rhythms.

    Science.gov (United States)

    Agostinelli, Forest; Ceglia, Nicholas; Shahbaba, Babak; Sassone-Corsi, Paolo; Baldi, Pierre

    2016-06-15

    Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken. We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic signals. We then use deep learning methods to develop and train BIO_CYCLE, a system to robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. Using the curated data, BIO_CYCLE is compared to other approaches and shown to achieve state-of-the-art performance across multiple metrics. We then use deep learning methods to develop and train BIO_CLOCK to robustly estimate the time at which a particular single-time-point transcriptomic experiment was carried. In most cases, BIO_CLOCK can reliably predict time, within approximately 1 h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is shown to work reasonably well across tissue types, and often with only small degradation across conditions. BIO_CLOCK is used to annotate most mouse experiments found in the GEO database with an inferred time stamp. All data and software are publicly available on the CircadiOmics web portal: circadiomics.igb.uci.edu/ fagostin@uci.edu or pfbaldi@uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  11. Real-time earthquake monitoring using a search engine method.

    Science.gov (United States)

    Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong

    2014-12-04

    When an earthquake occurs, seismologists want to use recorded seismograms to infer its location, magnitude and source-focal mechanism as quickly as possible. If such information could be determined immediately, timely evacuations and emergency actions could be undertaken to mitigate earthquake damage. Current advanced methods can report the initial location and magnitude of an earthquake within a few seconds, but estimating the source-focal mechanism may require minutes to hours. Here we present an earthquake search engine, similar to a web search engine, that we developed by applying a computer fast search method to a large seismogram database to find waveforms that best fit the input data. Our method is several thousand times faster than an exact search. For an Mw 5.9 earthquake on 8 March 2012 in Xinjiang, China, the search engine can infer the earthquake's parameters in <1 s after receiving the long-period surface wave data.

  12. Development of Real-Time Coal Monitoring Instrument

    Energy Technology Data Exchange (ETDEWEB)

    Rajan Gurjar, Ph.D.

    2010-06-17

    Relying on coal for energy requires optimizing the extraction of heat content from various blends of coal fuel and reducing harmful constituents and byproducts. Having a real-time measurement instrument provides relevant information about toxic constituents released in the atmosphere from burning coal and optimizes the performance of a power plant. A few commercial instruments exist and have been in operation for more than a decade. However, most of these instruments are based on radioactive sources and are bulky, expensive and time-consuming. The proposed instrument is based on the Laser Induced Breakdown Spectroscopy (LIBS). The advantage of LIBS is that it is a standoff instrument, does not require sample preparation and provides precise information about sample constituents.

  13. Real-Time Earthquake Monitoring with Spatio-Temporal Fields

    Science.gov (United States)

    Whittier, J. C.; Nittel, S.; Subasinghe, I.

    2017-10-01

    With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth's movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

  14. Time and data synchronization methods in competition monitoring systems

    OpenAIRE

    Kerys, Julijus

    2005-01-01

    Information synchronization problems are analyzed in this thesis. Two aspects are being surveyed – clock synchronization, algorithms and their use, and data synchronization and maintaining the functionality of software at the times, when connection with database is broken. Existing products, their uses, cons and pros are overviewed. There are suggested models, how to solve these problems, which were implemented in “Distributed basketball competition registration and analysis software system”,...

  15. Ultrafast chiroptical spectroscopy: Monitoring optical activity in quick time

    Directory of Open Access Journals (Sweden)

    Hanju Rhee

    2011-12-01

    Full Text Available Optical activity spectroscopy provides rich structural information of biologically important molecules in condensed phases. However, a few intrinsic problems of conventional method based on electric field intensity measurement scheme prohibited its extension to time domain technique. We have recently developed new types of optical activity spectroscopic methods capable of measuring chiroptical signals with femtosecond pulses. It is believed that these novel approaches will be applied to a variety of ultrafast chiroptical studies.

  16. Arbitrage, market definition and monitoring a time series approach

    OpenAIRE

    Burke, S; Hunter, J

    2012-01-01

    This article considers the application to regional price data of time series methods to test stationarity, multivariate cointegration and exogeneity. The discovery of stationary price differentials in a bivariate setting implies that the series are rendered stationary by capturing a common trend and we observe through this mechanism long-run arbitrage. This is indicative of a broader market definition and efficiency. The problem is considered in relation to more than 700 weekly data points on...

  17. Ensemble Deep Learning for Biomedical Time Series Classification

    Directory of Open Access Journals (Sweden)

    Lin-peng Jin

    2016-01-01

    Full Text Available Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.

  18. An elapsed time-temperature monitor for blood storage.

    Science.gov (United States)

    Harris, G E; Cloud, S; Myhre, B A

    1977-01-01

    Blood should not be allowed to exceed 10 C while being stored or transported. However, one cannot test the internal temperature of a unit of blood without contaminating it. Most blood banks have established an arbitrary time limit beyond which a blood unit cannot be kept out of the refrigerator. This method is ineffective if blood is stored in a satellite refrigerator, since the blood may be moved in and out of the refrigerator and the blood bank personnel will be unaware of it. An elapsed time indicator is described which employs a small condenser (E-Cell-Plessey Electronics) charged with a known amount of electricity. If the device is removed from the refrigerator, it begins to discharge at a known rate. The amount of time subsequently can be determined by the loss of charge. The prototype of this instrument has been found to be quite accurate and small (2 inches X 2 inches X 1 inch). It would be rather inexpensive if made in considerable numbers.

  19. Real-time diesel particulate monitor for underground mines.

    Science.gov (United States)

    Noll, James; Janisko, Samuel; Mischler, Steven E

    The standard method for determining diesel particulate matter (DPM) exposures in underground metal/ nonmetal mines provides the average exposure concentration for an entire working shift, and several weeks might pass before results are obtained. The main problem with this approach is that it only indicates that an overexposure has occurred rather than providing the ability to prevent an overexposure or detect its cause. Conversely, real-time measurement would provide miners with timely information to allow engineering controls to be deployed immediately and to identify the major factors contributing to any overexposures. Toward this purpose, the National Institute for Occupational Safety and Health (NIOSH) developed a laser extinction method to measure real-time elemental carbon (EC) concentrations (EC is a DPM surrogate). To employ this method, NIOSH developed a person-wearable instrument that was commercialized in 2011. This paper evaluates this commercial instrument, including the calibration curve, limit of detection, accuracy, and potential interferences. The instrument was found to meet the NIOSH accuracy criteria and to be capable of measuring DPM concentrations at levels observed in underground mines. In addition, it was found that a submicron size selector was necessary to avoid interference from mine dust and that cigarette smoke can be an interference when sampling in enclosed cabs.

  20. Evidence for an alternation strategy in time-place learning.

    Science.gov (United States)

    Pizzo, Matthew J; Crystal, Jonathon D

    2004-11-30

    Many different conclusions concerning what type of mechanism rats use to solve a daily time-place task have emerged in the literature. The purpose of this study was to test three competing explanations of time-place discrimination. Rats (n = 10) were tested twice daily in a T-maze, separated by approximately 7 h. Food was available at one location in the morning and another location in the afternoon. After the rats learned to visit each location at the appropriate time, tests were omitted to evaluate whether the rats were utilizing time-of-day (i.e., a circadian oscillator) or an alternation strategy (i.e., visiting a correct location is a cue to visit the next location). Performance on this test was significantly lower than chance, ruling out the use of time-of-day. A phase advance of the light cycle was conducted to test the alternation strategy and timing with respect to the light cycle (i.e., an interval timer). There was no difference between probe and baseline performance. These results suggest that the rats used an alternation strategy to meet the temporal and spatial contingencies in the time-place task.

  1. A real-time intercepting beam-profile monitor for a medical cyclotron

    Energy Technology Data Exchange (ETDEWEB)

    Hendriks, C.; Uittenbosch, T.; Cameron, D.; Kellogg, S.; Gray, D.; Buckley, K.; Schaffer, P.; Verzilov, V.; Hoehr, C. [TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T 2A3 (Canada)

    2013-11-15

    There is a lack of real-time continuous beam-diagnostic tools for medical cyclotrons due to high power deposition during proton irradiation. To overcome this limitation, we have developed a profile monitor that is capable of providing continuous feedback about beam shape and current in real time while it is inserted in the beam path. This enables users to optimize the beam profile and observe fluctuations in the beam over time with periodic insertion of the monitor.

  2. Monitoring and Acquisition Real-time System (MARS)

    Science.gov (United States)

    Holland, Corbin

    2013-01-01

    MARS is a graphical user interface (GUI) written in MATLAB and Java, allowing the user to configure and control the Scalable Parallel Architecture for Real-Time Acquisition and Analysis (SPARTAA) data acquisition system. SPARTAA not only acquires data, but also allows for complex algorithms to be applied to the acquired data in real time. The MARS client allows the user to set up and configure all settings regarding the data channels attached to the system, as well as have complete control over starting and stopping data acquisition. It provides a unique "Test" programming environment, allowing the user to create tests consisting of a series of alarms, each of which contains any number of data channels. Each alarm is configured with a particular algorithm, determining the type of processing that will be applied on each data channel and tested against a defined threshold. Tests can be uploaded to SPARTAA, thereby teaching it how to process the data. The uniqueness of MARS is in its capability to be adaptable easily to many test configurations. MARS sends and receives protocols via TCP/IP, which allows for quick integration into almost any test environment. The use of MATLAB and Java as the programming languages allows for developers to integrate the software across multiple operating platforms.

  3. Dynamic Modeling and Real-Time Monitoring of Froth Flotation

    Directory of Open Access Journals (Sweden)

    Khushaal Popli

    2015-08-01

    Full Text Available A dynamic fundamental model was developed linking processes from the microscopic scale to the equipment scale for batch froth flotation. State estimation, fault detection, and disturbance identification were implemented using the extended Kalman filter (EKF, which reconciles real-time measurements with dynamic models. The online measurements for the EKF were obtained through image analysis of froth images that were captured and analyzed using the commercial package VisioFroth (Metsor Minerals. The extracted image features were then correlated to recovery using principal component analysis and partial least squares regression. The performance of real-time state estimation and fault detection was validated using batch flotation of pure galena at various operating conditions. The image features that were strongly representative of recovery were identified, and calibration and validation were performed against off-line measurements of recovery. The EKF successfully captured the dynamics of the process by updating the model states and parameters using the online measurements. Finally, disturbances in the air flow rate and impeller speed were introduced into the system, and the dynamic behavior of the flotation process was successfully tracked and the disturbances were identified using state estimation.

  4. Unmanned airborne system in real-time radiological monitoring

    International Nuclear Information System (INIS)

    Zafrir, H.; Pernick, A.; Yaffe, U.; Grushka, A.

    1993-01-01

    The unmanned airborne vehicle (UAV) platform, equipped with an appropriate payload and capable of carrying a variety of modular sensors, is an effective tool for real-time control of environmental disasters of different types (e.g. nuclear or chemical accidents). The suggested payloads consist of a miniaturised self-collimating nuclear spectrometry sensor and electro-optical sensors for day and night imagery. The system provides means of both real-time field data acquisition in an endangered environment and on-line hazard assessment computation from the down link raw data. All the processing, including flight planning using an expert system, is performed by a dedicated microcomputer located in a Mobile Ground Control Station (MGCS) situated outside the hazardous area. The UAV equipment is part of a system designed especially for the critically important early phase of emergency response. Decisions by the Emergency Response Manager (ERM) are also based on the ability to estimate the potential dose to individuals and the mitigation of dose when protection measures are implemented. (author)

  5. Real-time long term measurement using integrated framework for ubiquitous smart monitoring

    Science.gov (United States)

    Heo, Gwanghee; Lee, Giu; Lee, Woosang; Jeon, Joonryong; Kim, Pil-Joong

    2007-04-01

    Ubiquitous monitoring combining internet technologies and wireless communication is one of the most promising technologies of infrastructure health monitoring against the natural of man-made hazards. In this paper, an integrated framework of the ubiquitous monitoring is developed for real-time long term measurement in internet environment. This framework develops a wireless sensor system based on Bluetooth technology and sends measured acceleration data to the host computer through TCP/IP protocol. And it is also designed to respond to the request of web user on real time basis. In order to verify this system, real time monitoring tests are carried out on a prototype self-anchored suspension bridge. Also, wireless measurement system is analyzed to estimate its sensing capacity and evaluate its performance for monitoring purpose. Based on the evaluation, this paper proposes the effective strategies for integrated framework in order to detect structural deficiencies and to design an early warning system.

  6. Cloud Computing: A model Construct of Real-Time Monitoring for Big Dataset Analytics Using Apache Spark

    Science.gov (United States)

    Alkasem, Ameen; Liu, Hongwei; Zuo, Decheng; Algarash, Basheer

    2018-01-01

    The volume of data being collected, analyzed, and stored has exploded in recent years, in particular in relation to the activity on the cloud computing. While large-scale data processing, analysis, storage, and platform model such as cloud computing were previously and currently are increasingly. Today, the major challenge is it address how to monitor and control these massive amounts of data and perform analysis in real-time at scale. The traditional methods and model systems are unable to cope with these quantities of data in real-time. Here we present a new methodology for constructing a model for optimizing the performance of real-time monitoring of big datasets, which includes a machine learning algorithms and Apache Spark Streaming to accomplish fine-grained fault diagnosis and repair of big dataset. As a case study, we use the failure of Virtual Machines (VMs) to start-up. The methodology proposition ensures that the most sensible action is carried out during the procedure of fine-grained monitoring and generates the highest efficacy and cost-saving fault repair through three construction control steps: (I) data collection; (II) analysis engine and (III) decision engine. We found that running this novel methodology can save a considerate amount of time compared to the Hadoop model, without sacrificing the classification accuracy or optimization of performance. The accuracy of the proposed method (92.13%) is an improvement on traditional approaches.

  7. Inaccurate Metacognitive Monitoring and Its Effects on Metacognitive Control and Task Outcomes in Self-Regulated L2 Learning

    Science.gov (United States)

    Ranalli, Jim

    2018-01-01

    Accurate metacognitive monitoring of one's own knowledge or performance is a precondition for self-regulated learning; monitoring informs metacognitive control, which in turn affects task outcomes. Studies of monitoring accuracy and its connection to knowledge and performance are common in psychology and educational research but rare in instructed…

  8. Supernova real-time monitor system in Kamiokande

    International Nuclear Information System (INIS)

    Oyama, Y.; Yamada, M.; Ishida, T.; Yamaguchi, T.; Yokoyama, H.

    1994-01-01

    A data-analysis program to discover possible supernova neutrino bursts has been installed in the online data-acquisition computer of the Kamiokande experiment. The program automatically analyzes data within 20 min and gives an alarm to collaborators if a possible supernova neutrino burst is found. The detection efficiency of the program is 96% for a typical supernova located 50 kpc from Earth. After a careful analysis by the Kamiokande collaborators, it will be possible to inform all optical observatories in the world about the occurrence of a supernova within 3 h from the time of first detecting the neutrino burst. Information concerning the celestial position of a supernova will also be available for supernovae having a distance less than ∼ 10 kpc. This information will be helpful for observing the first optical emissions from the newly born supernova. (orig.)

  9. Uncertainty analysis of power monitoring transit time ultrasonic flow meters

    International Nuclear Information System (INIS)

    Orosz, A.; Miller, D. W.; Christensen, R. N.; Arndt, S.

    2006-01-01

    A general uncertainty analysis is applied to chordal, transit time ultrasonic flow meters that are used in nuclear power plant feedwater loops. This investigation focuses on relationships between the major parameters of the flow measurement. For this study, mass flow rate is divided into three components, profile factor, density, and a form of volumetric flow rate. All system parameters are used to calculate values for these three components. Uncertainty is analyzed using a perturbation method. Sensitivity coefficients for major system parameters are shown, and these coefficients are applicable to a range of ultrasonic flow meters used in similar applications. Also shown is the uncertainty to be expected for density along with its relationship to other system uncertainties. One other conclusion is that pipe diameter sensitivity coefficients may be a function of the calibration technique used. (authors)

  10. Causes and consequences of timing errors associated with global positioning system collar accelerometer activity monitors

    Science.gov (United States)

    Adam J. Gaylord; Dana M. Sanchez

    2014-01-01

    Direct behavioral observations of multiple free-ranging animals over long periods of time and large geographic areas is prohibitively difficult. However, recent improvements in technology, such as Global Positioning System (GPS) collars equipped with motion-sensitive activity monitors, create the potential to remotely monitor animal behavior. Accelerometer-equipped...

  11. Design and implementation of an interactive web-based near real-time forest monitoring system

    NARCIS (Netherlands)

    Pratihast, Arun Kumar; Vries, de Ben; Avitabile, Valerio; Bruin, De Sytze; Herold, Martin; Bergsma, Aldo

    2016-01-01

    This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection

  12. Deep Learning versus Professional Healthcare Equipment: A Fine-Grained Breathing Rate Monitoring Model

    Directory of Open Access Journals (Sweden)

    Bang Liu

    2018-01-01

    Full Text Available In mHealth field, accurate breathing rate monitoring technique has benefited a broad array of healthcare-related applications. Many approaches try to use smartphone or wearable device with fine-grained monitoring algorithm to accomplish the task, which can only be done by professional medical equipment before. However, such schemes usually result in bad performance in comparison to professional medical equipment. In this paper, we propose DeepFilter, a deep learning-based fine-grained breathing rate monitoring algorithm that works on smartphone and achieves professional-level accuracy. DeepFilter is a bidirectional recurrent neural network (RNN stacked with convolutional layers and speeded up by batch normalization. Moreover, we collect 16.17 GB breathing sound recording data of 248 hours from 109 and another 10 volunteers to train and test our model, respectively. The results show a reasonably good accuracy of breathing rate monitoring.

  13. The Impact of Students' Temporal Perspectives on Time-on-Task and Learning Performance in Game Based Learning

    Science.gov (United States)

    Romero, Margarida; Usart, Mireia

    2013-01-01

    The use of games for educational purposes has been considered as a learning methodology that attracts the students' attention and may allow focusing individuals on the learning activity through the [serious games] SG game dynamic. Based on the hypothesis that students' Temporal Perspective has an impact on learning performance and time-on-task,…

  14. Time resolved aerosol monitoring in the urban centre of Soweto

    Science.gov (United States)

    Formenti, P.; Annegarn, H. J.; Piketh, S. J.

    1998-03-01

    A programme of aerosol sampling was conducted from 1982 to 1984 in the urban area of Soweto, Johannesburg, South Africa. The particulate matter (aerodynamic diameter source apportionment of crustal elements between coal smoke and traffic induced road dust, based on chemical elemental measurements. A novel technique is demonstrated for processing PIXE-derived time sequence elemental concentration vectors. Slowly varying background components have been extracted from sulphur and crustal aerosol components, using alternatively two digital filters: a moving minimum, and a moving average. The residuals of the crustal elements, assigned to locally generated aerosol components, were modelled using surrogate tracers: sulphur as a surrogate for coal smoke; and Pb as a surrogate for traffic activity. Results from this source apportionment revealed coal emissions contributed between 40% and 50% of the aerosol mineral matter, while 18-22% originated from road dust. Background aerosol, characteristic of the regional winter aerosol burden over the South African Highveld, was between 12% and 21%. Minor contributors identified included a manganese smelter, located 30 km from the sampling site, and informal trash burning, as the source of intermittent heavy metals (Cu, Zn). Elemental source profiles derived for these various sources are presented.

  15. Monitoring of historical frescoes by timed infrared imaging analysis

    Science.gov (United States)

    Cadelano, G.; Bison, P.; Bortolin, A.; Ferrarini, G.; Peron, F.; Girotto, M.; Volinia, M.

    2015-03-01

    The subflorescence and efflorescence phenomena are widely acknowledged as the major causes of permanent damage to fresco wall paintings. They are related to the occurrence of cycles of dry/wet conditions inside the walls. Therefore, it is essential to identify the presence of water on the decorated surfaces and inside the walls. Nondestructive testing in industrial applications have confirmed that active infrared thermography with continuous timed images acquisition can improve the outcomes of thermal analysis aimed to moisture identification. In spite of that, in cultural heritage investigations these techniques have not been yet used extensively on a regular basis. This paper illustrates an application of these principles in order to evaluate the decay of fresco mural paintings in a medieval chapel located in North-West of Italy. One important feature of this study is the use of a robotic system called aIRview that can be utilized to automatically acquire and process thermal images. Multiple accurate thermal views of the inside walls of the building have been produced in a survey that lasted several days. Signal processing algorithms based on Fast Fourier Transform analysis have been applied to the acquired data in order to formulate trustworthy hypotheses about the deterioration mechanisms.

  16. Learning the language of time: Children's acquisition of duration words.

    Science.gov (United States)

    Tillman, Katharine A; Barner, David

    2015-05-01

    Children use time words like minute and hour early in development, but take years to acquire their precise meanings. Here we investigate whether children assign meaning to these early usages, and if so, how. To do this, we test their interpretation of seven time words: second, minute, hour, day, week, month, and year. We find that preschoolers infer the orderings of time words (e.g., hour>minute), but have little to no knowledge of the absolute durations they encode. Knowledge of absolute duration is learned much later in development - many years after children first start using time words in speech - and in many children does not emerge until they have acquired formal definitions for the words. We conclude that associating words with the perception of duration does not come naturally to children, and that early intuitive meanings of time words are instead rooted in relative orderings, which children may infer from their use in speech. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. The Earth Observation Monitor - Automated monitoring and alerting for spatial time-series data based on OGC web services

    Science.gov (United States)

    Eberle, J.; Hüttich, C.; Schmullius, C.

    2014-12-01

    Spatial time series data are freely available around the globe from earth observation satellites and meteorological stations for many years until now. They provide useful and important information to detect ongoing changes of the environment; but for end-users it is often too complex to extract this information out of the original time series datasets. This issue led to the development of the Earth Observation Monitor (EOM), an operational framework and research project to provide simple access, analysis and monitoring tools for global spatial time series data. A multi-source data processing middleware in the backend is linked to MODIS data from Land Processes Distributed Archive Center (LP DAAC) and Google Earth Engine as well as daily climate station data from NOAA National Climatic Data Center. OGC Web Processing Services are used to integrate datasets from linked data providers or external OGC-compliant interfaces to the EOM. Users can either use the web portal (webEOM) or the mobile application (mobileEOM) to execute these processing services and to retrieve the requested data for a given point or polygon in userfriendly file formats (CSV, GeoTiff). Beside providing just data access tools, users can also do further time series analyses like trend calculations, breakpoint detections or the derivation of phenological parameters from vegetation time series data. Furthermore data from climate stations can be aggregated over a given time interval. Calculated results can be visualized in the client and downloaded for offline usage. Automated monitoring and alerting of the time series data integrated by the user is provided by an OGC Sensor Observation Service with a coupled OGC Web Notification Service. Users can decide which datasets and parameters are monitored with a given filter expression (e.g., precipitation value higher than x millimeter per day, occurrence of a MODIS Fire point, detection of a time series anomaly). Datasets integrated in the SOS service are

  18. CONCEPT AND STRUCTURE OF AUTOMATED SYSTEM FOR MONITORING STUDENT LEARNING QUALITY

    Directory of Open Access Journals (Sweden)

    M. Yu. Kataev

    2017-01-01

    organization and management of the learning process in a higher educational institution. The factors that affect the level of student knowledge obtained during training are shown. On this basis, the determining factors in assessing the level of knowledge are highlighted. It is offered to build the managing of individual training at any time interval on the basis of a calculation of the generalized criterion which consists of students’ current progress, their activity and time spent for training.The block structure of the automated program system of continuous monitoring of achievements of each student is described. All functional blocks of system are interconnected with educational process. The main advantage of this system is that students have continuous access to materials about own individual achievements and mistakes; from passive consumers of information they turn into active members of the education, and thus, they can achieve bigger effectiveness of personal vocational training. It is pointed out that information base of such system has to be available not only to students and teachers, but also future employers of university graduates.Practical significance. The concept of automated system for education results monitoring and technique of processing of collected material presented in the article are based on a simple and obvious circumstance: a student with high progress spends more time on training and leads active lifestyle in comparison with fellow students; therefore, that student with high probability will be more successful in the chosen profession. Thus, for ease of use, complete, fully detailed and digitized information on individual educational achievements of future expert is necessary not only for effective management of educational process in higher education institutions, but also for employers interested in well-prepared, qualified and hard-working staff intended to take responsibility for labour duties.

  19. Real time observation system for monitoring environmental impact on marine ecosystems from oil drilling operations.

    Science.gov (United States)

    Godø, Olav Rune; Klungsøyr, Jarle; Meier, Sonnich; Tenningen, Eirik; Purser, Autun; Thomsen, Laurenz

    2014-07-15

    Environmental awareness and technological advances has spurred development of new monitoring solutions for the petroleum industry. This paper presents experience from a monitoring program off Norway. To maintain operation within the limits of the government regulations Statoil tested a new monitoring concept. Multisensory data were cabled to surface buoys and transmitted to land via wireless communication. The system collected information about distribution of the drilling wastes and the welfare of the corals in relation to threshold values. The project experienced a series of failures, but the backup monitoring provided information to fulfil the requirements of the permit. The experience demonstrated the need for real time monitoring and how such systems enhance understanding of impacts on marine organisms. Also, drilling operations may improve by taking environmental information into account. The paper proposes to standardize and streamline monitoring protocols to maintain comparability during all phases of the operation and between drill sites. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Sitting Posture Monitoring System Based on a Low-Cost Load Cell Using Machine Learning

    Directory of Open Access Journals (Sweden)

    Jongryun Roh

    2018-01-01

    Full Text Available Sitting posture monitoring systems (SPMSs help assess the posture of a seated person in real-time and improve sitting posture. To date, SPMS studies reported have required many sensors mounted on the backrest plate and seat plate of a chair. The present study, therefore, developed a system that measures a total of six sitting postures including the posture that applied a load to the backrest plate, with four load cells mounted only on the seat plate. Various machine learning algorithms were applied to the body weight ratio measured by the developed SPMS to identify the method that most accurately classified the actual sitting posture of the seated person. After classifying the sitting postures using several classifiers, average and maximum classification rates of 97.20% and 97.94%, respectively, were obtained from nine subjects with a support vector machine using the radial basis function kernel; the results obtained by this classifier showed a statistically significant difference from the results of multiple classifications using other classifiers. The proposed SPMS was able to classify six sitting postures including the posture with loading on the backrest and showed the possibility of classifying the sitting posture even though the number of sensors is reduced.

  1. Hierarchical Meta-Learning in Time Series Forecasting for Improved Interference-Less Machine Learning

    Directory of Open Access Journals (Sweden)

    David Afolabi

    2017-11-01

    Full Text Available The importance of an interference-less machine learning scheme in time series prediction is crucial, as an oversight can have a negative cumulative effect, especially when predicting many steps ahead of the currently available data. The on-going research on noise elimination in time series forecasting has led to a successful approach of decomposing the data sequence into component trends to identify noise-inducing information. The empirical mode decomposition method separates the time series/signal into a set of intrinsic mode functions ranging from high to low frequencies, which can be summed up to reconstruct the original data. The usual assumption that random noises are only contained in the high-frequency component has been shown not to be the case, as observed in our previous findings. The results from that experiment reveal that noise can be present in a low frequency component, and this motivates the newly-proposed algorithm. Additionally, to prevent the erosion of periodic trends and patterns within the series, we perform the learning of local and global trends separately in a hierarchical manner which succeeds in detecting and eliminating short/long term noise. The algorithm is tested on four datasets from financial market data and physical science data. The simulation results are compared with the conventional and state-of-the-art approaches for time series machine learning, such as the non-linear autoregressive neural network and the long short-term memory recurrent neural network, respectively. Statistically significant performance gains are recorded when the meta-learning algorithm for noise reduction is used in combination with these artificial neural networks. For time series data which cannot be decomposed into meaningful trends, applying the moving average method to create meta-information for guiding the learning process is still better than the traditional approach. Therefore, this new approach is applicable to the forecasting

  2. Assessment of the usability of a digital learning technology prototype for monitoring intracranial pressure

    Directory of Open Access Journals (Sweden)

    Lilian Regina de Carvalho

    Full Text Available ABSTRACT Objective: to assess the usability of a digital learning technology prototype as a new method for minimally invasive monitoring of intracranial pressure. Method: descriptive study using a quantitative approach on assessing the usability of a prototype based on Nielsen's ten heuristics. Four experts in the area of Human-Computer interaction participated in the study. Results: the evaluation delivered eight violated heuristics and 31 usability problems in the 32 screens of the prototype. Conclusion: the suggestions of the evaluators were critical for developing an intuitive, user-friendly interface and will be included in the final version of the digital learning technology.

  3. Real-time stress monitoring of highway bridges with a secured wireless sensor network.

    Science.gov (United States)

    2011-12-01

    "This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...

  4. Time Reversal Acoustic Structural Health Monitoring Using Array of Embedded Sensors, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Time Reversal Acoustic (TRA) structural health monitoring with an embedded sensor array represents a new approach to in-situ nondestructive evaluation of air-space...

  5. Optimized Scheduling of Smart Meter Data Access for Real-time Voltage Quality Monitoring

    DEFF Research Database (Denmark)

    Kemal, Mohammed Seifu; Olsen, Rasmus Løvenstein; Schwefel, Hans-Peter

    2018-01-01

    Abstract—Active low-voltage distribution grids that support high integration of distributed generation such as photovoltaics and wind turbines require real-time voltage monitoring. At the same time, countries in Europe such as Denmark have close to 100% rollout of smart metering infrastructure....... The metering infrastructure has limitations to provide real-time measurements with small-time granularity. This paper presents an algorithm for optimized scheduling of smart meter data access to provide real-time voltage quality monitoring. The algorithm is analyzed using a real distribution grid in Denmark...

  6. A Machine-Learning and Filtering Based Data Assimilation Framework for Geologic Carbon Sequestration Monitoring Optimization

    Science.gov (United States)

    Chen, B.; Harp, D. R.; Lin, Y.; Keating, E. H.; Pawar, R.

    2017-12-01

    Monitoring is a crucial aspect of geologic carbon sequestration (GCS) risk management. It has gained importance as a means to ensure CO2 is safely and permanently stored underground throughout the lifecycle of a GCS project. Three issues are often involved in a monitoring project: (i) where is the optimal location to place the monitoring well(s), (ii) what type of data (pressure, rate and/or CO2 concentration) should be measured, and (iii) What is the optimal frequency to collect the data. In order to address these important issues, a filtering-based data assimilation procedure is developed to perform the monitoring optimization. The optimal monitoring strategy is selected based on the uncertainty reduction of the objective of interest (e.g., cumulative CO2 leak) for all potential monitoring strategies. To reduce the computational cost of the filtering-based data assimilation process, two machine-learning algorithms: Support Vector Regression (SVR) and Multivariate Adaptive Regression Splines (MARS) are used to develop the computationally efficient reduced-order-models (ROMs) from full numerical simulations of CO2 and brine flow. The proposed framework for GCS monitoring optimization is demonstrated with two examples: a simple 3D synthetic case and a real field case named Rock Spring Uplift carbon storage site in Southwestern Wyoming.

  7. Phase transitions between lower and higher level management learning in times of crisis: an experimental study based on synergetics.

    Science.gov (United States)

    Liening, Andreas; Strunk, Guido; Mittelstadt, Ewald

    2013-10-01

    Much has been written about the differences between single- and double-loop learning, or more general between lower level and higher level learning. Especially in times of a fundamental crisis, a transition between lower and higher level learning would be an appropriate reaction to a challenge coming entirely out of the dark. However, so far there is no quantitative method to monitor such a transition. Therefore we introduce theory and methods of synergetics and present results from an experimental study based on the simulation of a crisis within a business simulation game. Hypothesized critical fluctuations - as a marker for so-called phase transitions - have been assessed with permutation entropy. Results show evidence for a phase transition during the crisis, which can be interpreted as a transition between lower and higher level learning.

  8. Attention focussing and anomaly detection in real-time systems monitoring

    Science.gov (United States)

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

    1993-01-01

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

  9. Validation of performance of real-time kinematic PPP. A possible tool for deformation monitoring

    OpenAIRE

    Martín Furones, Ángel Esteban; Anquela Julián, Ana Belén; DIMAS PAGÉS, ALEJANDRO; Cos-Gayón López, Fernando José

    2015-01-01

    Structural failures (bridge or building collapses) and geohazards (landslides, ground subsi- dence or earthquakes) are worldwide problems that often lead to significant economic and loss of life. Monitoring the deformation of both natural phenomena and man-made struc- tures is a major key to assessing structural dynamic responses. Actually, this monitoring process is under real-time demand for developing warning and alert systems. One of the most used techniques for real-time deformation m...

  10. Real-time monitoring, prognosis, and resilient control for wind turbine systems

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Zhiwei; Sheng, Shuangwen

    2018-02-01

    This special issue aims to provide a platform for academic and industrial communities to report recent results and emerging research in real-time monitoring, fault diagnosis, prognosis, and resilient control and design of wind turbine systems. After a strict peer-review process, 20 papers were selected, which represent the most recent progress of the real-time monitoring, diagnosis, prognosis, and resilient control methods/techniques in wind turbine systems.

  11. Carbon Monitoring System Applications Framework: Lessons Learned from Stakeholder Engagement Activities

    Science.gov (United States)

    Sepulveda Carlo, E.; Escobar, V. M.; Delgado Arias, S.; Forgotson, C.

    2017-12-01

    The NASA Carbon Monitoring System initiated by U.S. Congress in 2010 is developing products that characterize and quantify carbon sources and sinks in the United States and the global tropics. In 2013, an applications effort was selected to engage potential end users and gather feedback about their data needs. For the past four years the CMS applications efforts has expanded and implemented a number of strategies to connect carbon scientists to decision-makers, contributing to the societal benefits of CMS data products. The applications efforts use crowd sourcing to collects feedback from stakeholders on challenges and lessons learned in the use of CMS data products. Some of the most common data needs from engaged organizations include above and below-ground biomass and fluxes in forestlands and wetlands, and greenhouse gas (GHG) emissions across all land use/cover and land use changes. Stakeholder organizations' needs for CMS data products support national GHG inventories following the Paris Agreement, carbon markets, and sub-national natural resources management and policies. The lessons learned report presents stakeholder specific applications, challenges, and successes from using CMS data products. To date, the most common uses of CMS products include: conservation efforts, emissions inventory, forestry and land cover applications, and carbon offset projects. The most common challenges include: the need for familiar and consistent products over time, budget constraints, and concern with uncertainty of modeled results. Recurrent recommendations from stakeholder indicate that CMS should provide high resolution (30m) and frequent data products updates (annually). The applications efforts have also helped identified success stories from different CMS projects, including the development of the GHG emissions inventory from Providence, RI, the improvement of the U.S. GHG Inventory though the use of satellite data, and the use of high resolution canopy cover maps for

  12. Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients.

    Science.gov (United States)

    Triantafyllopoulos, Dimitrios; Korvesis, Panagiotis; Mporas, Iosif; Megalooikonomou, Vasileios

    2016-03-01

    New generation of healthcare is represented by wearable health monitoring systems, which provide real-time monitoring of patient's physiological parameters. It is expected that continuous ambulatory monitoring of vital signals will improve treatment of patients and enable proactive personal health management. In this paper, we present the implementation of a multimodal real-time system for epilepsy management. The proposed methodology is based on a data streaming architecture and efficient management of a big flow of physiological parameters. The performance of this architecture is examined for varying spatial resolution of the recorded data.

  13. Using Online Lectures to Make Time for Active Learning

    Science.gov (United States)

    Prunuske, Amy J.; Batzli, Janet; Howell, Evelyn; Miller, Sarah

    2012-01-01

    To make time in class for group activities devoted to critical thinking, we integrated a series of short online lectures into the homework assignments of a large, introductory biology course at a research university. The majority of students viewed the online lectures before coming to class and reported that the online lectures helped them to complete the in-class activity and did not increase the amount of time they devoted to the course. In addition, students who viewed the online lecture performed better on clicker questions designed to test lower-order cognitive skills. The in-class activities then gave the students practice analyzing the information in groups and provided the instructor with feedback about the students’ understanding of the material. On the basis of the results of this study, we support creating hybrid course models that allow students to learn the fundamental information outside of class time, thereby creating time during the class period to be dedicated toward the conceptual understanding of the material. PMID:22714412

  14. Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

    Science.gov (United States)

    Lee, Hanbong

    2016-01-01

    Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

  15. EDUCATIONAL LEAPFROGGING IN THE mLEARNING TIME

    Directory of Open Access Journals (Sweden)

    Abdel Rahman IBRAHIM SULEIMAN

    2014-07-01

    Full Text Available In this theoretical study, researcher tries to shed light on the modern strategy of education, Mobile learning is this strategy, which has become a reality exists in the educational institutions and aims researcher of this study. Trying to figure out the reality of Mobil Determining if the mobile learning part of the E-Learning. Trying for identify future of mobile learning. And the researcher collect the information and the data from previous research in addition to what has been published on websites and blogs and has reached the researcher to achieve the successes of Mobile learning at the level of the educational process now , and that this strategy of mobile learning is not part of the e-learning, and generation of generations , but a new way for the development of the educational process educational , researcher is expected to evolve Mobile learning expands even at the all levels of educational.

  16. A real-time, wearable elemental carbon monitor for use in underground mines

    Energy Technology Data Exchange (ETDEWEB)

    Takiff, L. [ICx Technologies, Cambridge, MA (United States); Aiken, G. [ICx Technologies, Albuquerque, NM (United States)

    2010-07-01

    A real-time, wearable elemental carbon monitor has been developed to determines the exposure of workers in underground mines to diesel particulate material (DPM). ICx Technologies designed the device in an effort to address the health hazards associated with DPM exposure. Occupational exposure to DPM in underground metal and nonmetal mines is regulated by the Mine Safety and Health Administration. The most common method of measuring exposure to elemental or total carbon nanoparticles involves capturing the particles on a filter followed by a thermo-optical laboratory analysis, which integrates the exposure spatially and in time. The ICx monitor is based on a design developed and tested by the National Institute of Occupational Safety and Health (NIOSH). The ICx monitor uses a real-time particle capture and light transmission method to yield elemental carbon values that are displayed for the wearer and are stored internally in a compact device. The ICx monitoring results were found to be in good agreement with the established laboratory method (NIOSH Method 5040) for elemental carbon emissions from a diesel engine. The monitors are compact and powered by a rechargeable lithium-ion battery. Examples of DPM monitoring in mines demonstrated how the real-time data can be more useful that time-averaged results. The information can be used to determine ventilation rates needed at any given location to lower the DPM concentrations.15 refs., 6 figs.

  17. A real-time, wearable elemental carbon monitor for use in underground mines

    International Nuclear Information System (INIS)

    Takiff, L.; Aiken, G.

    2010-01-01

    A real-time, wearable elemental carbon monitor has been developed to determines the exposure of workers in underground mines to diesel particulate material (DPM). ICx Technologies designed the device in an effort to address the health hazards associated with DPM exposure. Occupational exposure to DPM in underground metal and nonmetal mines is regulated by the Mine Safety and Health Administration. The most common method of measuring exposure to elemental or total carbon nanoparticles involves capturing the particles on a filter followed by a thermo-optical laboratory analysis, which integrates the exposure spatially and in time. The ICx monitor is based on a design developed and tested by the National Institute of Occupational Safety and Health (NIOSH). The ICx monitor uses a real-time particle capture and light transmission method to yield elemental carbon values that are displayed for the wearer and are stored internally in a compact device. The ICx monitoring results were found to be in good agreement with the established laboratory method (NIOSH Method 5040) for elemental carbon emissions from a diesel engine. The monitors are compact and powered by a rechargeable lithium-ion battery. Examples of DPM monitoring in mines demonstrated how the real-time data can be more useful that time-averaged results. The information can be used to determine ventilation rates needed at any given location to lower the DPM concentrations.15 refs., 6 figs.

  18. Car-following Behavior Model Learning Using Timed Automata

    NARCIS (Netherlands)

    Zhang, Yihuan; Lin, Q.; Wang, Jun; Verwer, S.E.; Dochain, D.; Henrion, D.; Peaucelle, D.

    Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of car-following using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common

  19. Mental Time Travel, Memory and the Social Learning Strategies Tournament

    Science.gov (United States)

    Fogarty, L.; Rendell, L.; Laland, K. N.

    2012-01-01

    The social learning strategies tournament was an open computer-based tournament investigating the best way to learn in a changing environment. Here we present an analysis of the impact of memory on the ability of strategies entered into the social learning strategies tournament (Rendell, Boyd, et al., 2010) to modify their own behavior to suit a…

  20. Real-time monitoring of airborne beryllium, at OSHA limit levels, by time-resolved laser-induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    Radziemski, L.J.; Loree, T.R.; Cremers, D.A.

    1982-01-01

    Real-time detection of beryllium particulate is being investigated by the new technique of laser-induced breakdown spectroscopy. For beryllium detection we monitor the 313.1-nm feature of once ionized beryllium (Be II). Numerous publications describe the technique, our beryllium results, and other applications. Here we summarize the important points and describe our experiments with beryllium

  1. The effects of emotion on younger and older adults' monitoring of learning.

    Science.gov (United States)

    Tauber, Sarah K; Dunlosky, John; Urry, Heather L; Opitz, Philipp C

    2017-09-01

    Age-related differences in memory monitoring appear when people learn emotional words. Namely, younger adults' judgments of learning (JOLs) are higher for positive than neutral words, whereas older adults' JOLs do not discriminate between positive versus neutral words. In two experiments, we evaluated whether this age-related difference extends to learning positive versus neutral pictures. We also evaluated the contribution of two dimensions of emotion that may impact younger and older adults' JOLs: valence and arousal. Younger and older adults studied pictures that were positive or neutral and either high or low in arousal. Participants made immediate JOLs and completed memory tests. In both experiments, the magnitude of older adults' JOLs was influenced by emotion, and both younger and older adults demonstrated an emotional salience effect on JOLs. As important, the magnitude of participants' JOLs was influenced by valence, and not arousal. Emotional salience effects were also evident on participants' free recall, and older adults recalled as many pictures as did younger adults. Taken together, these data suggest that older adults do not have a monitoring deficit when learning positive (vs. neutral) pictures and that emotional salience effects on younger and older adults' JOLs are produced more by valence than by arousal.

  2. Understanding the Effects of Time on Collaborative Learning Processes in Problem Based Learning: A Mixed Methods Study

    Science.gov (United States)

    Hommes, J.; Van den Bossche, P.; de Grave, W.; Bos, G.; Schuwirth, L.; Scherpbier, A.

    2014-01-01

    Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning…

  3. Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

    Directory of Open Access Journals (Sweden)

    Juan Pardo

    2015-04-01

    Full Text Available Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

  4. Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

    Science.gov (United States)

    Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

    2015-01-01

    Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources. PMID:25905698

  5. Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.

    Science.gov (United States)

    Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

    2015-04-21

    Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

  6. A Lecture Supporting System Based on Real-Time Learning Analytics

    Science.gov (United States)

    Shimada, Atsushi; Konomi, Shin'ichi

    2017-01-01

    A new lecture supporting system based on real-time learning analytics is proposed. Our target is on-site classrooms where teachers give their lectures, and a lot of students listen to teachers' explanation, conduct exercises etc. We utilize not only an e-Learning system, but also an e-Book system to collect real-time learning activities during the…

  7. The learning in a science museum and the role of the monitor

    Directory of Open Access Journals (Sweden)

    Tassiana Fernanda Genzini de Carvalho

    2015-03-01

    Full Text Available The importance attributed to Science Museums regarding to their educational role increased in the past few decades. However there is a considerable distance between the intentions of an exhibition and the perception and possible interpretation of visitors to what is shown to them. This work investigates the part played by monitors at the Estação Ciência da USP in Brazil (Science Station when they follow visiting students groups. The process developed in the interaction with visitors aims to communicate the scientific knowledge involved in the exhibition object when the situation is permeated by social interactions that in a Vigotskian view about learning should favor the building up of scientific concepts. The focus, however, is to realize characteristics of the discourses of monitors with a view to scientific communication; Results have led us to conclude that monitors speeches are far from their intentions showing inconsistencies, and being simplistic, poor in analogies, without scientific rigor.

  8. Connection with seismic networks and construction of real time earthquake monitoring system

    Energy Technology Data Exchange (ETDEWEB)

    Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    2000-12-15

    It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system.

  9. Calibration of environmental monitors operating on time integrating principles for radon/thoron decay products

    International Nuclear Information System (INIS)

    Bigu, J.; Grenier, M.

    1982-03-01

    An environmental radiation monitor for radon decay products has been tested under laboratory controlled conditions. The instrument is of a quasi-time-integrating type and was tested in conjunction with a radon 'box' calibration facility. It has been found that the instrument appreciably underestimates the radon daughter Working Level (WL). This is attributed to plate-out of decay products in the monitor sampling head. The difference between monitor reading and the WL by grab-sampling was higher for low aerosol concentrations. Plate-out on the instrument detector and sampling head, and contamination effects have been observed for the thoron case. There is partial agreement between experimental results and theoretical expectation. The monitor is slow to react to sudden changes in radiation level. The instrument should prove quite useful in the routine monitoring of surface and underground environments provided some suggested changes in the instrument are introduced

  10. Long-term environmental monitoring for assessment of change: measurement inconsistencies over time and potential solutions.

    Science.gov (United States)

    Ellingsen, Kari E; Yoccoz, Nigel G; Tveraa, Torkild; Hewitt, Judi E; Thrush, Simon F

    2017-10-30

    The importance of long-term environmental monitoring and research for detecting and understanding changes in ecosystems and human impacts on natural systems is widely acknowledged. Over the last decades, a number of critical components for successful long-term monitoring have been identified. One basic component is quality assurance/quality control protocols to ensure consistency and comparability of data. In Norway, the authorities require environmental monitoring of the impacts of the offshore petroleum industry on the Norwegian continental shelf, and in 1996, a large-scale regional environmental monitoring program was established. As a case study, we used a sub-set of data from this monitoring to explore concepts regarding best practices for long-term environmental monitoring. Specifically, we examined data from physical and chemical sediment samples and benthic macroinvertebrate assemblages from 11 stations from six sampling occasions during the period 1996-2011. Despite the established quality assessment and quality control protocols for this monitoring program, we identified several data challenges, such as missing values and outliers, discrepancies in variable and station names, changes in procedures without calibration, and different taxonomic resolution. Furthermore, we show that the use of different laboratories over time makes it difficult to draw conclusions with regard to some of the observed changes. We offer recommendations to facilitate comparison of data over time. We also present a new procedure to handle different taxonomic resolution, so valuable historical data is not discarded. These topics have a broader relevance and application than for our case study.

  11. Sensor response monitoring in pressurized water reactors using time series modeling

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Kerlin, T.W.

    1978-01-01

    Random data analysis in nuclear power reactors for purposes of process surveillance, pattern recognition and monitoring of temperature, pressure, flow and neutron sensors has gained increasing attention in view of their potential for helping to ensure safe plant operation. In this study, application of autoregressive moving-average (ARMA) time series modeling for monitoring temperature sensor response characteristrics is presented. The ARMA model is used to estimate the step and ramp response of the sensors and the related time constant and ramp delay time. The ARMA parameters are estimated by a two-stage algorithm in the spectral domain. Results of sensor testing for an operating pressurized water reactor are presented. 16 refs

  12. Universal SaaS platform of internet of things for real-time monitoring

    Science.gov (United States)

    Liu, Tongke; Wu, Gang

    2018-04-01

    Real-time monitoring service, as a member of the IoT (Internet of Things) service, has a wide range application scenario. To support rapid construction and deployment of applications and avoid repetitive development works in these processes, this paper designs and develops a universal SaaS platform of IoT for real-time monitoring. Evaluation shows that this platform can provide SaaS service to multiple tenants and achieve high real-time performance under the situation of large amount of device access.

  13. Definition of a near real-time microbiological monitor for application in space vehicles

    Science.gov (United States)

    Kilgore, Melvin V., Jr.; Zahorchak, Robert J.; Arendale, William F.; Woodward, Samuel S.; Pierson, Duane L.

    1989-01-01

    The concepts and methodologies for microbiological monitoring in space are examined, focusing on the determination of the requirements of a near real-time microbiological monitor. Results are presented from the technical evaluation of five microbiological monitor concepts, including cultural methods, single cell detection, biomolecular detection, specific product detection, and general molecular composition. Within these concepts, twenty-eight specific methodolgies were assessed and the five candidate methodologies with the highest engineering and feasibility scores were selected for further evaluations. The candidate methodologies are laser light scattering, primary fluorescence, secondary fluorescence, volatile product detection, and electronic particle detection. The advantages and disadvantages of these five candidate methodologies are discussed.

  14. Validation of Prototype Continuous Real-Time Vital Signs Video Analytics Monitoring System CCATT Viewer

    Science.gov (United States)

    2018-01-26

    traditional monitors, this capability will facilitate management of a group of patients. Innovative visual analytics of the complex array of real-time...redundant system could be useful in managing hundreds of bedside monitor data sources. With too many data sources, a single central server may suffer...collection rate. 3.2 Viewer Elements Design For detailed elements to display, as well as their color, line styles , and locations on the screen, we

  15. On-line condition monitoring of nuclear systems via symbolic time series analysis

    International Nuclear Information System (INIS)

    Rajagopalan, V.; Ray, A.; Garcia, H. E.

    2006-01-01

    This paper provides a symbolic time series analysis approach to fault diagnostics and condition monitoring. The proposed technique is built upon concepts from wavelet theory, symbolic dynamics and pattern recognition. Various aspects of the methodology such as wavelet selection, choice of alphabet and determination of depth of D-Markov Machine are explained in the paper. The technique is validated with experiments performed in a Machine Condition Monitoring (MCM) test bed at the Idaho National Laboratory. (authors)

  16. Real-time monitoring and control of the plasma hearth process

    International Nuclear Information System (INIS)

    Power, M.A.; Carney, K.P.; Peters, G.G.

    1996-01-01

    A distributed monitoring and control system is proposed for a plasma hearth, which will be used to decompose hazardous organic materials, encapsulate actinide waste in an obsidian-like slag, and reduce storage volume of actinide waste. The plasma hearth will be installed at ANL-West with the assistance of SAIC. Real-time monitoring of the off-gas system is accomplished using a Sun Workstation and embedded PCs. LabWindows/CVI software serves as the graphical user interface

  17. Monitoring Natural Events Globally in Near Real-Time Using NASA's Open Web Services and Tools

    Science.gov (United States)

    Boller, Ryan A.; Ward, Kevin Alan; Murphy, Kevin J.

    2015-01-01

    Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based missions, many of which can be useful for monitoring natural events. In recent years, these measurements have been made available in near real-time, making it possible to use them to also aid in managing the response to natural events. We present the challenges and ongoing solutions to using NASA satellite data for monitoring and managing these events.

  18. A Wireless and Real-Time Monitoring System Design for Car Networking Applications

    Directory of Open Access Journals (Sweden)

    Li Wenjun

    2013-01-01

    Full Text Available We described a wireless and monitoring system to obtain several classes of vehicle data and send them to the server via General Packet Radio Service (GPRS in real-time. These data are consisted by on-board diagnostic (OBD which get from the vehicle’s OBD interface, Tire-Pressure Monitoring system (TPMS and Global Positioning System (GPS. The main content of this paper is the hardware design of the system, especially RF modules and antennas.

  19. Determination of velocity correction factors for real-time air velocity monitoring in underground mines

    OpenAIRE

    Zhou, Lihong; Yuan, Liming; Thomas, Rick; Iannacchione, Anthony

    2017-01-01

    When there are installations of air velocity sensors in the mining industry for real-time airflow monitoring, a problem exists with how the monitored air velocity at a fixed location corresponds to the average air velocity, which is used to determine the volume flow rate of air in an entry with the cross-sectional area. Correction factors have been practically employed to convert a measured centerline air velocity to the average air velocity. However, studies on the recommended correction fac...

  20. Building a satellite climate diagnostics data base for real-time climate monitoring

    International Nuclear Information System (INIS)

    Ropelewski, C.F.

    1991-01-01

    The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

  1. ToTCompute: A Novel EEG-Based TimeOnTask Threshold Computation Mechanism for Engagement Modelling and Monitoring

    Science.gov (United States)

    Ghergulescu, Ioana; Muntean, Cristina Hava

    2016-01-01

    Engagement influences participation, progression and retention in game-based e-learning (GBeL). Therefore, GBeL systems should engage the players in order to support them to maximize their learning outcomes, and provide the players with adequate feedback to maintain their motivation. Innovative engagement monitoring solutions based on players'…

  2. Air-Flow-Driven Triboelectric Nanogenerators for Self-Powered Real-Time Respiratory Monitoring.

    Science.gov (United States)

    Wang, Meng; Zhang, Jiahao; Tang, Yingjie; Li, Jun; Zhang, Baosen; Liang, Erjun; Mao, Yanchao; Wang, Xudong

    2018-06-04

    Respiration is one of the most important vital signs of humans, and respiratory monitoring plays an important role in physical health management. A low-cost and convenient real-time respiratory monitoring system is extremely desirable. In this work, we demonstrated an air-flow-driven triboelectric nanogenerator (TENG) for self-powered real-time respiratory monitoring by converting mechanical energy of human respiration into electric output signals. The operation of the TENG was based on the air-flow-driven vibration of a flexible nanostructured polytetrafluoroethylene (n-PTFE) thin film in an acrylic tube. This TENG can generate distinct real-time electric signals when exposed to the air flow from different breath behaviors. It was also found that the accumulative charge transferred in breath sensing corresponds well to the total volume of air exchanged during the respiration process. Based on this TENG device, an intelligent wireless respiratory monitoring and alert system was further developed, which used the TENG signal to directly trigger a wireless alarm or dial a cell phone to provide timely alerts in response to breath behavior changes. This research offers a promising solution for developing self-powered real-time respiratory monitoring devices.

  3. Real time monitoring of slope condition for transmission tower safety in Kenyir, Malaysia

    Science.gov (United States)

    Omar, R. C.; Ismail, A.; Khalid, N. H. N.; Din, N. M.; Hussain, H.; Jamaludin, M. Z.; Abdullah, F.; Arazad, A. Z.; Yusop, H.

    2013-06-01

    The Malaysia national electricity grid traverses throughout the nation over urban and rural areas including mountainous terrain. A major number of the transmission towers have been in existence for over 40 years and some traversed through very remote and high altitude areas like the Titiwangsa range that forms the backbone of the Malay Peninsula. This paper describes the instrumentation and real time monitoring in a transmission tower site in Kenyir, a hilly terrain in the East Coast of Malaysia. The site itself which is between 300-500m above sea level is deep in the rainforest area of Kenyir. The site and surrounding areas has been identified with signs of slope failure. A design concern is the real time slope monitoring sensors reliability and data integrity from the remote area with potential interference to the electronics equipment from the power line. The monitoring system comprised of an automated system for collecting and reporting field monitoring data. The instruments collect readings and transmit real time through GSM to the monitoring office over designated intervals. This initiative is a part of a project on developing an early warning system for monitoring landslide hazards at selected transmission towers. This paper reviews the various instrumentation used and challenges faced and the output received for slope movement warnings.

  4. Real time monitoring of slope condition for transmission tower safety in Kenyir, Malaysia

    International Nuclear Information System (INIS)

    Omar, R C; Ismail, A; Khalid, N H N; Din, N M; Hussain, H; Jamaludin, M Z; Abdullah, F; Arazad, A Z; Yusop, H

    2013-01-01

    The Malaysia national electricity grid traverses throughout the nation over urban and rural areas including mountainous terrain. A major number of the transmission towers have been in existence for over 40 years and some traversed through very remote and high altitude areas like the Titiwangsa range that forms the backbone of the Malay Peninsula. This paper describes the instrumentation and real time monitoring in a transmission tower site in Kenyir, a hilly terrain in the East Coast of Malaysia. The site itself which is between 300–500m above sea level is deep in the rainforest area of Kenyir. The site and surrounding areas has been identified with signs of slope failure. A design concern is the real time slope monitoring sensors reliability and data integrity from the remote area with potential interference to the electronics equipment from the power line. The monitoring system comprised of an automated system for collecting and reporting field monitoring data. The instruments collect readings and transmit real time through GSM to the monitoring office over designated intervals. This initiative is a part of a project on developing an early warning system for monitoring landslide hazards at selected transmission towers. This paper reviews the various instrumentation used and challenges faced and the output received for slope movement warnings.

  5. Machine learning in heart failure: ready for prime time.

    Science.gov (United States)

    Awan, Saqib Ejaz; Sohel, Ferdous; Sanfilippo, Frank Mario; Bennamoun, Mohammed; Dwivedi, Girish

    2018-03-01

    The aim of this review is to present an up-to-date overview of the application of machine learning methods in heart failure including diagnosis, classification, readmissions and medication adherence. Recent studies have shown that the application of machine learning techniques may have the potential to improve heart failure outcomes and management, including cost savings by improving existing diagnostic and treatment support systems. Recently developed deep learning methods are expected to yield even better performance than traditional machine learning techniques in performing complex tasks by learning the intricate patterns hidden in big medical data. The review summarizes the recent developments in the application of machine and deep learning methods in heart failure management.

  6. In real time: exploring nursing students' learning during an international experience.

    Science.gov (United States)

    Afriyie Asenso, Barbara; Reimer-Kirkham, Sheryl; Astle, Barbara

    2013-10-11

    Abstract Nursing education has increasingly turned to international learning experiences to educate students who are globally minded and aware of social injustices in local and global communities. To date, research with international learning experiences has focused on the benefits for the students participating, after they have completed the international experience. The purpose of this qualitative study was to explore how nursing students learn during the international experience. The sample consisted of eight nursing students who enrolled in an international learning experience, and data were collected in "real time" in Zambia. The students were observed during learning activities and were interviewed three times. Three major themes emerged from the thematic analysis: expectations shaped students' learning, engagement facilitated learning, and critical reflection enhanced learning. Implications are discussed, related to disrupting media representations of Africa that shape students' expectations, and educational strategies for transformative learning and global citizenship.

  7. Information extraction from dynamic PS-InSAR time series using machine learning

    Science.gov (United States)

    van de Kerkhof, B.; Pankratius, V.; Chang, L.; van Swol, R.; Hanssen, R. F.

    2017-12-01

    Due to the increasing number of SAR satellites, with shorter repeat intervals and higher resolutions, SAR data volumes are exploding. Time series analyses of SAR data, i.e. Persistent Scatterer (PS) InSAR, enable the deformation monitoring of the built environment at an unprecedented scale, with hundreds of scatterers per km2, updated weekly. Potential hazards, e.g. due to failure of aging infrastructure, can be detected at an early stage. Yet, this requires the operational data processing of billions of measurement points, over hundreds of epochs, updating this data set dynamically as new data come in, and testing whether points (start to) behave in an anomalous way. Moreover, the quality of PS-InSAR measurements is ambiguous and heterogeneous, which will yield false positives and false negatives. Such analyses are numerically challenging. Here we extract relevant information from PS-InSAR time series using machine learning algorithms. We cluster (group together) time series with similar behaviour, even though they may not be spatially close, such that the results can be used for further analysis. First we reduce the dimensionality of the dataset in order to be able to cluster the data, since applying clustering techniques on high dimensional datasets often result in unsatisfying results. Our approach is to apply t-distributed Stochastic Neighbor Embedding (t-SNE), a machine learning algorithm for dimensionality reduction of high-dimensional data to a 2D or 3D map, and cluster this result using Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The results show that we are able to detect and cluster time series with similar behaviour, which is the starting point for more extensive analysis into the underlying driving mechanisms. The results of the methods are compared to conventional hypothesis testing as well as a Self-Organising Map (SOM) approach. Hypothesis testing is robust and takes the stochastic nature of the observations into account

  8. Towards real-time regional earthquake simulation I: real-time moment tensor monitoring (RMT) for regional events in Taiwan

    Science.gov (United States)

    Lee, Shiann-Jong; Liang, Wen-Tzong; Cheng, Hui-Wen; Tu, Feng-Shan; Ma, Kuo-Fong; Tsuruoka, Hiroshi; Kawakatsu, Hitoshi; Huang, Bor-Shouh; Liu, Chun-Chi

    2014-01-01

    We have developed a real-time moment tensor monitoring system (RMT) which takes advantage of a grid-based moment tensor inversion technique and real-time broad-band seismic recordings to automatically monitor earthquake activities in the vicinity of Taiwan. The centroid moment tensor (CMT) inversion technique and a grid search scheme are applied to obtain the information of earthquake source parameters, including the event origin time, hypocentral location, moment magnitude and focal mechanism. All of these source parameters can be determined simultaneously within 117 s after the occurrence of an earthquake. The monitoring area involves the entire Taiwan Island and the offshore region, which covers the area of 119.3°E to 123.0°E and 21.0°N to 26.0°N, with a depth from 6 to 136 km. A 3-D grid system is implemented in the monitoring area with a uniform horizontal interval of 0.1° and a vertical interval of 10 km. The inversion procedure is based on a 1-D Green's function database calculated by the frequency-wavenumber (fk) method. We compare our results with the Central Weather Bureau (CWB) catalogue data for earthquakes occurred between 2010 and 2012. The average differences between event origin time and hypocentral location are less than 2 s and 10 km, respectively. The focal mechanisms determined by RMT are also comparable with the Broadband Array in Taiwan for Seismology (BATS) CMT solutions. These results indicate that the RMT system is realizable and efficient to monitor local seismic activities. In addition, the time needed to obtain all the point source parameters is reduced substantially compared to routine earthquake reports. By connecting RMT with a real-time online earthquake simulation (ROS) system, all the source parameters will be forwarded to the ROS to make the real-time earthquake simulation feasible. The RMT has operated offline (2010-2011) and online (since January 2012 to present) at the Institute of Earth Sciences (IES), Academia Sinica

  9. Miniaturized and Wireless Optical Neurotransmitter Sensor for Real-Time Monitoring of Dopamine in the Brain.

    Science.gov (United States)

    Kim, Min H; Yoon, Hargsoon; Choi, Sang H; Zhao, Fei; Kim, Jongsung; Song, Kyo D; Lee, Uhn

    2016-11-10

    Real-time monitoring of extracellular neurotransmitter concentration offers great benefits for diagnosis and treatment of neurological disorders and diseases. This paper presents the study design and results of a miniaturized and wireless optical neurotransmitter sensor (MWONS) for real-time monitoring of brain dopamine concentration. MWONS is based on fluorescent sensing principles and comprises a microspectrometer unit, a microcontroller for data acquisition, and a Bluetooth wireless network for real-time monitoring. MWONS has a custom-designed application software that controls the operation parameters for excitation light sources, data acquisition, and signal processing. MWONS successfully demonstrated a measurement capability with a limit of detection down to a 100 nanomole dopamine concentration, and high selectivity to ascorbic acid (90:1) and uric acid (36:1).

  10. Bunch-length and beam-timing monitors in the SLC final focus

    International Nuclear Information System (INIS)

    Zimmermann, F.; Yocky, G.; Whittum, D.H.; Seidel, M.; Ng, C.K.; McCormick, D.; Bane, K.L.F.

    1998-07-01

    During the 1997/98 luminosity run of the Stanford Linear Collider (SLC), two novel RF-based detectors were brought into operation, in order to monitor the interaction-point (IP) bunch lengths and fluctuations in the relative arrival time of the two colliding beams. Both bunch length and timing can strongly affect the SLC luminosity and had not been monitored in previous years. The two new detectors utilize a broad-band microwave signal, which is excited by the beam through a ceramic gap in the final-focus beam pipe and transported outside of the beam line vault by a 160-ft long X-Band waveguide. The authors describe the estimated luminosity reduction due to bunch-length drift and IP timing fluctuation, the monitor layout, the expected responses and signal levels, calibration measurements, and beam observations

  11. New and Emerging Technologies for Real-Time Air and Surface Beryllium Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Phifer, B.E. Jr.; Churnetski, E.L.; Cooke, L.E.; Reed, J.J.; Howell, M.L.; Smith, V.D.

    2001-09-01

    In this study, five emerging technologies were identified for real-time monitoring of airborne beryllium: Microwave-Induced Plasma Spectroscopy (MIPS), Aerosol Beam-Focused Laser-Induced Plasma Spectroscopy (ABFLIPS), Laser-Induced Breakdown Spectroscopy (LIBS), Surfaced-Enhanced Raman Scattering (SERS) Spectroscopy, and Micro-Calorimetric Spectroscopy (CalSpec). Desired features of real-time air beryllium monitoring instrumentation were developed from the Y-12 CBDPP. These features were used as guidelines for the identification of potential technologies as well as their unique demonstrated capability to provide real-time monitoring of similar materials. However, best available technologies were considered, regardless of their ability to comply with the desired features. None of the five technologies have the capability to measure the particle size of airborne beryllium. Although reducing the total concentration of airborne beryllium is important, current literature suggests that reducing or eliminating the concentration of respirable beryllium is critical for worker health protection. Eight emerging technologies were identified for surface monitoring of beryllium. CalSpec, MIPS, SERS, LIBS, Laser Ablation, Absorptive Stripping Voltametry (ASV), Modified Inductively Coupled Plasma (ICP) Spectroscopy, and Gamma BeAST. Desired features of real-time surface beryllium monitoring were developed from the Y-12 CBDPP. These features were used as guidelines for the identification of potential technologies. However, the best available technologies were considered regardless of their ability to comply with the desired features.

  12. Real-time monitoring of single-photon detectors against eavesdropping in quantum key distribution systems.

    Science.gov (United States)

    da Silva, Thiago Ferreira; Xavier, Guilherme B; Temporão, Guilherme P; von der Weid, Jean Pierre

    2012-08-13

    By employing real-time monitoring of single-photon avalanche photodiodes we demonstrate how two types of practical eavesdropping strategies, the after-gate and time-shift attacks, may be detected. Both attacks are identified with the detectors operating without any special modifications, making this proposal well suited for real-world applications. The monitoring system is based on accumulating statistics of the times between consecutive detection events, and extracting the afterpulse and overall efficiency of the detectors in real-time using mathematical models fit to the measured data. We are able to directly observe changes in the afterpulse probabilities generated from the after-gate and faint after-gate attacks, as well as different timing signatures in the time-shift attack. We also discuss the applicability of our scheme to other general blinding attacks.

  13. Nonintrusive Load Monitoring Based on Advanced Deep Learning and Novel Signature

    Directory of Open Access Journals (Sweden)

    Jihyun Kim

    2017-01-01

    Full Text Available Monitoring electricity consumption in the home is an important way to help reduce energy usage. Nonintrusive Load Monitoring (NILM is existing technique which helps us monitor electricity consumption effectively and costly. NILM is a promising approach to obtain estimates of the electrical power consumption of individual appliances from aggregate measurements of voltage and/or current in the distribution system. Among the previous studies, Hidden Markov Model (HMM based models have been studied very much. However, increasing appliances, multistate of appliances, and similar power consumption of appliances are three big issues in NILM recently. In this paper, we address these problems through providing our contributions as follows. First, we proposed state-of-the-art energy disaggregation based on Long Short-Term Memory Recurrent Neural Network (LSTM-RNN model and additional advanced deep learning. Second, we proposed a novel signature to improve classification performance of the proposed model in multistate appliance case. We applied the proposed model on two datasets such as UK-DALE and REDD. Via our experimental results, we have confirmed that our model outperforms the advanced model. Thus, we show that our combination between advanced deep learning and novel signature can be a robust solution to overcome NILM’s issues and improve the performance of load identification.

  14. The Effects of Self-Monitoring of Story Elements on the Reading Comprehension of High School Seniors with Learning Disabilities

    Science.gov (United States)

    Crabtree, Tim; Alber-Morgan, Sheila R.; Konrad, Moira

    2010-01-01

    This study used a multiple baseline across participants design to examine the effects of self-monitoring and active responding on the reading comprehension of three high school seniors with learning disabilities and significant attention problems. The self-monitoring intervention required the participants to read a story and stop reading at three…

  15. Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.

    Science.gov (United States)

    Pecevski, Dejan; Maass, Wolfgang

    2016-01-01

    Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.

  16. Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123

    Science.gov (United States)

    Pecevski, Dejan

    2016-01-01

    Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214

  17. Museums as spaces and times for learning and social participation.

    Directory of Open Access Journals (Sweden)

    César M.

    2014-12-01

    Full Text Available A museum is valued according to its collections, communication and knowledge exchange with visitors (Primo, 1999. Museums should be in dialogue with the public, contributing to their development (Skramstad, 2004 and collective memory (Wertsch, 2004. Social interactions and working in participants’ zone of proximal development (Vygotsky, 1934/1962 play an important role in non-formal learning opportunities that take place at museums. The National Museum of Natural History and Science (Lisbon University offers weekly holiday programmes for children and teenagers, aiming at developing scientific literacy in intercultural and inclusive spaces and times, facilitating knowledge appropriation and social participation. We studied these programmes, assuming an interpretive approach (Denzin, 2002 and developing an intrinsic case study (Stake, 1995. The main participants were these children and teenagers, their parents, and museum educational agents. Data collecting instruments included observation, interviews, questionnaires, children and teenagers’ protocols and tasks inspired in projective techniques. Data treatment and analysis was based on a narrative content analysis (Clandinin & Connelly, 1998 from which inductive categories emerged (Hamido & César, 2009. Some examples illuminate participants’ expectancies, their engagement in activities, and the contributions of social interactions and non-formal education to the development of scientific literacy.

  18. TU-EF-210-03: Real-Time Ablation Monitoring and Lesion Quantification Using Harmonic Motion Imaging

    International Nuclear Information System (INIS)

    Konofagou, E.

    2015-01-01

    The use of therapeutic ultrasound to provide targeted therapy is an active research area that has a broad application scope. The invited talks in this session will address currently implemented strategies and protocols for both hyperthermia and ablation applications using therapeutic ultrasound. The role of both ultrasound and MRI in the monitoring and assessment of these therapies will be explored in both pre-clinical and clinical applications. Katherine Ferrara: High Intensity Focused Ultrasound, Drug Delivery, and Immunotherapy Rajiv Chopra: Translating Localized Doxorubicin Delivery to Pediatric Oncology using MRI-guided HIFU Elisa Konofagou: Real-time Ablation Monitoring and Lesion Quantification using Harmonic Motion Imaging Keyvan Farahani: AAPM Task Groups in Interventional Ultrasound Imaging and Therapy Learning Objectives: Understand the role of ultrasound in localized drug delivery and the effects of immunotherapy when used in conjunction with ultrasound therapy. Understand potential targeted drug delivery clinical applications including pediatric oncology. Understand the technical requirements for performing targeted drug delivery. Understand how radiation-force approaches can be used to both monitor and assess high intensity focused ultrasound ablation therapy. Understand the role of AAPM task groups in ultrasound imaging and therapies. Chopra: Funding from Cancer Prevention and Research Initiative of Texas (CPRIT), Award R1308 Evelyn and M.R. Hudson Foundation; Research Support from Research Contract with Philips Healthcare; COI are Co-founder of FUS Instruments Inc Ferrara: Supported by NIH, UCDavis and California (CIRM and BHCE) Farahani: In-kind research support from Philips Healthcare

  19. TU-EF-210-03: Real-Time Ablation Monitoring and Lesion Quantification Using Harmonic Motion Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Konofagou, E. [Columbia University (United States)

    2015-06-15

    The use of therapeutic ultrasound to provide targeted therapy is an active research area that has a broad application scope. The invited talks in this session will address currently implemented strategies and protocols for both hyperthermia and ablation applications using therapeutic ultrasound. The role of both ultrasound and MRI in the monitoring and assessment of these therapies will be explored in both pre-clinical and clinical applications. Katherine Ferrara: High Intensity Focused Ultrasound, Drug Delivery, and Immunotherapy Rajiv Chopra: Translating Localized Doxorubicin Delivery to Pediatric Oncology using MRI-guided HIFU Elisa Konofagou: Real-time Ablation Monitoring and Lesion Quantification using Harmonic Motion Imaging Keyvan Farahani: AAPM Task Groups in Interventional Ultrasound Imaging and Therapy Learning Objectives: Understand the role of ultrasound in localized drug delivery and the effects of immunotherapy when used in conjunction with ultrasound therapy. Understand potential targeted drug delivery clinical applications including pediatric oncology. Understand the technical requirements for performing targeted drug delivery. Understand how radiation-force approaches can be used to both monitor and assess high intensity focused ultrasound ablation therapy. Understand the role of AAPM task groups in ultrasound imaging and therapies. Chopra: Funding from Cancer Prevention and Research Initiative of Texas (CPRIT), Award R1308 Evelyn and M.R. Hudson Foundation; Research Support from Research Contract with Philips Healthcare; COI are Co-founder of FUS Instruments Inc Ferrara: Supported by NIH, UCDavis and California (CIRM and BHCE) Farahani: In-kind research support from Philips Healthcare.

  20. Real-time health monitoring of civil infrastructure systems in Colombia

    Science.gov (United States)

    Thomson, Peter; Marulanda Casas, Johannio; Marulanda Arbelaez, Johannio; Caicedo, Juan

    2001-08-01

    Colombia's topography, climatic conditions, intense seismic activity and acute social problems place high demands on the nations deteriorating civil infrastructure. Resources that are available for maintenance of the road and railway networks are often misdirected and actual inspection methods are limited to a visual examination. New techniques for inspection and evaluation of safety and serviceability of civil infrastructure, especially bridges, must be developed. Two cases of civil structures with health monitoring systems in Colombia are presented in this paper. Construction of the Pereria-Dos Quebradas Viaduct was completed in 1997 with a total cost of 58 million dollars, including 1.5 million dollars in health monitoring instrumentation provided and installed by foreign companies. This health monitoring system is not yet fully operational due to the lack of training of national personnel in system operation and extremely limited technical documentation. In contrast to the Pereria-Dos Quebradas Viaduct monitoring system, the authors have proposed a relatively low cost health monitoring system via telemetry. This system has been implemented for real-time monitoring of accelerations of El Hormiguero Bridge spanning the Cauca River using the Colombian Southwest Earthquake Observatory telemetry systems. This two span metallic bridge, located along a critical road between the cities of Puerto Tejada and Cali in the Cauca Valley, was constructed approximately 50 years ago. Experiences with this system demonstrate how effective low cost systems can be used to remotely monitor the structural integrity of deteriorating structures that are continuously subject to high loading conditions.

  1. Project Management in Real Time: A Service-Learning Project

    Science.gov (United States)

    Larson, Erik; Drexler, John A., Jr.

    2010-01-01

    This article describes a service-learning assignment for a project management course. It is designed to facilitate hands-on student learning of both the technical and the interpersonal aspects of project management, and it involves student engagement with real customers and real stakeholders in the creation of real events with real outcomes. As…

  2. Age and time effects on implicit and explicit learning

    NARCIS (Netherlands)

    Verneau, M.; Kamp, J. van der; Savelsbergh, G.J.P.; Looze, M.P. de

    2014-01-01

    Study Context: It has been proposed that effects of aging are more pronounced for explicit than for implicit motor learning. The authors evaluated this claim by comparing the efficacy of explicit and implicit learning of a movement sequence in young and older adults, and by testing the resilience

  3. Age and Time Effects on Implicit and Explicit Learning

    NARCIS (Netherlands)

    Verneau, M.M.N.; van der Kamp, J.; Savelsbergh, G.J.P.; de Looze, M.P.

    2014-01-01

    Study Context: It has been proposed that effects of aging are more pronounced for explicit than for implicit motor learning. The authors evaluated this claim by comparing the efficacy of explicit and implicit learning of a movement sequence in young and older adults, and by testing the resilience

  4. Language Learning Attitudes: Ingrained Or Shaped In Time?

    Directory of Open Access Journals (Sweden)

    Gökçe DİŞLEN DAĞGÖL

    2017-09-01

    Full Text Available Language learning has become an essential need in today’s world. From academic to social settings, humans need to communicate in a different language to survive in their community. However, despite this increasing importance of language, it is difficult to say we have attained successful language learning on a large scale since there are a lot of factors in language learning process. Language attitudes, one of these factors, influence this process both positively and negatively, depending on how we view learning a foreign language. Therefore, this study deals with the issue of language attitudes to uncover learners’ language conceptions and probable effects on their learning. Moreover, this study aims to reveal the potential role of past learning experiences on the development of language beliefs positively or negatively. Thus, 35 university students in their 1st, 2nd, 3rd and 4th years constitute the participants of the study. Based on mixed research design, the study is comprised of both quantitative and qualitative data. Quantitative data were gathered through Attitude Scale towards English Course, and the analyses were performed with Statistical Packages for Social Sciences (SPSS 17.0 version for Windows. The qualitative data were collected from students’ reports of their own autobiographies regarding their previous language learning experiences in elementary, secondary, high school and university years, and were subjected to the content analysis. The study showed language attitudes from behavioural, cognitive and affective perspectives and found out different factors in shaping their learning conceptions.

  5. A framework to monitor activities of satellite data processing in real-time

    Science.gov (United States)

    Nguyen, M. D.; Kryukov, A. P.

    2018-01-01

    Space Monitoring Data Center (SMDC) of SINP MSU is one of the several centers in the world that collects data on the radiational conditions in near-Earth orbit from various Russian (Lomonosov, Electro-L1, Electro-L2, Meteor-M1, Meteor-M2, etc.) and foreign (GOES 13, GOES 15, ACE, SDO, etc.) satellites. The primary purposes of SMDC are: aggregating heterogeneous data from different sources; providing a unified interface for data retrieval, visualization, analysis, as well as development and testing new space weather models; and controlling the correctness and completeness of data. Space weather models rely on data provided by SMDC to produce forecasts. Therefore, monitoring the whole data processing cycle is crucial for further success in the modeling of physical processes in near-Earth orbit based on the collected data. To solve the problem described above, we have developed a framework called Live Monitor at SMDC. Live Monitor allows watching all stages and program components involved in each data processing cycle. All activities of each stage are logged by Live Monitor and shown in real-time on a web interface. When an error occurs, a notification message will be sent to satellite operators via email and the Telegram messenger service so that they could take measures in time. The Live Monitor’s API can be used to create a customized monitoring service with minimum coding.

  6. Harmonizing electricity markets with physics : real time performance monitoring using grid-3PTM

    International Nuclear Information System (INIS)

    Budhraja, V.S.

    2003-01-01

    The Electric Power Group, LLC provides management and strategic consulting services for the electric power industry, with special emphasis on industry restructuring, competitive electricity markets, grid operations and reliability, power technologies, venture investments and start-ups. The Consortium for Electric Reliability Technology Solutions involves national laboratories, universities, and industry partners in researching, developing, and commercializing electric reliability technology solutions to protect and enhance the reliability of the American electric power system under the emerging competitive electricity market structure. Physics differentiate electric markets from other markets: there is real-time balancing, no storage, interconnected network, and power flows governed by physics. Some issues affecting both grid reliability and market issues are difficult to separate, such as security and congestion management, voltage management, reserves, frequency volatility, and others. The author examined the following investment challenges facing the electricity market: grid solutions, market solutions, and technology solutions. The real time performance monitoring and prediction platform, grid-3P was described and applications discussed, such as ACE-frequency monitoring, performance monitoring for automatic generation control (AGC) and frequency response, voltage/VAR monitoring, stability monitoring using phasor technology, and market monitoring. figs

  7. Application of the statistical process control method for prospective patient safety monitoring during the learning phase: robotic kidney transplantation with regional hypothermia (IDEAL phase 2a-b).

    Science.gov (United States)

    Sood, Akshay; Ghani, Khurshid R; Ahlawat, Rajesh; Modi, Pranjal; Abaza, Ronney; Jeong, Wooju; Sammon, Jesse D; Diaz, Mireya; Kher, Vijay; Menon, Mani; Bhandari, Mahendra

    2014-08-01

    Traditional evaluation of the learning curve (LC) of an operation has been retrospective. Furthermore, LC analysis does not permit patient safety monitoring. To prospectively monitor patient safety during the learning phase of robotic kidney transplantation (RKT) and determine when it could be considered learned using the techniques of statistical process control (SPC). From January through May 2013, 41 patients with end-stage renal disease underwent RKT with regional hypothermia at one of two tertiary referral centers adopting RKT. Transplant recipients were classified into three groups based on the robotic training and kidney transplant experience of the surgeons: group 1, robot trained with limited kidney transplant experience (n=7); group 2, robot trained and kidney transplant experienced (n=20); and group 3, kidney transplant experienced with limited robot training (n=14). We employed prospective monitoring using SPC techniques, including cumulative summation (CUSUM) and Shewhart control charts, to perform LC analysis and patient safety monitoring, respectively. Outcomes assessed included post-transplant graft function and measures of surgical process (anastomotic and ischemic times). CUSUM and Shewhart control charts are time trend analytic techniques that allow comparative assessment of outcomes following a new intervention (RKT) relative to those achieved with established techniques (open kidney transplant; target value) in a prospective fashion. CUSUM analysis revealed an initial learning phase for group 3, whereas groups 1 and 2 had no to minimal learning time. The learning phase for group 3 varied depending on the parameter assessed. Shewhart control charts demonstrated no compromise in functional outcomes for groups 1 and 2. Graft function was compromised in one patient in group 3 (pcontrol chart analytic techniques. These methods allow determination of the duration of mentorship and identification of adverse events in a timely manner. A new operation

  8. The aquatic real-time monitoring network; in-situ optical sensors for monitoring the nation's water quality

    Science.gov (United States)

    Pellerin, Brian A.; Bergamaschi, Brian A.; Murdoch, Peter S.; Downing, Bryan D.; Saraceno, John Franco; Aiken, George R.; Striegl, Robert G.

    2011-01-01

    Floods, hurricanes, and longer-term changes in climate and land use can have profound effects on water quality due to shifts in hydrologic flow paths, water residence time, precipitation patterns, connectivity between rivers and uplands, and many other factors. In order to understand and respond to changes in hydrology and water quality, resource managers and policy makers have a need for accurate and early indicators, as well as the ability to assess possible mechanisms and likely outcomes. In-situ optical sensors-those making continuous measurements of constituents by absorbance or fluorescence properties in the environment at timescales of minutes to years-have a long history in oceanography for developing highly resolved concentrations and fluxes, but are not commonly used in freshwater systems. The United States Geological Survey (USGS) has developed the Aquatic Real-Time Monitoring Network, with high-resolution optical data collection for organic carbon, nutrients, and sediment in large coastal rivers, along with continuous measurements of discharge, water temperature, and dissolved inorganic carbon. The collecting of continuous water-quality data in the Nation?s waterways has revealed temporal trends and spatial patterns in constituents that traditional sampling approaches fail to capture, and will serve a critical role in monitoring, assessment and decision-making in a rapidly changing landscape.

  9. Devices for Self-Monitoring Sedentary Time or Physical Activity: A Scoping Review.

    Science.gov (United States)

    Sanders, James P; Loveday, Adam; Pearson, Natalie; Edwardson, Charlotte; Yates, Thomas; Biddle, Stuart J H; Esliger, Dale W

    2016-05-04

    It is well documented that meeting the guideline levels (150 minutes per week) of moderate-to-vigorous physical activity (PA) is protective against chronic disease. Conversely, emerging evidence indicates the deleterious effects of prolonged sitting. Therefore, there is a need to change both behaviors. Self-monitoring of behavior is one of the most robust behavior-change techniques available. The growing number of technologies in the consumer electronics sector provides a unique opportunity for individuals to self-monitor their behavior. The aim of this study is to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary time and/or PA. To identify technologies, four scientific databases were systematically searched using key terms related to behavior, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1, 2015. The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored PA, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring PA and/or sedentary behavior; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on PA (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary time (activPAL VT, the Lumo Back, and Darma

  10. Developments in real-time monitoring for geologic hazard warnings (Invited)

    Science.gov (United States)

    Leith, W. S.; Mandeville, C. W.; Earle, P. S.

    2013-12-01

    Real-time data from global, national and local sensor networks enable prompt alerts and warnings of earthquakes, tsunami, volcanic eruptions, geomagnetic storms , broad-scale crustal deformation and landslides. State-of-the-art seismic systems can locate and evaluate earthquake sources in seconds, enabling 'earthquake early warnings' to be broadcast ahead of the damaging surface waves so that protective actions can be taken. Strong motion monitoring systems in buildings now support near-real-time structural damage detection systems, and in quiet times can be used for state-of-health monitoring. High-rate GPS data are being integrated with seismic strong motion data, allowing accurate determination of earthquake displacements in near-real time. GPS data, combined with rainfall, groundwater and geophone data, are now used for near-real-time landslide monitoring and warnings. Real-time sea-floor water pressure data are key for assessing tsunami generation by large earthquakes. For monitoring remote volcanoes that lack local ground-based instrumentation, the USGS uses new technologies such as infrasound arrays and the worldwide lightning detection array to detect eruptions in progress. A new real-time UV-camera system for measuring the two dimensional SO2 flux from volcanic plumes will allow correlations with other volcano monitoring data streams to yield fundamental data on changes in gas flux as an eruption precursor, and how magmas de-gas prior to and during eruptions. Precision magnetic field data support the generation of real-time indices of geomagnetic disturbances (Dst, K and others), and can be used to model electrical currents in the crust and bulk power system. Ground-induced electrical current monitors are used to track those currents so that power grids can be effectively managed during geomagnetic storms. Beyond geophysical sensor data, USGS is using social media to rapidly detect possible earthquakes and to collect firsthand accounts of the impacts of

  11. [Research and implementation of a real-time monitoring system for running status of medical monitors based on the internet of things].

    Science.gov (United States)

    Li, Yiming; Qian, Mingli; Li, Long; Li, Bin

    2014-07-01

    This paper proposed a real-time monitoring system for running status of medical monitors based on the internet of things. In the aspect of hardware, a solution of ZigBee networks plus 470 MHz networks is proposed. In the aspect of software, graphical display of monitoring interface and real-time equipment failure alarm is implemented. The system has the function of remote equipment failure detection and wireless localization, which provides a practical and effective method for medical equipment management.

  12. Neonatal non-contact respiratory monitoring based on real-time infrared thermography

    Directory of Open Access Journals (Sweden)

    Abbas Abbas K

    2011-10-01

    Full Text Available Abstract Background Monitoring of vital parameters is an important topic in neonatal daily care. Progress in computational intelligence and medical sensors has facilitated the development of smart bedside monitors that can integrate multiple parameters into a single monitoring system. This paper describes non-contact monitoring of neonatal vital signals based on infrared thermography as a new biomedical engineering application. One signal of clinical interest is the spontaneous respiration rate of the neonate. It will be shown that the respiration rate of neonates can be monitored based on analysis of the anterior naris (nostrils temperature profile associated with the inspiration and expiration phases successively. Objective The aim of this study is to develop and investigate a new non-contact respiration monitoring modality for neonatal intensive care unit (NICU using infrared thermography imaging. This development includes subsequent image processing (region of interest (ROI detection and optimization. Moreover, it includes further optimization of this non-contact respiration monitoring to be considered as physiological measurement inside NICU wards. Results Continuous wavelet transformation based on Debauches wavelet function was applied to detect the breathing signal within an image stream. Respiration was successfully monitored based on a 0.3°C to 0.5°C temperature difference between the inspiration and expiration phases. Conclusions Although this method has been applied to adults before, this is the first time it was used in a newborn infant population inside the neonatal intensive care unit (NICU. The promising results suggest to include this technology into advanced NICU monitors.

  13. Improving Neuromuscular Monitoring and Reducing Residual Neuromuscular Blockade With E-Learning

    DEFF Research Database (Denmark)

    Thomsen, Jakob Louis Demant; Mathiesen, Ole; Hägi-Pedersen, Daniel

    2017-01-01

    neuromuscular blockade in surgical patients at 6 Danish teaching hospitals. METHODS: In this interrupted time series study, we are collecting data repeatedly, in consecutive 3-week periods, before and after the intervention, and we will analyze the effect using segmented regression analysis. Anesthesia...... and an increased risk of respiratory complications. Use of an objective neuromuscular monitoring device may prevent residual block. Despite this, many anesthetists refrain from using the device. Efforts to increase the use of objective monitoring are time consuming and require the presence of expert personnel...... practice, and patient outcomes. The primary outcome is use of neuromuscular monitoring in patients according to the type of muscle relaxant received. Secondary outcomes include last recorded train-of-four value, administration of reversal agents, and time to discharge from the postanesthesia care unit...

  14. The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent

    Science.gov (United States)

    Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie

    2017-01-01

    Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…

  15. Incremental Impact of Time on Students' Use of E-Learning via Facebook

    Science.gov (United States)

    Moghavvemi, Sedigheh; Salarzadeh Janatabadi, Hashem

    2018-01-01

    The majority of studies utilised the cross-sectional method to measure students' intention to learn and investigate their corresponding learning behaviours. Only a few studies have measured the process of change in students' learning behaviour in the context of time. The main purpose of this study is to determine the effects of using a Facebook…

  16. Crumpled Molecules and Edible Plastic: Science Learning Activation in Out-of-School Time

    Science.gov (United States)

    Dorph, Rena; Schunn, Christian D.; Crowley, Kevin

    2017-01-01

    The Coalition for Science After School highlights the dual nature of outcomes for science learning during out-of- school time (OST): Learning experiences should not only be positive in the moment, but also position youth for future success. Several frameworks speak to the first set of immediate outcomes--what youth learn, think, and feel as the…

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

    Science.gov (United States)

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

    1989-01-01

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

  18. Real-time measurement of dust in the workplace using video exposure monitoring: Farming to pharmaceuticals

    International Nuclear Information System (INIS)

    Walsh, P T; Forth, A R; Clark, R D R; Dowker, K P; Thorpe, A

    2009-01-01

    Real-time, photometric, portable dust monitors have been employed for video exposure monitoring (VEM) to measure and highlight dust levels generated by work activities, illustrate dust control techniques, and demonstrate good practice. Two workplaces, presenting different challenges for measurement, were used to illustrate the capabilities of VEM: (a) poultry farming activities and (b) powder transfer operations in a pharmaceutical company. For the poultry farm work, the real-time monitors were calibrated with respect to the respirable and inhalable dust concentrations using cyclone and IOM reference samplers respectively. Different rankings of exposure for typical activities were found on the small farm studied here compared to previous exposure measurements at larger poultry farms: these were mainly attributed to the different scales of operation. Large variations in the ratios of respirable, inhalable and real-time monitor TWA concentrations of poultry farm dust for various activities were found. This has implications for the calibration of light-scattering dust monitors with respect to inhalable dust concentration. In the pharmaceutical application, the effectiveness of a curtain barrier for dust control when dispensing powder in a downflow booth was rapidly demonstrated.

  19. Ubiquitous health monitoring and real-time cardiac arrhythmias detection: a case study.

    Science.gov (United States)

    Li, Jian; Zhou, Haiying; Zuo, Decheng; Hou, Kun-Mean; De Vaulx, Christophe

    2014-01-01

    As the symptoms and signs of heart diseases that cause sudden cardiac death, cardiac arrhythmia has attracted great attention. Due to limitations in time and space, traditional approaches to cardiac arrhythmias detection fail to provide a real-time continuous monitoring and testing service applicable in different environmental conditions. Integrated with the latest technologies in ECG (electrocardiograph) analysis and medical care, the pervasive computing technology makes possible the ubiquitous cardiac care services, and thus brings about new technical challenges, especially in the formation of cardiac care architecture and realization of the real-time automatic ECG detection algorithm dedicated to care devices. In this paper, a ubiquitous cardiac care prototype system is presented with its architecture framework well elaborated. This prototype system has been tested and evaluated in all the clinical-/home-/outdoor-care modes with a satisfactory performance in providing real-time continuous cardiac arrhythmias monitoring service unlimitedly adaptable in time and space.

  20. Integrating SAR with Optical and Thermal Remote Sensing for Operational Near Real-Time Volcano Monitoring

    Science.gov (United States)

    Meyer, F. J.; Webley, P.; Dehn, J.; Arko, S. A.; McAlpin, D. B.

    2013-12-01

    Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing techniques have become established in operational forecasting, monitoring, and managing of volcanic hazards. Monitoring organizations, like the Alaska Volcano Observatory (AVO), are nowadays heavily relying on remote sensing data from a variety of optical and thermal sensors to provide time-critical hazard information. Despite the high utilization of these remote sensing data to detect and monitor volcanic eruptions, the presence of clouds and a dependence on solar illumination often limit their impact on decision making processes. Synthetic Aperture Radar (SAR) systems are widely believed to be superior to optical sensors in operational monitoring situations, due to the weather and illumination independence of their observations and the sensitivity of SAR to surface changes and deformation. Despite these benefits, the contributions of SAR to operational volcano monitoring have been limited in the past due to (1) high SAR data costs, (2) traditionally long data processing times, and (3) the low temporal sampling frequencies inherent to most SAR systems. In this study, we present improved data access, data processing, and data integration techniques that mitigate some of the above mentioned limitations and allow, for the first time, a meaningful integration of SAR into operational volcano monitoring systems. We will introduce a new database interface that was developed in cooperation with the Alaska Satellite Facility (ASF) and allows for rapid and seamless data access to all of ASF's SAR data holdings. We will also present processing techniques that improve the temporal frequency with which hazard-related products can be produced. These techniques take advantage of modern signal processing technology as well as new radiometric normalization schemes, both enabling the combination of

  1. EFFECTS OF COOPERATIVE LEARNING MODEL TYPE STAD JUST-IN TIME BASED ON THE RESULTS OF LEARNING TEACHING PHYSICS COURSE IN PHYSICS SCHOOL IN PHYSICS PROGRAM FACULTY UNIMED

    Directory of Open Access Journals (Sweden)

    Teguh Febri Sudarma

    2013-06-01

    Full Text Available Research was aimed to determine: (1 Students’ learning outcomes that was taught with just in time teaching based STAD cooperative learning method and STAD cooperative learning method (2 Students’ outcomes on Physics subject that had high learning activity compared with low learning activity. The research sample was random by raffling four classes to get two classes. The first class taught with just in time teaching based STAD cooperative learning method, while the second class was taught with STAD cooperative learning method. The instrument used was conceptual understanding that had been validated with 7 essay questions. The average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,47 higher than average gain values of students learning results with STAD cooperative learning method. The high learning activity and low learning activity gave different learning results. In this case the average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,48 higher than average gain values of students learning results with STAD cooperative learning method. There was interaction between learning model and learning activity to the physics learning result test in students

  2. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  3. Substrate-Coated Illumination Droplet Spray Ionization: Real-Time Monitoring of Photocatalytic Reactions

    Science.gov (United States)

    Zhang, Hong; Li, Na; Zhao, Dandan; Jiang, Jie; You, Hong

    2017-09-01

    Real-time monitoring of photocatalytic reactions facilitates the elucidation of the mechanisms of the reactions. However, suitable tools for real-time monitoring are lacking. Herein, a novel method based on droplet spray ionization named substrate-coated illumination droplet spray ionization (SCI-DSI) for direct analysis of photocatalytic reaction solution is reported. SCI-DSI addresses many of the analytical limitations of electrospray ionization (ESI) for analysis of photocatalytic-reaction intermediates, and has potential for both in situ analysis and real-time monitoring of photocatalytic reactions. In SCI-DSI-mass spectrometry (MS), a photocatalytic reaction occurs by loading sample solutions onto the substrate-coated cover slip and by applying UV light above the modified slip; one corner of this slip adjacent to the inlet of a mass spectrometer is the high-electric-field location for launching a charged-droplet spray. After both testing and optimizing the performance of SCI-DSI, the value of this method for in situ analysis and real-time monitoring of photocatalytic reactions was demonstrated by the removal of cyclophosphamide (CP) in TiO2/UV. Reaction times ranged from seconds to minutes, and the proposed reaction intermediates were captured and identified by tandem mass spectrometry. Moreover, the free hydroxyl radical (·OH) was identified as the main radicals for CP removal. These results show that SCI-DSI is suitable for in situ analysis and real-time monitoring of CP removal under TiO2-based photocatalytic reactions. SCI-DSI is also a potential tool for in situ analysis and real-time assessment of the roles of radicals during CP removal under TiO2-based photocatalytic reactions. Graphical Abstract[Figure not available: see fulltext.

  4. Activity Learning as a Foundation for Security Monitoring in Smart Homes

    Directory of Open Access Journals (Sweden)

    Jessamyn Dahmen

    2017-03-01

    Full Text Available Smart environment technology has matured to the point where it is regularly used in everyday homes as well as research labs. With this maturation of the technology, we can consider using smart homes as a practical mechanism for improving home security. In this paper, we introduce an activity-aware approach to security monitoring and threat detection in smart homes. We describe our approach using the CASAS smart home framework and activity learning algorithms. By monitoring for activity-based anomalies we can detect possible threats and take appropriate action. We evaluate our proposed method using data collected in CASAS smart homes and demonstrate the partnership between activity-aware smart homes and biometric devices in the context of the CASAS on-campus smart apartment testbed.

  5. Activity Learning as a Foundation for Security Monitoring in Smart Homes.

    Science.gov (United States)

    Dahmen, Jessamyn; Thomas, Brian L; Cook, Diane J; Wang, Xiaobo

    2017-03-31

    Smart environment technology has matured to the point where it is regularly used in everyday homes as well as research labs. With this maturation of the technology, we can consider using smart homes as a practical mechanism for improving home security. In this paper, we introduce an activity-aware approach to security monitoring and threat detection in smart homes. We describe our approach using the CASAS smart home framework and activity learning algorithms. By monitoring for activity-based anomalies we can detect possible threats and take appropriate action. We evaluate our proposed method using data collected in CASAS smart homes and demonstrate the partnership between activity-aware smart homes and biometric devices in the context of the CASAS on-campus smart apartment testbed.

  6. FPGA implementation of a hybrid on-line process monitoring in PC based real-time systems

    Directory of Open Access Journals (Sweden)

    Jovanović Bojan

    2011-01-01

    Full Text Available This paper presents one way of FPGA implementation of hybrid (hardware-software based on-line process monitoring in Real-Time systems (RTS. The reasons for RTS monitoring are presented at the beginning. The summary of different RTS monitoring approaches along with its advantages and drawbacks are also exposed. Finally, monitoring module is described in details. Also, FPGA implementation results and some useful monitoring system applications are mentioned.

  7. Improving Neuromuscular Monitoring and Reducing Residual Neuromuscular Blockade With E-Learning

    DEFF Research Database (Denmark)

    Thomsen, Jakob Louis Demant; Mathiesen, Ole; Hägi-Pedersen, Daniel

    2017-01-01

    BACKGROUND: Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Residual neuromuscular blockade occurs when the patient is still partially paralyzed when awakened after surgery. The condition is associated with subjective discomfort and an......-learning module can increase anesthetists' use of neuromuscular monitoring. TRIAL REGISTRATION: Clinicaltrials.gov NCT02925143; https://clinicaltrials.gov/ct2/show/NCT02925143 (Archived by WebCite® at http://www.webcitation.org/6s50iTV2x)....

  8. Real Time Corrosion Monitoring in Lead and Lead-Bismuth Systems

    Energy Technology Data Exchange (ETDEWEB)

    James F. Stubbins; Alan Bolind; Ziang Chen

    2010-02-25

    The objective of this research program is to develop a real-time, in situ corrosion monitoring technique for flowing liquid Pb and eutectic PbBi (LBE) systems in a temperature range of 400 to 650 C. These conditions are relevant to future liquid metal cooled fast reactor operating parameters. THis program was aligned with the Gen IV Reactor initiative to develp technologies to support the design and opertion of a Pb or LBE-cooled fast reactor. The ability to monitor corrosion for protection of structural components is a high priority issue for the safe and prolonged operation of advanced liquid metal fast reactor systems. In those systems, protective oxide layers are intentionally formed and maintained to limit corrosion rates during operation. This program developed a real time, in situ corrosion monitoring tecnique using impedance spectroscopy (IS) technology.

  9. A Wearable System for Real-Time Continuous Monitoring of Physical Activity

    Directory of Open Access Journals (Sweden)

    Fabrizio Taffoni

    2018-01-01

    Full Text Available Over the last decades, wearable systems have gained interest for monitoring of physiological variables, promoting health, and improving exercise adherence in different populations ranging from elite athletes to patients. In this paper, we present a wearable system for the continuous real-time monitoring of respiratory frequency (fR, heart rate (HR, and movement cadence during physical activity. The system has been experimentally tested in the laboratory (by simulating the breathing pattern with a mechanical ventilator and by collecting data from one healthy volunteer. Results show the feasibility of the proposed device for real-time continuous monitoring of fR, HR, and movement cadence both in resting condition and during activity. Finally, different synchronization techniques have been investigated to enable simultaneous data collection from different wearable modules.

  10. Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

    Science.gov (United States)

    Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

    2017-04-09

    Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

  11. Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

    Directory of Open Access Journals (Sweden)

    Jude Adekunle Adeleke

    2017-04-01

    Full Text Available Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

  12. Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

    Science.gov (United States)

    Wang, Ji-Bo; Wang, Ming-Zheng; Ji, Ping

    2012-05-01

    In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.

  13. Competitive Reporter Monitored Amplification (CMA) - Quantification of Molecular Targets by Real Time Monitoring of Competitive Reporter Hybridization

    Science.gov (United States)

    Ullrich, Thomas; Ermantraut, Eugen; Schulz, Torsten; Steinmetzer, Katrin

    2012-01-01

    Background State of the art molecular diagnostic tests are based on the sensitive detection and quantification of nucleic acids. However, currently established diagnostic tests are characterized by elaborate and expensive technical solutions hindering the development of simple, affordable and compact point-of-care molecular tests. Methodology and Principal Findings The described competitive reporter monitored amplification allows the simultaneous amplification and quantification of multiple nucleic acid targets by polymerase chain reaction. Target quantification is accomplished by real-time detection of amplified nucleic acids utilizing a capture probe array and specific reporter probes. The reporter probes are fluorescently labeled oligonucleotides that are complementary to the respective capture probes on the array and to the respective sites of the target nucleic acids in solution. Capture probes and amplified target compete for reporter probes. Increasing amplicon concentration leads to decreased fluorescence signal at the respective capture probe position on the array which is measured after each cycle of amplification. In order to observe reporter probe hybridization in real-time without any additional washing steps, we have developed a mechanical fluorescence background displacement technique. Conclusions and Significance The system presented in this paper enables simultaneous detection and quantification of multiple targets. Moreover, the presented fluorescence background displacement technique provides a generic solution for real time monitoring of binding events of fluorescently labelled ligands to surface immobilized probes. With the model assay for the detection of human immunodeficiency virus type 1 and 2 (HIV 1/2), we have been able to observe the amplification kinetics of five targets simultaneously and accommodate two additional hybridization controls with a simple instrument set-up. The ability to accommodate multiple controls and targets into a

  14. Competitive reporter monitored amplification (CMA--quantification of molecular targets by real time monitoring of competitive reporter hybridization.

    Directory of Open Access Journals (Sweden)

    Thomas Ullrich

    Full Text Available BACKGROUND: State of the art molecular diagnostic tests are based on the sensitive detection and quantification of nucleic acids. However, currently established diagnostic tests are characterized by elaborate and expensive technical solutions hindering the development of simple, affordable and compact point-of-care molecular tests. METHODOLOGY AND PRINCIPAL FINDINGS: The described competitive reporter monitored amplification allows the simultaneous amplification and quantification of multiple nucleic acid targets by polymerase chain reaction. Target quantification is accomplished by real-time detection of amplified nucleic acids utilizing a capture probe array and specific reporter probes. The reporter probes are fluorescently labeled oligonucleotides that are complementary to the respective capture probes on the array and to the respective sites of the target nucleic acids in solution. Capture probes and amplified target compete for reporter probes. Increasing amplicon concentration leads to decreased fluorescence signal at the respective capture probe position on the array which is measured after each cycle of amplification. In order to observe reporter probe hybridization in real-time without any additional washing steps, we have developed a mechanical fluorescence background displacement technique. CONCLUSIONS AND SIGNIFICANCE: The system presented in this paper enables simultaneous detection and quantification of multiple targets. Moreover, the presented fluorescence background displacement technique provides a generic solution for real time monitoring of binding events of fluorescently labelled ligands to surface immobilized probes. With the model assay for the detection of human immunodeficiency virus type 1 and 2 (HIV 1/2, we have been able to observe the amplification kinetics of five targets simultaneously and accommodate two additional hybridization controls with a simple instrument set-up. The ability to accommodate multiple controls

  15. Machine learning application in the life time of materials

    OpenAIRE

    Yu, Xiaojiao

    2017-01-01

    Materials design and development typically takes several decades from the initial discovery to commercialization with the traditional trial and error development approach. With the accumulation of data from both experimental and computational results, data based machine learning becomes an emerging field in materials discovery, design and property prediction. This manuscript reviews the history of materials science as a disciplinary the most common machine learning method used in materials sc...

  16. Real-time risk monitoring in business processes : a sensor-based approach

    NARCIS (Netherlands)

    Conforti, R.; La Rosa, M.; Fortino, G.; Hofstede, ter A.H.M.; Recker, J.; Adams, M.

    2013-01-01

    This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis,

  17. Secure and Time-Aware Communication of Wireless Sensors Monitoring Overhead Transmission Lines.

    Science.gov (United States)

    Mazur, Katarzyna; Wydra, Michal; Ksiezopolski, Bogdan

    2017-07-11

    Existing transmission power grids suffer from high maintenance costs and scalability issues along with a lack of effective and secure system monitoring. To address these problems, we propose to use Wireless Sensor Networks (WSNs) as a technology to achieve energy efficient, reliable, and low-cost remote monitoring of transmission grids. With WSNs, smart grid enables both utilities and customers to monitor, predict and manage energy usage effectively and react to possible power grid disturbances in a timely manner. However, the increased application of WSNs also introduces new security challenges, especially related to privacy, connectivity, and security management, repeatedly causing unpredicted expenditures. Monitoring the status of the power system, a large amount of sensors generates massive amount of sensitive data. In order to build an effective Wireless Sensor Network (WSN) for a smart grid, we focus on designing a methodology of efficient and secure delivery of the data measured on transmission lines. We perform a set of simulations, in which we examine different routing algorithms, security mechanisms and WSN deployments in order to select the parameters that will not affect the delivery time but fulfill their role and ensure security at the same time. Furthermore, we analyze the optimal placement of direct wireless links, aiming at minimizing time delays, balancing network performance and decreasing deployment costs.

  18. How to study optimal timing of PET/CT for monitoring of cancer treatment

    DEFF Research Database (Denmark)

    Vach, Werner; Høilund-Carlsen, Poul Flemming; Fischer, Barbara Malene Bjerregaard

    2011-01-01

    Purpose: The use of PET/CT for monitoring treatment response in cancer patients after chemo- or radiotherapy is a very promising approach to optimize cancer treatment. However, the timing of the PET/CT-based evaluation of reduction in viable tumor tissue is a crucial question. We investigated how...

  19. Complex system approach to interpretation of monitoring time series: two case histories from NW Bohemia

    Czech Academy of Sciences Publication Activity Database

    Vařilová, Z.; Zvelebil, J.; Paluš, Milan

    2011-01-01

    Roč. 8, č. 2 (2011), s. 207-220 ISSN 1612-510X Grant - others:ICL(JP) IPL-M141 Project Institutional research plan: CEZ:AV0Z10300504 Keywords : displacement monitoring * time prognostication of rock fall * nonlinear dynamics Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.216, year: 2011

  20. Shape selection in Landsat time series: A tool for monitoring forest dynamics

    Science.gov (United States)

    Gretchen G. Moisen; Mary C. Meyer; Todd A. Schroeder; Xiyue Liao; Karen G. Schleeweis; Elizabeth A. Freeman; Chris Toney

    2016-01-01

    We present a new methodology for fitting nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral band or index of choice in temporal Landsat data, our method delivers a smoothed rendition of...

  1. 4g-Based Specialty Vehicles Real-Time Monitoring System Design and Implementation

    Directory of Open Access Journals (Sweden)

    Zhuang Yu-Feng

    2017-01-01

    Full Text Available In the future development of natural gas transportation industry, emerging ITS technology will be applied more and more, aiming at integrating precise positioning technology, geographic information system technology, database technology, multimedia technology and modern communication technology, sensor network technology and video capture technology, so as to achieve the transport steam (oil vehicles in real time monitoring and management. The main research content of this paper is to design and research the monitoring and locating system of luck (oil vehicle based on 4G on Android System. Real-time monitoring and alarming by sensor module, real-time video recording and uploading through camera module, real-time position recording and uploading through GPS module, vehicle navigation module and quick alarm module, which is composed of five parts. The system is the application of new intelligent transport technology in the field of special vehicle transport. It apply electronic information technology and internet of things technology to the vehicle system, so we can monitor natural gas and other special dangerous goods anytime, anywhere.

  2. System for continuous real time air monitoring by means of gamma spectrometry with germanium dosimeter

    International Nuclear Information System (INIS)

    Montalto, M.; Giacomelli, R.; Nocente, M.; Bortoluzzi, S.; Spezzano, P.

    1990-12-01

    Design of automatic system for real time air monitoring of radioactive particulates are relate. Recommendations are made for design and operation of sampling conduits to minimize losses. By means of experimental equipment loss of particles in long sampling conduits, minimum detectable activity and efficiency of gamma radiation detectable are evaluated. (author)

  3. Real-time monitoring/emergency response modeling workstation for a tritium facility

    International Nuclear Information System (INIS)

    Lawver, B.S.; Sims, J.M.; Baskett, R.L.

    1993-01-01

    At Lawrence Livermore National Laboratory (LLNL) we have developed a real-time system to monitor two stacks on our tritium handling facility. The monitors transmit the stack data to a workstation, which computes a three-dimensional numerical model of atmospheric dispersion. The workstation also collects surface and upper air data from meteorological towers and a sodar. The complex meteorological and terrain setting in the Livermore Valley demands more sophisticated resolution of the three-dimensional structure of the atmosphere to reliably calculate plume dispersion than afforded by Gaussian models. We experience both mountain valley and sea breeze flows. To address these complexities, we have implemented the three-dimensional diagnostic MATHEW mass-adjusted wind field and ADPIC particle-in-cell dispersion models on the workstation for use in real-time emergency response modeling. Both MATHEW and ADPIC have shown their utility in a variety of complex settings over the last 15 yr within the U.S. Department of Energy's Atmospheric Release Advisory Capability (ARAC) project. Faster workstations and real-time instruments allow utilization of more complex three-dimensional models, which provides a foundation for building a real-time monitoring and emergency response workstation for a tritium facility. The stack monitors are two ion chambers per stack

  4. Real-time monitoring of clinical processes using complex event processing and transition systems.

    Science.gov (United States)

    Meinecke, Sebastian

    2014-01-01

    Dependencies between tasks in clinical processes are often complex and error-prone. Our aim is to describe a new approach for the automatic derivation of clinical events identified via the behaviour of IT systems using Complex Event Processing. Furthermore we map these events on transition systems to monitor crucial clinical processes in real-time for preventing and detecting erroneous situations.

  5. A UAV based system for real time flash flood monitoring in desert environments using Lagrangian microsensors

    KAUST Repository

    Abdelkader, Mohamed; Shaqura, Mohammad; Claudel, Christian G.; Gueaieb, Wail

    2013-01-01

    with advance warning, for which real time monitoring is critical. While satellite-based high resolution weather forecasts can help predict floods to a certain extent, they are not reliable enough, as flood models depend on a large number of parameters

  6. Exploiting the airwave for time-lapse reservoir monitoring with CSEM on land

    NARCIS (Netherlands)

    Wirianto, M.; Mulder, W.A.; Slob, E.C.

    2011-01-01

    In the application of controlled source electromagnetics for reservoir monitoring on land, repeatability errors in the source will mask the time-lapse signal due to hydrocarbon production when recording surface data close to the source. We demonstrate that at larger distances, the airwave will still

  7. An Approach for Real-time Levee Health Monitoring Using Signal Processing Methods

    NARCIS (Netherlands)

    Pyayt, A.L.; Kozionov, A.P.; Mokhov, I.I.; Lang, B.; Krzhizhanovskaya, V.V.; Sloot, P.M.A.

    2013-01-01

    We developed a levee health monitoring system within the UrbanFlood project funded under the EU 7th Framework Programme. A novel real-time levee health assessment Artificial Intelligence system is developed using data-driven methods. The system is implemented in the UrbanFlood early warning system.

  8. Improvements in real time {sup 222}Rn monitoring at Stromboli volcano

    Energy Technology Data Exchange (ETDEWEB)

    Lavagno, A., E-mail: andrea.lavagno@polito.it [Dipartimento di Scienze Applicata e Tecnologia, Politecnico di Torino (Italy); INFN, Sezione di Torino (Italy); Laiolo, M. [Dipartimento di Scienze della Terra, Università di Torino (Italy); Gervino, G. [Dipartimento di Fisica, Università di Torino (Italy); INFN, Sezione di Torino (Italy); Cigolini, C.; Coppola, D.; Piscopo, D. [Dipartimento di Scienze della Terra, Università di Torino (Italy); Marino, C. [Dipartimento di Fisica, Università di Torino (Italy); INFN, Sezione di Torino (Italy)

    2013-08-01

    Monitoring gas emissions from soil allow to get information on volcanic activity, hidden faults and hydrothermal dynamics. Radon activities at Stromboli were collected by means of multi-parametric real-time stations, that measure radon as well as environmental parameters. The last improvements on the detection system are presented and discussed.

  9. Time-lapse monitoring of soil water content using electromagnetic conductivity imaging

    Science.gov (United States)

    The volumetric soil water content (VWC) is fundamental to agriculture. Unfortunately, the universally accepted thermogravimetric method is labour intensive and time-consuming to use for field-scale monitoring. Electromagnetic (EM) induction instruments have proven to be useful in mapping the spatio-...

  10. Multi-resolution time series imagery for forest disturbance and regrowth monitoring in Queensland, Australia

    NARCIS (Netherlands)

    Schmidt, M.; Lucas, R.; Bunting, P.; Verbesselt, J.; Armston, J.

    2015-01-01

    High spatio-temporal resolution optical remote sensing data provide unprecedented opportunities to monitor and detect forest disturbance and loss. To demonstrate this potential, a 12-year time series (2000 to 2011) with an 8-day interval of a 30 m spatial resolution data was generated by the use of

  11. Biosensor-based real-time monitoring of paracetamol photocatalytic degradation.

    Science.gov (United States)

    Calas-Blanchard, Carole; Istamboulié, Georges; Bontoux, Margot; Plantard, Gaël; Goetz, Vincent; Noguer, Thierry

    2015-07-01

    This paper presents for the first time the integration of a biosensor for the on-line, real-time monitoring of a photocatalytic degradation process. Paracetamol was used as a model molecule due to its wide use and occurrence in environmental waters. The biosensor was developed based on tyrosinase immobilization in a polyvinylalcohol photocrosslinkable polymer. It was inserted in a computer-controlled flow system installed besides a photocatalytic reactor including titanium dioxide (TiO2) as photocatalyst. It was shown that the biosensor was able to accurately monitor the paracetamol degradation with time. Compared with conventional HPLC analysis, the described device provides a real-time information on the reaction advancement, allowing a better control of the photodegradation process. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Availability of anesthetic effect monitoring: utilization, intraoperative management and time to extubation in liver transplantation.

    Science.gov (United States)

    Schumann, R; Hudcova, J; Bonney, I; Cepeda, M S

    2010-12-01

    Titration of volatile anesthetics to anesthetic effect monitoring using the bispectral index (BIS) has been shown to decrease anesthetic requirements and facilitate recovery from anesthesia unrelated to liver transplantation (OLT). To determine whether availability of such monitoring influences its utilization pattern and affect anesthetic care and outcomes in OLT, we conducted a retrospective analysis in recipients with and without such monitoring. We evaluated annual BIS utilization over a period of 7 years, and compared 41 BIS-monitored patients to 42 controls. All received an isoflurane/air/oxygen and opioid-based anesthetic with planned postoperative ventilation. Data collection included age, body mass index (BMI), gender, Model for End-stage Liver Disease (MELD) score, and time to extubation (TtE). Mean preanhepatic, anhepatic, and postanhepatic end-tidal isoflurane concentrations were compared, as well as BIS values for each phase of OLT using the Kruskal-Wallis and Wilcoxon signed-rank tests, respectively. The use of anesthetic effect monitoring when available increased steadily from 15% of cases in the first year to almost 93% by year 7. There was no significant difference in age, gender, BMI, MELD, or TtE between groups. The BIS group received less inhalational anesthetic during each phase of OLT compared to the control group. However, this difference was statistically significant only during the anhepatic phase (P = .026), and was clinically not impressive. Within the BIS group, the mean BIS value was 38.74 ± 5.25 (mean ± standard deviation), and there was no difference for the BIS value between different transplant phases. Availability of anesthetic effect monitoring as an optional monitoring tool during OLT results in its increasing utilization by anesthesia care teams over time. However, unless integrated into an intraoperative algorithm and an early extubation protocol for fast tracking of OLT recipients, this utilization does not appear to provide

  13. Comparison of sensor characteristics of three real-time monitors for organic vapors.

    Science.gov (United States)

    Hori, Hajime; Ishimatsu, Sumiyo; Fueta, Yukiko; Hinoue, Mitsuo; Ishidao, Toru

    2015-01-01

    Sensor characteristics and performance of three real-time monitors for volatile organic compounds (VOC monitor) equipped with a photo ionization detector (PID), a sensor using the interference enhanced reflection (IER) method and a semiconductor gas sensor were investigated for 52 organic solvent vapors designated as class 1 and class 2 of organic solvents by the Ordinance of Organic Solvent Poisoning Prevention in Japan. Test vapors were prepared by injecting each liquid solvent into a 50 l Tedlar® bag and perfectly vaporizing it. The vapor concentration was from one-tenth to twice the administrative control level for all solvents. The vapor concentration was measured with the monitors and a gas chromatograph equipped with a flame ionization detector simultaneously, and the values were compared. The monitor with the PID sensor could measure many organic vapors, but it could not detect some vapors with high ionization potential. The IER sensor could also detect many vapors, but a linear response was not obtained for some vapors. A semiconductor sensor could detect methanol that could not be detected by PID and IER sensors. Working environment measurement of organic vapors by real-time monitors may be possible, but sensor characteristics and their limitations should be known.

  14. Real time monitoring to the odour of excrement for health of infants and elderly completely bedridden

    Science.gov (United States)

    Ye, Jiancheng; Huang, Guoliang

    2017-01-01

    In the domain of biomedical signals measurements, monitoring human physiological parameters is an important issue. With the rapid development of wireless body area network, it makes monitor, transmit and record physiological parameters faster and more convenient. Infants and the elderly completely bedridden are two special groups of the society who need more medical care. According to researches investigating current frontier domains and the market products, the detection of physiological parameters from the excrement is rare. However, urine and faeces contain a large number of physiological information, which are high relative to health. The mainly distributed odour from urine is NH4 and the distributed odour from feces is mainly H2S, which are both could be detected by the sensors. In this paper, we introduce the design and implementation of a portable wireless device based on body area network for real time monitoring to the odour of excrement for health of infants and the elderly completely bedridden. The device not only could monitor in real time the emitted odour of faeces and urine for health analysis, but also measures the body temperature and environment humidity, and send data to the mobile phone of paramedics to alarm or the server for storage and process, which has prospect to monitoring infants and the paralysis elderly.

  15. Numerical and machine learning simulation of parametric distributions of groundwater residence time in streams and wells

    Science.gov (United States)

    Starn, J. J.; Belitz, K.; Carlson, C.

    2017-12-01

    Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to contamination. This novel approach for estimating regional RTDs was to first simulate groundwater flow using existing regional digital data sets in 13 intermediate size watersheds (each an average of 7,000 square kilometers) that are representative of a wide range of glacial systems. RTDs were simulated with particle tracking. We refer to these models as "general models" because they are based on regional, as opposed to site-specific, digital data. Parametric RTDs were created from particle RTDs by fitting 1- and 2-component Weibull, gamma, and inverse Gaussian distributions, thus reducing a large number of particle travel times to 3 to 7 parameters (shape, location, and scale for each component plus a mixing fraction) for each modeled area. The scale parameter of these distributions is related to the mean exponential age; the shape parameter controls departure from the ideal exponential distribution and is partly a function of interaction with bedrock and with drainage density. Given the flexible shape and mathematical similarity of these distributions, any of them are potentially a good fit to particle RTDs. The 1-component gamma distribution provided a good fit to basin-wide particle RTDs. RTDs at monitoring wells and streams often have more complicated shapes than basin-wide RTDs, caused in part by heterogeneity in the model, and generally require 2-component distributions. A machine learning model was trained on the RTD parameters using features derived from regionally available watershed characteristics such as recharge rate, material thickness, and stream density. RTDs appeared to vary systematically across the landscape in relation to watershed features. This relation was used to produce maps of useful metrics with respect to risk-based thresholds, such as the time to first exceedance, time to maximum concentration, time above the threshold

  16. Development of a real-time extremity dose monitor for personnel in interventional radiology

    International Nuclear Information System (INIS)

    Ban, Nobuhiko; Kusama, Tomoko; Adachi, Akiko

    2000-01-01

    Protection of personnel in interventional radiology is one of the most important issues of radiological protection in medicine. Fluoroscopically guided interventional procedures require the operation near X-ray beam, which brings a considerable hand exposure to the operators. For the purpose of effectual control of their extremity doses, we have developed a real-time extremity dose monitor which is worn on a strap around the wrist. The monitor consists of a silicon semiconductor detector, thin lithium battery and a waterproof frame with a four-digit LED display. Experiment was carried out to examine a response of the monitor to diagnostic X-rays. A practical test was also performed to evaluate usability in the actual interventional procedures. In the experiment, the extremity dose monitor was placed on an arm phantom and exposed to diagnostic X-rays. Readings of the monitor were compared to those of Capintec PS-033 shallow chamber. The monitor was highly sensitive to diagnostic X-rays. It showed a linear response down to doses of a few tens of microsieverts. For high dose-rate exposure, however, a slight decrease in the response was observed, about 10% of counting loss for 80 kV, 40 mA X-ray at one meter from the focus. With regard to energy dependence, variation was within 20% for 60 to 100 kV X-rays. The monitor showed a good angular response in general, except lateral geometry facing the far side from a detector center. In the practical test, hand exposures of medical staff were measured with the extremity dose monitor. They were also asked to fill in a questionnaire regarding size and weight of the monitor, clarity of the display and usefulness. The subjects consisted of physicians, technicians and nurses who engaged in angiography, PTCD, CT-biopsy, barium enema and so on. The readings of the monitor were less than 1 mSv in most cases while 93 mSv was recorded in an extreme case due to direct-beam exposure. In some cases, TLD rings were used together with the

  17. Development of a real-time extremity dose monitor for personnel in interventional radiology

    Energy Technology Data Exchange (ETDEWEB)

    Ban, Nobuhiko; Kusama, Tomoko [Oita University of Nursing and Health Sciences, Oita (Japan); Adachi, Akiko [Oita Medical University, Oita (JP)] [and others

    2000-05-01

    Protection of personnel in interventional radiology is one of the most important issues of radiological protection in medicine. Fluoroscopically guided interventional procedures require the operation near X-ray beam, which brings a considerable hand exposure to the operators. For the purpose of effectual control of their extremity doses, we have developed a real-time extremity dose monitor which is worn on a strap around the wrist. The monitor consists of a silicon semiconductor detector, thin lithium battery and a waterproof frame with a four-digit LED display. Experiment was carried out to examine a response of the monitor to diagnostic X-rays. A practical test was also performed to evaluate usability in the actual interventional procedures. In the experiment, the extremity dose monitor was placed on an arm phantom and exposed to diagnostic X-rays. Readings of the monitor were compared to those of Capintec PS-033 shallow chamber. The monitor was highly sensitive to diagnostic X-rays. It showed a linear response down to doses of a few tens of microsieverts. For high dose-rate exposure, however, a slight decrease in the response was observed, about 10% of counting loss for 80 kV, 40 mA X-ray at one meter from the focus. With regard to energy dependence, variation was within 20% for 60 to 100 kV X-rays. The monitor showed a good angular response in general, except lateral geometry facing the far side from a detector center. In the practical test, hand exposures of medical staff were measured with the extremity dose monitor. They were also asked to fill in a questionnaire regarding size and weight of the monitor, clarity of the display and usefulness. The subjects consisted of physicians, technicians and nurses who engaged in angiography, PTCD, CT-biopsy, barium enema and so on. The readings of the monitor were less than 1 mSv in most cases while 93 mSv was recorded in an extreme case due to direct-beam exposure. In some cases, TLD rings were used together with the

  18. The Relationship Between a Balanced Time Perspective and Self-monitoring of Blood Glucose Among People With Type 1 Diabetes.

    Science.gov (United States)

    Baird, Harriet M; Webb, Thomas L; Martin, Jilly; Sirois, Fuschia M

    2018-05-10

    Self-monitoring of blood glucose helps people with type 1 diabetes to maintain glycemic control and reduce the risk of complications. However, adherence to blood glucose monitoring is often suboptimal. Like many health behaviors, self-monitoring of blood glucose involves exerting effort in the present to achieve future benefits. As such, the present research explored whether individual differences in time perspective-specifically, the extent to which people have a balanced time perspective-are associated with the frequency with which people with type 1 diabetes monitor their blood glucose and, thus, maintain glycemic control. Adults with type 1 diabetes completed measures of time perspective, feelings associated with monitoring, attitudes toward monitoring, and trait self-control. Objective data regarding the frequency with which participants monitored their blood glucose levels and their long-term glycemic control were extracted from their medical records. Hierarchical regression analyses and tests of indirect effects (N = 129) indicated that having a more balanced time perspective was associated with more frequent monitoring of blood glucose and, as a result, better glycemic control. Further analyses (N = 158) also indicated that there was an indirect relationship between balanced time perspective and monitoring of blood glucose via the feelings that participants associated with monitoring and their subsequent attitudes toward monitoring. These findings point to the importance and relevance of time perspective for understanding health-related behavior and may help to inform interventions designed to promote self-monitoring of blood glucose in people with type 1 diabetes.

  19. Off-line and real-time monitoring of acetaminophen photodegradation by an electrochemical sensor.

    Science.gov (United States)

    Berto, Silvia; Carena, Luca; Chiavazza, Enrico; Marletti, Matteo; Fin, Andrea; Giacomino, Agnese; Malandrino, Mery; Barolo, Claudia; Prenesti, Enrico; Vione, Davide

    2018-08-01

    The photochemistry of N-acetyl-para-aminophenol (acetaminophen, APAP) is here investigated by using differential pulse voltammetry (DPV) analysis to monitor APAP photodegradation upon steady-state irradiation. The purpose of this work is to assess the applicability of DPV to monitor the photochemical behaviour of xenobiotics, along with the development of an electrochemical set-up for the real-time monitoring of APAP photodegradation. We here investigated the APAP photoreactivity towards the main photogenerated reactive transients species occurring in sunlit surface waters (hydroxyl radical HO, carbonate radical CO 3 - , excited triplet state of anthraquinone-2-sulfonate used as proxy of the chromophoric DOM, and singlet oxygen 1 O 2 ), and determined relevant kinetic parameters. A standard procedure based on UV detection coupled with liquid chromatography (HPLC-UV) was used under identical experimental conditions to compare and verify the DPV-based results. The latter were in agreement with HPLC data, with the exception of the triplet-sensitized processes. In the other cases, DPV could be used as an alternative to the well-tested but more costly and time-consuming HPLC-UV technique. We have also assessed the reaction rate constant between APAP and HO by real-time DPV, which allowed for the monitoring of APAP photodegradation inside the irradiation chamber. Unfortunately, real-time DPV measurements are likely to be affected by temperature variations of the irradiated samples. Overall, DPV appeared as a fast, cheap and reasonably reliable technique when used for the off-line monitoring of APAP photodegradation. When a suitable real-time procedure is developed, it could become a very straightforward method to study the photochemical behaviour of electroactive xenobiotics. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. Power System Real-Time Monitoring by Using PMU-Based Robust State Estimation Method

    DEFF Research Database (Denmark)

    Zhao, Junbo; Zhang, Gexiang; Das, Kaushik

    2016-01-01

    Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions...... the system real-time states with good robustness and can address several kinds of BD.......-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track...

  1. The new Athens center on data processing from the neutron monitor network in real time

    Directory of Open Access Journals (Sweden)

    Mavromichalaki

    2005-11-01

    Full Text Available The ground-based neutron monitors (NMs record galactic and solar relativistic cosmic rays which can play a useful key role in space weather forecasting, as a result of their interaction with interplanetary disturbances. The Earth's-based neutron monitor network has been used in order to produce a real-time prediction of space weather phenomena. Therefore, the Athens Neutron Monitor Data Processing Center (ANMODAP takes advantage of this unique multi-directional device to solve problems concerning the diagnosis and forecasting of space weather. At this moment there has been a multi-sided use of neutron monitors. On the one hand, a preliminary alert for ground level enhancements (GLEs may be provided due to relativistic solar particles and can be registered around 20 to 30 min before the arrival of the main part of lower energy particles responsible for radiation hazard. To make a more reliable prognosis of these events, real time data from channels of lower energy particles and X-ray intensity from the GOES satellite are involved in the analysis. The other possibility is to search in real time for predictors of geomagnetic storms when they occur simultaneously with Forbush effects, using hourly, on-line accessible neutron monitor data from the worldwide network and applying a special method of processing. This chance of prognosis is only being elaborated and considered here as one of the possible uses of the Neutron Monitor Network for forecasting the arrival of interplanetary disturbance to the Earth. The achievements, the processes and the future results, are discussed in this work.

  2. Real time monitoring of accelerated chemical reactions by ultrasonication-assisted spray ionization mass spectrometry.

    Science.gov (United States)

    Lin, Shu-Hsuan; Lo, Ta-Ju; Kuo, Fang-Yin; Chen, Yu-Chie

    2014-01-01

    Ultrasonication has been used to accelerate chemical reactions. It would be ideal if ultrasonication-assisted chemical reactions could be monitored by suitable detection tools such as mass spectrometry in real time. It would be helpful to clarify reaction intermediates/products and to have a better understanding of reaction mechanism. In this work, we developed a system for ultrasonication-assisted spray ionization mass spectrometry (UASI-MS) with an ~1.7 MHz ultrasonic transducer to monitor chemical reactions in real time. We demonstrated that simply depositing a sample solution on the MHz-based ultrasonic transducer, which was placed in front of the orifice of a mass spectrometer, the analyte signals can be readily detected by the mass spectrometer. Singly and multiply charged ions from small and large molecules, respectively, can be observed in the UASI mass spectra. Furthermore, the ultrasonic transducer used in the UASI setup accelerates the chemical reactions while being monitored via UASI-MS. The feasibility of using this approach for real-time acceleration/monitoring of chemical reactions was demonstrated. The reactions of Girard T reagent and hydroxylamine with steroids were used as the model reactions. Upon the deposition of reactant solutions on the ultrasonic transducer, the intermediate/product ions are readily generated and instantaneously monitored using MS within 1 s. Additionally, we also showed the possibility of using this reactive UASI-MS approach to assist the confirmation of trace steroids from complex urine samples by monitoring the generation of the product ions. Copyright © 2014 John Wiley & Sons, Ltd.

  3. Real time n/γ discrimination for the JET neutron profile monitor

    Energy Technology Data Exchange (ETDEWEB)

    Riva, M., E-mail: marco.riva@enea.it [Associazione EURATOM-ENEA sulla Fusione, C.P. 65, Frascati I-00044, Roma (Italy); Esposito, B.; Marocco, D.; Belli, F. [Associazione EURATOM-ENEA sulla Fusione, C.P. 65, Frascati I-00044, Roma (Italy); Syme, B. [EURATOM/CCFE Fusion Association, OX14 3DB Abingdon (United Kingdom); Giacomelli, L. [Dipartimento di Fisica, Università degli Studi di Milano-Bicocca (Italy); Istituto di Fisica del Plasma, Associazione EURATOM-ENEA-CNR, 20100 Milano (Italy); JET-EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)

    2013-10-15

    Highlights: ► Development of a pulse oriented acquisition system able for the JET neutron profile monitor to separate neutron and gamma pulses. ► Description of the FPGA hardware architecture. ► Comparison between the off-line and real time neutron count rates from the last JET experimental campaign. ► Estimate of the maximum sustainable count rate of the system. ► Statistical analysis of neutron measurements from JET neutron profile monitor and neutron monitors. -- Abstract: The JET neutron profile monitor provides the measurement of the neutron flux along 19 collimated lines of sight from which the neutron emissivity profile can be obtained through reconstruction based on inversion methods. The neutron detectors are liquid organic scintillators featuring n/γ pulse shape discrimination. A recent digital upgrade of the neutron profile monitor acquisition system (200 MSamples/s sampling rate per channel, 14 bit resolution) offers new real-time capabilities. An algorithm performing real-time n/γ discrimination by means of the charge comparison method is implemented in the acquisition system FPGA. The algorithm produces two distinct count rates (n and γ) that are sent to the JET real time network ready for control applications and are simultaneously stored into the JET archive together with all the samples of each pulse. The paper describes the architecture of the FPGA implementation and reports the analysis of data collected during the 2011–2012 JET campaigns. The comparison between the real-time and post-processed (off-line) neutron count rates shows an agreement within 5% for all 19 detectors. Moreover, it is shown that the maximum count rate sustainable by the acquisition system when storing raw data (∼900 kHz as evaluated in laboratory tests) can be extended up to 5 MHz when using the real-time implementation with no local data storage. Finally, a statistical analysis of the ratio between the line-integrated measurements from the neutron profile

  4. A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL

    2011-01-01

    Online time series change detection is a critical component of many monitoring systems, such as space and air-borne remote sensing instruments, cardiac monitors, and network traffic profilers, which continuously analyze observations recorded by sensors. Data collected by such sensors typically has a periodic (seasonal) component. Most existing time series change detection methods are not directly applicable to handle such data, either because they are not designed to handle periodic time series or because they cannot operate in an online mode. We propose an online change detection algorithm which can handle periodic time series. The algorithm uses a Gaussian process based non-parametric time series prediction model and monitors the difference between the predictions and actual observations within a statistically principled control chart framework to identify changes. A key challenge in using Gaussian process in an online mode is the need to solve a large system of equations involving the associated covariance matrix which grows with every time step. The proposed algorithm exploits the special structure of the covariance matrix and can analyze a time series of length T in O(T^2) time while maintaining a O(T) memory footprint, compared to O(T^4) time and O(T^2) memory requirement of standard matrix manipulation methods. We experimentally demonstrate the superiority of the proposed algorithm over several existing time series change detection algorithms on a set of synthetic and real time series. Finally, we illustrate the effectiveness of the proposed algorithm for identifying land use land cover changes using Normalized Difference Vegetation Index (NDVI) data collected for an agricultural region in Iowa state, USA. Our algorithm is able to detect different types of changes in a NDVI validation data set (with ~80% accuracy) which occur due to crop type changes as well as disruptive changes (e.g., natural disasters).

  5. Real-time monitoring of atom vapor concentration with laser absorption spectroscopy

    International Nuclear Information System (INIS)

    Fan Fengying; Gao Peng; Jiang Tao

    2012-01-01

    The technology of laser absorption spectroscopy was used for real-time monitoring of gadolinium atom vapor concentration measurement and the solid state laser pumped ring dye laser was used as optical source. The optical fiber was taken to improve the stability of laser transmission. The multi-pass absorption technology combined with reference optical signal avoided the influence of laser power fluctuation. The experiment result shows that the system based on this detection method has a standard error of 4%. It is proved that the monitoring system provides reliable data for atom vapor laser isotope separation process and the separation efficiency can be improved. (authors)

  6. Education technology with continuous real time monitoring of the current functional and emotional students' states

    Science.gov (United States)

    Alyushin, M. V.; Kolobashkina, L. V.

    2017-01-01

    The education technology with continuous monitoring of the current functional and emotional students' states is suggested. The application of this technology allows one to increase the effectiveness of practice through informed planning of the training load. For monitoring the current functional and emotional students' states non-contact remote technologies of person bioparameters registration are encouraged to use. These technologies are based on recording and processing in real time the main person bioparameters in a purely passive mode. Experimental testing of this technology has confirmed its effectiveness.

  7. Combining real-time monitoring and knowledge-based analysis in MARVEL

    Science.gov (United States)

    Schwuttke, Ursula M.; Quan, A. G.; Angelino, R.; Veregge, J. R.

    1993-01-01

    Real-time artificial intelligence is gaining increasing attention for applications in which conventional software methods are unable to meet technology needs. One such application area is the monitoring and analysis of complex systems. MARVEL, a distributed monitoring and analysis tool with multiple expert systems, was developed and successfully applied to the automation of interplanetary spacecraft operations at NASA's Jet Propulsion Laboratory. MARVEL implementation and verification approaches, the MARVEL architecture, and the specific benefits that were realized by using MARVEL in operations are described.

  8. Real-time geomagnetic monitoring for space weather-related applications: Opportunities and challenges

    Science.gov (United States)

    Love, Jeffrey J.; Finn, Carol A.

    2017-07-01

    An examination is made of opportunities and challenges for enhancing global, real-time geomagnetic monitoring that would be beneficial for a variety of operational projects. This enhancement in geomagnetic monitoring can be attained by expanding the geographic distribution of magnetometer stations, improving the quality of magnetometer data, increasing acquisition sampling rates, increasing the promptness of data transmission, and facilitating access to and use of the data. Progress will benefit from new partnerships to leverage existing capacities and harness multisector, cross-disciplinary, and international interests.

  9. Adequate technologies for wireless real-time dose rate monitoring for off-site emergency management

    International Nuclear Information System (INIS)

    Dielmann, R.; Buerkin, W.

    2003-01-01

    Full text: What are the requirements for off-site gamma dose rate monitoring systems? What are the pros and cons of available communication technologies? This report gives an overview of modern communication techniques and their applicability for reliable real-time data acquisition as basis for off-site nuclear emergency management. The results of three years operating experience with a wireless gamma dose rate monitoring system, installed around the NPPs of KURSK, KALININ and BALAKOVA (Russia) in the year 2000, are shown. (author)

  10. A matter of timing: harm reduction in learned helplessness.

    Science.gov (United States)

    Richter, Sophie Helene; Sartorius, Alexander; Gass, Peter; Vollmayr, Barbara

    2014-11-03

    Learned helplessness has excellent validity as an animal model for depression, but problems in reproducibility limit its use and the high degree of stress involved in the paradigm raises ethical concerns. We therefore aimed to identify which and how many trials of the learned helplessness paradigm are necessary to distinguish between helpless and non-helpless rats. A trial-by-trial reanalysis of tests from 163 rats with congenital learned helplessness or congenital non-learned helplessness and comparison of 82 rats exposed to inescapable shock with 38 shock-controls revealed that neither the first test trials, when rats showed unspecific hyperlocomotion, nor trials of the last third of the test, when almost all animals responded quickly to the stressor, contributed to sensitivity and specificity of the test. Considering only trials 3-10 improved the classification of helpless and non-helpless rats. The refined analysis allows abbreviation of the test for learned helplessness from 15 trials to 10 trials thereby reducing pain and stress of the experimental animals without losing statistical power.

  11. Learning from your mistakes: The functional value of spontaneous error monitoring in aphasia

    Directory of Open Access Journals (Sweden)

    Erica L. Middleton

    2014-04-01

    Ex. 4.\t(T = umbrella “umbelella, umbrella”: Phonological error; DetCorr We used mixed effects logistic regression to assess whether the log odds of changing from error to correct was predicted by monitoring status of the error (DetCorr vs. NoDet; DetNoCorr vs. NoDet; whether the monitoring benefit interacted with direction of change (forward, backward; and whether effects varied by error type. Figure 1 (top shows that the proportion accuracy change was higher for DetCorr, relative to NoDet, consistent with a monitoring benefit. The difference in log odds was significant for semantic errors in both directions (forward: coeff. = -1.73; z= -7.78; p < .001; backward: coeff = -0.92; z= -3.60; p < .001, and for phonological errors in both directions (forward: coeff. = -0.74; z= -2.73; p=.006; backward : coeff. = -.76; z = -2.73; p = .006. The difference between DetNoCorr and NoDet was not significant in any condition. Figure 1 (bottom shows that for Semantic errors, there was a directional asymmetry favoring the Forward condition (interaction: coeff. = .79; z = 2.32; p = .02. Phonological errors, in contrast, produced comparable effects in Forward and Backward direction. The results demonstrated a benefit for errors that were detected and corrected. This monitoring benefit was present in both the forward and backward direction, supporting the Strength hypothesis. Of greatest interest, the monitoring benefit for Semantic errors was greater in the forward than backward direction, indicating a role for learning.

  12. Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

    Science.gov (United States)

    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.

  13. Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

    Directory of Open Access Journals (Sweden)

    Ingvar Eide

    Full Text Available 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.

  14. DeepRT: deep learning for peptide retention time prediction in proteomics

    OpenAIRE

    Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

    2017-01-01

    Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

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

    Science.gov (United States)

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

    2018-04-01

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

  16. Real Time Monitoring of Containerless Microreactions in Acoustically Levitated Droplets via Ambient Ionization Mass Spectrometry.

    Science.gov (United States)

    Crawford, Elizabeth A; Esen, Cemal; Volmer, Dietrich A

    2016-09-06

    Direct in-droplet (in stillo) microreaction monitoring using acoustically levitated micro droplets has been achieved by combining acoustic (ultrasonic) levitation for the first time with real time ambient tandem mass spectrometry (MS/MS). The acoustic levitation and inherent mixing of microliter volumes of reactants (3 μL droplets), yielding total reaction volumes of 6 μL, supported monitoring the acid-catalyzed degradation reaction of erythromycin A. This reaction was chosen to demonstrate the proof-of-principle of directly monitoring in stillo microreactions via hyphenated acoustic levitation and ambient ionization mass spectrometry. The microreactions took place completely in stillo over 30, 60, and 120 s within the containerless stable central pressure node of an acoustic levitator, thus readily promoting reaction miniaturization. For the evaluation of the miniaturized in stillo reactions, the degradation reactions were also carried out in vials (in vitro) with a total reaction volume of 400 μL. The reacted in vitro mixtures (6 μL total) were similarly introduced into the acoustic levitator prior to ambient ionization MS/MS analysis. The in stillo miniaturized reactions provided immediate real-time snap-shots of the degradation process for more accurate reaction monitoring and used a fraction of the reactants, while the larger scale in vitro reactions only yielded general reaction information.

  17. Real time neutron flux monitoring using Rh self powered neutron detector

    International Nuclear Information System (INIS)

    Juna, Byung Jin; Lee, Byung Chul; Park, Sang Jun; Jung, Hoan Sung

    2012-01-01

    Rhodium (Rh) self powered neutron detectors (SPNDs) are widely used for on line monitoring of local neutron flux. Its signal is slower than the actual variation of neutron flux owing to a delayed β decay of the Rh activation product, but real time monitoring is possible by solving equations between the neutron reaction rate in the detector and its signal. While the measuring system is highly reliable, the accuracy depends on the method solving the equations and accuracy of the parameters in the equations. The uncertain parameters are the contribution of gamma rays to the signal, and the branching ratios of Rh 104 and Rh 104m after the neutron absorption of Rh 103. Real time neutron flux monitoring using Rh SPNDs has been quite successful for neutron transmutation doping (NTD) at HANARO. We revisited the initial data used for the verification of a real time monitoring system, to refine algorithm for a better solution and to check the parameters for correctness. As a result, we suggest an effective way to determine the prompt parameter

  18. Real time neutron flux monitoring using Rh self powered neutron detector

    Energy Technology Data Exchange (ETDEWEB)

    Juna, Byung Jin; Lee, Byung Chul; Park, Sang Jun; Jung, Hoan Sung [KAERI, Daejeon (Korea, Republic of)

    2012-10-15

    Rhodium (Rh) self powered neutron detectors (SPNDs) are widely used for on line monitoring of local neutron flux. Its signal is slower than the actual variation of neutron flux owing to a delayed {beta} decay of the Rh activation product, but real time monitoring is possible by solving equations between the neutron reaction rate in the detector and its signal. While the measuring system is highly reliable, the accuracy depends on the method solving the equations and accuracy of the parameters in the equations. The uncertain parameters are the contribution of gamma rays to the signal, and the branching ratios of Rh 104 and Rh 104m after the neutron absorption of Rh 103. Real time neutron flux monitoring using Rh SPNDs has been quite successful for neutron transmutation doping (NTD) at HANARO. We revisited the initial data used for the verification of a real time monitoring system, to refine algorithm for a better solution and to check the parameters for correctness. As a result, we suggest an effective way to determine the prompt parameter.

  19. Field Demonstration of Real-Time Wind Turbine Foundation Strain Monitoring.

    Science.gov (United States)

    Rubert, Tim; Perry, Marcus; Fusiek, Grzegorz; McAlorum, Jack; Niewczas, Pawel; Brotherston, Amanda; McCallum, David

    2017-12-31

    Onshore wind turbine foundations are generally over-engineered as their internal stress states are challenging to directly monitor during operation. While there are industry drivers to shift towards more economical foundation designs, making this transition safely will require new monitoring techniques, so that the uncertainties around structural health can be reduced. This paper presents the initial results of a real-time strain monitoring campaign for an operating wind turbine foundation. Selected reinforcement bars were instrumented with metal packaged optical fibre strain sensors prior to concrete casting. In this paper, we outline the sensors' design, characterisation and installation, and present 67 days of operational data. During this time, measured foundation strains did not exceed 95 μ ϵ , and showed a strong correlation with both measured tower displacements and the results of a foundation finite element model. The work demonstrates that real-time foundation monitoring is not only achievable, but that it has the potential to help operators and policymakers quantify the conservatism of their existing design codes.

  20. Long-term real-time structural health monitoring using wireless smart sensor

    Science.gov (United States)

    Jang, Shinae; Mensah-Bonsu, Priscilla O.; Li, Jingcheng; Dahal, Sushil

    2013-04-01

    Improving the safety and security of civil infrastructure has become a critical issue for decades since it plays a central role in the economics and politics of a modern society. Structural health monitoring of civil infrastructure using wireless smart sensor network has emerged as a promising solution recently to increase structural reliability, enhance inspection quality, and reduce maintenance costs. Though hardware and software framework are well prepared for wireless smart sensors, the long-term real-time health monitoring strategy are still not available due to the lack of systematic interface. In this paper, the Imote2 smart sensor platform is employed, and a graphical user interface for the long-term real-time structural health monitoring has been developed based on Matlab for the Imote2 platform. This computer-aided engineering platform enables the control, visualization of measured data as well as safety alarm feature based on modal property fluctuation. A new decision making strategy to check the safety is also developed and integrated in this software. Laboratory validation of the computer aided engineering platform for the Imote2 on a truss bridge and a building structure has shown the potential of the interface for long-term real-time structural health monitoring.

  1. Clean Air Markets - Monitoring Surface Water Chemistry

    Science.gov (United States)

    Learn about how EPA uses Long Term Monitoring (LTM) and Temporily Integrated Monitoring of Ecosystems (TIME) to track the effect of the Clean Air Act Amendments on acidity of surface waters in the eastern U.S.

  2. Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

    Science.gov (United States)

    Niazmardi, S.; Safari, A.; Homayouni, S.

    2017-09-01

    Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

  3. A GPS-based Real-time Road Traffic Monitoring System

    Science.gov (United States)

    Tanti, Kamal Kumar

    In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.

  4. Alternate mode for data acquisition and real-time monitoring system based on CAMAC system

    International Nuclear Information System (INIS)

    Luo, J.R.; Wei, P.J.; Li, G.M.; Wang, H.

    2006-01-01

    Long discharges (about 250 s) have been achieved on HT-7 tokamak experiments in the Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP). And in the next generation tokamaks like ITER , KSTAR and EAST , the pulses will be about 1000 s. In such steady-state operation, we have to upgrade the CAMAC-based data acquisition system, with higher sampling rates and longer acquisition times. It is necessary to monitor the plasma parameters in real-time so that the operators can change the operational conditions during the discharge to maintain the plasma. A design of the system named alternant data acquisition and real-time monitoring system for steady-state tokamak operation based on CAMAC system has been setup in ASIPP. The application of this system has been demonstrated in the HT-7 and TRIAM-1M tokamaks during their 2004 experiment campaigns

  5. Time-Lapse Monitoring of Subsurface Fluid Flow using Parsimonious Seismic Interferometry

    KAUST Repository

    Hanafy, Sherif

    2017-04-21

    A typical small-scale seismic survey (such as 240 shot gathers) takes at least 16 working hours to be completed, which is a major obstacle in case of time-lapse monitoring experiments. This is especially true if the subject that needs to be monitored is rapidly changing. In this work, we will discuss how to decrease the recording time from 16 working hours to less than one hour of recording. Here, the virtual data has the same accuracy as the conventional data. We validate the efficacy of parsimonious seismic interferometry with the time-lapse mentoring idea with field examples, where we were able to record 30 different data sets within a 2-hour period. The recorded data are then processed to generate 30 snapshots that shows the spread of water from the ground surface down to a few meters.

  6. Tropical Forest Monitoring in Southeast Asia Using Remotely Sensed Optical Time Series

    DEFF Research Database (Denmark)

    Grogan, Kenneth Joseph

    of forest cover using satellite remote sensing technology. Recently, there has been a shift in data protection policy where rich archives of satellite imagery are now freely available. This has spurred a new era in satellite-based forest monitoring leading to advancements in optical time series processing...... markets. At the Landsat 30-m resolution, annual time series coupled with linear segmentation using LandTrendr was found to be an effective approach for monitoring forest disturbance, with moderate to high accuracies, depending on forest type. At the MODIS 250-m resolution, intra-annual time series...... global rubber markets can be linked to forest cover change, the effects of land policy in Cambodia, and beyond, have also had a major influence. It remains to be seen if intervention initiatives such as REDD+ can materialise over the coming years to make a meaningful contribution to tropical forest...

  7. Gun Launch System: efficient and low-cost means of research and real-time monitoring

    Science.gov (United States)

    Degtyarev, Alexander; Ventskovsky, Oleg; Korostelev, Oleg; Yakovenko, Peter; Kanevsky, Valery; Tselinko, Alexander

    2005-08-01

    The Gun Launch System with a reusable sub-orbital launch vehicle as a central element is proposed by a consortium of several Ukrainian high-tech companies as an effective, fast-response and low-cost means of research and real-time monitoring. The system is described in details, with the emphasis on its most important advantages. Multiple applications of the system are presented, including ones for the purposes of microgravity research; chemical, bacteriological and radiation monitoring and research of atmosphere and ionosphere; operational monitoring of natural and man-made disasters, as well as for some other areas of great practical interest. The current level of the system development is given, and the way ahead towards full system's implementation is prescribed.

  8. Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes

    Energy Technology Data Exchange (ETDEWEB)

    Chou, Q B [Ontario Hydro, Toronto, ON (Canada); Mylopoulos, J [Toronto Univ., ON (Canada); Opala, J [CAE Electronics, Montreal, Quebec (Canada)

    1997-12-31

    The complexity of modern industrial processes and the large amount of data available to their operators make it difficult to monitor their status and diagnose potential failures. Although there have been many attempts to apply knowledge-based technologies to this problem, there have not been any convincing success. This paper describes recent experiences with a technology that combines artificial intelligence and simulation techniques for building real-time monitoring and diagnosis systems. A prototype system for monitoring and diagnosing the feedwater system of a nuclear power plant built using this technology is described. The paper then describes several interesting classes of failures that the prototype is capable of diagnosing. (author). 19 refs, 6 figs.

  9. Invited commentary: Monitoring fecundity over time, if we do it, then let us do it right

    DEFF Research Database (Denmark)

    Olsen, Jørn; Rachootin, Pamela

    2003-01-01

    A number of investigators have pointed to the possibility of a secular decline in human fecundity due to changes in sperm concentration. It is unlikely that any historical trends will be definitively quantified, but a good case can be made for more precise monitoring of this phenomenon in the fut......A number of investigators have pointed to the possibility of a secular decline in human fecundity due to changes in sperm concentration. It is unlikely that any historical trends will be definitively quantified, but a good case can be made for more precise monitoring of this phenomenon...... in the future. Such monitoring would be justified on the grounds of the importance of early detection of environmental effects on the capacity of humans to reproduce. Establishing a surveillance system that will be sensitive enough to detect changes in fecundity over time is, however, a challenging enterprise...

  10. Monitoring Acidophilic Microbes with Real-Time Polymerase Chain Reaction (PCR) Assays

    Energy Technology Data Exchange (ETDEWEB)

    Frank F. Roberto

    2008-08-01

    Many techniques that are used to characterize and monitor microbial populations associated with sulfide mineral bioleaching require the cultivation of the organisms on solid or liquid media. Chemolithotrophic species, such as Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans, or thermophilic chemolithotrophs, such as Acidianus brierleyi and Sulfolobus solfataricus can grow quite slowly, requiring weeks to complete efforts to identify and quantify these microbes associated with bioleach samples. Real-time PCR (polymerase chain reaction) assays in which DNA targets are amplified in the presence of fluorescent oligonucleotide primers, allowing the monitoring and quantification of the amplification reactions as they progress, provide a means of rapidly detecting the presence of microbial species of interest, and their relative abundance in a sample. This presentation will describe the design and use of such assays to monitor acidophilic microbes in the environment and in bioleaching operations. These assays provide results within 2-3 hours, and can detect less than 100 individual microbial cells.

  11. Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes

    International Nuclear Information System (INIS)

    Chou, Q.B.; Mylopoulos, J.; Opala, J.

    1996-01-01

    The complexity of modern industrial processes and the large amount of data available to their operators make it difficult to monitor their status and diagnose potential failures. Although there have been many attempts to apply knowledge-based technologies to this problem, there have not been any convincing success. This paper describes recent experiences with a technology that combines artificial intelligence and simulation techniques for building real-time monitoring and diagnosis systems. A prototype system for monitoring and diagnosing the feedwater system of a nuclear power plant built using this technology is described. The paper then describes several interesting classes of failures that the prototype is capable of diagnosing. (author). 19 refs, 6 figs

  12. A real-time stack radioactivity monitoring system and dose projection program

    Energy Technology Data Exchange (ETDEWEB)

    Hull, A.P.; Michael, P.A. [Brookhaven National Laboratory, Upton, NY (United States); Bernstein, H.J. [Bernstein & Sons, Bellport, NY (United States)

    1995-02-01

    At Brookhaven National Laboratory, a commercial Low- and High-Range Air Effluent Monitor has become operational at the 60 Mw (t) High Flux Beam Reactor. Its output data is combined with that from ground-level and elevated meteorological sensors to provide a real-time projection of the down-wind dose rates from noble gases and radioiodines released from the HFBR`s 100 m stack. The output of the monitor, and the meteorological sensors and the dose projections can be viewed at emergency response terminals located in the Reactor Control Room, its Technical Support Center and at the laboratory`s separately located Meteorological Station and Monitoring and Assessment Center.

  13. Technology survey for real-time monitoring of plutonium in a vitrifier off-gas system

    International Nuclear Information System (INIS)

    Berg, J.M.; Veirs, D.K.

    1996-01-01

    We surveyed several promising measurement technologies for the real-time monitoring of plutonium in a vitrifier off-gas system. The vitrifier is being developed by Westinghouse Savannah River Corp. and will be used to demonstrate vitrification of plutonium dissolved in nitric acid for fissile material disposition. The risk of developing a criticality hazard in the off-gas processing equipment can be managed by using available measurement technologies. We identified several potential technologies and methods for detecting plutonium that are sensitive enough to detect the accumulation of a mass sufficient to form a criticality hazard. We recommend gross alpha-monitoring technologies as the most promising option for Westinghouse Savannah River Corp. to consider because that option appears to require the least additional development. We also recommend further consideration for several other technologies because they offer specific advantages and because gross alpha-monitoring could prove unsuitable when tested for this specific application

  14. Real-time stability monitoring method for boiling water reactor nuclear power plants

    International Nuclear Information System (INIS)

    Fukunishi, K.; Suzuki, S.

    1987-01-01

    A method for real-time stability monitoring is developed for supervising the steady-state operation of a boiling water reactor core. The decay ratio of the reactor power fluctuation is determined by measuring only the output neutron noise. The concept of an inverse system is introduced to identify the dynamic characteristics of the reactor core. The adoption of an adaptive digital filter is useful in real-time identification. A feasibility test that used measured output noise as an indication of reactor power suggests that this method is useful in a real-time stability monitoring system. Using this method, the tedious and difficult work for modeling reactor core dynamics can be reduced. The method employs a simple algorithm that eliminates the need for stochastic computation, thus making the method suitable for real-time computation with a simple microprocessor. In addition, there is no need to disturb the reactor core during operation. Real-time stability monitoring using the proposed algorithm may allow operation under less stable margins

  15. Real-time power plant monitoring and verification and validation issues

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.; Tuerkcan, E.

    1993-03-01

    By means of the advances in the computer technology, the implementation of a real-time power plant monitoring and dynamic signal analysis system is described. As hardware and software, the system has several essential components to perform the task. Among these, mention may be made of a remote-controlled data acquisition system, a fast data processing system and a dynamic signal analysis system. For a complex system like an NPP, the system verification and validation is an important issue as the plant operation involves many engineering disciplines and also the 'soft sciences'. Additionally, the real-time requirements impose substantial time limitation for the implementation of tasks. The system V and V is accomplished partly by means of V and V of the system components which are monitored by the help of sensory signals. Therefore, an essential part of the V and V task involves the real-time analyses of the data provided by these signals. In this respect the NPP real-time monitoring system described possesses the required design features to carry out this task which provides enhanced reliability and availability in plant operation. (orig./HP)

  16. Towards Real-Time Speech Emotion Recognition for Affective E-Learning

    Science.gov (United States)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2016-01-01

    This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…

  17. Radiation environmental real-time monitoring and dispersion modeling: A comprehensive solution

    International Nuclear Information System (INIS)

    Kovacik, A.; Bartokova, I.; Omelka, J.; Melicherova, T.

    2014-01-01

    The system of real-time radiation monitoring provided by MicroStep-MIS is a turn-key solution for measurement, acquisition, processing, reporting, archiving and displaying of various radiation data. At the level of measurements, the monitoring stations can be equipped with various devices from radiation probes, measuring the actual ambient gamma dose rate, to fully automated aerosol monitors, returning analysis results of natural and manmade radionuclides concentrations in the air. Using data gathered by our radiation probes RPSG-05 integrated into monitoring network of Crisis Management of the Slovak Republic and into monitoring network of Slovak Hydrometeorological Institute, we demonstrate its reliability and long-term stability of measurements. Data from RPSG-05 probes and GammaTracer probes, both of these types are used in the SHI network, are compared. The sensitivity of RPSG-05 is documented on data where changes of dose rate are caused by precipitation. Qualities of RPSG-05 probe are illustrated also on example of its use in radiation monitoring network in the United Arab Emirates. A more detailed information about radioactivity of the atmosphere can be obtained by using spectrometric detectors (e.g. scintillation detectors) which, besides gamma dose rate values, offer also a possibility to identify different radionuclides. However, this possibility is limited by technical parameters of detector like energetic resolution and detection efficiency in given geometry of measurement. A clearer information with less doubts can be obtained from aerosol monitors with a built-in silicon detector of alpha and beta particles and with an electrically cooled HPGe detector dedicated for gamma-ray spectrometry, which is performed during the sampling. Data from a complex radiation monitoring network can be used, together with meteorological data, in radiation dispersion model by MicroStep-MIS. This model serves for simulation of atmospheric propagation of radionuclides

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

    Science.gov (United States)

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

    2017-09-21

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

  19. On-line, real-time monitoring for petrochemical and pipeline process control applications

    Energy Technology Data Exchange (ETDEWEB)

    Kane, Russell D.; Eden, D.C.; Cayard, M.S.; Eden, D.A.; Mclean, D.T. [InterCorr International, Inc., 14503 Bammel N. Houston, Suite 300, Houston Texas 77014 (United States); Kintz, J. [BASF Corporation, 602 Copper Rd., Freeport, Texas 77541 (United States)

    2004-07-01

    Corrosion problems in petroleum and petrochemical plants and pipeline may be inherent to the processes, but costly and damaging equipment losses are not. With the continual drive to increase productivity, while protecting both product quality, safety and the environment, corrosion must become a variable that can be continuously monitored and assessed. This millennium has seen the introduction of new 'real-time', online measurement technologies and vast improvements in methods of electronic data handling. The 'replace when it fails' approach is receding into a distant memory; facilities management today is embracing new technology, and rapidly appreciating the value it has to offer. It has offered the capabilities to increase system run time between major inspections, reduce the time and expense associated with turnaround or in-line inspections, and reduce major upsets which cause unplanned shut downs. The end result is the ability to know on a practical basis of how 'hard' facilities can be pushed before excessive corrosion damage will result, so that process engineers can understand the impact of their process control actions and implement true asset management. This paper makes reference to use of a online, real-time electrochemical corrosion monitoring system - SmartCET 1- in a plant running a mostly organic process media. It also highlights other pertinent examples where similar systems have been used to provide useful real-time information to detect system upsets, which would not have been possible otherwise. This monitoring/process control approach has operators and engineers to see, for the first time, changes in corrosion behavior caused by specific variations in process parameters. Process adjustments have been identified that reduce corrosion rates while maintaining acceptable yields and quality. The monitoring system has provided a new window into the chemistry of the process, helping chemical engineers improve their process

  20. Noninvasive Strategy Based on Real-Time in Vivo Cataluminescence Monitoring for Clinical Breath Analysis.

    Science.gov (United States)

    Zhang, Runkun; Huang, Wanting; Li, Gongke; Hu, Yufei

    2017-03-21

    The development of noninvasive methods for real-time in vivo analysis is of great significant, which provides powerful tools for medical research and clinical diagnosis. In the present work, we described a new strategy based on cataluminescence (CTL) for real-time in vivo clinical breath analysis. To illustrate such strategy, a homemade real-time CTL monitoring system characterized by coupling an online sampling device with a CTL sensor for sevoflurane (SVF) was designed, and a real-time in vivo method for the monitoring of SVF in exhaled breath was proposed. The accuracy of the method was evaluated by analyzing the real exhaled breath samples, and the results were compared with those obtained by GC/MS. The measured data obtained by the two methods were in good agreement. Subsequently, the method was applied to real-time monitoring of SVF in exhaled breath from rat models of the control group to investigate elimination pharmacokinetics. In order to further probe the potential of the method for clinical application, the elimination pharmacokinetics of SVF from rat models of control group, liver fibrosis group alcohol liver group, and nonalcoholic fatty liver group were monitored by the method. The raw data of pharmacokinetics of different groups were normalized and subsequently subjected to linear discriminant analysis (LDA). These data were transformed to canonical scores which were visualized as well-clustered with the classification accuracy of 100%, and the overall accuracy of leave-one-out cross-validation procedure is 88%, thereby indicating the utility of the potential of the method for liver disease diagnosis. Our strategy undoubtedly opens up a new door for real-time clinical analysis in a pain-free and noninvasive way and also guides a promising development direction for CTL.

  1. A real time status monitor for transistor bank driver power limit resistor in boost injection kicker power supply

    Energy Technology Data Exchange (ETDEWEB)

    Mi, J.; Tan, Y.; Zhang, W.

    2011-03-28

    For years suffering of Booster Injection Kicker transistor bank driver regulator troubleshooting, a new real time monitor system has been developed. A simple and floating circuit has been designed and tested. This circuit monitor system can monitor the driver regulator power limit resistor status in real time and warn machine operator if the power limit resistor changes values. This paper will mainly introduce the power supply and the new designed monitoring system. This real time resistor monitor circuit shows a useful method to monitor some critical parts in the booster pulse power supply. After two years accelerator operation, it shows that this monitor works well. Previously, we spent a lot of time in booster machine trouble shooting. We will reinstall all 4 PCB into Euro Card Standard Chassis when the power supply system will be updated.

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

    Science.gov (United States)

    Mariprasath, T.; Kirubakaran, V.

    2018-05-01

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

  3. The Piston Compressor: The Methodology of the Real-Time Condition Monitoring

    International Nuclear Information System (INIS)

    Naumenko, A P; Kostyukov, V N

    2012-01-01

    The methodology of a diagnostic signal processing, a function chart of the monitoring system are considered in the article. The methodology of monitoring and diagnosing is based on measurement of indirect processes' parameters (vibroacoustic oscillations) therefore no more than five sensors is established on the cylinder, measurement of direct structural and thermodynamic parameters is envisioned as well. The structure and principle of expert system's functioning of decision-making is given. Algorithm of automatic expert system includes the calculation diagnostic attributes values based on their normative values, formation sets of diagnostic attributes that correspond to individual classes to malfunction, formation of expert system messages. The scheme of a real-time condition monitoring system for piston compressors is considered. The system have consistently-parallel structure of information-measuring equipment, which allows to measure the vibroacoustic signal for condition monitoring of reciprocating compressors and modes of its work. Besides, the system allows to measure parameters of other physical processes, for example, system can measure and use for monitoring and statements of the diagnosis the pressure in decreasing spaces (the indicator diagram), the inlet pressure and flowing pressure of each cylinder, inlet and delivery temperature of gas, valves temperature, position of a rod, leakage through compression packing and others.

  4. Cyber Dating Abuse: Investigating Digital Monitoring Behaviors Among Adolescents From a Social Learning Perspective.

    Science.gov (United States)

    Van Ouytsel, Joris; Ponnet, Koen; Walrave, Michel

    2017-07-01

    Just as with other forms of abuse such as bullying, dating violence is no longer limited to physical spaces. Several forms of dating violence can also be perpetrated by means of technology. Few studies have used a theoretical perspective to investigate cyber dating abuse. This study addresses this gap in the literature by focusing on the perpetration of digital monitoring behaviors-a form of cyber dating abuse-from a social learning perspective. We investigate the extent to which perceived social norms about cyber dating abuse, witnessing controlling behaviors among parents, and endorsing gender stereotypes are linked with adolescents' engagement in digital monitoring behaviors. The study draws on data from 466 secondary school students (71.0% girls, n = 331) aged between 16 and 22 years ( M = 17.99 years, SD = 0.92) in Flanders, Belgium, who were in a romantic relationship. Linear regression analysis indicates that being female, being older, the perceived social norms of peers, the endorsement of gender stereotypes, and having observed intrusive controlling behaviors by the father are significantly and positively related to adolescents' perpetration of digital monitoring behaviors. The findings have implications for practice and underscore the need for prevention efforts to address and lower the influence of these perceived social norms. Further implications include the need for prevention efforts to focus on diminishing the impact of gender stereotypical attitudes and the influence of witnessing controlling behaviors within the family context on cyber dating abuse perpetration.

  5. Adventures in Citizen Science: Lessons learned engaging volunteer water quality monitors for over 30 years.

    Science.gov (United States)

    Schloss, J. A.

    2012-12-01

    The New Hampshire Lakes Lay Monitoring Program was originally designed by faculty at the University of New Hampshire in 1979 to provide the capacity to better monitor for long-term lake water quality changes and trends. As participants became educated, empowered and engaged the program soon evolved to also become a participatory research enterprise. This resulted in not only providing useful information for informed local stewardship and protection at the local level but also for state and region-wide decision-making, state and federal assessments/reporting and advancing our understanding of lake and watershed science. Our successes and failures have been more dependent on understanding the particular human dimensions that influence our volunteers and less to do with the typical project management, quality assurance, and communication concerns we typically deal with in professional based research efforts. Our participants are extremely diverse in terms of their life experiences, interests and motivations so the key to long-term commitment and high quality participation is understanding the difference between a citizen monitor and your archetypical research technician or student. This presentation will highlight some important lessons learned on how to involve various types of volunteers from school groups to retirees, as well as particular approaches and concerns regarding program management, retention, quality control and communications.

  6. Food Gardening and Intergenerational Learning in Times of ...

    African Journals Online (AJOL)

    The focus of discussion is the intergenerational interactions and learning ... pastoralism and, to a lesser degree, cultivation (Mayer, 1971; Mostert, 1992). ... discouraged about the hard physical work and rather limited economic ... in the Amanzi for Food project, a middle-aged female participant, Mrs Peters, has involved a.

  7. Real-Time Barcode Detection and Classification Using Deep Learning

    DEFF Research Database (Denmark)

    Hansen, Daniel Kold; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

    2017-01-01

    Barcodes, in their different forms, can be found on almost any packages available in the market. Detecting and then decoding of barcodes have therefore great applications. We describe how to adapt the state-of-the- art deep learning-based detector of You Only Look Once (YOLO) for the purpose...

  8. Food Gardening and Intergenerational Learning in Times of ...

    African Journals Online (AJOL)

    Uncertainty is a universal phenomenon, a lived experience, an unease about acting ... uncertainty through mediations of knowledge, the formation of new social relations and ... Environmental Affairs and Tourism, 53% of young people in the country are ... Bubomi learning network connected to the Amanzi for Food project.

  9. Application of rule-based data mining techniques to real time ATLAS Grid job monitoring data

    CERN Document Server

    Ahrens, R; The ATLAS collaboration; Kalinin, S; Maettig, P; Sandhoff, M; dos Santos, T; Volkmer, F

    2012-01-01

    The Job Execution Monitor (JEM) is a job-centric grid job monitoring software developed at the University of Wuppertal and integrated into the pilot-based “PanDA” job brokerage system leveraging physics analysis and Monte Carlo event production for the ATLAS experiment on the Worldwide LHC Computing Grid (WLCG). With JEM, job progress and grid worker node health can be supervised in real time by users, site admins and shift personnel. Imminent error conditions can be detected early and countermeasures can be initiated by the Job’s owner immideatly. Grid site admins can access aggregated data of all monitored jobs to infer the site status and to detect job and Grid worker node misbehaviour. Shifters can use the same aggregated data to quickly react to site error conditions and broken production tasks. In this work, the application of novel data-centric rule based methods and data-mining techniques to the real time monitoring data is discussed. The usage of such automatic inference techniques on monitorin...

  10. A Real-Time Data Monitoring and Accumulation System for Dynamic Studies with Radionuclides

    Energy Technology Data Exchange (ETDEWEB)

    Ammann, W.; Doll, J.; Lorenz, W. J.; Ostertag, H.; Adam, W. E.; Scheer, K. E. [German Cancer Research Centre, Institute of Nuclear Medicine, Heidelberg, Federal Republic of Germany (Germany)

    1971-02-15

    A multipurpose digital data monitoring and accumulation system is described. The central unit of the system is a PDP-8 computer with a 12K memory. The system contains furthermore a multipurpose digital input/output register for low data rates, a fourfold and a twofold ADC connected to the high-speed multiplexor unit of the PDP-8 and a digital timet. Data from various process peripheries are recorded on a nine-track IBM compatible Ampex tape recorder. When two co-ordinates are recorded the system is used in the ''add-one-to-storage'' mode. In the case of more than two co-ordinates the data are stored in the sequential mode, event by event. A dialogue real-time monitor program in assembler language was developed to control the process peripheries. The 4K-Fortran operating system was modified in such a way that monitor subroutines were called into the Fortran program without loss of the real-time properties of the monitor system during a Fortran run. The use of the system for lung function studies with an Anger-type scintillation camera and {sup 133}Xe is discussed as an example of the application of the system. (author)

  11. Real-time monitoring of emissions from monoethanolamine-based industrial scale carbon capture facilities.

    Science.gov (United States)

    Zhu, Liang; Schade, Gunnar Wolfgang; Nielsen, Claus Jørgen

    2013-12-17

    We demonstrate the capabilities and properties of using Proton Transfer Reaction time-of-flight mass spectrometry (PTR-ToF-MS) to real-time monitor gaseous emissions from industrial scale amine-based carbon capture processes. The benchmark monoethanolamine (MEA) was used as an example of amines needing to be monitored from carbon capture facilities, and to describe how the measurements may be influenced by potentially interfering species in CO2 absorber stack discharges. On the basis of known or expected emission compositions, we investigated the PTR-ToF-MS MEA response as a function of sample flow humidity, ammonia, and CO2 abundances, and show that all can exhibit interferences, thus making accurate amine measurements difficult. This warrants a proper sample pretreatment, and we show an example using a dilution with bottled zero air of 1:20 to 1:10 to monitor stack gas concentrations at the CO2 Technology Center Mongstad (TCM), Norway. Observed emissions included many expected chemical species, dominantly ammonia and acetaldehyde, but also two new species previously not reported but emitted in significant quantities. With respect to concerns regarding amine emissions, we show that accurate amine quantifications in the presence of water vapor, ammonia, and CO2 become feasible after proper sample dilution, thus making PTR-ToF-MS a viable technique to monitor future carbon capture facility emissions, without conventional laborious sample pretreatment.

  12. Patient satisfaction and barriers to initiating real-time continuous glucose monitoring in early pregnancy in women with diabetes

    DEFF Research Database (Denmark)

    Secher, A L; Madsen, A B; Nielsen, Lene Ringholm

    2012-01-01

    of initial monitoring). Ten women (15%) did not wish to use continuous glucose monitoring again in pregnancy. Main causes behind early removal of continuous glucose monitoring were self-reported skin irritation, technical problems and continuous glucose monitoring inaccuracy. No differences were found......Aim: To evaluate self-reported satisfaction and barriers to initiating real-time continuous glucose monitoring in early pregnancy among women with pregestational diabetes. Methods: Fifty-four women with Type 1 diabetes and 14 women with Type 2 diabetes were offered continuous glucose monitoring...

  13. Real-time monitoring for fast deformations using GNSS low-cost receivers

    Directory of Open Access Journals (Sweden)

    T. Bellone

    2016-03-01

    Full Text Available Landslides are one of the major geo-hazards which have constantly affected Italy especially over the last few years. In fact 82% of the Italian territory is affected by this phenomenon which destroys the environment and often causes deaths: therefore it is necessary to monitor these effects in order to detect and prevent these risks. Nowadays, most of this type of monitoring is carried out by using traditional topographic instruments (e.g. total stations or satellite techniques such as global navigation satellite system (GNSS receivers. The level of accuracy obtainable with these instruments is sub-centimetrical in post-processing and centimetrical in real-time; however, the costs are very high (many thousands of euros. The rapid diffusion of GNSS networks has led to an increase of using mass-market receivers for real-time positioning. In this paper, the performances of GNSS mass-market receiver are reported with the aim of verifying if this type of sensor can be used for real-time landslide monitoring: for this purpose a special slide was used for simulating a landslide, since it enabled us to give manual displacements thanks to a micrometre screw. These experiments were also carried out by considering a specific statistical test (a modified Chow test which enabled us to understand if there were any displacements from a statistical point of view in real time. The tests, the algorithm and results are reported in this paper.

  14. Real Time Radioactivity Monitoring and its Interface with predictive atmospheric transport modelling

    International Nuclear Information System (INIS)

    Raes, F.

    1990-01-01

    After the Chernobyl accident, a programme was initiated at the Joint Research Centre of the Commission of the European Communities named 'Radioactivity Environmental Monitoring' (REM). The main aspects considered in REM are: data handling, atmospheric modelling and data quality control related to radioactivity in the environment. The first REM workshop was held in December 1987: 'Aerosol Measurements and Nuclear Accidents: A Reconsideration'. (CEC EUR 11755 EN). These are the proceedings of the second REM workshop, held in December 1989, dealing with real-time radioactivity monitoring and its interface with predictive atmospheric models. Atmospheric transport models, in applications extending over time scales of the order of a day or more become progressively less reliable to the extent that an interface with real-time radiological field data becomes highly desirable. Through international arrangements for early exchange of information in the event of a nuclear accident (European Community, IAEA) such data might become available on a quasi real-time basis. The question is how best to use such information to improve our predictive capabilities. During the workshop the present status of on-line monitoring networks for airborne radioactivity in the EC Member States has been reviewed. Possibilities were discussed to use data from such networks as soon as they become available, in order to update predictions made with long range transport models. This publication gives the full text of 13 presentations and a report of the Round Table Discussion held afterwards

  15. Performance results of cooperating expert systems in a distributed real-time monitoring system

    Science.gov (United States)

    Schwuttke, U. M.; Veregge, J. R.; Quan, A. G.

    1994-01-01

    There are numerous definitions for real-time systems, the most stringent of which involve guaranteeing correct system response within a domain-dependent or situationally defined period of time. For applications such as diagnosis, in which the time required to produce a solution can be non-deterministic, this requirement poses a unique set of challenges in dynamic modification of solution strategy that conforms with maximum possible latencies. However, another definition of real time is relevant in the case of monitoring systems where failure to supply a response in the proper (and often infinitesimal) amount of time allowed does not make the solution less useful (or, in the extreme example of a monitoring system responsible for detecting and deflecting enemy missiles, completely irrelevant). This more casual definition involves responding to data at the same rate at which it is produced, and is more appropriate for monitoring applications with softer real-time constraints, such as interplanetary exploration, which results in massive quantities of data transmitted at the speed of light for a number of hours before it even reaches the monitoring system. The latter definition of real time has been applied to the MARVEL system for automated monitoring and diagnosis of spacecraft telemetry. An early version of this system has been in continuous operational use since it was first deployed in 1989 for the Voyager encounter with Neptune. This system remained under incremental development until 1991 and has been under routine maintenance in operations since then, while continuing to serve as an artificial intelligence (AI) testbed in the laboratory. The system architecture has been designed to facilitate concurrent and cooperative processing by multiple diagnostic expert systems in a hierarchical organization. The diagnostic modules adhere to concepts of data-driven reasoning, constrained but complete nonoverlapping domains, metaknowledge of global consequences of anomalous

  16. A Computational Model of the Temporal Dynamics of Plasticity in Procedural Learning: Sensitivity to Feedback Timing

    Directory of Open Access Journals (Sweden)

    Vivian V. Valentin

    2014-07-01

    Full Text Available The evidence is now good that different memory systems mediate the learning of different types of category structures. In particular, declarative memory dominates rule-based (RB category learning and procedural memory dominates information-integration (II category learning. For example, several studies have reported that feedback timing is critical for II category learning, but not for RB category learning – results that have broad support within the memory systems literature. Specifically, II category learning has been shown to be best with feedback delays of 500ms compared to delays of 0 and 1000ms, and highly impaired with delays of 2.5 seconds or longer. In contrast, RB learning is unaffected by any feedback delay up to 10 seconds. We propose a neurobiologically detailed theory of procedural learning that is sensitive to different feedback delays. The theory assumes that procedural learning is mediated by plasticity at cortical-striatal synapses that are modified by dopamine-mediated reinforcement learning. The model captures the time-course of the biochemical events in the striatum that cause synaptic plasticity, and thereby accounts for the empirical effects of various feedback delays on II category learning.

  17. A knowledge-based system framework for real-time monitoring applications

    International Nuclear Information System (INIS)

    Heaberlin, J.O.; Robinson, A.H.

    1989-01-01

    A real-time environment presents a challenge for knowledge-based systems for process monitoring with on-line data acquisition in nuclear power plants. These applications are typically data intensive. This, coupled with the dynamic nature of events on which problematic decisions are based, requires the development of techniques fundamentally different from those generally employed. Traditional approaches involve knowledge management techniques developed for static data, the majority of which is elicited directly from the user in a consultation environment. Inference mechanisms are generally noninterruptible, requiring all appropriate rules to be fired before new data can be accommodated. As a result, traditional knowledge-based applications in real-time environments have inherent problems in dealing with the time dependence of both the data and the solution process. For example, potential problems include obtaining a correct solution too late to be of use or focusing computing resources on problems that no longer exist. A knowledge-based system framework, the real-time framework (RTF), has been developed that can accommodate the time dependencies and resource trade-offs required for real-time process monitoring applications. This framework provides real-time functionality by using generalized problem-solving goals and control strategies that are modifiable during system operation and capable of accommodating feedback for redirection of activities

  18. Experiences and recommendations in deploying a real-time, water quality monitoring system

    Science.gov (United States)

    O'Flynn, B.; Regan, F.; Lawlor, A.; Wallace, J.; Torres, J.; O'Mathuna, C.

    2010-12-01

    Monitoring of water quality at a river basin level to meet the requirements of the Water Framework Directive (WFD) using conventional sampling and laboratory-based techniques poses a significant financial burden. Wireless sensing systems offer the potential to reduce these costs considerably, as well as provide more useful, continuous monitoring capabilities by giving an accurate idea of the changing environmental and water quality in real time. It is unlikely that the traditional spot/grab sampling will provide a reasonable estimate of the true maximum and/or mean concentration for a particular physicochemical variable in a water body with marked temporal variability. When persistent fluctuations occur, it is likely only to be detected through continuous measurements, which have the capability of detecting sporadic peaks of concentration. Thus, in situ sensors capable of continuous sampling of parameters required under the WFD would therefore provide more up-to-date information, cut monitoring costs and provide better coverage representing long-term trends in fluctuations of pollutant concentrations. DEPLOY is a technology demonstration project, which began planning and station selection and design in August 2008 aiming to show how state-of-the-art technology could be implemented for cost-effective, continuous and real-time monitoring of a river catchment. The DEPLOY project is seen as an important building block in the realization of a wide area autonomous network of sensors capable of monitoring the spatial and temporal distribution of important water quality and environmental target parameters. The demonstration sites chosen are based in the River Lee, which flows through Ireland's second largest city, Cork, and were designed to include monitoring stations in five zones considered typical of significant river systems--these monitor water quality parameters such as pH, temperature, depth, conductivity, turbidity and dissolved oxygen. Over one million data points

  19. Experiences and recommendations in deploying a real-time, water quality monitoring system

    International Nuclear Information System (INIS)

    O'Flynn, B; O'Mathuna, C; Regan, F; Lawlor, A; Wallace, J; Torres, J

    2010-01-01

    Monitoring of water quality at a river basin level to meet the requirements of the Water Framework Directive (WFD) using conventional sampling and laboratory-based techniques poses a significant financial burden. Wireless sensing systems offer the potential to reduce these costs considerably, as well as provide more useful, continuous monitoring capabilities by giving an accurate idea of the changing environmental and water quality in real time. It is unlikely that the traditional spot/grab sampling will provide a reasonable estimate of the true maximum and/or mean concentration for a particular physicochemical variable in a water body with marked temporal variability. When persistent fluctuations occur, it is likely only to be detected through continuous measurements, which have the capability of detecting sporadic peaks of concentration. Thus, in situ sensors capable of continuous sampling of parameters required under the WFD would therefore provide more up-to-date information, cut monitoring costs and provide better coverage representing long-term trends in fluctuations of pollutant concentrations. DEPLOY is a technology demonstration project, which began planning and station selection and design in August 2008 aiming to show how state-of-the-art technology could be implemented for cost-effective, continuous and real-time monitoring of a river catchment. The DEPLOY project is seen as an important building block in the realization of a wide area autonomous network of sensors capable of monitoring the spatial and temporal distribution of important water quality and environmental target parameters. The demonstration sites chosen are based in the River Lee, which flows through Ireland's second largest city, Cork, and were designed to include monitoring stations in five zones considered typical of significant river systems-–these monitor water quality parameters such as pH, temperature, depth, conductivity, turbidity and dissolved oxygen. Over one million data

  20. The RASNIK real-time relative alignment monitor for the CDF inner tracking detectors

    International Nuclear Information System (INIS)

    Goldstein, David; Saltzberg, David

    2003-01-01

    We describe the design and operation of the RASNIK optical relative alignment system designed for and installed on the CDF inner tracking detectors. The system provides low-cost minute-by-minute alignment monitoring with submicron precision. To reduce ambiguities, we modified the original three-element RASNIK design to a two-element one. Since the RASNIKs are located within 10-40 cm of the beam line, the systems were built from low-mass and radiation-hard components and are operated in a mode which reduces damage from radiation. We describe the data-acquisition system, which has been running without interruption since before the CDF detector was rolled into its collision hall in March 2001. We evaluate what has been learned about sources of detector motion from almost 2 years of RASNIK data and discuss possible improvements to the system