Assessment Study of the State of the Art in Adaptive Control and its Applications to Aircraft Control

NASA Technical Reports Server (NTRS)

Kaufman, Howard

1998-01-01

Many papers relevant to reconfigurable flight control have appeared over the past fifteen years. In general these have consisted of theoretical issues, simulation experiments, and in some cases, actual flight tests. Results indicate that reconfiguration of flight controls is certainly feasible for a wide class of failures. However many of the proposed procedures although quite attractive, need further analytical and experimental studies for meaningful validation. Many procedures assume the availability of failure detection and identification logic that will supply adequately fast, the dynamics corresponding to the failed aircraft. This in general implies that the failure detection and fault identification logic must have access to all possible anticipated faults and the corresponding dynamical equations of motion. Unless some sort of explicit on line parameter identification is included, the computational demands could possibly be too excessive. This suggests the need for some form of adaptive control, either by itself as the prime procedure for control reconfiguration or in conjunction with the failure detection logic. If explicit or indirect adaptive control is used, then it is important that the identified models be such that the corresponding computed controls deliver adequate performance to the actual aircraft. Unknown changes in trim should be modelled, and parameter identification needs to be adequately insensitive to noise and at the same time capable of tracking abrupt changes. If however, both failure detection and system parameter identification turn out to be too time consuming in an emergency situation, then the concepts of direct adaptive control should be considered. If direct model reference adaptive control is to be used (on a linear model) with stability assurances, then a positive real or passivity condition needs to be satisfied for all possible configurations. This condition is often satisfied with a feedforward compensator around the plant. This compensator must be robustly designed such that the compensated plant satisfies the required positive real conditions over all expected parameter values. Furthermore, with the feedforward only around the plant, a nonzero (but bounded error) will exist in steady state between the plant and model outputs. This error can be removed by placing the compensator also in the reference model. Design of such a compensator should not be too difficult a problem since for flight control it is generally possible to feedback all the system states.

A preliminary evaluation of the generalized likelihood ratio for detecting and identifying control element failures in a transport aircraft

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1985-01-01

The application of the Generalized Likelihood Ratio technique to the detection and identification of aircraft control element failures has been evaluated in a linear digital simulation of the longitudinal dynamics of a B-737 aircraft. Simulation results show that the technique has potential but that the effects of wind turbulence and Kalman filter model errors are problems which must be overcome.

Nonparametric method for failures detection and localization in the actuating subsystem of aircraft control system

NASA Astrophysics Data System (ADS)

Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures detection and localization in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on algebraic solvability conditions for the aircraft model identification problem. This makes it possible to significantly increase the efficiency of detection and localization problem solution by completely eliminating errors, associated with aircraft model uncertainties.

Expert system for identification of simultaneous and sequential reactor fuel failures with gas tagging

DOEpatents

Gross, K.C.

1994-07-26

Failure of a fuel element in a nuclear reactor core is determined by a gas tagging failure detection system and method. Failures are catalogued and characterized after the event so that samples of the reactor's cover gas are taken at regular intervals and analyzed by mass spectroscopy. Employing a first set of systematic heuristic rules which are applied in a transformed node space allows the number of node combinations which must be processed within a barycentric algorithm to be substantially reduced. A second set of heuristic rules treats the tag nodes of the most recent one or two leakers as background'' gases, further reducing the number of trial node combinations. Lastly, a fuzzy'' set theory formalism minimizes experimental uncertainties in the identification of the most likely volumes of tag gases. This approach allows for the identification of virtually any number of sequential leaks and up to five simultaneous gas leaks from fuel elements. 14 figs.

Investigation of an automatic trim algorithm for restructurable aircraft control

NASA Technical Reports Server (NTRS)

Weiss, J.; Eterno, J.; Grunberg, D.; Looze, D.; Ostroff, A.

1986-01-01

This paper develops and solves an automatic trim problem for restructurable aircraft control. The trim solution is applied as a feed-forward control to reject measurable disturbances following control element failures. Disturbance rejection and command following performances are recovered through the automatic feedback control redesign procedure described by Looze et al. (1985). For this project the existence of a failure detection mechanism is assumed, and methods to cope with potential detection and identification inaccuracies are addressed.

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Wilson, Edward; Lages, Chris; Mah, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,

Reliability Assessment for Low-cost Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Freeman, Paul Michael

Existing low-cost unmanned aerospace systems are unreliable, and engineers must blend reliability analysis with fault-tolerant control in novel ways. This dissertation introduces the University of Minnesota unmanned aerial vehicle flight research platform, a comprehensive simulation and flight test facility for reliability and fault-tolerance research. An industry-standard reliability assessment technique, the failure modes and effects analysis, is performed for an unmanned aircraft. Particular attention is afforded to the control surface and servo-actuation subsystem. Maintaining effector health is essential for safe flight; failures may lead to loss of control incidents. Failure likelihood, severity, and risk are qualitatively assessed for several effector failure modes. Design changes are recommended to improve aircraft reliability based on this analysis. Most notably, the control surfaces are split, providing independent actuation and dual-redundancy. The simulation models for control surface aerodynamic effects are updated to reflect the split surfaces using a first-principles geometric analysis. The failure modes and effects analysis is extended by using a high-fidelity nonlinear aircraft simulation. A trim state discovery is performed to identify the achievable steady, wings-level flight envelope of the healthy and damaged vehicle. Tolerance of elevator actuator failures is studied using familiar tools from linear systems analysis. This analysis reveals significant inherent performance limitations for candidate adaptive/reconfigurable control algorithms used for the vehicle. Moreover, it demonstrates how these tools can be applied in a design feedback loop to make safety-critical unmanned systems more reliable. Control surface impairments that do occur must be quickly and accurately detected. This dissertation also considers fault detection and identification for an unmanned aerial vehicle using model-based and model-free approaches and applies those algorithms to experimental faulted and unfaulted flight test data. Flight tests are conducted with actuator faults that affect the plant input and sensor faults that affect the vehicle state measurements. A model-based detection strategy is designed and uses robust linear filtering methods to reject exogenous disturbances, e.g. wind, while providing robustness to model variation. A data-driven algorithm is developed to operate exclusively on raw flight test data without physical model knowledge. The fault detection and identification performance of these complementary but different methods is compared. Together, enhanced reliability assessment and multi-pronged fault detection and identification techniques can help to bring about the next generation of reliable low-cost unmanned aircraft.

Detection of low frequency external electronic identification devices using commercial panel readers.

PubMed

Stewart, S C; Rapnicki, P; Lewis, J R; Perala, M

2007-09-01

The ability of a commercially available panel reader system to read International Standards Organization-compliant electronic identification devices under commercial dairy conditions was examined. Full duplex (FDX-B) and half-duplex (HDX) low frequency radio-frequency identification external ear tags were utilized. The study involved 498 Holstein cows in the final 6 wk of gestation. There were 516 total electronic identification devices (n = 334 HDX and n = 182 FDX-B). Eighteen FDX-B were replaced with HDX during the study due to repeated detection failure. There were 6,679 HDX and 3,401 FDX-B device detection attempts. There were 220 (2.2%) unsuccessful and 9,860 (97.8%) successful identification detection attempts. There were 9 unsuccessful detection attempts for HDX (6,670/6,679 = 99.9% successful detection attempts) and 211 unsuccessful detection attempts for FDX-B (3,190/3,401 = 93.8% successful detection attempts). These results demonstrate that this panel system can achieve high detection rates of HDX devices and meet the needs of the most demanding management applications. The FDX-B detection rate was not sufficient for the most demanding applications, requiring a high degree of detection by panel readers. The lower FDX-B rate may not be inherent in the device technology itself, but could be due to other factors, including the particular panel reader utilized or the tuning of the panel reader.

Automatic tracking of wake vortices using ground-wind sensor data

DOT National Transportation Integrated Search

1977-01-03

Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...

On Restructurable Control System Theory

NASA Technical Reports Server (NTRS)

Athans, M.

1983-01-01

The state of stochastic system and control theory as it impacts restructurable control issues is addressed. The multivariable characteristics of the control problem are addressed. The failure detection/identification problem is discussed as a multi-hypothesis testing problem. Control strategy reconfiguration, static multivariable controls, static failure hypothesis testing, dynamic multivariable controls, fault-tolerant control theory, dynamic hypothesis testing, generalized likelihood ratio (GLR) methods, and adaptive control are discussed.

Forensic identification of CITES protected slimming cactus (Hoodia) using DNA barcoding.

PubMed

Gathier, Gerard; van der Niet, Timotheus; Peelen, Tamara; van Vugt, Rogier R; Eurlings, Marcel C M; Gravendeel, Barbara

2013-11-01

Slimming cactus (Hoodia), found only in southwestern Africa, is a well-known herbal product for losing weight. Consequently, Hoodia extracts are sought-after worldwide despite a CITES Appendix II status. The failure to eradicate illegal trade is due to problems with detecting and identifying Hoodia using morphological and chemical characters. Our aim was to evaluate the potential of molecular identification of Hoodia based on DNA barcoding. Screening of nrITS1 and psbA-trnH DNA sequences from 26 accessions of Ceropegieae resulted in successful identification, while conventional chemical profiling using DLI-MS led to inaccurate detection and identification of Hoodia. The presence of Hoodia in herbal products was also successfully established using DNA sequences. A validation procedure of our DNA barcoding protocol demonstrated its robustness to changes in PCR conditions. We conclude that DNA barcoding is an effective tool for Hoodia detection and identification which can contribute to preventing illegal trade. © 2013 American Academy of Forensic Sciences.

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

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

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

Fractography, NDE, and fracture mechanics applications in failure analysis studies

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

Morin, C.R.; Shipley, R.J.; Wilkinson, J.A.

1994-10-01

While identification of the precise mode of a failure can lead logically to the underlying cause, a thorough failure investigation requires much more than just the identification of a specific metallurgical mechanism, for example, fatigue, creep, stress corrosion cracking, etc. Failures involving fracture provide good illustrations of this concept. An initial step in characterizing fracture surfaces is often the identification of an origin or origins. However, the analysis should not stop there. If the origin is associated with a discontinuity, the manner in which it was formed must also be addressed. The stresses that would have existed at the originmore » must be determined and compared with material properties to determine whether or not a crack should have initiated and propagated during normal operation. Many critical components are inspected throughout their lives by nondestructive methods. When a crack progresses to failure, its nondetection at earlier inspections must also be understood. Careful study of the fracture surface combined with crack growth analysis based on fracture mechanics can provide an estimate of the crack length at the times of previous inspections. An important issue often overlooked in such studies is how processing of parts during manufacture or rework affects the probability of detection of such cracks. The ultimate goal is to understand thoroughly the progression of the failure, to understand the root cause(s), and to design appropriate corrective action(s) to minimize recurrence.« less

Identification of corrosion and damage mechanisms by using scanning electron microscopy and energy-dispersive X-ray microanalysis: contribution to failure analysis case histories

NASA Astrophysics Data System (ADS)

Pantazopoulos, G.; Vazdirvanidis, A.

2014-03-01

Emphasis is placed on the evaluation of corrosion failures of copper and machineable brass alloys during service. Typical corrosion failures of the presented case histories mainly focussed on stress corrosion cracking and dezincification that acted as the major degradation mechanisms in components used in piping and water supply systems. SEM assessment, coupled with EDS spectroscopy, revealed the main cracking modes together with the root-source(s) that are responsible for the damage initiation and evolution. In addition, fracture surface observations contributed to the identification of the incurred fracture mechanisms and potential environmental issues that stimulated crack initiation and propagation. Very frequently, the detection of chlorides among the corrosion products served as a suggestive evidence of the influence of working environment on passive layer destabilisation and metal dissolution.

Analytical redundancy and the design of robust failure detection systems

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Willsky, A. S.

1984-01-01

The Failure Detection and Identification (FDI) process is viewed as consisting of two stages: residual generation and decision making. It is argued that a robust FDI system can be achieved by designing a robust residual generation process. Analytical redundancy, the basis for residual generation, is characterized in terms of a parity space. Using the concept of parity relations, residuals can be generated in a number of ways and the design of a robust residual generation process can be formulated as a minimax optimization problem. An example is included to illustrate this design methodology. Previously announcedd in STAR as N83-20653

Application of failure mode and effects analysis to intracranial stereotactic radiation surgery by linear accelerator.

PubMed

Masini, Laura; Donis, Laura; Loi, Gianfranco; Mones, Eleonora; Molina, Elisa; Bolchini, Cesare; Krengli, Marco

2014-01-01

The aim of this study was to analyze the application of the failure modes and effects analysis (FMEA) to intracranial stereotactic radiation surgery (SRS) by linear accelerator in order to identify the potential failure modes in the process tree and adopt appropriate safety measures to prevent adverse events (AEs) and near-misses, thus improving the process quality. A working group was set up to perform FMEA for intracranial SRS in the framework of a quality assurance program. FMEA was performed in 4 consecutive tasks: (1) creation of a visual map of the process; (2) identification of possible failure modes; (3) assignment of a risk probability number (RPN) to each failure mode based on tabulated scores of severity, frequency of occurrence and detectability; and (4) identification of preventive measures to minimize the risk of occurrence. The whole SRS procedure was subdivided into 73 single steps; 116 total possible failure modes were identified and a score of severity, occurrence, and detectability was assigned to each. Based on these scores, RPN was calculated for each failure mode thus obtaining values from 1 to 180. In our analysis, 112/116 (96.6%) RPN values were <60, 2 (1.7%) between 60 and 125 (63, 70), and 2 (1.7%) >125 (135, 180). The 2 highest RPN scores were assigned to the risk of using the wrong collimator's size and incorrect coordinates on the laser target localizer frame. Failure modes and effects analysis is a simple and practical proactive tool for systematic analysis of risks in radiation therapy. In our experience of SRS, FMEA led to the adoption of major changes in various steps of the SRS procedure.

[Diagnostics and antimicrobial therapy of severe community-acquired pneumonia].

PubMed

Sinopalnikov, A I; Zaitsev, A A

2015-04-01

In the current paper authors presented the latest information concerning etiology of severe community-acquired pneumonia. Most cases are caused by a relatively small number ofpathogenic bacterial and viral natures. The frequency of detection of various pathogens of severe community-acquired pneumonia may vary greatly depending on the region, season and clinical profile of patients, availability of relevant risk factors. Authors presented clinical characteristics of severe community-acquired pneumonia and comparative evaluation of a number of scales to assess the risk of adverse outcome of the disease. Diagnosis of severe community-acquired pneumonia includes the following: collecting of epidemiological history, identification of pneumonia, detection of sepsis and identification of multiple organ dysfunction syndrome, detection of acute respiratory failure, assessment of comorbidity. Authors gave recommendations concerning evaluation of the clinical manifestations of the disease, the use of instrumental and laboratory methods for diagnosis of severe community-acquired pneumonia. To select the mode of antimicrobial therapy is most important local monitoring antimicrobial resistance of pathogens. The main criteria for the effectiveness of treatment are to reduce body temperature, severe intoxication, respiratory and organ failure.

Dynamic Structural Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Smith, Timothy; Reichenbach, Eric; Urnes, James M.

2009-01-01

Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai Frank; Stoelting, Paul; Curran, Simon

2009-01-01

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Virtual Sensor for Failure Detection, Identification and Recovery in the Transition Phase of a Morphing Aircraft

PubMed Central

Heredia, Guillermo; Ollero, Aníbal

2010-01-01

The Helicopter Adaptive Aircraft (HADA) is a morphing aircraft which is able to take-off as a helicopter and, when in forward flight, unfold the wings that are hidden under the fuselage, and transfer the power from the main rotor to a propeller, thus morphing from a helicopter to an airplane. In this process, the reliable folding and unfolding of the wings is critical, since a failure may determine the ability to perform a mission, and may even be catastrophic. This paper proposes a virtual sensor based Fault Detection, Identification and Recovery (FDIR) system to increase the reliability of the HADA aircraft. The virtual sensor is able to capture the nonlinear interaction between the folding/unfolding wings aerodynamics and the HADA airframe using the navigation sensor measurements. The proposed FDIR system has been validated using a simulation model of the HADA aircraft, which includes real phenomena as sensor noise and sampling characteristics and turbulence and wind perturbations. PMID:22294922

Virtual sensor for failure detection, identification and recovery in the transition phase of a morphing aircraft.

PubMed

Heredia, Guillermo; Ollero, Aníbal

2010-01-01

The Helicopter Adaptive Aircraft (HADA) is a morphing aircraft which is able to take-off as a helicopter and, when in forward flight, unfold the wings that are hidden under the fuselage, and transfer the power from the main rotor to a propeller, thus morphing from a helicopter to an airplane. In this process, the reliable folding and unfolding of the wings is critical, since a failure may determine the ability to perform a mission, and may even be catastrophic. This paper proposes a virtual sensor based Fault Detection, Identification and Recovery (FDIR) system to increase the reliability of the HADA aircraft. The virtual sensor is able to capture the nonlinear interaction between the folding/unfolding wings aerodynamics and the HADA airframe using the navigation sensor measurements. The proposed FDIR system has been validated using a simulation model of the HADA aircraft, which includes real phenomena as sensor noise and sampling characteristics and turbulence and wind perturbations.

Rule-Based Relaxation of Reference Identification Failures. Technical Report No. 396.

ERIC Educational Resources Information Center

Goodman, Bradley A.

In a step toward creating a robust natural language understanding system which detects and avoids miscommunication, this artificial intelligence research report provides a taxonomy of miscommunication problems that arise in expert-apprentice dialogues (including misunderstandings, wrong communication, and bad analogies), and proposes a flexible…

[Early detection, prevention and management of renal failure in liver transplantation].

PubMed

Castells, Lluís; Baliellas, Carme; Bilbao, Itxarone; Cantarell, Carme; Cruzado, Josep Maria; Esforzado, Núria; García-Valdecasas, Juan Carlos; Lladó, Laura; Rimola, Antoni; Serón, Daniel; Oppenheimer, Federico

2014-10-01

Renal failure is a frequent complication in liver transplant recipients and is associated with increased morbidity and mortality. A variety of risk factors for the development of renal failure in the pre- and post-transplantation periods have been described, as well as at the time of surgery. To reduce the negative impact of renal failure in this population, an active approach is required for the identification of those patients with risk factors, the implementation of preventive strategies, and the early detection of progressive deterioration of renal function. Based on published evidence and on clinical experience, this document presents a series of recommendations on monitoring RF in LT recipients, as well as on the prevention and management of acute and chronic renal failure after LT and referral of these patients to the nephrologist. In addition, this document also provides an update of the various immunosuppressive regimens tested in this population for the prevention and control of post-transplantation deterioration of renal function. Copyright © 2013 Elsevier España, S.L.U. and AEEH y AEG. All rights reserved.

Closed-Loop Evaluation of an Integrated Failure Identification and Fault Tolerant Control System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine; Khong, thuan

2006-01-01

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems developed for failure detection, identification, and reconfiguration, as well as upset recovery, need to be evaluated over broad regions of the flight envelope or under extreme flight conditions, and should include various sources of uncertainty. To apply formal robustness analysis, formulation of linear fractional transformation (LFT) models of complex parameter-dependent systems is required, which represent system uncertainty due to parameter uncertainty and actuator faults. This paper describes a detailed LFT model formulation procedure from the nonlinear model of a transport aircraft by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The closed-loop system is evaluated over the entire flight envelope based on the generated LFT model which can cover nonlinear dynamics. The robustness analysis results of the closed-loop fault tolerant control system of a transport aircraft are presented. A reliable flight envelope (safe flight regime) is also calculated from the robust performance analysis results, over which the closed-loop system can achieve the desired performance of command tracking and failure detection.

Application of Failure Mode and Effects Analysis to Intraoperative Radiation Therapy Using Mobile Electron Linear Accelerators

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

Ciocca, Mario, E-mail: mario.ciocca@cnao.it; Cantone, Marie-Claire; Veronese, Ivan

2012-02-01

Purpose: Failure mode and effects analysis (FMEA) represents a prospective approach for risk assessment. A multidisciplinary working group of the Italian Association for Medical Physics applied FMEA to electron beam intraoperative radiation therapy (IORT) delivered using mobile linear accelerators, aiming at preventing accidental exposures to the patient. Methods and Materials: FMEA was applied to the IORT process, for the stages of the treatment delivery and verification, and consisted of three steps: 1) identification of the involved subprocesses; 2) identification and ranking of the potential failure modes, together with their causes and effects, using the risk probability number (RPN) scoring system,more » based on the product of three parameters (severity, frequency of occurrence and detectability, each ranging from 1 to 10); 3) identification of additional safety measures to be proposed for process quality and safety improvement. RPN upper threshold for little concern of risk was set at 125. Results: Twenty-four subprocesses were identified. Ten potential failure modes were found and scored, in terms of RPN, in the range of 42-216. The most critical failure modes consisted of internal shield misalignment, wrong Monitor Unit calculation and incorrect data entry at treatment console. Potential causes of failure included shield displacement, human errors, such as underestimation of CTV extension, mainly because of lack of adequate training and time pressures, failure in the communication between operators, and machine malfunctioning. The main effects of failure were represented by CTV underdose, wrong dose distribution and/or delivery, unintended normal tissue irradiation. As additional safety measures, the utilization of a dedicated staff for IORT, double-checking of MU calculation and data entry and finally implementation of in vivo dosimetry were suggested. Conclusions: FMEA appeared as a useful tool for prospective evaluation of patient safety in radiotherapy. The application of this method to IORT lead to identify three safety measures for risk mitigation.« less

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet

1994-01-01

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

NASA Astrophysics Data System (ADS)

Al Azzawi, Dia

Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight simulator. The abnormal conditions considered in this work include locked actuators (stabilator, aileron, rudder, and throttle), structural damage of the wing, horizontal tail, and vertical tail, malfunctioning sensors, and reduced engine effectiveness. The results of applying the proposed approach to this wide range of abnormal conditions show its high capability in detecting the abnormal conditions with zero false alarms and very high detection rates, correctly identifying the failed subsystem and evaluating the type and severity of the failure. The results also reveal that the post-failure flight envelope can be reasonably predicted within this framework.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

Detection of imminent vein graft occlusion: what is the optimal surveillance program?

PubMed

Tinder, Chelsey N; Bandyk, Dennis F

2009-12-01

The prediction of infrainguinal vein bypass failure remains an inexact judgment. Patient demographics, technical factors, and vascular laboratory graft surveillance testing are helpful in identifying a high-risk graft cohort. The optimal surveillance program to detect the bypass at risk for imminent occlusion continues to be developed, but required elements are known and include clinical assessment for new or changes in limb ischemia symptoms, measurement of ankle and/or toe systolic pressure, and duplex ultrasound imaging of the bypass graft. Duplex ultrasound assessment of bypass hemodynamics may be the most accurate method to detect imminent vein graft occlusion. The finding of low graft flow during intraoperative assessment or at a scheduled surveillance study predicts failure; and if associated with an occlusive lesion, a graft revision can prolong patency. The most common abnormality producing graft failure is conduit stenosis caused by myointimal hyperplasia; and the majority can be repaired by an endovascular intervention. Frequency of testing to detect the failing bypass should be individualized to the patient, the type of arterial bypass, and prior duplex ultrasound scan findings. The focus of surveillance is on identification of the low-flow arterial bypass and timely repair of detected critical stenosis defined by duplex velocity spectra criteria of a peak systolic velocity 300 cm/s and peak systolic velocity ratio across the stenosis >3.5-correlating with >70% diameter-reducing stenosis. When conducted appropriately, a graft surveillance program should result in an unexpected graft failure rate of <3% per year.

Full Envelope Reconfigurable Control Design for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Cotting, M. Christopher; Burken, John J.; Lee, Seung-Hee (Technical Monitor)

2001-01-01

In the event of a control surface failure, the purpose of a reconfigurable control system is to redistribute the control effort among the remaining working surfaces such that satisfactory stability and performance are retained. An Off-line Nonlinear General Constrained Optimization (ONCO) approach was used for the reconfigurable X-33 control design method. Three example failures are shown using a high fidelity 6 DOF simulation (case I ascent with a left body flap jammed at 25 deg.; case 2 entry with a right inboard elevon jam at 25 deg.; and case 3, landing (TAEM) with a left rudder jam at -30 deg.) Failure comparisons between responses with the nominal controller and reconfigurable controllers show the benefits of reconfiguration. Single jam aerosurface failures were considered, and failure detection and identification is considered accomplished in the actuator controller. The X-33 flight control system will incorporate reconfigurable flight control in the baseline system.

Failure to Detect Deaf-Blindness in a Population of People with Intellectual Disability

ERIC Educational Resources Information Center

Fellinger, J.; Holzinger, D.; Dirmhirn, A.; van Dijk, J.; Goldberg, D.

2009-01-01

Background: Early identification of deaf-blindness is essential to ensure appropriate management. Previous studies indicate that deaf-blindness is often missed. We aim to discover the extent to which deaf-blindness in people with intellectual disability (ID) is undiagnosed. Method: A survey was made of the 253 residents of an institute offering…

Expanded envelope concepts for aircraft control-element failure detection and identification

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1988-01-01

The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.

Joint University Program for Air Transportation Research, 1990-1991

NASA Technical Reports Server (NTRS)

Morrell, Frederick R. (Compiler)

1991-01-01

The goals of this program are consistent with the interests of both NASA and the FAA in furthering the safety and efficiency of the National Airspace System. Research carried out at the Massachusetts Institute of Technology (MIT), Ohio University, and Princeton University are covered. Topics studied include passive infrared ice detection for helicopters, the cockpit display of hazardous windshear information, fault detection and isolation for multisensor navigation systems, neural networks for aircraft system identification, and intelligent failure tolerant control.

Robust detection-isolation-accommodation for sensor failures

NASA Technical Reports Server (NTRS)

Weiss, J. L.; Pattipati, K. R.; Willsky, A. S.; Eterno, J. S.; Crawford, J. T.

1985-01-01

The results of a one year study to: (1) develop a theory for Robust Failure Detection and Identification (FDI) in the presence of model uncertainty, (2) develop a design methodology which utilizes the robust FDI ththeory, (3) apply the methodology to a sensor FDI problem for the F-100 jet engine, and (4) demonstrate the application of the theory to the evaluation of alternative FDI schemes are presented. Theoretical results in statistical discrimination are used to evaluate the robustness of residual signals (or parity relations) in terms of their usefulness for FDI. Furthermore, optimally robust parity relations are derived through the optimization of robustness metrics. The result is viewed as decentralization of the FDI process. A general structure for decentralized FDI is proposed and robustness metrics are used for determining various parameters of the algorithm.

Object memory and change detection: dissociation as a function of visual and conceptual similarity.

PubMed

Yeh, Yei-Yu; Yang, Cheng-Ta

2008-01-01

People often fail to detect a change between two visual scenes, a phenomenon referred to as change blindness. This study investigates how a post-change object's similarity to the pre-change object influences memory of the pre-change object and affects change detection. The results of Experiment 1 showed that similarity lowered detection sensitivity but did not affect the speed of identifying the pre-change object, suggesting that similarity between the pre- and post-change objects does not degrade the pre-change representation. Identification speed for the pre-change object was faster than naming the new object regardless of detection accuracy. Similarity also decreased detection sensitivity in Experiment 2 but improved the recognition of the pre-change object under both correct detection and detection failure. The similarity effect on recognition was greatly reduced when 20% of each pre-change stimulus was masked by random dots in Experiment 3. Together the results suggest that the level of pre-change representation under detection failure is equivalent to the level under correct detection and that the pre-change representation is almost complete. Similarity lowers detection sensitivity but improves explicit access in recognition. Dissociation arises between recognition and change detection as the two judgments rely on the match-to-mismatch signal and mismatch-to-match signal, respectively.

Reducing time to identification of positive blood cultures with MALDI-TOF MS analysis after a 5-h subculture.

PubMed

Verroken, A; Defourny, L; Lechgar, L; Magnette, A; Delmée, M; Glupczynski, Y

2015-02-01

Speeding up the turn-around time of positive blood culture identifications is essential in order to optimize the treatment of septic patients. Several sample preparation techniques have been developed allowing direct matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) identification of positive blood cultures. Yet, the hands-on time restrains their routine workflow. In this study, we evaluated an approach whereby MALDI-TOF MS identification without any additional steps was carried out on short subcultured colonies from positive blood bottles with the objective of allowing results reporting on the day of positivity detection. Over a 7-month period in 2012, positive blood cultures detected by 9 am with an automated system were inoculated onto a Columbia blood agar and processed after a 5-h incubation on a MALDI-TOF MicroFlex platform (Bruker Daltonik GmbH). Single-spotted colonies were covered with 1 μl formic acid and 1 μl matrix solution. The results were compared to the validated identification techniques. A total of 925 positive blood culture bottles (representing 470 bacteremic episodes) were included. Concordant identification was obtained in 727 (81.1 %) of the 896 monomicrobial blood cultures, with failure being mostly observed with anaerobes and yeasts. In 17 episodes of polymicrobic bacteremia, the identification of one of the two isolates was achieved in 24/29 (82.7 %) positive cultures. Routine implementation of MALDI-TOF MS identification on young positive blood subcultures provides correct results to the clinician in more than 80 % of the bacteremic episodes and allows access to identification results on the day of blood culture positivity detection, potentially accelerating the implementation of targeted clinical treatments.

[Patient identification errors and biological samples in the analytical process: Is it possible to improve patient safety?].

PubMed

Cuadrado-Cenzual, M A; García Briñón, M; de Gracia Hills, Y; González Estecha, M; Collado Yurrita, L; de Pedro Moro, J A; Fernández Pérez, C; Arroyo Fernández, M

2015-01-01

Patient identification errors and biological samples are one of the problems with the highest risk factor in causing an adverse event in the patient. To detect and analyse the causes of patient identification errors in analytical requests (PIEAR) from emergency departments, and to develop improvement strategies. A process and protocol was designed, to be followed by all professionals involved in the requesting and performing of laboratory tests. Evaluation and monitoring indicators of PIEAR were determined, before and after the implementation of these improvement measures (years 2010-2014). A total of 316 PIEAR were detected in a total of 483,254 emergency service requests during the study period, representing a mean of 6.80/10,000 requests. Patient identification failure was the most frequent in all the 6-monthly periods assessed, with a significant difference (P<.0001). The improvement strategies applied showed to be effective in detecting PIEAR, as well as the prevention of such errors. However, we must continue working with this strategy, promoting a culture of safety for all the professionals involved, and trying to achieve the goal that 100% of the analytical and samples are properly identified. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

Potential of airborne LiDAR data analysis to detect subtle landforms of slope failure: Portainé, Central Pyrenees

NASA Astrophysics Data System (ADS)

Ortuño, María; Guinau, Marta; Calvet, Jaume; Furdada, Glòria; Bordonau, Jaume; Ruiz, Antonio; Camafort, Miquel

2017-10-01

Slope failures have been traditionally detected by field inspection and aerial-photo interpretation. These approaches are generally insufficient to identify subtle landforms, especially those generated during the early stages of failures, and particularly where the site is located in forested and remote terrains. We present the identification and characterization of several large and medium size slope failures previously undetected within the Orri massif, Central Pyrenees. Around 130 scarps were interpreted as being part of Rock Slope Failures (RSFs), while other smaller and more superficial failures were interpreted as complex movements combining colluvium slow flow/slope creep and RSFs. Except for one of them, these slope failures had not been previously detected, albeit they extend across a 15% of the studied region. The failures were identified through the analysis of a high-resolution (1 m) LIDAR-derived bare earth Digital Elevation Model (DEM). Most of the scarps are undetectable either by fieldwork, photo interpretation or 5 m resolution topography analysis owing to their small heights (0.5 to 2 m) and their location within forest areas. In many cases, these landforms are not evident in the field due to the presence of other minor irregularities in the slope and the lack of open views due to the forest. 2D and 3D visualization of hillshade maps with different sun azimuths provided an overall picture of the scarp assemblage and permitted a more complete analysis of the geometry of the scarps with respect to the slope and the structural fabric. The sharpness of some of the landforms suggests ongoing activity, which should be explored in future detailed studies in order to assess potential hazards affecting the Portainé ski resort. Our results reveal that close analysis of the 1 m LIDAR-derived DEM can significantly help to detect early-stage slope deformations in high mountain regions, and that expert judgment of the DEM is essential when dealing with subtle landforms. The incorporation of this approach in regional mapping represents a great advance in completing the catalogue of slope failures and will eventually contribute to a better understanding of the spatial factors controlling them.

Characterization of the behavior of three definitions of prostate-specific antigen-based biochemical failure in relation to detection and follow-up biases: comparison with the American Society for Therapeutic Radiology and Oncology consensus definition.

PubMed

Williams, Scott G

2006-03-01

To examine the impact of detection biases on three prostate cancer biochemical failure (bF) definitions in comparison with the existing American Society for Therapeutic Radiology and Oncology Consensus Definition (ACD). Three alternative bF definitions were tested against the ACD: three rises in prostate-specific antigen (PSA) level without backdating, nadir plus 2 ng/mL, and a threshold PSA level of >3 ng/mL, according to data from 1050 men. The mean time between PSA tests (MTBT), regularity of collection, and calendar year of analysis were examined in each bF definition. The MTBT produced a statistically significant difference in the derived hazard ratio for identification of bF in all definitions. The influence of test regularity was statistically significant beyond the median level of regularity in all definitions. The year of analysis impacted greatly on the ACD, whereas the three alternative definitions exhibited minor follow-up duration variations by comparison. The alternative definitions had reliable follow-up when the crude median time to censoring was at least 1.6 times greater than that of failure. Detection biases will always be a significant issue in defining bF. A number of alternative failure definitions have more predictable interactions with these biases than the existing ACD.

Deterministic Reconfigurable Control Design for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Wagner, Elaine A.; Burken, John J.; Hanson, Curtis E.; Wohletz, Jerry M.

1998-01-01

In the event of a control surface failure, the purpose of a reconfigurable control system is to redistribute the control effort among the remaining working surfaces such that satisfactory stability and performance are retained. Four reconfigurable control design methods were investigated for the X-33 vehicle: Redistributed Pseudo-Inverse, General Constrained Optimization, Automated Failure Dependent Gain Schedule, and an Off-line Nonlinear General Constrained Optimization. The Off-line Nonlinear General Constrained Optimization approach was chosen for implementation on the X-33. Two example failures are shown, a right outboard elevon jam at 25 deg. at a Mach 3 entry condition, and a left rudder jam at 30 degrees. Note however, that reconfigurable control laws have been designed for the entire flight envelope. Comparisons between responses with the nominal controller and reconfigurable controllers show the benefits of reconfiguration. Single jam aerosurface failures were considered, and failure detection and identification is considered accomplished in the actuator controller. The X-33 flight control system will incorporate reconfigurable flight control in the baseline system.

Clinical identification of compensatory structures on projective tests: a self psychological approach.

PubMed

Silverstein, M L

2001-06-01

In this article I discuss compensatory structure, a concept from Kohut's (1971, 1977) psychology of the self that is not as familiar as Kohut's other views about the self. Compensatory structures are attempts to repair selfobject failure, usually by strengthening idealization or twinship in the face of mirroring deficits. Compensatory structures, particularly their early indications, can be detected on projective tests for identifying adaptive resources and treatment potential. The clinical identification of compensatory structures on test findings is described using Rorschach and Thematic Apperception Test (Murray, 1943) content. Particular attention is devoted to the 2-part process of demonstrating first, an injury to the self, and second, how attempts to recover from such injuries can be detected on projective tests. Clinical examples are provided, and the differentiation between compensatory structures and defenses and sublimation is discussed.

Assessment of cerebral microbleeds by susceptibility-weighted imaging at 3T in patients with end-stage organ failure.

PubMed

Sparacia, Gianvincenzo; Cannella, Roberto; Lo Re, Vincenzina; Gambino, Angelo; Mamone, Giuseppe; Miraglia, Roberto

2018-02-17

Cerebral microbleeds (CMBs) are small rounded lesions representing cerebral hemosiderin deposits surrounded by macrophages that results from previous microhemorrhages. The aim of this study was to review the distribution of cerebral microbleeds in patients with end-stage organ failure and their association with specific end-stage organ failure risk factors. Between August 2015 and June 2017, we evaluated 15 patients, 9 males, and 6 females, (mean age 65.5 years). Patients population was subdivided into three groups according to the organ failure: (a) chronic kidney failure (n = 8), (b) restrictive cardiomyopathy undergoing heart transplantation (n = 1), and (c) end-stage liver failure undergoing liver transplantation (n = 6). The MR exams were performed on a 3T MR unit and the SWI sequence was used for the detection of CMBs. CMBs were subdivided in supratentorial lobar distributed, supratentorial non-lobar distributed, and infratentorial distributed. A total of 91 microbleeds were observed in 15 patients. Fifty-nine CMBs lesions (64.8%) had supratentorial lobar distribution, 17 CMBs lesions (18.8%) had supratentorial non-lobar distribution and the remaining 15 CMBs lesions (16.4%) were infratentorial distributed. An overall predominance of supratentorial multiple lobar localizations was found in all types of end-stage organ failure. The presence of CMBs was significantly correlated with age, hypertension, and specific end-stage organ failure risk factors (p < 0.001). CMBs are mostly founded in supratentorial lobar localization in end-stage organ failure. The improved detection of CMBs with SWI sequences may contribute to a more accurate identification of patients with cerebral risk factors to prevent complications during or after the organ transplantation.

Shoreline Erosion and Slope Failure Detection over Southwest Lakeshore Michigan using Temporal Radar and Digital Elevation Model

NASA Astrophysics Data System (ADS)

Sataer, G.; Sultan, M.; Yellich, J. A.; Becker, R.; Emil, M. K.; Palaseanu, M.

2017-12-01

Throughout the 20th century and into the 21st century, significant losses of residential, commercial and governmental property were reported along the shores of the Great Lakes region due to one or more of the following factors: high lake levels, wave actions, groundwater discharge. A collaborative effort (Western Michigan University, University of Toledo, Michigan Geological Survey [MGS], United States Geological Survey [USGS], National Oceanographic and Atmospheric Administration [NOAA]) is underway to examine the temporal topographic variations along the shoreline and the adjacent bluff extending from the City of South Haven in the south to the City of Saugatuck in the north within the Allegan County. Our objectives include two main tasks: (1) identification of the timing of, and the areas, witnessing slope failure and shoreline erosion, and (2) investigating the factors causing the observed failures and erosion. This is being accomplished over the study area by: (1) detecting and measuring slope subsidence rates (velocities along line of site) and failures using radar interferometric persistent scatter (PS) techniques applied to ESA's European Remote Sensing (ERS) satellites, ERS-1 and -2 (spatial resolution: 25 m) that were acquired in 1995 to 2007, (2) extracting temporal high resolution (20 cm) digital elevation models (DEM) for the study area from temporal imagery acquired by Unmanned Aerial Vehicles (UAVs), and applying change detection techniques to the extracted DEMs, (3) detecting change in elevation and slope profiles extracted from two LIDAR Coastal National Elevation Database (CoNED) DEMs (spatial resolution: 0.5m), acquired on 2008 and 2012, and (4) spatial and temporal correlation of the detected changes in elevation with relevant data sets (e.g., lake levels, precipitation, groundwater levels) in search of causal effects.

Fault Management Metrics

NASA Technical Reports Server (NTRS)

Johnson, Stephen B.; Ghoshal, Sudipto; Haste, Deepak; Moore, Craig

2017-01-01

This paper describes the theory and considerations in the application of metrics to measure the effectiveness of fault management. Fault management refers here to the operational aspect of system health management, and as such is considered as a meta-control loop that operates to preserve or maximize the system's ability to achieve its goals in the face of current or prospective failure. As a suite of control loops, the metrics to estimate and measure the effectiveness of fault management are similar to those of classical control loops in being divided into two major classes: state estimation, and state control. State estimation metrics can be classified into lower-level subdivisions for detection coverage, detection effectiveness, fault isolation and fault identification (diagnostics), and failure prognosis. State control metrics can be classified into response determination effectiveness and response effectiveness. These metrics are applied to each and every fault management control loop in the system, for each failure to which they apply, and probabilistically summed to determine the effectiveness of these fault management control loops to preserve the relevant system goals that they are intended to protect.

Failure detection system design methodology. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chow, E. Y.

1980-01-01

The design of a failure detection and identification system consists of designing a robust residual generation process and a high performance decision making process. The design of these two processes are examined separately. Residual generation is based on analytical redundancy. Redundancy relations that are insensitive to modelling errors and noise effects are important for designing robust residual generation processes. The characterization of the concept of analytical redundancy in terms of a generalized parity space provides a framework in which a systematic approach to the determination of robust redundancy relations are developed. The Bayesian approach is adopted for the design of high performance decision processes. The FDI decision problem is formulated as a Bayes sequential decision problem. Since the optimal decision rule is incomputable, a methodology for designing suboptimal rules is proposed. A numerical algorithm is developed to facilitate the design and performance evaluation of suboptimal rules.

An adaptive tracking observer for failure-detection systems

NASA Technical Reports Server (NTRS)

Sidar, M.

1982-01-01

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

27 CFR 70.113 - Penalty for failure to supply taxpayer identification number.

Code of Federal Regulations, 2010 CFR

2010-04-01

... supply taxpayer identification number. 70.113 Section 70.113 Alcohol, Tobacco Products and Firearms..., Additional Amounts, and Assessable Penalties § 70.113 Penalty for failure to supply taxpayer identification... notice and demand therefor. (b) Reasonable cause. If any person who is required by the regulations under...

Automatic crack detection method for loaded coal in vibration failure process

PubMed Central

Li, Chengwu

2017-01-01

In the coal mining process, the destabilization of loaded coal mass is a prerequisite for coal and rock dynamic disaster, and surface cracks of the coal and rock mass are important indicators, reflecting the current state of the coal body. The detection of surface cracks in the coal body plays an important role in coal mine safety monitoring. In this paper, a method for detecting the surface cracks of loaded coal by a vibration failure process is proposed based on the characteristics of the surface cracks of coal and support vector machine (SVM). A large number of cracked images are obtained by establishing a vibration-induced failure test system and industrial camera. Histogram equalization and a hysteresis threshold algorithm were used to reduce the noise and emphasize the crack; then, 600 images and regions, including cracks and non-cracks, were manually labelled. In the crack feature extraction stage, eight features of the cracks are extracted to distinguish cracks from other objects. Finally, a crack identification model with an accuracy over 95% was trained by inputting the labelled sample images into the SVM classifier. The experimental results show that the proposed algorithm has a higher accuracy than the conventional algorithm and can effectively identify cracks on the surface of the coal and rock mass automatically. PMID:28973032

Automatic crack detection method for loaded coal in vibration failure process.

PubMed

Li, Chengwu; Ai, Dihao

2017-01-01

In the coal mining process, the destabilization of loaded coal mass is a prerequisite for coal and rock dynamic disaster, and surface cracks of the coal and rock mass are important indicators, reflecting the current state of the coal body. The detection of surface cracks in the coal body plays an important role in coal mine safety monitoring. In this paper, a method for detecting the surface cracks of loaded coal by a vibration failure process is proposed based on the characteristics of the surface cracks of coal and support vector machine (SVM). A large number of cracked images are obtained by establishing a vibration-induced failure test system and industrial camera. Histogram equalization and a hysteresis threshold algorithm were used to reduce the noise and emphasize the crack; then, 600 images and regions, including cracks and non-cracks, were manually labelled. In the crack feature extraction stage, eight features of the cracks are extracted to distinguish cracks from other objects. Finally, a crack identification model with an accuracy over 95% was trained by inputting the labelled sample images into the SVM classifier. The experimental results show that the proposed algorithm has a higher accuracy than the conventional algorithm and can effectively identify cracks on the surface of the coal and rock mass automatically.

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

Rusu, I; Thomas, T; Roeske, J

Purpose: To identify areas of improvement in our liver stereotactic body radiation therapy (SBRT) program, using failure mode and effect analysis (FMEA). Methods: A multidisciplinary group consisting of one physician, three physicists, one dosimetrist and two therapists was formed. A process map covering 10 major stages of the liver SBRT program from the initial diagnosis to post treatment follow-up was generated. A total of 102 failure modes, together with their causes and effects, were identified. The occurrence (O), severity (S) and lack of detectability (D) were independently scored. The ranking was done using the risk probability number (RPN) defined asmore » the product of average O, S and D numbers for each mode. The scores were normalized to remove inter-observer variability, while preserving individual ranking order. Further, a correlation analysis on the overall agreement on rank order of all failure modes resulted in positive values for successive pairs of evaluators. The failure modes with the highest RPN value were considered for further investigation. Results: The average normalized RPN values for all modes were 39 with a range of 9 to 103. The FMEA analysis resulted in the identification of the top 10 critical failures modes as: Incorrect CT-MR registration, MR scan not performed in treatment position, patient movement between CBCT acquisition and treatment, daily IGRT QA not verified, incorrect or incomplete ITV delineation, OAR contours not verified, inaccurate normal liver effective dose (Veff) calculation, failure of bolus tracking for 4D CT scan, setup instructions not followed for treatment and plan evaluation metrics missed. Conclusion: The application of FMEA to our liver SBRT program led to the identification and possible improvement of areas affecting patient safety.« less

Reconfigurable Control Design for the Full X-33 Flight Envelope

NASA Technical Reports Server (NTRS)

Cotting, M. Christopher; Burken, John J.

2001-01-01

A reconfigurable control law for the full X-33 flight envelope has been designed to accommodate a failed control surface and redistribute the control effort among the remaining working surfaces to retain satisfactory stability and performance. An offline nonlinear constrained optimization approach has been used for the X-33 reconfigurable control design method. Using a nonlinear, six-degree-of-freedom simulation, three example failures are evaluated: ascent with a left body flap jammed at maximum deflection; entry with a right inboard elevon jammed at maximum deflection; and landing with a left rudder jammed at maximum deflection. Failure detection and identification are accomplished in the actuator controller. Failure response comparisons between the nominal control mixer and the reconfigurable control subsystem (mixer) show the benefits of reconfiguration. Single aerosurface jamming failures are considered. The cases evaluated are representative of the study conducted to prove the adequate and safe performance of the reconfigurable control mixer throughout the full flight envelope. The X-33 flight control system incorporates reconfigurable flight control in the existing baseline system.

Eigenstructure Assignment for Fault Tolerant Flight Control Design

NASA Technical Reports Server (NTRS)

Sobel, Kenneth; Joshi, Suresh (Technical Monitor)

2002-01-01

In recent years, fault tolerant flight control systems have gained an increased interest for high performance military aircraft as well as civil aircraft. Fault tolerant control systems can be described as either active or passive. An active fault tolerant control system has to either reconfigure or adapt the controller in response to a failure. One approach is to reconfigure the controller based upon detection and identification of the failure. Another approach is to use direct adaptive control to adjust the controller without explicitly identifying the failure. In contrast, a passive fault tolerant control system uses a fixed controller which achieves acceptable performance for a presumed set of failures. We have obtained a passive fault tolerant flight control law for the F/A-18 aircraft which achieves acceptable handling qualities for a class of control surface failures. The class of failures includes the symmetric failure of any one control surface being stuck at its trim value. A comparison was made of an eigenstructure assignment gain designed for the unfailed aircraft with a fault tolerant multiobjective optimization gain. We have shown that time responses for the unfailed aircraft using the eigenstructure assignment gain and the fault tolerant gain are identical. Furthermore, the fault tolerant gain achieves MIL-F-8785C specifications for all failure conditions.

Unique Association of Rare Cardiovascular Disease in an Athlete With Ventricular Arrhythmias.

PubMed

Santomauro, V; Contursi, M; Dellegrottaglie, S; Borsellino, G

2015-01-01

Ventricular arrhythmias are a leading cause of non-elegibility to competitive sport. The failure to detect a significant organic substrate in the initial stage of screening does not preclude the identification of structural pathologies in the follow-up by using advanced imaging techniques. Here we report the case of a senior athlete judged not elegible because an arrhythmia with the morphology consistent with the origin of the left ventricle, in which subsequent execution of a cardiac MR and a thoracic CT scan has allowed the identification of an unique association between an area of myocardial damage, probable site of origine of the arrhythma, and a rare aortic malformation.

Software Risk Identification for Interplanetary Probes

NASA Technical Reports Server (NTRS)

Dougherty, Robert J.; Papadopoulos, Periklis E.

2005-01-01

The need for a systematic and effective software risk identification methodology is critical for interplanetary probes that are using increasingly complex and critical software. Several probe failures are examined that suggest more attention and resources need to be dedicated to identifying software risks. The direct causes of these failures can often be traced to systemic problems in all phases of the software engineering process. These failures have lead to the development of a practical methodology to identify risks for interplanetary probes. The proposed methodology is based upon the tailoring of the Software Engineering Institute's (SEI) method of taxonomy-based risk identification. The use of this methodology will ensure a more consistent and complete identification of software risks in these probes.

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

Padalkar, S.; Karsai, G.; Sztipanovits, J.

1988-01-01

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Neural Networks and other Techniques for Fault Identification and Isolation of Aircraft Systems

NASA Technical Reports Server (NTRS)

Innocenti, M.; Napolitano, M.

2003-01-01

Fault identification, isolation, and accomodation have become critical issues in the overall performance of advanced aircraft systems. Neural Networks have shown to be a very attractive alternative to classic adaptation methods for identification and control of non-linear dynamic systems. The purpose of this paper is to show the improvements in neural network applications achievable through the use of learning algorithms more efficient than the classic Back-Propagation, and through the implementation of the neural schemes in parallel hardware. The results of the analysis of a scheme for Sensor Failure, Detection, Identification and Accommodation (SFDIA) using experimental flight data of a research aircraft model are presented. Conventional approaches to the problem are based on observers and Kalman Filters while more recent methods are based on neural approximators. The work described in this paper is based on the use of neural networks (NNs) as on-line learning non-linear approximators. The performances of two different neural architectures were compared. The first architecture is based on a Multi Layer Perceptron (MLP) NN trained with the Extended Back Propagation algorithm (EBPA). The second architecture is based on a Radial Basis Function (RBF) NN trained with the Extended-MRAN (EMRAN) algorithms. In addition, alternative methods for communications links fault detection and accomodation are presented, relative to multiple unmanned aircraft applications.

Aircraft Flight Envelope Determination using Upset Detection and Physical Modeling Methods

NASA Technical Reports Server (NTRS)

Keller, Jeffrey D.; McKillip, Robert M. Jr.; Kim, Singwan

2009-01-01

The development of flight control systems to enhance aircraft safety during periods of vehicle impairment or degraded operations has been the focus of extensive work in recent years. Conditions adversely affecting aircraft flight operations and safety may result from a number of causes, including environmental disturbances, degraded flight operations, and aerodynamic upsets. To enhance the effectiveness of adaptive and envelope limiting controls systems, it is desirable to examine methods for identifying the occurrence of anomalous conditions and for assessing the impact of these conditions on the aircraft operational limits. This paper describes initial work performed toward this end, examining the use of fault detection methods applied to the aircraft for aerodynamic performance degradation identification and model-based methods for envelope prediction. Results are presented in which a model-based fault detection filter is applied to the identification of aircraft control surface and stall departure failures/upsets. This application is supported by a distributed loading aerodynamics formulation for the flight dynamics system reference model. Extensions for estimating the flight envelope due to generalized aerodynamic performance degradation are also described.

Academic-Community Hospital Comparison of Vulnerabilities in Door-to-Needle Process for Acute Ischemic Stroke.

PubMed

Prabhakaran, Shyam; Khorzad, Rebeca; Brown, Alexandra; Nannicelli, Anna P; Khare, Rahul; Holl, Jane L

2015-10-01

Although best practices have been developed for achieving door-to-needle (DTN) times ≤60 minutes for stroke thrombolysis, critical DTN process failures persist. We sought to compare these failures in the Emergency Department at an academic medical center and a community hospital. Failure modes effects and criticality analysis was used to identify system and process failures. Multidisciplinary teams involved in DTN care participated in moderated sessions at each site. As a result, DTN process maps were created and potential failures and their causes, frequency, severity, and existing safeguards were identified. For each failure, a risk priority number and criticality score were calculated; failures were then ranked, with the highest scores representing the most critical failures and targets for intervention. We detected a total of 70 failures in 50 process steps and 76 failures in 42 process steps at the community hospital and academic medical center, respectively. At the community hospital, critical failures included (1) delay in registration because of Emergency Department overcrowding, (2) incorrect triage diagnosis among walk-in patients, and (3) delay in obtaining consent for thrombolytic treatment. At the academic medical center, critical failures included (1) incorrect triage diagnosis among walk-in patients, (2) delay in stroke team activation, and (3) delay in obtaining computed tomographic imaging. Although the identification of common critical failures suggests opportunities for a generalizable process redesign, differences in the criticality and nature of failures must be addressed at the individual hospital level, to develop robust and sustainable solutions to reduce DTN time. © 2015 American Heart Association, Inc.

A benchmark for fault tolerant flight control evaluation

NASA Astrophysics Data System (ADS)

Smaili, H.; Breeman, J.; Lombaerts, T.; Stroosma, O.

2013-12-01

A large transport aircraft simulation benchmark (REconfigurable COntrol for Vehicle Emergency Return - RECOVER) has been developed within the GARTEUR (Group for Aeronautical Research and Technology in Europe) Flight Mechanics Action Group 16 (FM-AG(16)) on Fault Tolerant Control (2004 2008) for the integrated evaluation of fault detection and identification (FDI) and reconfigurable flight control strategies. The benchmark includes a suitable set of assessment criteria and failure cases, based on reconstructed accident scenarios, to assess the potential of new adaptive control strategies to improve aircraft survivability. The application of reconstruction and modeling techniques, based on accident flight data, has resulted in high-fidelity nonlinear aircraft and fault models to evaluate new Fault Tolerant Flight Control (FTFC) concepts and their real-time performance to accommodate in-flight failures.

A Framework for Creating a Function-based Design Tool for Failure Mode Identification

NASA Technical Reports Server (NTRS)

Arunajadai, Srikesh G.; Stone, Robert B.; Tumer, Irem Y.; Clancy, Daniel (Technical Monitor)

2002-01-01

Knowledge of potential failure modes during design is critical for prevention of failures. Currently industries use procedures such as Failure Modes and Effects Analysis (FMEA), Fault Tree analysis, or Failure Modes, Effects and Criticality analysis (FMECA), as well as knowledge and experience, to determine potential failure modes. When new products are being developed there is often a lack of sufficient knowledge of potential failure mode and/or a lack of sufficient experience to identify all failure modes. This gives rise to a situation in which engineers are unable to extract maximum benefits from the above procedures. This work describes a function-based failure identification methodology, which would act as a storehouse of information and experience, providing useful information about the potential failure modes for the design under consideration, as well as enhancing the usefulness of procedures like FMEA. As an example, the method is applied to fifteen products and the benefits are illustrated.

Distributed Health Monitoring System for Reusable Liquid Rocket Engines

NASA Technical Reports Server (NTRS)

Lin, C. F.; Figueroa, F.; Politopoulos, T.; Oonk, S.

2009-01-01

The ability to correctly detect and identify any possible failure in the systems, subsystems, or sensors within a reusable liquid rocket engine is a major goal at NASA John C. Stennis Space Center (SSC). A health management (HM) system is required to provide an on-ground operation crew with an integrated awareness of the condition of every element of interest by determining anomalies, examining their causes, and making predictive statements. However, the complexity associated with relevant systems, and the large amount of data typically necessary for proper interpretation and analysis, presents difficulties in implementing complete failure detection, identification, and prognostics (FDI&P). As such, this paper presents a Distributed Health Monitoring System for Reusable Liquid Rocket Engines as a solution to these problems through the use of highly intelligent algorithms for real-time FDI&P, and efficient and embedded processing at multiple levels. The end result is the ability to successfully incorporate a comprehensive HM platform despite the complexity of the systems under consideration.

Recurrent herpetic keratitis: failure to detect herpes simplex virus infection using the Syva MicroTrak HSV1/HSV2 direct specimen identification/typing test.

PubMed

Kumano, Y; Yamamoto, M; Inomata, H; Sakuma, S; Hidaka, Y; Minagawa, H; Mori, R

1990-01-01

A 35-year-old man had developed recurrent herpetic keratitis characterized by dendritic keratitis at intervals of a year. We were able to culture cytopathic agents repeatedly from his lesions by inoculating Vero cells. The cultures yielded definitive evidence of a virus that caused a cytopathic effect within 3 days. However, these virus strains could not be identified as herpes simplex virus (HSV) in immunofluorescence assays using the Syva MicroTrak HSV1/HSV2 direct specimen identification/typing test. Rather they were identified as strains of HSV type 1 (HSV-1) on the basis of plaque morphology, neutralization tests, electron-microscopic examination and DNA restriction endonuclease analysis. Our results allow us to assume the existence of HSV-1 strains isolated clinically that are negative to analysis using the Syva Micro-Trak HSV1/HSV2 direct specimen identification/typing test.

Electromechanical actuators affected by multiple failures: Prognostic method based on spectral analysis techniques

NASA Astrophysics Data System (ADS)

Belmonte, D.; Vedova, M. D. L. Dalla; Ferro, C.; Maggiore, P.

2017-06-01

The proposal of prognostic algorithms able to identify precursors of incipient failures of primary flight command electromechanical actuators (EMA) is beneficial for the anticipation of the incoming failure: an early and correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. An innovative prognostic model-based approach, able to recognize the EMA progressive degradations before his anomalous behaviors become critical, is proposed: the Fault Detection and Identification (FDI) of the considered incipient failures is performed analyzing proper system operational parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters will be correlated with the actual EMA health condition by means of failure maps created by a reference monitoring model-based algorithm. In this work, the proposed method has been tested in case of EMA affected by combined progressive failures: in particular, partial stator single phase turn to turn short-circuit and rotor static eccentricity are considered. In order to evaluate the prognostic method, a numerical test-bench has been conceived. Results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual malfunctioning, minimizing the risk of fake alarms or unannounced failures.

A possible alternative to the error prone modified Hodge test to correctly identify the carbapenemase producing Gram-negative bacteria.

PubMed

Jeremiah, S S; Balaji, V; Anandan, S; Sahni, R D

2014-01-01

The modified Hodge test (MHT) is widely used as a screening test for the detection of carbapenemases in Gram-negative bacteria. This test has several pitfalls in terms of validity and interpretation. Also the test has a very low sensitivity in detecting the New Delhi metallo-β-lactamase (NDM). Considering the degree of dissemination of the NDM and the growing pandemic of carbapenem resistance, a more accurate alternative test is needed at the earliest. The study intends to compare the performance of the MHT with the commercially available Neo-Sensitabs - Carbapenemases/Metallo-β-Lactamase (MBL) Confirmative Identification pack to find out whether the latter could be an efficient alternative to the former. A total of 105 isolates of Klebsiella pneumoniae resistant to imipenem and meropenem, collected prospectively over a period of 2 years were included in the study. The study isolates were tested with the MHT, the Neo-Sensitabs - Carbapenemases/MBL Confirmative Identification pack and polymerase chain reaction (PCR) for detecting the blaNDM-1 gene. Among the 105 isolates, the MHT identified 100 isolates as carbapenemase producers. In the five isolates negative for the MHT, four were found to produce MBLs by the Neo-Sensitabs. The Neo-Sensitabs did not have any false negatives when compared against the PCR. The MHT can give false negative results, which lead to failure in detecting the carbapenemase producers. Also considering the other pitfalls of the MHT, the Neo-Sensitabs--Carbapenemases/MBL Confirmative Identification pack could be a more efficient alternative for detection of carbapenemase production in Gram-negative bacteria.

Clinical cytometry and progress in HLA antibody detection.

PubMed

Bray, Robert A; Tarsitani, Christine; Gebel, Howard M; Lee, Jar-How

2011-01-01

For most solid organ and selected stem cell transplants, antibodies against mismatched HLA antigens can lead to early and late graft failure. In recognition of the clinical significance of these antibodies, HLA antibody identification is one of the most critical functions of histocompatibility laboratories. Early methods employed cumbersome and insensitive complement-dependent cytotoxicity assays with a visual read-out. A little over 20 years ago flow cytometry entered the realm of antibody detection with the introduction of the flow cytometric crossmatch. Cytometry's increased sensitivity and objectivity quickly earned it popularity as a preferred crossmatch method especially for sensitized recipients. Although a sensitive method, the flow crossmatch was criticized as being "too sensitive" as false positive reactions were a know drawback. In part, the shortcomings of the flow crossmatch were due to the lack of corresponding sensitive and specific HLA antibody screening assays. However, in the mid 1990s, solid phase assays, capable of utilizing standard flow cytometers, were developed. These assays used microparticles coated with purified HLA molecules. Hence, the era of solid-phase, microparticle technology for HLA antibody detection was born permitting the sensitive and specific detection of HLA antibody. It was now possible to provide better correlation between HLA antibody detection and the flow cytometric crossmatch. This flow-based technology was soon followed by adaptation to the Luminex platform permitting a mutltiplexed approach for the identification and characterization of HLA antibodies. It is hoped that these technologies will ultimately lead to the identification of parameters that best correlate with and/or predict transplant outcomes. Copyright © 2011 Elsevier Inc. All rights reserved.

Software For Fault-Tree Diagnosis Of A System

NASA Technical Reports Server (NTRS)

Iverson, Dave; Patterson-Hine, Ann; Liao, Jack

1993-01-01

Fault Tree Diagnosis System (FTDS) computer program is automated-diagnostic-system program identifying likely causes of specified failure on basis of information represented in system-reliability mathematical models known as fault trees. Is modified implementation of failure-cause-identification phase of Narayanan's and Viswanadham's methodology for acquisition of knowledge and reasoning in analyzing failures of systems. Knowledge base of if/then rules replaced with object-oriented fault-tree representation. Enhancement yields more-efficient identification of causes of failures and enables dynamic updating of knowledge base. Written in C language, C++, and Common LISP.

Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.

PubMed

Kislinger, Thomas; Gramolini, Anthony O; MacLennan, David H; Emili, Andrew

2005-08-01

An optimized analytical expression profiling strategy based on gel-free multidimensional protein identification technology (MudPIT) is reported for the systematic investigation of biochemical (mal)-adaptations associated with healthy and diseased heart tissue. Enhanced shotgun proteomic detection coverage and improved biological inference is achieved by pre-fractionation of excised mouse cardiac muscle into subcellular components, with each organellar fraction investigated exhaustively using multiple repeat MudPIT analyses. Functional-enrichment, high-confidence identification, and relative quantification of hundreds of organelle- and tissue-specific proteins are achieved readily, including detection of low abundance transcriptional regulators, signaling factors, and proteins linked to cardiac disease. Important technical issues relating to data validation, including minimization of artifacts stemming from biased under-sampling and spurious false discovery, together with suggestions for further fine-tuning of sample preparation, are discussed. A framework for follow-up bioinformatic examination, pattern recognition, and data mining is also presented in the context of a stringent application of MudPIT for probing fundamental aspects of heart muscle physiology as well as the discovery of perturbations associated with heart failure.

Near-infrared imaging spectroscopy for counterfeit drug detection

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2011-06-01

Pharmaceutical counterfeiting is a significant issue in the healthcare community as well as for the pharmaceutical industry worldwide. The use of counterfeit medicines can result in treatment failure or even death. A rapid screening technique such as near infrared (NIR) spectroscopy could aid in the search for and identification of counterfeit drugs. This work presents a comparison of two laboratory NIR imaging systems and the chemometric analysis of the acquired spectroscopic image data. The first imaging system utilizes a NIR liquid crystal tuneable filter and is designed for the investigation of stationary objects. The second imaging system utilizes a NIR imaging spectrograph and is designed for the fast analysis of moving objects on a conveyor belt. Several drugs in form of tablets and capsules were analyzed. Spectral unmixing techniques were applied to the mixed reflectance spectra to identify constituent parts of the investigated drugs. The results show that NIR spectroscopic imaging can be used for contact-less detection and identification of a variety of counterfeit drugs.

Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing.

PubMed

Ivy, Morgan I; Thoendel, Matthew J; Jeraldo, Patricio R; Greenwood-Quaintance, Kerryl E; Hanssen, Arlen D; Abdel, Matthew P; Chia, Nicholas; Yao, Janet Z; Tande, Aaron J; Mandrekar, Jayawant N; Patel, Robin

2018-05-30

Background: Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis, since synovial fluid cultures are not universally positive, and synovial fluid is easily obtained pre-operatively. We applied a metagenomics-based approach to synovial fluid in an attempt to detect microorganisms in 168 failed total knee arthroplasties. Results: Genus- and species-level analysis of metagenomic sequencing yielded the known pathogen in 74 (90%) and 68 (83%) of the 82 culture-positive PJIs analyzed, respectively, with testing of two (2%) and three (4%) samples, respectively, yielding additional pathogens not detected by culture. For the 25 culture-negative PJIs tested, genus- and species-level analysis yielded 19 (76%) and 21 (84%) samples with insignificant findings, respectively, and 6 (24%) and 4 (16%) with potential pathogens detected, respectively. Genus- and species-level analysis of the 60 culture-negative aseptic failure cases yielded 53 (88.3%) and 56 (93.3%) cases with insignificant findings, and 7 (11.7%) and 4 (6.7%) with potential clinically-significant organisms detected, respectively. There was one case of aseptic failure with synovial fluid culture growth; metagenomic analysis showed insignificant findings, suggesting possible synovial fluid culture contamination. Conclusion: Metagenomic shotgun sequencing can detect pathogens involved in PJI when applied to synovial fluid and may be particularly useful for culture-negative cases. Copyright © 2018 American Society for Microbiology.

Identification of Parts Failures. FOS: Fundamentals of Service.

ERIC Educational Resources Information Center

John Deere Co., Moline, IL.

This parts failures identification manual is one of a series of power mechanics texts and visual aids covering theory of operation, diagnosis of trouble problems, and repair of automotive and off-the-road construction and agricultural equipment. Materials provide basic information with many illustrations for use by vocational students and teachers…

Prevalence of Heart Failure Signs and Symptoms in a Large Primary Care Population Identified Through the Use of Text and Data Mining of the Electronic Health Record

PubMed Central

Vijayakrishnan, Rajakrishnan; Steinhubl, Steven R.; Ng, Kenney; Sun, Jimeng; Byrd, Roy J.; Daar, Zahra; Williams, Brent A.; deFilippi, Christopher; Ebadollahi, Shahram; Stewart, Walter F.

2014-01-01

Background The electronic health record contains a tremendous amount of data that if appropriately detected can lead to earlier identification of disease states such as heart failure (HF). Using a novel text and data analytic tool we explored the longitudinal EHR of over 50,000 primary care patients to identify the documentation of the signs and symptoms of HF in the years preceding its diagnosis. Methods and Results Retrospective analysis consisting of 4,644 incident HF cases and 45,981 group-matched controls. Documentation of Framingham HF signs and symptoms within encounter notes were carried out using a previously validated natural language processing procedure. A total of 892,805 affirmed criteria were documented over an average observation period of 3.4 years. Among eventual HF cases, 85% had at least one criterion within a year prior to their HF diagnosis (as did 55% of controls). Substantial variability in the prevalence of individual signs and symptoms were found in both cases and controls. Conclusions HF signs and symptoms are frequently documented in a primary care population as identified through automated text and data mining of EHRs. Their frequent identification demonstrates the rich data available within EHRs that will allow for future work on automated criterion identification to help develop predictive models for HF. PMID:24709663

Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

PubMed

Sudarshan, Vidya K; Acharya, U Rajendra; Oh, Shu Lih; Adam, Muhammad; Tan, Jen Hong; Chua, Chua Kuang; Chua, Kok Poo; Tan, Ru San

2017-04-01

Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients. From these DTCWT coefficients, statistical features are extracted and ranked using Bhattacharyya, entropy, minimum redundancy maximum relevance (mRMR), receiver-operating characteristics (ROC), Wilcoxon, t-test and reliefF methods. Ranked features are subjected to k-nearest neighbor (KNN) and decision tree (DT) classifiers for automated differentiation of CHF and normal ECG signals. We have achieved 99.86% accuracy, 99.78% sensitivity and 99.94% specificity in the identification of CHF affected ECG signals using 45 features. The proposed method is able to detect CHF patients accurately using only 2s of ECG signal length and hence providing sufficient time for the clinicians to further investigate on the severity of CHF and treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic modelling and estimation of the error due to asynchronism in a redundant asynchronous multiprocessor system

NASA Technical Reports Server (NTRS)

Huynh, Loc C.; Duval, R. W.

1986-01-01

The use of Redundant Asynchronous Multiprocessor System to achieve ultrareliable Fault Tolerant Control Systems shows great promise. The development has been hampered by the inability to determine whether differences in the outputs of redundant CPU's are due to failures or to accrued error built up by slight differences in CPU clock intervals. This study derives an analytical dynamic model of the difference between redundant CPU's due to differences in their clock intervals and uses this model with on-line parameter identification to idenitify the differences in the clock intervals. The ability of this methodology to accurately track errors due to asynchronisity generate an error signal with the effect of asynchronisity removed and this signal may be used to detect and isolate actual system failures.

Donor-specific anti-HLA Abs and graft failure in matched unrelated donor hematopoietic stem cell transplantation

PubMed Central

Ciurea, Stefan O.; Thall, Peter F.; Wang, Xuemei; Wang, Sa A.; Hu, Ying; Cano, Pedro; Aung, Fleur; Rondon, Gabriela; Molldrem, Jeffrey J.; Korbling, Martin; Shpall, Elizabeth J.; de Lima, Marcos; Champlin, Richard E.

2011-01-01

Anti-HLA donor-specific Abs (DSAs) have been reported to be associated with graft failure in mismatched hematopoietic stem cell transplantation; however, their role in the development of graft failure in matched unrelated donor (MUD) transplantation remains unclear. We hypothesize that DSAs against a mismatched HLA-DPB1 locus is associated with graft failure in this setting. The presence of anti-HLA Abs before transplantation was determined prospectively in 592 MUD transplantation recipients using mixed-screen beads in a solid-phase fluorescent assay. DSA identification was performed using single-Ag beads containing the corresponding donor's HLA-mismatched Ags. Anti-HLA Abs were detected in 116 patients (19.6%), including 20 patients (3.4%) with anti-DPB1 Abs. Overall, graft failure occurred in 19 of 592 patients (3.2%), including 16 of 584 (2.7%) patients without anti-HLA Abs compared with 3 of 8 (37.5%) patients with DSA (P = .0014). In multivariate analysis, DSAs were the only factor highly associated with graft failure (P = .0001; odds ratio = 21.3). Anti-HLA allosensitization was higher overall in women than in men (30.8% vs 12.1%; P < .0001) and higher in women with 1 (P = .008) and 2 or more pregnancies (P = .0003) than in men. We conclude that the presence of anti-DPB1 DSAs is associated with graft failure in MUD hematopoietic stem cell transplantation. PMID:21967975

Complex Pattern of Resistance-Associated Substitutions of Hepatitis C Virus after Daclatasvir/Asunaprevir Treatment Failure

PubMed Central

Hasebe, Chitomi; Osaki, Yukio; Joko, Kouji; Yagisawa, Hitoshi; Sakita, Shinya; Okushin, Hiroaki; Satou, Takashi; Hisai, Hiroyuki; Abe, Takehiko; Tsuji, Keiji; Tamada, Takashi; Kobashi, Haruhiko; Mitsuda, Akeri; Ide, Yasushi; Ogawa, Chikara; Tsuruta, Syotaro; Takaguchi, Kouichi; Murakawa, Miyako; Asahina, Yasuhiro; Enomoto, Nobuyuki; Izumi, Namiki

2016-01-01

Backgrounds & Aims We aimed to clarify the characteristics of resistance-associated substitutions (RASs) after treatment failure with NS5A inhibitor, daclatasvir (DCV) in combination with NS3/4A inhibitor, asunaprevir (ASV), in patients with chronic hepatitis C virus genotype 1b infection. Methods This is a nationwide multicenter study conducted by the Japanese Red Cross Liver Study Group. The sera were obtained from 68 patients with virological failure after 24 weeks of DCV/ASV treatment. RASs in NS5A and NS3 were determined by population sequencing. Results The frequency of signature RASs at position D168 of NS3 was 68%, and at positions L31 and Y93 of NS5A was 79 and 76%, respectively. The frequency of dual signature RASs in NS5A (L31-RAS and Y93-RAS) was 63%. RASs at L28, R30, P32, Q54, P58, and A92 in addition to dual signature RAS were detected in 5, 5, 1, 22, 2, and 0 patients, respectively. In total, triple, quadruple, and quintuple RASs in combination with dual signature RAS were detected in 35, 10, and 1.5% patients, respectively. These RASs were detected in patients without baseline RASs or who prematurely discontinued therapy. Co-existence of D168 RAS in NS3 and L31 and/or Y93 RAS in NS5A was observed in 62% of patients. Conclusion Treatment-emergent RASs after failure with DCV/ASV combination therapy are highly complex in more than 50% of the patients. The identification of complex RAS patterns, which may indicate high levels of resistance to NS5A inhibitors, highlights the need for RAS sequencing when considering re-treatment with regimens including NS5A inhibitors. PMID:27776192

Design of analytical failure detection using secondary observers

NASA Technical Reports Server (NTRS)

Sisar, M.

1982-01-01

The problem of designing analytical failure-detection systems (FDS) for sensors and actuators, using observers, is addressed. The use of observers in FDS is related to the examination of the n-dimensional observer error vector which carries the necessary information on possible failures. The problem is that in practical systems, in which only some of the components of the state vector are measured, one has access only to the m-dimensional observer-output error vector, with m or = to n. In order to cope with these cases, a secondary observer is synthesized to reconstruct the entire observer-error vector from the observer output error vector. This approach leads toward the design of highly sensitive and reliable FDS, with the possibility of obtaining a unique fingerprint for every possible failure. In order to keep the observer's (or Kalman filter) false-alarm rate under a certain specified value, it is necessary to have an acceptable matching between the observer (or Kalman filter) models and the system parameters. A previously developed adaptive observer algorithm is used to maintain the desired system-observer model matching, despite initial mismatching or system parameter variations. Conditions for convergence for the adaptive process are obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors, while accurate and fast parameter identification, in both deterministic and stochastic cases, is obtained.

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

Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminousmore » flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.« less

Practical Implementation of Failure Mode and Effects Analysis for Safety and Efficiency in Stereotactic Radiosurgery

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

Younge, Kelly Cooper, E-mail: kyounge@med.umich.edu; Wang, Yizhen; Thompson, John

2015-04-01

Purpose: To improve the safety and efficiency of a new stereotactic radiosurgery program with the application of failure mode and effects analysis (FMEA) performed by a multidisciplinary team of health care professionals. Methods and Materials: Representatives included physicists, therapists, dosimetrists, oncologists, and administrators. A detailed process tree was created from an initial high-level process tree to facilitate the identification of possible failure modes. Group members were asked to determine failure modes that they considered to be the highest risk before scoring failure modes. Risk priority numbers (RPNs) were determined by each group member individually and then averaged. Results: A totalmore » of 99 failure modes were identified. The 5 failure modes with an RPN above 150 were further analyzed to attempt to reduce these RPNs. Only 1 of the initial items that the group presumed to be high-risk (magnetic resonance imaging laterality reversed) was ranked in these top 5 items. New process controls were put in place to reduce the severity, occurrence, and detectability scores for all of the top 5 failure modes. Conclusions: FMEA is a valuable team activity that can assist in the creation or restructuring of a quality assurance program with the aim of improved safety, quality, and efficiency. Performing the FMEA helped group members to see how they fit into the bigger picture of the program, and it served to reduce biases and preconceived notions about which elements of the program were the riskiest.« less

Limited effectiveness of patent blue dye in addition to isotope scanning for identification of sentinel lymph nodes: Cross-sectional real-life study in 1024 breast cancer patients.

PubMed

Rauch, Philippe; Merlin, Jean-Louis; Leufflen, Lea; Salleron, Julia; Harlé, Alexandre; Olivier, Pierre; Marchal, Frédéric

2016-09-01

Although morbidity is reduced when sentinel lymph node (SLN) biopsy is performed with dual isotopic and blue dye identification, the effectiveness of adding blue dye to radioisotope remains debated because side effects including anaphylactic reactions. Using data from a prospectively maintained database, 1884 lymph node-negative breast cancer patients who underwent partial mastectomy with SLN mapping by a dual-tracer using patent blue dye (PBD) and radioisotope were retrospectively studied between January 2000 and July 2013. Patients with tumors <3 cm and with >1 node detected by one of the two techniques (N = 1024) were included in this real-life cross-sectional study. Among the 1024 patients, 274 had positive SLN detected by isotopic and/or PBD staining. Only 4 patients having no detectable radioactivity in the axilla had SLN identified only by PBD staining (blue-only) while 26 patients had SLN only identified by isotopic detection (hot-only) illustrating failure rates of 9.5% (26/274) and 1.5% (4/274), respectively. Among these four patients, two had negative lymphoscintigraphy. Therefore, the contribution of PBD to metastatic nodes identification was relevant for only 2/274 patients (0.8%). Three patients (0.3%) had an allergic reaction with PBD, and anaphylactic shock occurred in two cases (0.2%). The added-value of PBD to reduce the false-negative rate of SLN mapping is only limited to the rare cases in which no radioactivity is detectable in the axilla (<1%). When a radioisotope mapping agent is available, the use of PBD should be avoided, because it can induce anaphylaxis. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Identification and Reconfigurable Control of Impaired Multi-Rotor Drones

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Bencomo, Alfredo

2016-01-01

The paper presents an algorithm for control and safe landing of impaired multi-rotor drones when one or more motors fail simultaneously or in any sequence. It includes three main components: an identification block, a reconfigurable control block, and a decisions making block. The identification block monitors each motor load characteristics and the current drawn, based on which the failures are detected. The control block generates the required total thrust and three axis torques for the altitude, horizontal position and/or orientation control of the drone based on the time scale separation and nonlinear dynamic inversion. The horizontal displacement is controlled by modulating the roll and pitch angles. The decision making algorithm maps the total thrust and three torques into the individual motor thrusts based on the information provided by the identification block. The drone continues the mission execution as long as the number of functioning motors provide controllability of it. Otherwise, the controller is switched to the safe mode, which gives up the yaw control, commands a safe landing spot and descent rate while maintaining the horizontal attitude.

Health management system for rocket engines

NASA Technical Reports Server (NTRS)

Nemeth, Edward

1990-01-01

The functional framework of a failure detection algorithm for the Space Shuttle Main Engine (SSME) is developed. The basic algorithm is based only on existing SSME measurements. Supplemental measurements, expected to enhance failure detection effectiveness, are identified. To support the algorithm development, a figure of merit is defined to estimate the likelihood of SSME criticality 1 failure modes and the failure modes are ranked in order of likelihood of occurrence. Nine classes of failure detection strategies are evaluated and promising features are extracted as the basis for the failure detection algorithm. The failure detection algorithm provides early warning capabilities for a wide variety of SSME failure modes. Preliminary algorithm evaluation, using data from three SSME failures representing three different failure types, demonstrated indications of imminent catastrophic failure well in advance of redline cutoff in all three cases.

PHOTOELECTRIC CONTROL FOR TAPE POSITIONING

DOEpatents

Woody, J.W. Jr.

1961-07-25

A control system is described for producing control impulses which may be used to start, stop, and position a magnetic tape with respect to a transducer, and to locate discrete areas on the tape. Means are provided for positive identification of data blocks, exact positioning of the tape under the magnetic head, drive in either direction, accurate skip-over of imperfect regions of the tape, stopping the tape if equipment malfunction results in a failure to detect the block-identifying signals, and starting and stopping those parts of the tape between of the tape drive clutches.

Instrumentation for In-Flight SSME Rocket Engine Plume Spectroscopy

NASA Technical Reports Server (NTRS)

Madzsar, George C.; Bickford, Randall L.; Duncan, David B.

1994-01-01

This paper describes instrumentation that is under development for an in-flight demonstration of a plume spectroscopy system on the space shuttle main engine. The instrumentation consists of a nozzle mounted optical probe for observation of the plume, and a spectrometer for identification and quantification of plume content. This instrumentation, which is intended for use as a diagnostic tool to detect wear and incipient failure in rocket engines, will be validated by a hardware demonstration on the Technology Test Bed engine at the Marshall Space Flight Center.

Unnecessary antiretroviral treatment switches and accumulation of HIV resistance mutations; two arguments for viral load monitoring in Africa.

PubMed

Sigaloff, Kim C E; Hamers, Raph L; Wallis, Carole L; Kityo, Cissy; Siwale, Margaret; Ive, Prudence; Botes, Mariette E; Mandaliya, Kishor; Wellington, Maureen; Osibogun, Akin; Stevens, Wendy S; van Vugt, Michèle; de Wit, Tobias F Rinke

2011-09-01

This study aimed to investigate the consequences of using clinicoimmunological criteria to detect antiretroviral treatment (ART) failure and guide regimen switches in HIV-infected adults in sub-Saharan Africa. Frequencies of unnecessary switches, patterns of HIV drug resistance, and risk factors for the accumulation of nucleoside reverse transcriptase inhibitor (NRTI)-associated mutations were evaluated. Cross-sectional analysis of adults switching ART regimens at 13 clinical sites in 6 African countries was performed. Two types of failure identification were compared: diagnosis of clinicoimmunological failure without viral load testing (CIF only) or CIF with local targeted viral load testing (targeted VL). After study enrollment, reference HIV RNA and genotype were determined retrospectively. Logistic regression assessed factors associated with multiple thymidine analogue mutations (TAMs) and NRTI cross-resistance (≥2 TAMs or Q151M or K65R/K70E). Of 250 patients with CIF switching to second-line ART, targeted VL was performed in 186. Unnecessary switch at reference HIV RNA <1000 copies per milliliter occurred in 46.9% of CIF only patients versus 12.4% of patients with targeted VL (P < 0.001). NRTI cross-resistance was observed in 48.0% of 183 specimens available for genotypic analysis, comprising ≥2 TAMs (37.7%), K65R (7.1%), K70E (3.3%), or Q151M (3.3%). The presence of NRTI cross-resistance was associated with the duration of ART exposure and zidovudine use. Clinicoimmunological monitoring without viral load testing resulted in frequent unnecessary regimen switches. Prolonged treatment failure was indicated by extensive NRTI cross-resistance. Access to virological monitoring should be expanded to prevent inappropriate switches, enable early failure detection and preserve second-line treatment options in Africa.

Unsupervised Learning —A Novel Clustering Method for Rolling Bearing Faults Identification

NASA Astrophysics Data System (ADS)

Kai, Li; Bo, Luo; Tao, Ma; Xuefeng, Yang; Guangming, Wang

2017-12-01

To promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rolling bearing. Among these studies, such as artificial neural networks, support vector machines, decision trees and other supervised learning methods are used commonly. These methods can detect the failure of rolling bearing effectively, but to achieve better detection results, it often requires a lot of training samples. Based on above, a novel clustering method is proposed in this paper. This novel method is able to find the correct number of clusters automatically the effectiveness of the proposed method is validated using datasets from rolling element bearings. The diagnosis results show that the proposed method can accurately detect the fault types of small samples. Meanwhile, the diagnosis results are also relative high accuracy even for massive samples.

Antiviral resistance and correlates of virologic failure in the first cohort of HIV-infected children gaining access to structured antiretroviral therapy in Lima, Peru: a cross-sectional analysis.

PubMed

Rath, Barbara A; von Kleist, Max; Castillo, Maria E; Kolevic, Lenka; Caballero, Patricia; Soto-Castellares, Giselle; Amedee, Angela M; Robinson, James E; Katzenstein, David K; Van Dyke, Russell B; Oberhelman, Richard A

2013-01-02

The impact of extended use of ART in developing countries has been enormous. A thorough understanding of all factors contributing to the success of antiretroviral therapy is required. The current study aims to investigate the value of cross-sectional drug resistance monitoring using DNA and RNA oligonucleotide ligation assays (OLA) in treatment cohorts in low-resource settings. The study was conducted in the first cohort of children gaining access to structured ART in Peru. Between 2002-5, 46 eligible children started the standard regimen of AZT, 3TC and NFV Patients had a median age of 5.6 years (range: 0.7-14y), a median viral load of 1.7·105 RNA/ml (range: 2.1·10(3) - 1.2·10(6)), and a median CD4-count of 232 cells/μL (range: 1-1591). Of these, 20 patients were classified as CDC clinical category C and 31/46 as CDC immune category 3. At the time of cross-sectional analysis in 2005, adherence questionnaires were administered. DNA OLAs and RNA OLAs were performed from frozen PBMC and plasma, RNA genotyping from dried blood spots. During the first year of ART, 44% of children experienced virologic failure, with an additional 9% failing by the end of the second year. Virologic failure was significantly associated with the number of resistance mutations detected by DNA-OLA (p < 0.001) during cross-sectional analysis, but also with low immunologic CDC-scores at baseline (p < 0.001). Children who had been exposed to unsupervised short-term antiretrovirals before starting structured ART showed significantly higher numbers of resistance mutations by DNA-OLA (p = 0.01). Detection of M184V (3TC resistance) by RNA-OLA and DNA-OLA demonstrated a sensitivity of 0.93 and 0.86 and specificity of 0.67 and 0.7, respectively, for the identification of virologic failure. The RT mutations N88D and L90M (NFV resistance) detected by DNA-OLA correlated with virologic failure, whereas mutations at RT position 215 (AZT resistance) were not associated with virologic failure. Advanced immunosuppression at baseline and previous exposures to unsupervised brief cycles of ART significantly impaired treatment outcomes at a time when structured ART was finally introduced in his cohort. Brief maternal exposures to with AZT +/- NVP for the prevention of mother-to-child transmission did not affect treatment outcomes in this group of children. DNA-OLA from frozen PBMC provided a highly specific tool to detect archived drug resistance. RNA consensus genotyping from dried blood spots and RNA-OLA from plasma consistently detected drug resistance mutations, but merely in association with virologic failure.

Method of preparing gas tags for identification of single and multiple failures of nuclear reactor fuel assemblies

DOEpatents

McCormick, Norman J.

1976-01-01

For use in the identification of failed fuel assemblies in a nuclear reactor, the ratios of the tag gas isotopic concentrations are located on curved surfaces to enable the ratios corresponding to failure of a single fuel assembly to be distinguished from those formed from any combination of two or more failed assemblies.

Identification of unusual events in multi-channel bridge monitoring data

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; Brownjohn, James Mark William; Moyo, Pilate

2004-03-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure such as bridges. However, converting large amounts of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localising sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Patient Safety in Complementary Medicine through the Application of Clinical Risk Management in the Public Health System

PubMed Central

Rossi, Elio G.; Picchi, Marco; Baccetti, Sonia; Monechi, Maria Valeria; Vuono, Catia; Sabatini, Federica; Traversi, Antonella; Di Stefano, Mariella; Firenzuoli, Fabio; Albolino, Sara; Tartaglia, Riccardo

2017-01-01

Aim: To develop a systematic approach to detect and prevent clinical risks in complementary medicine (CM) and increase patient safety through the analysis of activities in homeopathy and acupuncture centres in the Tuscan region using a significant event audit (SEA) and failure modes and effects analysis (FMEA). Methods: SEA is the selected tool for studying adverse events (AE) and detecting the best solutions to prevent future incidents in our Regional Healthcare Service (RHS). This requires the active participation of all the actors and external experts to validate the analysis. FMEA is a proactive risk assessment tool involving the selection of the clinical process, the input of a multidisciplinary group of experts, description of the process, identification of the failure modes (FMs) for each step, estimates of the frequency, severity, and detectability of FMs, calculation of the risk priority number (RPN), and prioritized improvement actions to prevent FMs. Results: In homeopathy, the greatest risk depends on the decision to switch from allopathic to homeopathic therapy. In acupuncture, major problems can arise, mainly from delayed treatment and from the modalities of needle insertion. Conclusions: The combination of SEA and FMEA can reveal potential risks for patients and suggest actions for safer and more reliable services in CM. PMID:29258191

Patient Safety in Complementary Medicine through the Application of Clinical Risk Management in the Public Health System.

PubMed

Rossi, Elio G; Bellandi, Tommaso; Picchi, Marco; Baccetti, Sonia; Monechi, Maria Valeria; Vuono, Catia; Sabatini, Federica; Traversi, Antonella; Di Stefano, Mariella; Firenzuoli, Fabio; Albolino, Sara; Tartaglia, Riccardo

2017-12-16

Aim: To develop a systematic approach to detect and prevent clinical risks in complementary medicine (CM) and increase patient safety through the analysis of activities in homeopathy and acupuncture centres in the Tuscan region using a significant event audit (SEA) and failure modes and effects analysis (FMEA). Methods: SEA is the selected tool for studying adverse events (AE) and detecting the best solutions to prevent future incidents in our Regional Healthcare Service (RHS). This requires the active participation of all the actors and external experts to validate the analysis. FMEA is a proactive risk assessment tool involving the selection of the clinical process, the input of a multidisciplinary group of experts, description of the process, identification of the failure modes (FMs) for each step, estimates of the frequency, severity, and detectability of FMs, calculation of the risk priority number (RPN), and prioritized improvement actions to prevent FMs. Results: In homeopathy, the greatest risk depends on the decision to switch from allopathic to homeopathic therapy. In acupuncture, major problems can arise, mainly from delayed treatment and from the modalities of needle insertion. Conclusions: The combination of SEA and FMEA can reveal potential risks for patients and suggest actions for safer and more reliable services in CM.

Practical, transparent prospective risk analysis for the clinical laboratory.

PubMed

Janssens, Pim Mw

2014-11-01

Prospective risk analysis (PRA) is an essential element in quality assurance for clinical laboratories. Practical approaches to conducting PRA in laboratories, however, are scarce. On the basis of the classical Failure Mode and Effect Analysis method, an approach to PRA was developed for application to key laboratory processes. First, the separate, major steps of the process under investigation are identified. Scores are then given for the Probability (P) and Consequence (C) of predefined types of failures and the chances of Detecting (D) these failures. Based on the P and C scores (on a 10-point scale), an overall Risk score (R) is calculated. The scores for each process were recorded in a matrix table. Based on predetermined criteria for R and D, it was determined whether a more detailed analysis was required for potential failures and, ultimately, where risk-reducing measures were necessary, if any. As an illustration, this paper presents the results of the application of PRA to our pre-analytical and analytical activities. The highest R scores were obtained in the stat processes, the most common failure type in the collective process steps was 'delayed processing or analysis', the failure type with the highest mean R score was 'inappropriate analysis' and the failure type most frequently rated as suboptimal was 'identification error'. The PRA designed is a useful semi-objective tool to identify process steps with potential failures rated as risky. Its systematic design and convenient output in matrix tables makes it easy to perform, practical and transparent. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A System for Fault Management for NASA's Deep Space Habitat

NASA Technical Reports Server (NTRS)

Colombano, Silvano P.; Spirkovska, Liljana; Aaseng, Gordon B.; Mccann, Robert S.; Baskaran, Vijayakumar; Ossenfort, John P.; Smith, Irene Skupniewicz; Iverson, David L.; Schwabacher, Mark A.

2013-01-01

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy.

A System for Fault Management and Fault Consequences Analysis for NASA's Deep Space Habitat

NASA Technical Reports Server (NTRS)

Colombano, Silvano; Spirkovska, Liljana; Baskaran, Vijaykumar; Aaseng, Gordon; McCann, Robert S.; Ossenfort, John; Smith, Irene; Iverson, David L.; Schwabacher, Mark

2013-01-01

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy

Real-time monitoring for detection of retained surgical sponges and team motion in the surgical operation room using radio-frequency-identification (RFID) technology: a preclinical evaluation.

PubMed

Kranzfelder, Michael; Zywitza, Dorit; Jell, Thomas; Schneider, Armin; Gillen, Sonja; Friess, Helmut; Feussner, Hubertus

2012-06-15

Technical progress in the surgical operating room (OR) increases constantly, facilitating the development of intelligent OR systems functioning as "safety backup" in the background of surgery. Precondition is comprehensive data retrieval to identify imminent risky situations and inaugurate adequate security mechanisms. Radio-frequency-identification (RFID) technology may have the potential to meet these demands. We set up a pilot study investigating feasibility and appliance reliability of a stationary RFID system for real-time surgical sponge monitoring (passive tagged sponges, position monitoring: mayo-stand/abdominal situs/waste bucket) and OR team tracking (active transponders, position monitoring: right/left side of OR table). In vitro: 20/20 sponges (100%) were detected on the mayo-stand and within the OR-phantom, however, real-time detection accuracy declined to 7/20 (33%) when the tags were moved simultaneously. All retained sponges were detected correctly. In vivo (animal): 7-10/10 sterilized sponges (70%-100%) were detected correctly within the abdominal cavity. OR-team: detection accuracy within the OR (surveillance antenna) and on both sides of the OR table (sector antenna) was 100%. Mean detection time for position change (left to right side and contrariwise) was 30-60 s. No transponder failure was noted. This is the first combined RFID system that has been developed for stationary use in the surgical OR. Preclinical evaluation revealed a reliable sponge tracking and correct detection of retained textiles (passive RFID) but also demonstrated feasibility of comprehensive data acquisition of team motion (active RFID). However, detection accuracy needs to be further improved before implementation into the surgical OR. Copyright © 2012 Elsevier Inc. All rights reserved.

Lithographic chip identification: meeting the failure analysis challenge

NASA Astrophysics Data System (ADS)

Perkins, Lynn; Riddell, Kevin G.; Flack, Warren W.

1992-06-01

This paper describes a novel method using stepper photolithography to uniquely identify individual chips for permanent traceability. A commercially available 1X stepper is used to mark chips with an identifier or `serial number' which can be encoded with relevant information for the integrated circuit manufacturer. The permanent identification of individual chips can improve current methods of quality control, failure analysis, and inventory control. The need for this technology is escalating as manufacturers seek to provide six sigma quality control for their products and trace fabrication problems to their source. This need is especially acute for parts that fail after packaging and are returned to the manufacturer for analysis. Using this novel approach, failure analysis data can be tied back to a particular batch, wafer, or even a position within a wafer. Process control can be enhanced by identifying the root cause of chip failures. Chip identification also addresses manufacturers concerns with increasing incidences of chip theft. Since chips currently carry no identification other than the manufacturer's name and part number, recovery efforts are hampered by the inability to determine the sales history of a specific packaged chip. A definitive identifier or serial number for each chip would address this concern. The results of chip identification (patent pending) are easily viewed through a low power microscope. Batch number, wafer number, exposure step, and chip location within the exposure step can be recorded, as can dates and other items of interest. An explanation of the chip identification procedure and processing requirements are described. Experimental testing and results are presented, and potential applications are discussed.

Redundancy relations and robust failure detection

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Lou, X. C.; Verghese, G. C.; Willsky, A. S.

1984-01-01

All failure detection methods are based on the use of redundancy, that is on (possible dynamic) relations among the measured variables. Consequently the robustness of the failure detection process depends to a great degree on the reliability of the redundancy relations given the inevitable presence of model uncertainties. The problem of determining redundancy relations which are optimally robust in a sense which includes the major issues of importance in practical failure detection is addressed. A significant amount of intuition concerning the geometry of robust failure detection is provided.

Integrated Neural Flight and Propulsion Control System

NASA Technical Reports Server (NTRS)

Kaneshige, John; Gundy-Burlet, Karen; Norvig, Peter (Technical Monitor)

2001-01-01

This paper describes an integrated neural flight and propulsion control system. which uses a neural network based approach for applying alternate sources of control power in the presence of damage or failures. Under normal operating conditions, the system utilizes conventional flight control surfaces. Neural networks are used to provide consistent handling qualities across flight conditions and for different aircraft configurations. Under damage or failure conditions, the system may utilize unconventional flight control surface allocations, along with integrated propulsion control, when additional control power is necessary for achieving desired flight control performance. In this case, neural networks are used to adapt to changes in aircraft dynamics and control allocation schemes. Of significant importance here is the fact that this system can operate without emergency or backup flight control mode operations. An additional advantage is that this system can utilize, but does not require, fault detection and isolation information or explicit parameter identification. Piloted simulation studies were performed on a commercial transport aircraft simulator. Subjects included both NASA test pilots and commercial airline crews. Results demonstrate the potential for improving handing qualities and significantly increasing survivability rates under various simulated failure conditions.

Identification of spider-mite species and their endosymbionts using multiplex PCR.

PubMed

Zélé, Flore; Weill, Mylène; Magalhães, Sara

2018-02-01

Spider mites of the genus Tetranychidae are severe crop pests. In the Mediterranean a few species coexist, but they are difficult to identify based on morphological characters. Additionally, spider mites often harbour several species of endosymbiotic bacteria, which may affect the biology of their hosts. Here, we propose novel, cost-effective, multiplex diagnostic methods allowing a quick identification of spider-mite species as well as of the endosymbionts they carry. First, we developed, and successfully multiplexed in a single PCR, primers to identify Tetranychus urticae, T. evansi and T. ludeni, some of the most common tetranychids found in southwest Europe. Moreover, we demonstrated that this method allows detecting multiple species in a single pool, even at low frequencies (up to 1/100), and can be used on entire mites without DNA extraction. Second, we developed another set of primers to detect spider-mite endosymbionts, namely Wolbachia, Cardinium and Rickettsia in a multiplex PCR, along with a generalist spider-mite primer to control for potential failure of DNA amplification in each PCR. Overall, our method represents a simple, cost-effective and reliable method to identify spider-mite species and their symbionts in natural field populations, as well as to detect contaminations in laboratory rearings. This method may easily be extended to other species.

Rapid detection of undesired cosmetic ingredients by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.

PubMed

Ouyang, Jie; An, Dongli; Chen, Tengteng; Lin, Zhiwei

2017-10-01

In recent years, cosmetic industry profits soared due to the widespread use of cosmetics, which resulted in illicit manufacturers and products of poor quality. Therefore, the rapid and accurate detection of the composition of cosmetics has become crucial. At present, numerous methods, such as gas chromatography and liquid chromatography-mass spectrometry, were available for the analysis of cosmetic ingredients. However, these methods present several limitations, such as failure to perform comprehensive and rapid analysis of the samples. Compared with other techniques, matrix-assisted laser desorption ionization time-of-flight mass spectrometry offered the advantages of wide detection range, fast speed and high accuracy. In this article, we briefly summarized how to select a suitable matrix and adjust the appropriate laser energy. We also discussed the rapid identification of undesired ingredients, focusing on antibiotics and hormones in cosmetics.

Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission

PubMed Central

Zhang, Zhiheng; Yang, Guoan; Hu, Kun

2018-01-01

Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of the blade status. Experiments on fatigue crack propagation based on the AE monitoring of gas turbine engine blades and TC11 titanium alloy plates were conducted. The relationship between the cumulative AE hits and the fatigue crack length was established, before a method of using the AE parameters to determine the crack propagation stage was proposed. A method for predicting the degree of crack propagation and residual fatigue life based on the AE energy was obtained. The results provide a new method for the online monitoring of cracks in the gas turbine engine blade. PMID:29693556

Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission.

PubMed

Zhang, Zhiheng; Yang, Guoan; Hu, Kun

2018-04-25

Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of the blade status. Experiments on fatigue crack propagation based on the AE monitoring of gas turbine engine blades and TC11 titanium alloy plates were conducted. The relationship between the cumulative AE hits and the fatigue crack length was established, before a method of using the AE parameters to determine the crack propagation stage was proposed. A method for predicting the degree of crack propagation and residual fatigue life based on the AE energy was obtained. The results provide a new method for the online monitoring of cracks in the gas turbine engine blade.

Solid motor diagnostic instrumentation. [design of self-contained instrumentation

NASA Technical Reports Server (NTRS)

Nakamura, Y.; Arens, W. E.; Wuest, W. S.

1973-01-01

A review of typical surveillance and monitoring practices followed during the flight phases of representative solid-propellant upper stages and apogee motors was conducted to evaluate the need for improved flight diagnostic instrumentation on future spacecraft. The capabilities of the flight instrumentation package were limited to the detection of whether or not the solid motor was the cause of failure and to the identification of probable primary failure modes. Conceptual designs of self-contained flight instrumentation packages capable of meeting these reqirements were generated and their performance, typical cost, and unit characteristics determined. Comparisons of a continuous real time and a thresholded hybrid design were made on the basis of performance, mass, power, cost, and expected life. The results of this analysis substantiated the feasibility of a self-contained independent flight instrumentation module as well as the existence of performance margins by which to exploit growth option applications.

Predicting failing performance on a standardized patient clinical performance examination: the importance of communication and professionalism skills deficits.

PubMed

Chang, Anna; Boscardin, Christy; Chou, Calvin L; Loeser, Helen; Hauer, Karen E

2009-10-01

The purpose is to determine which assessment measures identify medical students at risk of failing a clinical performance examination (CPX). Retrospective case-control, multiyear design, contingency table analysis, n = 149. We identified two predictors of CPX failure in patient-physician interaction skills: low clerkship ratings (odds ratio 1.79, P = .008) and student progress review for communication or professionalism concerns (odds ratio 2.64, P = .002). No assessments predicted CPX failure in clinical skills. Performance concerns in communication and professionalism identify students at risk of failing the patient-physician interaction portion of a CPX. This correlation suggests that both faculty and standardized patients can detect noncognitive traits predictive of failing performance. Early identification of these students may allow for development of a structured supplemental curriculum with increased opportunities for practice and feedback. The lack of predictors in the clinical skills portion suggests limited faculty observation or feedback.

Real-time automated failure identification in the Control Center Complex (CCC)

NASA Technical Reports Server (NTRS)

Kirby, Sarah; Lauritsen, Janet; Pack, Ginger; Ha, Anhhoang; Jowers, Steven; Mcnenny, Robert; Truong, The; Dell, James

1993-01-01

A system which will provide real-time failure management support to the Space Station Freedom program is described. The system's use of a simplified form of model based reasoning qualifies it as an advanced automation system. However, it differs from most such systems in that it was designed from the outset to meet two sets of requirements. First, it must provide a useful increment to the fault management capabilities of the Johnson Space Center (JSC) Control Center Complex (CCC) Fault Detection Management system. Second, it must satisfy CCC operational environment constraints such as cost, computer resource requirements, verification, and validation, etc. The need to meet both requirement sets presents a much greater design challenge than would have been the case had functionality been the sole design consideration. The choice of technology, discussing aspects of that choice and the process for migrating it into the control center is overviewed.

 Rapid identification system of frontal dysfunction in subclinical hepatic encephalopathy.

PubMed

Moretti, Rita; Gazzin, Silvia; Crocè, Lory Saveria; Baso, Beatrice; Masutti, Flora; Bedogni, Giorgio; Tiribelli, Claudio

2016-01-01

 Introduction and aim. Liver disease is associated with cognitive dysfunction also at early stages, and minimal hepatic encephalopathy, affecting 20-70% of patients, is frequently under-recognized. The main purpose of this work was to demonstrate that a substantial number of patients, enrolled due to an acute confusional state in absence of a diagnosis of liver disease, suffers of hepatic encephalopathy. Before a diagnosis of a well-compensated liver diseases was performed, 410 patients with an acute confusional state were enrolled in this study. Even in the presence of minimal alterations of hepatic function, the psychometric tests applied demonstrated early signs of cerebral frontal alteration. The alteration was associated with the severity of liver disease, paralleling the progression of the patient to minimal hepatic failure or chronic liver disease. These psychometric tests are essential to detect early and subclinical frontal failure. Frontal dysfunction may be a useful tool in the follow-up of these patients.

The application of the detection filter to aircraft control surface and actuator failure detection and isolation

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Wagner, E.; Motyka, P.; Hall, S. R.

1985-01-01

The performance of the detection filter in detecting and isolating aircraft control surface and actuator failures is evaluated. The basic detection filter theory assumption of no direct input-output coupling is violated in this application due to the use of acceleration measurements for detecting and isolating failures. With this coupling, residuals produced by control surface failures may only be constrained to a known plane rather than to a single direction. A detection filter design with such planar failure signatures is presented, with the design issues briefly addressed. In addition, a modification to constrain the residual to a single known direction even with direct input-output coupling is also presented. Both the detection filter and the modification are tested using a nonlinear aircraft simulation. While no thresholds were selected, both filters demonstrated an ability to detect control surface and actuator failures. Failure isolation may be a problem if there are several control surfaces which produce similar effects on the aircraft. In addition, the detection filter was sensitive to wind turbulence and modeling errors.

Accelerated Aging System for Prognostics of Power Semiconductor Devices

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Vashchenko, Vladislav; Wysocki, Philip; Saha, Sankalita

2010-01-01

Prognostics is an engineering discipline that focuses on estimation of the health state of a component and the prediction of its remaining useful life (RUL) before failure. Health state estimation is based on actual conditions and it is fundamental for the prediction of RUL under anticipated future usage. Failure of electronic devices is of great concern as future aircraft will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. Therefore, development of prognostics solutions for electronics is of key importance. This paper presents an accelerated aging system for gate-controlled power transistors. This system allows for the understanding of the effects of failure mechanisms, and the identification of leading indicators of failure which are essential in the development of physics-based degradation models and RUL prediction. In particular, this system isolates electrical overstress from thermal overstress. Also, this system allows for a precise control of internal temperatures, enabling the exploration of intrinsic failure mechanisms not related to the device packaging. By controlling the temperature within safe operation levels of the device, accelerated aging is induced by electrical overstress only, avoiding the generation of thermal cycles. The temperature is controlled by active thermal-electric units. Several electrical and thermal signals are measured in-situ and recorded for further analysis in the identification of leading indicators of failures. This system, therefore, provides a unique capability in the exploration of different failure mechanisms and the identification of precursors of failure that can be used to provide a health management solution for electronic devices.

F-8C adaptive flight control extensions. [for maximum likelihood estimation

NASA Technical Reports Server (NTRS)

Stein, G.; Hartmann, G. L.

1977-01-01

An adaptive concept which combines gain-scheduled control laws with explicit maximum likelihood estimation (MLE) identification to provide the scheduling values is described. The MLE algorithm was improved by incorporating attitude data, estimating gust statistics for setting filter gains, and improving parameter tracking during changing flight conditions. A lateral MLE algorithm was designed to improve true air speed and angle of attack estimates during lateral maneuvers. Relationships between the pitch axis sensors inherent in the MLE design were examined and used for sensor failure detection. Design details and simulation performance are presented for each of the three areas investigated.

Orthogonal series generalized likelihood ratio test for failure detection and isolation. [for aircraft control

NASA Technical Reports Server (NTRS)

Hall, Steven R.; Walker, Bruce K.

1990-01-01

A new failure detection and isolation algorithm for linear dynamic systems is presented. This algorithm, the Orthogonal Series Generalized Likelihood Ratio (OSGLR) test, is based on the assumption that the failure modes of interest can be represented by truncated series expansions. This assumption leads to a failure detection algorithm with several desirable properties. Computer simulation results are presented for the detection of the failures of actuators and sensors of a C-130 aircraft. The results show that the OSGLR test generally performs as well as the GLR test in terms of time to detect a failure and is more robust to failure mode uncertainty. However, the OSGLR test is also somewhat more sensitive to modeling errors than the GLR test.

A new debris sensor based on dual excitation sources for online debris monitoring

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Tomovic, Mileta M.; Liu, Haokuo; Wang, Xingjian

2015-09-01

Mechanical systems could be severely damaged by loose debris generated through wear processes between contact surfaces. Hence, debris detection is necessary for effective fault diagnosis, life prediction, and prevention of catastrophic failures. This paper presents a new in-line debris sensor for hydraulic systems based on dual excitation sources. The proposed sensor makes magnetic lines more concentrated while at the same time improving magnetic field uniformity. As a result the sensor has higher sensitivity and improved precision. This paper develops the sensor model, discusses sensor structural features, and introduces a measurement method for debris size identification. Finally, experimental verification is presented indicating that that the sensor can effectively detect 81 μm (cube) or larger particles in 12 mm outside diameter (OD) organic glass pipe.

Microwave imaging of spinning object using orbital angular momentum

NASA Astrophysics Data System (ADS)

Liu, Kang; Li, Xiang; Gao, Yue; Wang, Hongqiang; Cheng, Yongqiang

2017-09-01

The linear Doppler shift used for the detection of a spinning object becomes significantly weakened when the line of sight (LOS) is perpendicular to the object, which will result in the failure of detection. In this paper, a new detection and imaging technique for spinning objects is developed. The rotational Doppler phenomenon is observed by using the microwave carrying orbital angular momentum (OAM). To converge the radiation energy on the area where objects might exist, the generation method of OAM beams is proposed based on the frequency diversity principle, and the imaging model is derived accordingly. The detection method of the rotational Doppler shift and the imaging approach of the azimuthal profiles are proposed, which are verified by proof-of-concept experiments. Simulation and experimental results demonstrate that OAM beams can still be used to obtain the azimuthal profiles of spinning objects even when the LOS is perpendicular to the object. This work remedies the insufficiency in existing microwave sensing technology and offers a new solution to the object identification problem.

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.

PubMed

Park, Albert; Hartzler, Andrea L; Huh, Jina; McDonald, David W; Pratt, Wanda

2015-08-31

The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time. The primary objective of this study is to explore an alternative approach-using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap. Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap's commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures. From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap's mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively. We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.

Precise Geolocation Of Persistent Scatterers Aided And Validated By Lidar DSM

NASA Astrophysics Data System (ADS)

Chang, Ling; Dheenathayalan, Prabu; Hanessen, Ramon

2013-12-01

Persistent Scatterers (PS) interferometry results in the de- formation history of time-coherent scatterers. Although several applications focus on smooth, spatially correlated signals, we aim for the detection, identification and analysis of single anomalies. These targets can be indicative of, e.g., strain in structures, potentially leading to the failure of such structures. For the identification and analysis it is of the greatest importance to know the exact position of the effective scattering center, to avoid an improper interpretation of the driving mechanism. Here we present an approach to optimize the geolocation of important scatterers, when necessary aided by an a priori Lidar-derived DSM (AHN-1 data) with 15cm and 5m resolution in vertical and horizontal directions, respectively. The DSM is also used to validate the geocoding. We implement our approach on a near-collapse event of a shopping mall in Heerlen, the Netherlands, to generate the precise geolocation of local PS points.

Detection of wood failure by image processing method: influence of algorithm, adhesive and wood species

Treesearch

Lanying Lin; Sheng He; Feng Fu; Xiping Wang

2015-01-01

Wood failure percentage (WFP) is an important index for evaluating the bond strength of plywood. Currently, the method used for detecting WFP is visual inspection, which lacks efficiency. In order to improve it, image processing methods are applied to wood failure detection. The present study used thresholding and K-means clustering algorithms in wood failure detection...

Antiviral Resistance and Correlates of Virologic Failure in the first Cohort of HIV-Infected Children Gaining Access to Structured Antiretroviral Therapy in Lima, Peru: A Cross-Sectional Analysis

PubMed Central

2013-01-01

Background The impact of extended use of ART in developing countries has been enormous. A thorough understanding of all factors contributing to the success of antiretroviral therapy is required. The current study aims to investigate the value of cross-sectional drug resistance monitoring using DNA and RNA oligonucleotide ligation assays (OLA) in treatment cohorts in low-resource settings. The study was conducted in the first cohort of children gaining access to structured ART in Peru. Methods Between 2002–5, 46 eligible children started the standard regimen of AZT, 3TC and NFV Patients had a median age of 5.6 years (range: 0.7-14y), a median viral load of 1.7·105 RNA/ml (range: 2.1·103 – 1.2·106), and a median CD4-count of 232 cells/μL (range: 1–1591). Of these, 20 patients were classified as CDC clinical category C and 31/46 as CDC immune category 3. At the time of cross-sectional analysis in 2005, adherence questionnaires were administered. DNA OLAs and RNA OLAs were performed from frozen PBMC and plasma, RNA genotyping from dried blood spots. Results During the first year of ART, 44% of children experienced virologic failure, with an additional 9% failing by the end of the second year. Virologic failure was significantly associated with the number of resistance mutations detected by DNA-OLA (p < 0.001) during cross-sectional analysis, but also with low immunologic CDC-scores at baseline (p < 0.001). Children who had been exposed to unsupervised short-term antiretrovirals before starting structured ART showed significantly higher numbers of resistance mutations by DNA-OLA (p = 0.01). Detection of M184V (3TC resistance) by RNA-OLA and DNA-OLA demonstrated a sensitivity of 0.93 and 0.86 and specificity of 0.67 and 0.7, respectively, for the identification of virologic failure. The RT mutations N88D and L90M (NFV resistance) detected by DNA-OLA correlated with virologic failure, whereas mutations at RT position 215 (AZT resistance) were not associated with virologic failure. Conclusions Advanced immunosuppression at baseline and previous exposures to unsupervised brief cycles of ART significantly impaired treatment outcomes at a time when structured ART was finally introduced in his cohort. Brief maternal exposures to with AZT +/− NVP for the prevention of mother-to-child transmission did not affect treatment outcomes in this group of children. DNA-OLA from frozen PBMC provided a highly specific tool to detect archived drug resistance. RNA consensus genotyping from dried blood spots and RNA-OLA from plasma consistently detected drug resistance mutations, but merely in association with virologic failure. PMID:23280237

Detection and molecular identification of leishmania RNA virus (LRV) in Iranian Leishmania species.

PubMed

Hajjaran, Homa; Mahdi, Maryam; Mohebali, Mehdi; Samimi-Rad, Katayoun; Ataei-Pirkooh, Angila; Kazemi-Rad, Elham; Naddaf, Saied Reza; Raoofian, Reza

2016-12-01

Leishmania RNA virus (LRV) was first detected in members of the subgenus Leishmania (Viannia), and later, the virulence and metastasis of the New World species were attributed to this virus. The data on the presence of LRV in Old World species are confined to Leishmania major and a few Leishmania aethiopica isolates. The aim of this study was to survey the presence of LRV in various Iranian Leishmania species originating from patients and animal reservoir hosts. Genomic nucleic acids were extracted from 50 cultured isolates belonging to the species Leishmania major, Leishmania tropica, and Leishmania infantum. A partial sequence of the viral RNA-dependent RNA polymerase (RdRp) gene was amplified, sequenced and compared with appropriate sequences from the GenBank database. We detected the virus in two parasite specimens: an isolate of L. infantum derived from a visceral leishmaniasis (VL) patient who was unresponsive to meglumine antimoniate treatment, and an L. major isolate originating from a great gerbil, Rhombomys opimus. The Iranian LRV sequences showed the highest similarities to an Old World L. major LRV2 and were genetically distant from LRV1 isolates detected in New World Leishmania parasites. We could not attribute treatment failure in VL patient to the presence of LRV due to the limited number of specimens analyzed. Further studies with inclusion of more clinical samples are required to elucidate the potential role of LRVs in pathogenesis or treatment failure of Old World leishmaniasis.

The use of light emission in failure analysis of CMOS ICs

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

Hawkins, C.F.; Soden, J.M.; Cole, E.I. Jr.

1990-01-01

The use of photon emission for analyzing failure mechanisms and defects in CMOS ICs is presented. Techniques are given for accurate identification and spatial localization of failure mechanisms and physical defects, including defects such as short and open circuits which do not themselves emit photons.

Analysis of arrhythmic events is useful to detect lead failure earlier in patients followed by remote monitoring.

PubMed

Nishii, Nobuhiro; Miyoshi, Akihito; Kubo, Motoki; Miyamoto, Masakazu; Morimoto, Yoshimasa; Kawada, Satoshi; Nakagawa, Koji; Watanabe, Atsuyuki; Nakamura, Kazufumi; Morita, Hiroshi; Ito, Hiroshi

2018-03-01

Remote monitoring (RM) has been advocated as the new standard of care for patients with cardiovascular implantable electronic devices (CIEDs). RM has allowed the early detection of adverse clinical events, such as arrhythmia, lead failure, and battery depletion. However, lead failure was often identified only by arrhythmic events, but not impedance abnormalities. To compare the usefulness of arrhythmic events with conventional impedance abnormalities for identifying lead failure in CIED patients followed by RM. CIED patients in 12 hospitals have been followed by the RM center in Okayama University Hospital. All transmitted data have been analyzed and summarized. From April 2009 to March 2016, 1,873 patients have been followed by the RM center. During the mean follow-up period of 775 days, 42 lead failure events (atrial lead 22, right ventricular pacemaker lead 5, implantable cardioverter defibrillator [ICD] lead 15) were detected. The proportion of lead failures detected only by arrhythmic events, which were not detected by conventional impedance abnormalities, was significantly higher than that detected by impedance abnormalities (arrhythmic event 76.2%, 95% CI: 60.5-87.9%; impedance abnormalities 23.8%, 95% CI: 12.1-39.5%). Twenty-seven events (64.7%) were detected without any alert. Of 15 patients with ICD lead failure, none has experienced inappropriate therapy. RM can detect lead failure earlier, before clinical adverse events. However, CIEDs often diagnose lead failure as just arrhythmic events without any warning. Thus, to detect lead failure earlier, careful human analysis of arrhythmic events is useful. © 2017 Wiley Periodicals, Inc.

Analysis of a risk prevention document using dependability techniques: a first step towards an effectiveness model

NASA Astrophysics Data System (ADS)

Ferrer, Laetitia; Curt, Corinne; Tacnet, Jean-Marc

2018-04-01

Major hazard prevention is a main challenge given that it is specifically based on information communicated to the public. In France, preventive information is notably provided by way of local regulatory documents. Unfortunately, the law requires only few specifications concerning their content; therefore one can question the impact on the general population relative to the way the document is concretely created. Ergo, the purpose of our work is to propose an analytical methodology to evaluate preventive risk communication document effectiveness. The methodology is based on dependability approaches and is applied in this paper to the Document d'Information Communal sur les Risques Majeurs (DICRIM; in English, Municipal Information Document on Major Risks). DICRIM has to be made by mayors and addressed to the public to provide information on major hazards affecting their municipalities. An analysis of law compliance of the document is carried out thanks to the identification of regulatory detection elements. These are applied to a database of 30 DICRIMs. This analysis leads to a discussion on points such as usefulness of the missing elements. External and internal function analysis permits the identification of the form and content requirements and service and technical functions of the document and its components (here its sections). Their results are used to carry out an FMEA (failure modes and effects analysis), which allows us to define the failure and to identify detection elements. This permits the evaluation of the effectiveness of form and content of each components of the document. The outputs are validated by experts from the different fields investigated. Those results are obtained to build, in future works, a decision support model for the municipality (or specialised consulting firms) in charge of drawing up documents.

Cardio-Ankle Vascular Index and C-Reactive Protein Are Useful Parameters for Identification of Ischemic Heart Disease in Acute Heart Failure Patients.

PubMed

Kiuchi, Shunsuke; Hisatake, Shinji; Kabuki, Takayuki; Oka, Takashi; Dobashi, Shintaro; Fujii, Takahiro; Ikeda, Takanori

2017-05-01

The most common cause of heart failure (HF) is ischemic heart disease (IHD). Evaluation of IHD with non-invasive examinations is useful for the treatment of HF, and cardio-ankle vascular index (CAVI) is a good parameter for detecting systemic arteriosclerosis. However, the relationship between IHD and CAVI in acute HF (AHF) patients is still unclear. Therefore, we investigated the effect of non-invasive examinations, including CAVI to detect IHD. We studied 53 consecutive patients (average age of 66.5 ± 10.9 years old, 36 males) with AHF from January 2009 to December 2012. These patients were classified into the IHD group (n = 19) and non-IHD group (n = 34) according to the coronary artery angiography results. We evaluated the vital signs, laboratory findings and CAVI. According to the laboratory findings, the C-reactive protein (CRP) in IHD group was significantly higher than non-IHD group (1.5 ± 2.1 mg/dL vs. 0.4 ± 0.4 mg/dL, P = 0.002). CAVI in IHD group was significantly higher than non-IHD group (9.58 ± 1.73 vs. 7.83 ± 1.86, P < 0.001). In the receiver operating characteristic (ROC) curve for discriminating the probability of IHD, the cut-off point of the CRP plus CAVI was 9.00. At that cut-off point, the sensitivity and the specificity were 69.7% and 89.5%, respectively. The mean area under the ROC curve (AUC) defined by the CRP plus CAVI was the greatest at all parameters. The CRP and CAVI were useful parameters for the identification of IHD in patients with AHF.

Detection of system failures in multi-axes tasks. [pilot monitored instrument approach

NASA Technical Reports Server (NTRS)

Ephrath, A. R.

1975-01-01

The effects of the pilot's participation mode in the control task on his workload level and failure detection performance were examined considering a low visibility landing approach. It is found that the participation mode had a strong effect on the pilot's workload, the induced workload being lowest when the pilot acted as a monitoring element during a coupled approach and highest when the pilot was an active element in the control loop. The effects of workload and participation mode on failure detection were separated. The participation mode was shown to have a dominant effect on the failure detection performance, with a failure in a monitored (coupled) axis being detected significantly faster than a comparable failure in a manually controlled axis.

On-Board Particulate Filter Failure Prevention and Failure Diagnostics Using Radio Frequency Sensing

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

Sappok, Alex; Ragaller, Paul; Herman, Andrew

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directlymore » monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications. The testing included controlled engine dynamometer evaluations, which characterized soot slip from various filter failure modes, as well as on-road fleet vehicle tests. The results show a high sensitivity to detect conditions resulting in soot leakage from the particulate filter, as well as potential for direct detection of structural failures including internal cracks and melted regions within the filter media itself. Furthermore, the measurements demonstrate, for the first time, the capability to employ a direct and continuous monitor of particulate filter diagnostics to both prevent and detect potential failure conditions in the field.« less

Rapid detection of urinary polyomavirus BK by heterodyne-based surface plasmon resonance biosensor

NASA Astrophysics Data System (ADS)

Su, Li-Chen; Tian, Ya-Chung; Chang, Ying-Feng; Chou, Chien; Lai, Chao-Sung

2014-01-01

In renal transplant patients, immunosuppressive therapy may result in the reactivation of polyomavirus BK (BKV), leading to polyomavirus-associated nephropathy (PVAN), which inevitably causes allograft failure. Since the treatment outcomes of PVAN remain unsatisfactory, early identification and continuous monitoring of BKV reactivation and reduction of immunosuppressants are essential to prevent PVAN development. The present study demonstrated that the developed dual-channel heterodyne-based surface plasmon resonance (SPR) biosensor is applicable for the rapid detection of urinary BKV. The use of a symmetrical reference channel integrated with the poly(ethylene glycol)-based low-fouling self-assembled monolayer to reduce the environmental variations and the nonspecific noise was proven to enhance the sensitivity in urinary BKV detection. Experimentally, the detection limit of the biosensor for BKV detection was estimated to be around 8500 copies/mL. In addition, urine samples from five renal transplant patients were tested to rapidly distinguish PVAN-positive and PVAN-negative renal transplant patients. By virtue of its simplicity, rapidity, and applicability, the SPR biosensor is a remarkable potential to be used for continuous clinical monitoring of BKV reactivation.

Bearing failure detection of micro wind turbine via power spectral density analysis for stator current signals spectrum

NASA Astrophysics Data System (ADS)

Mahmood, Faleh H.; Kadhim, Hussein T.; Resen, Ali K.; Shaban, Auday H.

2018-05-01

The failure such as air gap weirdness, rubbing, and scrapping between stator and rotor generator arise unavoidably and may cause extremely terrible results for a wind turbine. Therefore, we should pay more attention to detect and identify its cause-bearing failure in wind turbine to improve the operational reliability. The current paper tends to use of power spectral density analysis method of detecting internal race and external race bearing failure in micro wind turbine by estimation stator current signal of the generator. The failure detector method shows that it is well suited and effective for bearing failure detection.

Identification of unusual events in multichannel bridge monitoring data using wavelet transform and outlier analysis

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; Brownjohn, James M. W.; Moyo, Pilate

2003-08-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure. However, converting large amount of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure in Singapore and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localizing sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Turbofan engine demonstration of sensor failure detection

NASA Technical Reports Server (NTRS)

Merrill, Walter C.; Delaat, John C.; Abdelwahab, Mahmood

1991-01-01

In the paper, the results of a full-scale engine demonstration of a sensor failure detection algorithm are presented. The algorithm detects, isolates, and accommodates sensor failures using analytical redundancy. The experimental hardware, including the F100 engine, is described. Demonstration results were obtained over a large portion of a typical flight envelope for the F100 engine. They include both subsonic and supersonic conditions at both medium and full, nonafter burning, power. Estimated accuracy, minimum detectable levels of sensor failures, and failure accommodation performance for an F100 turbofan engine control system are discussed.

Study of an automatic trajectory following control system

NASA Technical Reports Server (NTRS)

Vanlandingham, H. F.; Moose, R. L.; Zwicke, P. E.; Lucas, W. H.; Brinkley, J. D.

1983-01-01

It is shown that the estimator part of the Modified Partitioned Adaptive Controller, (MPAC) developed for nonlinear aircraft dynamics of a small jet transport can adapt to sensor failures. In addition, an investigation is made into the potential usefulness of the configuration detection technique used in the MPAC and the failure detection filter is developed that determines how a noise plant output is associated with a line or plane characteristic of a failure. It is shown by computer simulation that the estimator part and the configuration detection part of the MPAC can readily adapt to actuator and sensor failures and that the failure detection filter technique cannot detect actuator or sensor failures accurately for this type of system because of the plant modeling errors. In addition, it is shown that the decision technique, developed for the failure detection filter, can accurately determine that the plant output is related to the characteristic line or plane in the presence of sensor noise.

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit. [inertial platforms

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures.

Identification of Bearing Failure Using Signal Vibrations

NASA Astrophysics Data System (ADS)

Yani, Irsyadi; Resti, Yulia; Burlian, Firmansyah

2018-04-01

Vibration analysis can be used to identify damage to mechanical systems such as journal bearings. Identification of failure can be done by observing the resulting vibration spectrum by measuring the vibration signal occurring in a mechanical system Bearing is one of the engine elements commonly used in mechanical systems. The main purpose of this research is to monitor the bearing condition and to identify bearing failure on a mechanical system by observing the resulting vibration. Data collection techniques based on recordings of sound caused by the vibration of the mechanical system were used in this study, then created a database system based bearing failure due to vibration signal recording sounds on a mechanical system The next step is to group the bearing damage by type based on the databases obtained. The results show the percentage of success in identifying bearing damage is 98 %.

Role of failure-mechanism identification in accelerated testing

NASA Technical Reports Server (NTRS)

Hu, J. M.; Barker, D.; Dasgupta, A.; Arora, A.

1993-01-01

Accelerated life testing techniques provide a short-cut method to investigate the reliability of electronic devices with respect to certain dominant failure mechanisms that occur under normal operating conditions. However, accelerated tests have often been conducted without knowledge of the failure mechanisms and without ensuring that the test accelerated the same mechanism as that observed under normal operating conditions. This paper summarizes common failure mechanisms in electronic devices and packages and investigates possible failure mechanism shifting during accelerated testing.

Experimental investigation on frequency shifting of imperfect adhesively bonded pipe joints

NASA Astrophysics Data System (ADS)

Haiyam, F. N.; Hilmy, I.; Sulaeman, E.; Firdaus, T.; Adesta, E. Y. T.

2018-01-01

Inspection tests for any manufactured structure are compulsory in order to detect the existence of damage.It is to ensure the product integrity, reliability and to avoid further catastrophic failure. In this research, modal analysis was utilized to detect structural damage as one of the Non Destructive Testing (NDT) methods. Comparing the vibration signal of a healthy structure with a non-healthy signal was performed. A modal analysis of an adhesively bonded pipe joint was investigated with a healthy joint as a reference. The damage joint was engineered by inserting a nylon fiber, which act as an impurity at adhesive region. The impact test using hammer was utilized in this research. Identification of shifting frequency of a free supported and clamped pipe joint was performed.It was found that shifting frequency occurred to the lower side by 5%.

The role of modern control theory in the design of controls for aircraft turbine engines

NASA Technical Reports Server (NTRS)

Zeller, J.; Lehtinen, B.; Merrill, W.

1982-01-01

The development, applications, and current research in modern control theory (MCT) are reviewed, noting the importance for fuel-efficient operation of turbines with variable inlet guide vanes, compressor stators, and exhaust nozzle area. The evolution of multivariable propulsion control design is examined, noting a basis in a matrix formulation of the differential equations defining the process, leading to state space formulations. Reports and papers which appeared from 1970-1982 which dealt with problems in MCT applications to turbine engine control design are outlined, including works on linear quadratic regulator methods, frequency domain methods, identification, estimation, and model reduction, detection, isolation, and accommodation, and state space control, adaptive control, and optimization approaches. Finally, NASA programs in frequency domain design, sensor failure detection, computer-aided control design, and plant modeling are explored

Recombinations in Staphylococcal Cassette Chromosome mec Elements Compromise the Molecular Detection of Methicillin Resistance in Staphylococcus aureus

PubMed Central

Hill-Cawthorne, Grant A.; Hudson, Lyndsey O.; El Ghany, Moataz Fouad Abd; Piepenburg, Olaf; Nair, Mridul; Dodgson, Andrew; Forrest, Matthew S.

2014-01-01

Clinical laboratories are increasingly using molecular tests for methicillin-resistant Staphylococcus aureus (MRSA) screening. However, primers have to be targeted to a variable chromosomal region, the staphylococcal cassette chromosome mec (SCCmec). We initially screened 726 MRSA isolates from a single UK hospital trust by recombinase polymerase amplification (RPA), a novel, isothermal alternative to PCR. Undetected isolates were further characterised using multilocus sequence, spa typing and whole genome sequencing. 96% of our tested phenotypically MRSA isolates contained one of the six orfX-SCCmec junctions our RPA test and commercially available molecular tests target. However 30 isolates could not be detected. Sequencing of 24 of these isolates demonstrated recombinations within the SCCmec element with novel insertions that interfered with the RPA, preventing identification as MRSA. This result suggests that clinical laboratories cannot rely solely upon molecular assays to reliably detect all methicillin-resistance. The presence of significant recombinations in the SCCmec element, where the majority of assays target their primers, suggests that there will continue to be isolates that escape identification. We caution that dependence on amplification-based molecular assays will continue to result in failure to diagnose a small proportion (∼4%) of MRSA isolates, unless the true level of SCCmec natural diversity is determined by whole genome sequencing of a large collection of MRSA isolates. PMID:24972080

A near full-length open reading frame next generation sequencing assay for genotyping and identification of resistance-associated variants in hepatitis C virus.

PubMed

Pedersen, M S; Fahnøe, U; Hansen, T A; Pedersen, A G; Jenssen, H; Bukh, J; Schønning, K

2018-06-01

The current treatment options for hepatitis C virus (HCV), based on direct acting antivirals (DAA), are dependent on virus genotype and previous treatment experience. Treatment failures have been associated with detection of resistance-associated substitutions (RASs) in the DAA targets of HCV, the NS3, NS5A and NS5 B proteins. To develop a next generation sequencing based method that provides genotype and detection of HCV NS3, NS5A, and NS5 B RASs without prior knowledge of sample genotype. In total, 101 residual plasma samples from patients with HCV covering 10 different viral subtypes across 4 genotypes with viral loads of 3.84-7.61 Log IU/mL were included. All samples were de-identified and consequently prior treatment status for patients was unknown. Almost full open reading frame amplicons (∼ 9 kb) were generated using RT-PCR with a single primer set. The resulting amplicons were sequenced with high throughput sequencing and analysed using an in-house developed script for detecting RASs. The method successfully amplified and sequenced 94% (95/101) of samples with an average coverage of 14,035; four of six failed samples were genotype 4a. Samples analysed twice yielded reproducible nucleotide frequencies across all sites. RASs were detected in 21/95 (22%) samples at a 15% threshold. The method identified one patient infected with two genotype 2b variants, and the presence of subgenomic deletion variants in 8 (8.4%) of 95 successfully sequenced samples. The presented method may provide identification of HCV genotype, RASs detection, and detect multiple HCV infection without prior knowledge of sample genotype. Copyright © 2018 Elsevier B.V. All rights reserved.

In Operation Detection and Correction of Rotor Imbalance in Jet Engines Using Active Vibration Control

NASA Technical Reports Server (NTRS)

Manchala, Daniel W.; Palazzolo, Alan B.; Kascak, Albert F.; Montague, Gerald T.; Brown, Gerald V.; Lawrence, Charles; Klusman, Steve

1994-01-01

Jet Engines may experience severe vibration due to the sudden imbalance caused by blade failure. This research investigates employment of on board magnetic bearings or piezoelectric actuators to cancel these forces in flight. This operation requires identification of the source of the vibrations via an expert system, determination of the required phase angles and amplitudes for the correction forces, and application of the desired control signals to the magnetic bearings or piezo electric actuators. This paper will show the architecture of the software system, details of the control algorithm used for the sudden imbalance correction project described above, and the laboratory test results.

B-type natriuretic peptide testing for detection of heart failure.

PubMed

Saul, Lauren; Shatzer, Melanie

2003-01-01

The incidence of heart failure (HF) is on the increase with the aging population. Heart failure can manifest as either systolic or diastolic dysfunction. Systolic dysfunction causes impaired ventricular contractility with an ejection fraction of less than 45%. In contrast, diastolic dysfunction is evidenced by impaired ventricular relaxation and an ejection fraction greater than 45%. The diagnosis of HF is challenging with patients who present with acute dyspnea and a history of chronic obstructive pulmonary disease or pneumonia. The pathophysiology of HF and the resulting compensatory mechanisms involve a complex neuroendocrine response that includes a release of natriuretic peptides including B-type natriuretic peptides (BNPs). Elevation of BNP is in response to ventricular wall stress and volume overload from HF. BNP promotes natriuresis, diuresis, and vasodilitation and therefore counteracts some of the deleterious effects of the neuroendocrine response in HF Recently, a new laboratory test for BNP has been developed to assist in rapid identification of patients with HF. Research studies have shown that BNP testing assists in differentiating between cardiac and pulmonary causes of acute dyspnea and could be used to evaluate effectiveness of therapy and as a predictor for length of stay and readmission.

Detecting Solenoid Valve Deterioration in In-Use Electronic Diesel Fuel Injection Control Systems

PubMed Central

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves. PMID:22163597

Detecting solenoid valve deterioration in in-use electronic diesel fuel injection control systems.

PubMed

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves.

A vector-based failure detection and isolation algorithm for a dual fail-operational redundant strapdown inertial measurement unit

NASA Technical Reports Server (NTRS)

Morrell, Frederick R.; Bailey, Melvin L.

1987-01-01

A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.

Identifying Students at Risk of School Failure in Luxembourgish Secondary School

ERIC Educational Resources Information Center

Klapproth, Florian; Schaltz, Paule

2013-01-01

If teachers knew in advance whether their students are at risk of school failure, they would have the opportunity to supply these students with additional or special instruction. In Luxembourg, the likelihood of failure in school is particularly high. Taking this result into account, this paper deals with the identification of variables of primary…

Accuracy of a Rationally Derived Method for Identifying Treatment Failure in Children and Adolescents

ERIC Educational Resources Information Center

Bishop, Matthew J.; Bybee, Taige S.; Lambert, Michael J.; Burlingame, Gary M.; Wells, M. Gawain; Poppleton, Landon E.

2005-01-01

Psychotherapy outcome can be enhanced by early identification of potential treatment failures before they leave treatment. In adults, compelling data are emerging that provide evidence that an early warning system that identifies potential treatment failures can be developed and applied to enhance outcome. The present study reports an analysis of…

Detection, Diagnosis and Prognosis: Contribution to the energy challenge: Proceedings of the Meeting of the Mechanical Failures Prevention Group

NASA Technical Reports Server (NTRS)

Shives, T. R. (Editor); Willard, W. A. (Editor)

1981-01-01

The contribution of failure detection, diagnosis and prognosis to the energy challenge is discussed. Areas of special emphasis included energy management, techniques for failure detection in energy related systems, improved prognostic techniques for energy related systems and opportunities for detection, diagnosis and prognosis in the energy field.

The Role of In Vitro Susceptibility Testing in the Management of Candida and Aspergillus.

PubMed

Ostrosky-Zeichner, Luis; Andes, David

2017-08-15

Antifungal susceptibility testing has evolved from a research technique to a standardized and well-validated tool for the clinical management of fungal infections and for epidemiological studies. Genetic mutations and phenotypic resistance in vitro have been shown to correlate with clinical outcomes and treatment failures, and this in turn has led to the creation of clinical breakpoints and, more recently, epidemiological cutoff values for clinically relevant fungal pathogens. Resistance mechanisms for Candida and Aspergillus species have been extensively described and their corresponding genetic mutations can now be readily detected. Epidemiological studies have been able to detect the emergence of regional clonal and nonclonal resistance in several countries. The clinical microbiology laboratory is expected to transition from culture and traditional susceptibility testing to molecular methods for detection, identification, and resistance profiling over the next 5-10 years. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model

PubMed Central

Johnson, Robin R.; Popovic, Djordje P.; Olmstead, Richard E.; Stikic, Maja; Levendowski, Daniel J.; Berka, Chris

2011-01-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: 1) lack of generalizability, 2) failure to address individual variability in generalized models, and/or 3) they lack a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. PMID:21419826

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model.

PubMed

Johnson, Robin R; Popovic, Djordje P; Olmstead, Richard E; Stikic, Maja; Levendowski, Daniel J; Berka, Chris

2011-05-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: (1) lack of generalizability, (2) failure to address individual variability in generalized models, and/or (3) lack of a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. Copyright © 2011 Elsevier B.V. All rights reserved.

Investigation of the cross-ship comparison monitoring method of failure detection in the HIMAT RPRV. [digital control techniques using airborne microprocessors

NASA Technical Reports Server (NTRS)

Wolf, J. A.

1978-01-01

The Highly maneuverable aircraft technology (HIMAT) remotely piloted research vehicle (RPRV) uses cross-ship comparison monitoring of the actuator RAM positions to detect a failure in the aileron, canard, and elevator control surface servosystems. Some possible sources of nuisance trips for this failure detection technique are analyzed. A FORTRAN model of the simplex servosystems and the failure detection technique were utilized to provide a convenient means of changing parameters and introducing system noise. The sensitivity of the technique to differences between servosystems and operating conditions was determined. The cross-ship comparison monitoring method presently appears to be marginal in its capability to detect an actual failure and to withstand nuisance trips.

Real-time failure control (SAFD)

NASA Technical Reports Server (NTRS)

Panossian, Hagop V.; Kemp, Victoria R.; Eckerling, Sherry J.

1990-01-01

The Real Time Failure Control program involves development of a failure detection algorithm, referred as System for Failure and Anomaly Detection (SAFD), for the Space Shuttle Main Engine (SSME). This failure detection approach is signal-based and it entails monitoring SSME measurement signals based on predetermined and computed mean values and standard deviations. Twenty four engine measurements are included in the algorithm and provisions are made to add more parameters if needed. Six major sections of research are presented: (1) SAFD algorithm development; (2) SAFD simulations; (3) Digital Transient Model failure simulation; (4) closed-loop simulation; (5) SAFD current limitations; and (6) enhancements planned for.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

Application of failure mode and effects analysis (FMEA) to pretreatment phases in tomotherapy.

PubMed

Broggi, Sara; Cantone, Marie Claire; Chiara, Anna; Di Muzio, Nadia; Longobardi, Barbara; Mangili, Paola; Veronese, Ivan

2013-09-06

The aim of this paper was the application of the failure mode and effects analysis (FMEA) approach to assess the risks for patients undergoing radiotherapy treatments performed by means of a helical tomotherapy unit. FMEA was applied to the preplanning imaging, volume determination, and treatment planning stages of the tomotherapy process and consisted of three steps: 1) identification of the involved subprocesses; 2) identification and ranking of the potential failure modes, together with their causes and effects, using the risk probability number (RPN) scoring system; and 3) identification of additional safety measures to be proposed for process quality and safety improvement. RPN upper threshold for little concern of risk was set at 125. A total of 74 failure modes were identified: 38 in the stage of preplanning imaging and volume determination, and 36 in the stage of planning. The threshold of 125 for RPN was exceeded in four cases: one case only in the phase of preplanning imaging and volume determination, and three cases in the stage of planning. The most critical failures appeared related to (i) the wrong or missing definition and contouring of the overlapping regions, (ii) the wrong assignment of the overlap priority to each anatomical structure, (iii) the wrong choice of the computed tomography calibration curve for dose calculation, and (iv) the wrong (or not performed) choice of the number of fractions in the planning station. On the basis of these findings, in addition to the safety strategies already adopted in the clinical practice, novel solutions have been proposed for mitigating the risk of these failures and to increase patient safety.

DETECTING LOW-LEVEL SYNTHESIS IMPURITIES IN MODIFIED PHOSPHOROTHIOATE OLIGONUCLEOTIDES USING LIQUID CHROMATOGRAPHY – HIGH RESOLUTION MASS SPECTROMETRY

PubMed Central

Nikcevic, Irena; Wyrzykiewicz, Tadeusz K.; Limbach, Patrick A.

2010-01-01

Summary An LC-MS method based on the use of high resolution Fourier transform ion cyclotron resonance mass spectrometry (FTIRCMS) for profiling oligonucleotides synthesis impurities is described. Oligonucleotide phosphorothioatediesters (phosphorothioate oligonucleotides), in which one of the non-bridging oxygen atoms at each phosphorus center is replaced by a sulfur atom, are now one of the most popular oligonucleotide modifications due to their ease of chemical synthesis and advantageous pharmacokinetic properties. Despite significant progress in the solid-phase oligomerization chemistry used in the manufacturing of these oligonucleotides, multiple classes of low-level impurities always accompany synthetic oligonucleotides. Liquid chromatography-mass spectrometry has emerged as a powerful technique for the identification of these synthesis impurities. However, impurity profiling, where the entire complement of low-level synthetic impurities is identified in a single analysis, is more challenging. Here we present an LC-MS method based the use of high resolution-mass spectrometry, specifically Fourier transform ion cyclotron resonance mass spectrometry (FTIRCMS or FTMS). The optimal LC-FTMS conditions, including the stationary phase and mobile phases for the separation and identification of phosphorothioate oligonucleotides, were found. The characteristics of FTMS enable charge state determination from single m/z values of low-level impurities. Charge state information then enables more accurate modeling of the detected isotopic distribution for identification of the chemical composition of the detected impurity. Using this approach, a number of phosphorothioate impurities can be detected by LC-FTMS including failure sequences carrying 3′-terminal phosphate monoester and 3′-terminal phosphorothioate monoester, incomplete backbone sulfurization and desulfurization products, high molecular weight impurities, and chloral, isobutyryl, and N3 (2-cyanoethyl) adducts of the full length product. When compared with low resolution LC-MS, ~60% more impurities can be identified when charge state and isotopic distribution information is available and used for impurity profiling. PMID:21811394

Multidrug-resistant tuberculosis treatment failure detection depends on monitoring interval and microbiological method

PubMed Central

White, Richard A.; Lu, Chunling; Rodriguez, Carly A.; Bayona, Jaime; Becerra, Mercedes C.; Burgos, Marcos; Centis, Rosella; Cohen, Theodore; Cox, Helen; D'Ambrosio, Lia; Danilovitz, Manfred; Falzon, Dennis; Gelmanova, Irina Y.; Gler, Maria T.; Grinsdale, Jennifer A.; Holtz, Timothy H.; Keshavjee, Salmaan; Leimane, Vaira; Menzies, Dick; Milstein, Meredith B.; Mishustin, Sergey P.; Pagano, Marcello; Quelapio, Maria I.; Shean, Karen; Shin, Sonya S.; Tolman, Arielle W.; van der Walt, Martha L.; Van Deun, Armand; Viiklepp, Piret

2016-01-01

Debate persists about monitoring method (culture or smear) and interval (monthly or less frequently) during treatment for multidrug-resistant tuberculosis (MDR-TB). We analysed existing data and estimated the effect of monitoring strategies on timing of failure detection. We identified studies reporting microbiological response to MDR-TB treatment and solicited individual patient data from authors. Frailty survival models were used to estimate pooled relative risk of failure detection in the last 12 months of treatment; hazard of failure using monthly culture was the reference. Data were obtained for 5410 patients across 12 observational studies. During the last 12 months of treatment, failure detection occurred in a median of 3 months by monthly culture; failure detection was delayed by 2, 7, and 9 months relying on bimonthly culture, monthly smear and bimonthly smear, respectively. Risk (95% CI) of failure detection delay resulting from monthly smear relative to culture is 0.38 (0.34–0.42) for all patients and 0.33 (0.25–0.42) for HIV-co-infected patients. Failure detection is delayed by reducing the sensitivity and frequency of the monitoring method. Monthly monitoring of sputum cultures from patients receiving MDR-TB treatment is recommended. Expanded laboratory capacity is needed for high-quality culture, and for smear microscopy and rapid molecular tests. PMID:27587552

Road Anomalies Detection System Evaluation.

PubMed

Silva, Nuno; Shah, Vaibhav; Soares, João; Rodrigues, Helena

2018-06-21

Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.

Development and Evaluation of Fault-Tolerant Flight Control Systems

NASA Technical Reports Server (NTRS)

Song, Yong D.; Gupta, Kajal (Technical Monitor)

2004-01-01

The research is concerned with developing a new approach to enhancing fault tolerance of flight control systems. The original motivation for fault-tolerant control comes from the need for safe operation of control elements (e.g. actuators) in the event of hardware failures in high reliability systems. One such example is modem space vehicle subjected to actuator/sensor impairments. A major task in flight control is to revise the control policy to balance impairment detectability and to achieve sufficient robustness. This involves careful selection of types and parameters of the controllers and the impairment detecting filters used. It also involves a decision, upon the identification of some failures, on whether and how a control reconfiguration should take place in order to maintain a certain system performance level. In this project new flight dynamic model under uncertain flight conditions is considered, in which the effects of both ramp and jump faults are reflected. Stabilization algorithms based on neural network and adaptive method are derived. The control algorithms are shown to be effective in dealing with uncertain dynamics due to external disturbances and unpredictable faults. The overall strategy is easy to set up and the computation involved is much less as compared with other strategies. Computer simulation software is developed. A serious of simulation studies have been conducted with varying flight conditions.

A tri-fold hybrid classification approach for diagnostics with unexampled faulty states

NASA Astrophysics Data System (ADS)

Tamilselvan, Prasanna; Wang, Pingfeng

2015-01-01

System health diagnostics provides diversified benefits such as improved safety, improved reliability and reduced costs for the operation and maintenance of engineered systems. Successful health diagnostics requires the knowledge of system failures. However, with an increasing system complexity, it is extraordinarily difficult to have a well-tested system so that all potential faulty states can be realized and studied at product testing stage. Thus, real time health diagnostics requires automatic detection of unexampled system faulty states based upon sensory data to avoid sudden catastrophic system failures. This paper presents a trifold hybrid classification (THC) approach for structural health diagnosis with unexampled health states (UHS), which comprises of preliminary UHS identification using a new thresholded Mahalanobis distance (TMD) classifier, UHS diagnostics using a two-class support vector machine (SVM) classifier, and exampled health states diagnostics using a multi-class SVM classifier. The proposed THC approach, which takes the advantages of both TMD and SVM-based classification techniques, is able to identify and isolate the unexampled faulty states through interactively detecting the deviation of sensory data from the exampled health states and forming new ones autonomously. The proposed THC approach is further extended to a generic framework for health diagnostics problems with unexampled faulty states and demonstrated with health diagnostics case studies for power transformers and rolling bearings.

SCADA alarms processing for wind turbine component failure detection

NASA Astrophysics Data System (ADS)

Gonzalez, E.; Reder, M.; Melero, J. J.

2016-09-01

Wind turbine failure and downtime can often compromise the profitability of a wind farm due to their high impact on the operation and maintenance (O&M) costs. Early detection of failures can facilitate the changeover from corrective maintenance towards a predictive approach. This paper presents a cost-effective methodology to combine various alarm analysis techniques, using data from the Supervisory Control and Data Acquisition (SCADA) system, in order to detect component failures. The approach categorises the alarms according to a reviewed taxonomy, turning overwhelming data into valuable information to assess component status. Then, different alarms analysis techniques are applied for two purposes: the evaluation of the SCADA alarm system capability to detect failures, and the investigation of the relation between components faults being followed by failure occurrences in others. Various case studies are presented and discussed. The study highlights the relationship between faulty behaviour in different components and between failures and adverse environmental conditions.

Development and testing of an algorithm to detect implantable cardioverter-defibrillator lead failure.

PubMed

Gunderson, Bruce D; Gillberg, Jeffrey M; Wood, Mark A; Vijayaraman, Pugazhendhi; Shepard, Richard K; Ellenbogen, Kenneth A

2006-02-01

Implantable cardioverter-defibrillator (ICD) lead failures often present as inappropriate shock therapy. An algorithm that can reliably discriminate between ventricular tachyarrhythmias and noise due to lead failure may prevent patient discomfort and anxiety and avoid device-induced proarrhythmia by preventing inappropriate ICD shocks. The goal of this analysis was to test an ICD tachycardia detection algorithm that differentiates noise due to lead failure from ventricular tachyarrhythmias. We tested an algorithm that uses a measure of the ventricular intracardiac electrogram baseline to discriminate the sinus rhythm isoelectric line from the right ventricular coil-can (i.e., far-field) electrogram during oversensing of noise caused by a lead failure. The baseline measure was defined as the product of the sum (mV) and standard deviation (mV) of the voltage samples for a 188-ms window centered on each sensed electrogram. If the minimum baseline measure of the last 12 beats was <0.35 mV-mV, then the detected rhythm was considered noise due to a lead failure. The first ICD-detected episode of lead failure and inappropriate detection from 24 ICD patients with a pace/sense lead failure and all ventricular arrhythmias from 56 ICD patients without a lead failure were selected. The stored data were analyzed to determine the sensitivity and specificity of the algorithm to detect lead failures. The minimum baseline measure for the 24 lead failure episodes (0.28 +/- 0.34 mV-mV) was smaller than the 135 ventricular tachycardia (40.8 +/- 43.0 mV-mV, P <.0001) and 55 ventricular fibrillation episodes (19.1 +/- 22.8 mV-mV, P <.05). A minimum baseline <0.35 mV-mV threshold had a sensitivity of 83% (20/24) with a 100% (190/190) specificity. A baseline measure of the far-field electrogram had a high sensitivity and specificity to detect lead failure noise compared with ventricular tachycardia or fibrillation.

Artificial-neural-network-based failure detection and isolation

NASA Astrophysics Data System (ADS)

Sadok, Mokhtar; Gharsalli, Imed; Alouani, Ali T.

1998-03-01

This paper presents the design of a systematic failure detection and isolation system that uses the concept of failure sensitive variables (FSV) and artificial neural networks (ANN). The proposed approach was applied to tube leak detection in a utility boiler system. Results of the experimental testing are presented in the paper.

Automatic patient respiration failure detection system with wireless transmission

NASA Technical Reports Server (NTRS)

Dimeff, J.; Pope, J. M.

1968-01-01

Automatic respiration failure detection system detects respiration failure in patients with a surgically implanted tracheostomy tube, and actuates an audible and/or visual alarm. The system incorporates a miniature radio transmitter so that the patient is unencumbered by wires yet can be monitored from a remote location.

Design and evaluation of a failure detection and isolation algorithm for restructurable control systems

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1986-01-01

The use of a decentralized approach to failure detection and isolation for use in restructurable control systems is examined. This work has produced: (1) A method for evaluating fundamental limits to FDI performance; (2) Application using flight recorded data; (3) A working control element FDI system with maximal sensitivity to critical control element failures; (4) Extensive testing on realistic simulations; and (5) A detailed design methodology involving parameter optimization (with respect to model uncertainties) and sensitivity analyses. This project has concentrated on detection and isolation of generic control element failures since these failures frequently lead to emergency conditions and since knowledge of remaining control authority is essential for control system redesign. The failures are generic in the sense that no temporal failure signature information was assumed. Thus, various forms of functional failures are treated in a unified fashion. Such a treatment results in a robust FDI system (i.e., one that covers all failure modes) but sacrifices some performance when detailed failure signature information is known, useful, and employed properly. It was assumed throughout that all sensors are validated (i.e., contain only in-spec errors) and that only the first failure of a single control element needs to be detected and isolated. The FDI system which has been developed will handle a class of multiple failures.

Studies in knowledge-based diagnosis of failures in robotic assembly

NASA Technical Reports Server (NTRS)

Lam, Raymond K.; Pollard, Nancy S.; Desai, Rajiv S.

1990-01-01

The telerobot diagnostic system (TDS) is a knowledge-based system that is being developed for identification and diagnosis of failures in the space robotic domain. The system is able to isolate the symptoms of the failure, generate failure hypotheses based on these symptoms, and test their validity at various levels by interpreting or simulating the effects of the hypotheses on results of plan execution. The implementation of the TDS is outlined. The classification of failures and the types of system models used by the TDS are discussed. A detailed example of the TDS approach to failure diagnosis is provided.

Fault detection and fault tolerance in robotics

NASA Technical Reports Server (NTRS)

Visinsky, Monica; Walker, Ian D.; Cavallaro, Joseph R.

1992-01-01

Robots are used in inaccessible or hazardous environments in order to alleviate some of the time, cost and risk involved in preparing men to endure these conditions. In order to perform their expected tasks, the robots are often quite complex, thus increasing their potential for failures. If men must be sent into these environments to repair each component failure in the robot, the advantages of using the robot are quickly lost. Fault tolerant robots are needed which can effectively cope with failures and continue their tasks until repairs can be realistically scheduled. Before fault tolerant capabilities can be created, methods of detecting and pinpointing failures must be perfected. This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot. The resulting failure flow chart can also be used to analyze the resiliency of the robot in the presence of specific faults. By simulating robot failures and fault detection schemes, the problems involved in detecting failures for robots are explored in more depth.

A Multiplex PCR/LDR Assay for the Simultaneous Identification of Category A Infectious Pathogens: Agents of Viral Hemorrhagic Fever and Variola Virus

PubMed Central

Das, Sanchita; Rundell, Mark S.; Mirza, Aashiq H.; Pingle, Maneesh R.; Shigyo, Kristi; Garrison, Aura R.; Paragas, Jason; Smith, Scott K.; Olson, Victoria A.; Larone, Davise H.; Spitzer, Eric D.; Barany, Francis; Golightly, Linnie M.

2015-01-01

CDC designated category A infectious agents pose a major risk to national security and require special action for public health preparedness. They include viruses that cause viral hemorrhagic fever (VHF) syndrome as well as variola virus, the agent of smallpox. VHF is characterized by hemorrhage and fever with multi-organ failure leading to high morbidity and mortality. Smallpox, a prior scourge, has been eradicated for decades, making it a particularly serious threat if released nefariously in the essentially non-immune world population. Early detection of the causative agents, and the ability to distinguish them from other pathogens, is essential to contain outbreaks, implement proper control measures, and prevent morbidity and mortality. We have developed a multiplex detection assay that uses several species-specific PCR primers to generate amplicons from multiple pathogens; these are then targeted in a ligase detection reaction (LDR). The resultant fluorescently-labeled ligation products are detected on a universal array enabling simultaneous identification of the pathogens. The assay was evaluated on 32 different isolates associated with VHF (ebolavirus, marburgvirus, Crimean Congo hemorrhagic fever virus, Lassa fever virus, Rift Valley fever virus, Dengue virus, and Yellow fever virus) as well as variola virus and vaccinia virus (the agent of smallpox and its vaccine strain, respectively). The assay was able to detect all viruses tested, including 8 sequences representative of different variola virus strains from the CDC repository. It does not cross react with other emerging zoonoses such as monkeypox virus or cowpox virus, or six flaviviruses tested (St. Louis encephalitis virus, Murray Valley encephalitis virus, Powassan virus, Tick-borne encephalitis virus, West Nile virus and Japanese encephalitis virus). PMID:26381398

A Multiplex PCR/LDR Assay for the Simultaneous Identification of Category A Infectious Pathogens: Agents of Viral Hemorrhagic Fever and Variola Virus.

PubMed

Das, Sanchita; Rundell, Mark S; Mirza, Aashiq H; Pingle, Maneesh R; Shigyo, Kristi; Garrison, Aura R; Paragas, Jason; Smith, Scott K; Olson, Victoria A; Larone, Davise H; Spitzer, Eric D; Barany, Francis; Golightly, Linnie M

2015-01-01

CDC designated category A infectious agents pose a major risk to national security and require special action for public health preparedness. They include viruses that cause viral hemorrhagic fever (VHF) syndrome as well as variola virus, the agent of smallpox. VHF is characterized by hemorrhage and fever with multi-organ failure leading to high morbidity and mortality. Smallpox, a prior scourge, has been eradicated for decades, making it a particularly serious threat if released nefariously in the essentially non-immune world population. Early detection of the causative agents, and the ability to distinguish them from other pathogens, is essential to contain outbreaks, implement proper control measures, and prevent morbidity and mortality. We have developed a multiplex detection assay that uses several species-specific PCR primers to generate amplicons from multiple pathogens; these are then targeted in a ligase detection reaction (LDR). The resultant fluorescently-labeled ligation products are detected on a universal array enabling simultaneous identification of the pathogens. The assay was evaluated on 32 different isolates associated with VHF (ebolavirus, marburgvirus, Crimean Congo hemorrhagic fever virus, Lassa fever virus, Rift Valley fever virus, Dengue virus, and Yellow fever virus) as well as variola virus and vaccinia virus (the agent of smallpox and its vaccine strain, respectively). The assay was able to detect all viruses tested, including 8 sequences representative of different variola virus strains from the CDC repository. It does not cross react with other emerging zoonoses such as monkeypox virus or cowpox virus, or six flaviviruses tested (St. Louis encephalitis virus, Murray Valley encephalitis virus, Powassan virus, Tick-borne encephalitis virus, West Nile virus and Japanese encephalitis virus).

Rocket Engine Health Management: Early Definition of Critical Flight Measurements

NASA Technical Reports Server (NTRS)

Christenson, Rick L.; Nelson, Michael A.; Butas, John P.

2003-01-01

The NASA led Space Launch Initiative (SLI) program has established key requirements related to safety, reliability, launch availability and operations cost to be met by the next generation of reusable launch vehicles. Key to meeting these requirements will be an integrated vehicle health management ( M) system that includes sensors, harnesses, software, memory, and processors. Such a system must be integrated across all the vehicle subsystems and meet component, subsystem, and system requirements relative to fault detection, fault isolation, and false alarm rate. The purpose of this activity is to evolve techniques for defining critical flight engine system measurements-early within the definition of an engine health management system (EHMS). Two approaches, performance-based and failure mode-based, are integrated to provide a proposed set of measurements to be collected. This integrated approach is applied to MSFC s MC-1 engine. Early identification of measurements supports early identification of candidate sensor systems whose design and impacts to the engine components must be considered in engine design.

Failure Mode and Effect Analysis (FMEA) may enhance implementation of clinical practice guidelines: An experience from the Middle East.

PubMed

Babiker, Amir; Amer, Yasser S; Osman, Mohamed E; Al-Eyadhy, Ayman; Fatani, Solafa; Mohamed, Sarar; Alnemri, Abdulrahman; Titi, Maher A; Shaikh, Farheen; Alswat, Khalid A; Wahabi, Hayfaa A; Al-Ansary, Lubna A

2018-02-01

Implementation of clinical practice guidelines (CPGs) has been shown to reduce variation in practice and improve health care quality and patients' safety. There is a limited experience of CPG implementation (CPGI) in the Middle East. The CPG program in our institution was launched in 2009. The Quality Management department conducted a Failure Mode and Effect Analysis (FMEA) for further improvement of CPGI. This is a prospective study of a qualitative/quantitative design. Our FMEA included (1) process review and recording of the steps and activities of CPGI; (2) hazard analysis by recording activity-related failure modes and their effects, identification of actions required, assigned severity, occurrence, and detection scores for each failure mode and calculated the risk priority number (RPN) by using an online interactive FMEA tool; (3) planning: RPNs were prioritized, recommendations, and further planning for new interventions were identified; and (4) monitoring: after reduction or elimination of the failure mode. The calculated RPN will be compared with subsequent analysis in post-implementation phase. The data were scrutinized from a feedback of quality team members using a FMEA framework to enhance the implementation of 29 adapted CPGs. The identified potential common failure modes with the highest RPN (≥ 80) included awareness/training activities, accessibility of CPGs, fewer advocates from clinical champions, and CPGs auditing. Actions included (1) organizing regular awareness activities, (2) making CPGs printed and electronic copies accessible, (3) encouraging senior practitioners to get involved in CPGI, and (4) enhancing CPGs auditing as part of the quality sustainability plan. In our experience, FMEA could be a useful tool to enhance CPGI. It helped us to identify potential barriers and prepare relevant solutions. © 2017 John Wiley & Sons, Ltd.

Practices to improve identification of Adult Antiretroviral Therapy failure at the Lighthouse Trust clinic in Lilongwe, Malawi

PubMed Central

Vorkas, Charles Kyriakos; Tweya, Hannock; Mzinganjira, Dalitso; Dickie, George; Weigel, Ralf; Phiri, Sam; Hosseinipour, Mina C.

2011-01-01

Summary Background Evaluating treatment failure is critical when deciding to modify antiretroviral therapy (ART). Virologic Assessment Forms (VAFs) were implemented in July 2008 as a prerequisite for ordering viral load. The form requires assessment of clinical and immunologic status. Methods Using the Electronic Medical Record (EMR), we retrospectively evaluated patients who met 2006 WHO guidelines for immunologic failure (≥15 years old; on ART ≥6 months; CD4 count 50% drop from peak OR CD4 persistently <100 cells) at the Lighthouse Trust clinic from 12/2007–12/2009. We compared virologic screening, VAF implementation and ART modification during the same period using Fisher’s exact tests and unpaired t-tests as appropriate. Results Of 7,000 enrolled ART patients ≥ 15 years old with at least two CD4 counts, 10% had immunologic failure with a median follow-up time on ART of 1.4 years (IQR: 0.8–2.3). Forty (6%) viral loads were ordered: 14 (35%) were detectable (>400 HIV RNA copies/mL) and 1 (7%) patient was switched to second-line therapy. Overall, 259 VAFs were completed: 67% for immunologic failure and 33% for WHO Stage 4 condition. Before VAF implementation, 1% of patients had viral loads drawn during routine care, whereas afterwards, 8% did (p<0.0001; 95% CI 0.03–0.08). Conclusions Clinicians did not identify a large proportion of immunologic failure patients for screening. Implementation of VAFs produced little improvement in virologic screening during routine care. Better training and monitoring systems are needed. PMID:22039960

Crack identification and evolution law in the vibration failure process of loaded coal

NASA Astrophysics Data System (ADS)

Li, Chengwu; Ai, Dihao; Sun, Xiaoyuan; Xie, Beijing

2017-08-01

To study the characteristics of coal cracks produced in the vibration failure process, we set up a static load and static and dynamic combination load failure test simulation system, prepared with different particle size, formation pressure, and firmness coefficient coal samples. Through static load damage testing of coal samples and then dynamic load (vibration exciter) and static (jack) combination destructive testing, the crack images of coal samples under the load condition were obtained. Combined with digital image processing technology, an algorithm of crack identification with high precision and in real-time is proposed. With the crack features of the coal samples under different load conditions as the research object, we analyzed the distribution of cracks on the surface of the coal samples and the factors influencing crack evolution using the proposed algorithm and a high-resolution industrial camera. Experimental results showed that the major portion of the crack after excitation is located in the rear of the coal sample where the vibration exciter cannot act. Under the same disturbance conditions, crack size and particle size exhibit a positive correlation, while crack size and formation pressure exhibit a negative correlation. Soft coal is more likely to lead to crack evolution than hard coal, and more easily causes instability failure. The experimental results and crack identification algorithm provide a solid basis for the prevention and control of instability and failure of coal and rock mass, and they are helpful in improving the monitoring method of coal and rock dynamic disasters.

Rapid and specific detection of porcine parvovirus by isothermal recombinase polymerase amplification assays.

PubMed

Yang, Yang; Qin, Xiaodong; Zhang, Wei; Li, Yanmin; Zhang, Zhidong

2016-10-01

Porcine parvovirus (PPV) is a major cause of swine reproductive failure and reported in many countries worldwide. Recombinase polymerase amplification (RPA) assays using a real-time fluorescent detection (PPV real-time RPA assay) and a lateral flow dipstick (PPV RPA LFD assay) were developed targeting PPV NS1 gene. The detection limit of PPV real-time RPA assay was 300 copies per reaction within 9 min at 38 °C, while the RPA LFD assay has a detection limit of 400 copies per reaction in less than 20 min at 38 °C. In both assays, there were no cross-reactions with porcine circovirus type 2, pseudorabies virus, porcine reproductive and respiratory syndrome virus, classical swine fever virus, and foot-and-mouth disease virus. Based on a total of 128 clinical samples examined, the sensitivity and the specificity of the developed RPA assays for identification of PPV was 94.4% and 100%, respectively, when compared to real-time (qPCR) assay. Therefore, the RPA assay provides a rapid, sensitive and specific alternative for PPV detection. Copyright © 2016 Elsevier Ltd. All rights reserved.

Achieving fast and stable failure detection in WDM Networks

NASA Astrophysics Data System (ADS)

Gao, Donghui; Zhou, Zhiyu; Zhang, Hanyi

2005-02-01

In dynamic networks, the failure detection time takes a major part of the convergence time, which is an important network performance index. To detect a node or link failure in the network, traditional protocols, like Hello protocol in OSPF or RSVP, exchanges keep-alive messages between neighboring nodes to keep track of the link/node state. But by default settings, it can get a minimum detection time in the measure of dozens of seconds, which can not meet the demands of fast network convergence and failure recovery. When configuring the related parameters to reduce the detection time, there will be notable instability problems. In this paper, we analyzed the problem and designed a new failure detection algorithm to reduce the network overhead of detection signaling. Through our experiment we found it is effective to enhance the stability by implicitly acknowledge other signaling messages as keep-alive messages. We conducted our proposal and the previous approaches on the ASON test-bed. The experimental results show that our algorithm gives better performances than previous schemes in about an order magnitude reduction of both false failure alarms and queuing delay to other messages, especially under light traffic load.

Identification and Evaluation of Deepwater Port Hose Inspection Methods

DOT National Transportation Integrated Search

1979-01-01

The work contained in this report consists of a review of deepwater port hose failures to date, and the causes leading to these failures, as well as an evaluation of current hose inspection techniques and procedures, and an examination of available n...

Sensor Failure Detection of FASSIP System using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Sudarno; Juarsa, Mulya; Santosa, Kussigit; Deswandri; Sunaryo, Geni Rina

2018-02-01

In the nuclear reactor accident of Fukushima Daiichi in Japan, the damages of core and pressure vessel were caused by the failure of its active cooling system (diesel generator was inundated by tsunami). Thus researches on passive cooling system for Nuclear Power Plant are performed to improve the safety aspects of nuclear reactors. The FASSIP system (Passive System Simulation Facility) is an installation used to study the characteristics of passive cooling systems at nuclear power plants. The accuracy of sensor measurement of FASSIP system is essential, because as the basis for determining the characteristics of a passive cooling system. In this research, a sensor failure detection method for FASSIP system is developed, so the indication of sensor failures can be detected early. The method used is Principal Component Analysis (PCA) to reduce the dimension of the sensor, with the Squarred Prediction Error (SPE) and statistic Hotteling criteria for detecting sensor failure indication. The results shows that PCA method is capable to detect the occurrence of a failure at any sensor.

Early Diagnosis and Prediction of Anticancer Drug-induced Cardiotoxicity: From Cardiac Imaging to "Omics" Technologies.

PubMed

Madonna, Rosalinda

2017-07-01

Heart failure due to antineoplastic therapy remains a major cause of morbidity and mortality in oncological patients. These patients often have no prior manifestation of disease. There is therefore a need for accurate identification of individuals at risk of such events before the appearance of clinical manifestations. The present article aims to provide an overview of cardiac imaging as well as new "-omics" technologies, especially with regard to genomics and proteomics as promising tools for the early detection and prediction of cardiotoxicity and individual responses to antineoplastic drugs. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Performance and sensitivity analysis of the generalized likelihood ratio method for failure detection. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bueno, R. A.

1977-01-01

Results of the generalized likelihood ratio (GLR) technique for the detection of failures in aircraft application are presented, and its relationship to the properties of the Kalman-Bucy filter is examined. Under the assumption that the system is perfectly modeled, the detectability and distinguishability of four failure types are investigated by means of analysis and simulations. Detection of failures is found satisfactory, but problems in identifying correctly the mode of a failure may arise. These issues are closely examined as well as the sensitivity of GLR to modeling errors. The advantages and disadvantages of this technique are discussed, and various modifications are suggested to reduce its limitations in performance and computational complexity.

Application of failure mode and effects analysis (FMEA) to pretreatment phases in tomotherapy

PubMed Central

Broggi, Sara; Cantone, Marie Claire; Chiara, Anna; Muzio, Nadia Di; Longobardi, Barbara; Mangili, Paola

2013-01-01

The aim of this paper was the application of the failure mode and effects analysis (FMEA) approach to assess the risks for patients undergoing radiotherapy treatments performed by means of a helical tomotherapy unit. FMEA was applied to the preplanning imaging, volume determination, and treatment planning stages of the tomotherapy process and consisted of three steps: 1) identification of the involved subprocesses; 2) identification and ranking of the potential failure modes, together with their causes and effects, using the risk probability number (RPN) scoring system; and 3) identification of additional safety measures to be proposed for process quality and safety improvement. RPN upper threshold for little concern of risk was set at 125. A total of 74 failure modes were identified: 38 in the stage of preplanning imaging and volume determination, and 36 in the stage of planning. The threshold of 125 for RPN was exceeded in four cases: one case only in the phase of preplanning imaging and volume determination, and three cases in the stage of planning. The most critical failures appeared related to (i) the wrong or missing definition and contouring of the overlapping regions, (ii) the wrong assignment of the overlap priority to each anatomical structure, (iii) the wrong choice of the computed tomography calibration curve for dose calculation, and (iv) the wrong (or not performed) choice of the number of fractions in the planning station. On the basis of these findings, in addition to the safety strategies already adopted in the clinical practice, novel solutions have been proposed for mitigating the risk of these failures and to increase patient safety. PACS number: 87.55.Qr PMID:24036868

Failure detection in high-performance clusters and computers using chaotic map computations

DOEpatents

Rao, Nageswara S.

2015-09-01

A programmable media includes a processing unit capable of independent operation in a machine that is capable of executing 10.sup.18 floating point operations per second. The processing unit is in communication with a memory element and an interconnect that couples computing nodes. The programmable media includes a logical unit configured to execute arithmetic functions, comparative functions, and/or logical functions. The processing unit is configured to detect computing component failures, memory element failures and/or interconnect failures by executing programming threads that generate one or more chaotic map trajectories. The central processing unit or graphical processing unit is configured to detect a computing component failure, memory element failure and/or an interconnect failure through an automated comparison of signal trajectories generated by the chaotic maps.

Control system failure monitoring using generalized parity relations. M.S. Thesis Interim Technical Report

NASA Technical Reports Server (NTRS)

Vanschalkwyk, Christiaan Mauritz

1991-01-01

Many applications require that a control system must be tolerant to the failure of its components. This is especially true for large space-based systems that must work unattended and with long periods between maintenance. Fault tolerance can be obtained by detecting the failure of the control system component, determining which component has failed, and reconfiguring the system so that the failed component is isolated from the controller. Component failure detection experiments that were conducted on an experimental space structure, the NASA Langley Mini-Mast are presented. Two methodologies for failure detection and isolation (FDI) exist that do not require the specification of failure modes and are applicable to both actuators and sensors. These methods are known as the Failure Detection Filter and the method of Generalized Parity Relations. The latter method was applied to three different sensor types on the Mini-Mast. Failures were simulated in input-output data that were recorded during operation of the Mini-Mast. Both single and double sensor parity relations were tested and the effect of several design parameters on the performance of these relations is discussed. The detection of actuator failures is also treated. It is shown that in all the cases it is possible to identify the parity relations directly from input-output data. Frequency domain analysis is used to explain the behavior of the parity relations.

Optimally robust redundancy relations for failure detection in uncertain systems

NASA Technical Reports Server (NTRS)

Lou, X.-C.; Willsky, A. S.; Verghese, G. C.

1986-01-01

All failure detection methods are based, either explicitly or implicitly, on the use of redundancy, i.e. on (possibly dynamic) relations among the measured variables. The robustness of the failure detection process consequently depends to a great degree on the reliability of the redundancy relations, which in turn is affected by the inevitable presence of model uncertainties. In this paper the problem of determining redundancy relations that are optimally robust is addressed in a sense that includes several major issues of importance in practical failure detection and that provides a significant amount of intuition concerning the geometry of robust failure detection. A procedure is given involving the construction of a single matrix and its singular value decomposition for the determination of a complete sequence of redundancy relations, ordered in terms of their level of robustness. This procedure also provides the basis for comparing levels of robustness in redundancy provided by different sets of sensors.

Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

NASA Technical Reports Server (NTRS)

Wong, Derek; Poll, Scott; KrishnaKumar, Kalmanje

2005-01-01

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

Microbial Profiling of Combat Wound Infection through Detection Microarray and Next-Generation Sequencing

PubMed Central

Allen, Jonathan E.; Brown, Trevor S.; Gardner, Shea N.; McLoughlin, Kevin S.; Forsberg, Jonathan A.; Kirkup, Benjamin C.; Chromy, Brett A.; Luciw, Paul A.; Elster, Eric A.

2014-01-01

Combat wound healing and resolution are highly affected by the resident microbial flora. We therefore sought to achieve comprehensive detection of microbial populations in wounds using novel genomic technologies and bioinformatics analyses. We employed a microarray capable of detecting all sequenced pathogens for interrogation of 124 wound samples from extremity injuries in combat-injured U.S. service members. A subset of samples was also processed via next-generation sequencing and metagenomic analysis. Array analysis detected microbial targets in 51% of all wound samples, with Acinetobacter baumannii being the most frequently detected species. Multiple Pseudomonas species were also detected in tissue biopsy specimens. Detection of the Acinetobacter plasmid pRAY correlated significantly with wound failure, while detection of enteric-associated bacteria was associated significantly with successful healing. Whole-genome sequencing revealed broad microbial biodiversity between samples. The total wound bioburden did not associate significantly with wound outcome, although temporal shifts were observed over the course of treatment. Given that standard microbiological methods do not detect the full range of microbes in each wound, these data emphasize the importance of supplementation with molecular techniques for thorough characterization of wound-associated microbes. Future application of genomic protocols for assessing microbial content could allow application of specialized care through early and rapid identification and management of critical patterns in wound bioburden. PMID:24829242

Sensor failure and multivariable control for airbreathing propulsion systems. Ph.D. Thesis - Dec. 1979 Final Report

NASA Technical Reports Server (NTRS)

Behbehani, K.

1980-01-01

A new sensor/actuator failure analysis technique for turbofan jet engines was developed. Three phases of failure analysis, namely detection, isolation, and accommodation are considered. Failure detection and isolation techniques are developed by utilizing the concept of Generalized Likelihood Ratio (GLR) tests. These techniques are applicable to both time varying and time invariant systems. Three GLR detectors are developed for: (1) hard-over sensor failure; (2) hard-over actuator failure; and (3) brief disturbances in the actuators. The probability distribution of the GLR detectors and the detectability of sensor/actuator failures are established. Failure type is determined by the maximum of the GLR detectors. Failure accommodation is accomplished by extending the Multivariable Nyquest Array (MNA) control design techniques to nonsquare system designs. The performance and effectiveness of the failure analysis technique are studied by applying the technique to a turbofan jet engine, namely the Quiet Clean Short Haul Experimental Engine (QCSEE). Single and multiple sensor/actuator failures in the QCSEE are simulated and analyzed and the effects of model degradation are studied.

Retrospective Identification of Herpes Simplex 2 Virus-Associated Acute Liver Failure in an Immunocompetent Patient Detected Using Whole Transcriptome Shotgun Sequencing.

PubMed

Ono, Atsushi; Hayes, C Nelson; Akamatsu, Sakura; Imamura, Michio; Aikata, Hiroshi; Chayama, Kazuaki

2017-01-01

Acute liver failure (ALF) is a severe condition in which liver function rapidly deteriorates in individuals without prior history of liver disease. While most cases result from acetaminophen overdose or viral hepatitis, in up to a third of patients, no clear cause can be identified. Liver transplantation has greatly reduced mortality among these patients, but 40% of patients recover without liver transplantation. Therefore, there is an urgent need for rapid determination of the etiology of acute liver failure. In this case report, we present a case of herpes simplex 2 virus- (HSV-) associated ALF in an immunocompetent patient. The patient recovered without LT, but the presence of HSV was not suspected at the time, precluding more effective treatment with acyclovir. To determine the etiology, stored blood samples were analyzed using whole transcriptome shotgun sequencing followed by mapping to a panel of viral reference sequences. The presence of HSV-DNA in blood samples at the time of admission was confirmed using real-time polymerase chain reaction, and, at the time of discharge, HSV-DNA levels had decreased by a factor of 10 6 . Conclusions. In ALF cases of undetermined etiology, uncommon causes should be considered, especially those for which an effective treatment is available.

A hybrid approach for nondestructive assessment and design optimisation and testing of in-service machinery

NASA Astrophysics Data System (ADS)

Rahman, Abdul Ghaffar Abdul; Noroozi, Siamak; Dupac, Mihai; Mahathir Syed Mohd Al-Attas, Syed; Vinney, John E.

2013-03-01

Complex rotating machinery requires regular condition monitoring inspections to assess their running conditions and their structural integrity to prevent catastrophic failures. Machine failures can be divided into two categories. First is the wear and tear during operation, they range from bearing defects, gear damage, misalignment, imbalance or mechanical looseness, for which simple condition-based maintenance techniques can easily detect the root cause and trigger remedial action process. The second factor in machine failure is caused by the inherent design faults that usually happened due to many reasons such as improper installation, poor servicing, bad workmanship and structural dynamics design deficiency. In fact, individual machines components are generally dynamically well designed and rigorously tested. However, when these machines are assembled on sight and linked together, their dynamic characteristics will change causing unexpected behaviour of the system. Since nondestructive evaluation provides an excellent alternative to the classical monitoring and proved attractive due to the possibility of performing reliable assessments of all types of machinery, the novel dynamic design verification procedure - based on the combination of in-service operation deflection shape measurement, experimental modal analysis and iterative inverse finite element analysis - proposed here allows quick identification of structural weakness, and helps to provide and verify the solutions.

Evaluation of a new commercial real-time PCR assay for diagnosis of Pneumocystis jirovecii pneumonia and identification of dihydropteroate synthase (DHPS) mutations.

PubMed

Montesinos, Isabel; Delforge, Marie-Luce; Ajjaham, Farida; Brancart, Françoise; Hites, Maya; Jacobs, Frederique; Denis, Olivier

2017-01-01

The PneumoGenius® real-time PCR assay is a new commercial multiplex real-time PCR method, which detects the Pneumocystis mitochondrial ribosomal large subunit (mtLSU) and two dihydropteroate synthase (DHPS) point mutations. To evaluate the clinical performance of this new real-time PCR assay we tested 120 extracted DNA samples from bronchoalveolar lavage specimens. These set of extracted DNA samples had already tested positive for Pneumocystis and patients had been classified in probable and unlikely PCP in a previous study. To evaluate de accuracy of the DHPS mutant's identification, an "in house" PCR and sequencing was performed. The sensitivity and specificity of PneumoGenius® PCR in discriminating between probable and unlikely Pneumocystis pneumonia (PCP) were 70% and 82% respectively. PneumoGenius® PCR was able to genotype more samples than "in house" DHPS PCR and sequencing. The same DHPS mutations were observed by both methods in four patients: two patients with a single mutation in position 171 (Pro57Ser) and two patients with a double mutation in position 165 (Thr55Ala) and in position 171 (Pro57Ser). A low rate of P. jirovecii (4.5%) harboring DHPS mutations was found, comparable to rates observed in other European countries. The PneumoGenius® real-time PCR is a suitable real-time PCR for PCP diagnosis and detection of DHPS mutants. The added value of DHPS mutation identification can assist in understanding the role of these mutations in prophylaxis failure or treatment outcome. Copyright © 2016 Elsevier Inc. All rights reserved.

TU-FG-201-11: Evaluating the Validity of Prospective Risk Analysis Methods: A Comparison of Traditional FMEA and Modified Healthcare FMEA

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

Lah, J; Manger, R; Kim, G

Purpose: To examine the ability of traditional Failure mode and effects analysis (FMEA) and a light version of Healthcare FMEA (HFMEA), called Scenario analysis of FMEA (SAFER) by comparing their outputs in terms of the risks identified and their severity rankings. Methods: We applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation are based on risk priority number (RPN). RPN is a product of three indices: occurrence, severity and detectability. The SAFER approach; utilized two indices-frequency and severity-which were defined by a multidisciplinarymore » team. A criticality matrix was divided into 4 categories; very low, low, high and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. Results: Two methods were independently compared to determine if the results and rated risks were matching or not. Our results showed an agreement of 67% between FMEA and SAFER approaches for the 15 riskiest SIG-specific failure modes. The main differences between the two approaches were the distribution of the values and the failure modes (No.52, 54, 154) that have high SAFER scores do not necessarily have high FMEA RPN scores. In our results, there were additional risks identified by both methods with little correspondence. In the SAFER, when the risk score is determined, the basis of the established decision tree or the failure mode should be more investigated. Conclusion: The FMEA method takes into account the probability that an error passes without being detected. SAFER is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allow the prioritization of risks and mitigation measures, and thus is perfectly applicable to clinical parts of radiotherapy.« less

Damage of composite structures: Detection technique, dynamic response and residual strength

NASA Astrophysics Data System (ADS)

Lestari, Wahyu

2001-10-01

Reliable and accurate health monitoring techniques can prevent catastrophic failures of structures. Conventional damage detection methods are based on visual or localized experimental methods and very often require prior information concerning the vicinity of the damage or defect. The structure must also be readily accessible for inspections. The techniques are also labor intensive. In comparison to these methods, health-monitoring techniques that are based on the structural dynamic response offers unique information on failure of structures. However, systematic relations between the experimental data and the defect are not available and frequently, the number of vibration modes needed for an accurate identification of defects is much higher than the number of modes that can be readily identified in the experiment. These motivated us to develop an experimental data based detection method with systematic relationships between the experimentally identified information and the analytical or mathematical model representing the defective structures. The developed technique use changes in vibrational curvature modes and natural frequencies. To avoid misinterpretation of the identified information, we also need to understand the effects of defects on the structural dynamic response prior to developing health-monitoring techniques. In this thesis work we focus on two type of defects in composite structures, namely delamination and edge notch like defect. Effects of nonlinearity due to the presence of defect and due to the axial stretching are studied for beams with delamination. Once defects are detected in a structure, next concern is determining the effects of the defects on the strength of the structure and its residual stiffness under dynamic loading. In this thesis, energy release rate due to dynamic loading in a delaminated structure is studied, which will be a foundation toward determining the residual strength of the structure.

Sensor failure detection system. [for the F100 turbofan engine

NASA Technical Reports Server (NTRS)

Beattie, E. C.; Laprad, R. F.; Mcglone, M. E.; Rock, S. M.; Akhter, M. M.

1981-01-01

Advanced concepts for detecting, isolating, and accommodating sensor failures were studied to determine their applicability to the gas turbine control problem. Five concepts were formulated based upon such techniques as Kalman filters and a screening process led to the selection of one advanced concept for further evaluation. The selected advanced concept uses a Kalman filter to generate residuals, a weighted sum square residuals technique to detect soft failures, likelihood ratio testing of a bank of Kalman filters for isolation, and reconfiguring of the normal mode Kalman filter by eliminating the failed input to accommodate the failure. The advanced concept was compared to a baseline parameter synthesis technique. The advanced concept was shown to be a viable concept for detecting, isolating, and accommodating sensor failures for the gas turbine applications.

An Adaptive Failure Detector Based on Quality of Service in Peer-to-Peer Networks

PubMed Central

Dong, Jian; Ren, Xiao; Zuo, Decheng; Liu, Hongwei

2014-01-01

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen's classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen's model. Moreover, B-AFD has better adaptability to P2P network. PMID:25198005

Incipient failure detection of space shuttle main engine turbopump bearings using vibration envelope detection

NASA Technical Reports Server (NTRS)

Hopson, Charles B.

1987-01-01

The results of an analysis performed on seven successive Space Shuttle Main Engine (SSME) static test firings, utilizing envelope detection of external accelerometer data are discussed. The results clearly show the great potential for using envelope detection techniques in SSME incipient failure detection.

Device for detecting imminent failure of high-dielectric stress capacitors. [Patent application

DOEpatents

McDuff, G.G.

1980-11-05

A device is described for detecting imminent failure of a high-dielectric stress capacitor utilizing circuitry for detecting pulse width variations and pulse magnitude variations. Inexpensive microprocessor circuitry is utilized to make numerical calculations of digital data supplied by detection circuitry for comparison of pulse width data and magnitude data to determine if preselected ranges have been exceeded, thereby indicating imminent failure of a capacitor. Detection circuitry may be incorporated in transmission lines, pulse power circuitry, including laser pulse circuitry or any circuitry where capacitors or capacitor banks are utilized.

Device for detecting imminent failure of high-dielectric stress capacitors

DOEpatents

McDuff, George G.

1982-01-01

A device for detecting imminent failure of a high-dielectric stress capacitor utilizing circuitry for detecting pulse width variations and pulse magnitude variations. Inexpensive microprocessor circuitry is utilized to make numerical calculations of digital data supplied by detection circuitry for comparison of pulse width data and magnitude data to determine if preselected ranges have been exceeded, thereby indicating imminent failure of a capacitor. Detection circuitry may be incorporated in transmission lines, pulse power circuitry, including laser pulse circuitry or any circuitry where capacitors or capactior banks are utilized.

Behavioral pattern identification for structural health monitoring in complex systems

NASA Astrophysics Data System (ADS)

Gupta, Shalabh

Estimation of structural damage and quantification of structural integrity are critical for safe and reliable operation of human-engineered complex systems, such as electromechanical, thermofluid, and petrochemical systems. Damage due to fatigue crack is one of the most commonly encountered sources of structural degradation in mechanical systems. Early detection of fatigue damage is essential because the resulting structural degradation could potentially cause catastrophic failures, leading to loss of expensive equipment and human life. Therefore, for reliable operation and enhanced availability, it is necessary to develop capabilities for prognosis and estimation of impending failures, such as the onset of wide-spread fatigue crack damage in mechanical structures. This dissertation presents information-based online sensing of fatigue damage using the analytical tools of symbolic time series analysis ( STSA). Anomaly detection using STSA is a pattern recognition method that has been recently developed based upon a fixed-structure, fixed-order Markov chain. The analysis procedure is built upon the principles of Symbolic Dynamics, Information Theory and Statistical Pattern Recognition. The dissertation demonstrates real-time fatigue damage monitoring based on time series data of ultrasonic signals. Statistical pattern changes are measured using STSA to monitor the evolution of fatigue damage. Real-time anomaly detection is presented as a solution to the forward (analysis) problem and the inverse (synthesis) problem. (1) the forward problem - The primary objective of the forward problem is identification of the statistical changes in the time series data of ultrasonic signals due to gradual evolution of fatigue damage. (2) the inverse problem - The objective of the inverse problem is to infer the anomalies from the observed time series data in real time based on the statistical information generated during the forward problem. A computer-controlled special-purpose fatigue test apparatus, equipped with multiple sensing devices (e.g., ultrasonics and optical microscope) for damage analysis, has been used to experimentally validate the STSA method for early detection of anomalous behavior. The sensor information is integrated with a software module consisting of the STSA algorithm for real-time monitoring of fatigue damage. Experiments have been conducted under different loading conditions on specimens constructed from the ductile aluminium alloy 7075 - T6. The dissertation has also investigated the application of the STSA method for early detection of anomalies in other engineering disciplines. Two primary applications include combustion instability in a generic thermal pulse combustor model and whirling phenomenon in a typical misaligned shaft.

Identification of priorities for medication safety in neonatal intensive care.

PubMed

Kunac, Desireé L; Reith, David M

2005-01-01

Although neonates are reported to be at greater risk of medication error than infants and older children, little is known about the causes and characteristics of error in this patient group. Failure mode and effects analysis (FMEA) is a technique used in industry to evaluate system safety and identify potential hazards in advance. The aim of this study was to identify and prioritize potential failures in the neonatal intensive care unit (NICU) medication use process through application of FMEA. Using the FMEA framework and a systems-based approach, an eight-member multidisciplinary panel worked as a team to create a flow diagram of the neonatal unit medication use process. Then by brainstorming, the panel identified all potential failures, their causes and their effects at each step in the process. Each panel member independently rated failures based on occurrence, severity and likelihood of detection to allow calculation of a risk priority score (RPS). The panel identified 72 failures, with 193 associated causes and effects. Vulnerabilities were found to be distributed across the entire process, but multiple failures and associated causes were possible when prescribing the medication and when preparing the drug for administration. The top ranking issue was a perceived lack of awareness of medication safety issues (RPS score 273), due to a lack of medication safety training. The next highest ranking issues were found to occur at the administration stage. Common potential failures related to errors in the dose, timing of administration, infusion pump settings and route of administration. Perceived causes were multiple, but were largely associated with unsafe systems for medication preparation and storage in the unit, variable staff skill level and lack of computerised technology. Interventions to decrease medication-related adverse events in the NICU should aim to increase staff awareness of medication safety issues and focus on medication administration processes.

49 CFR 395.15 - Automatic on-board recording devices.

Code of Federal Regulations, 2010 CFR

2010-10-01

... information concerning on-board system sensor failures and identification of edited data. Such support systems... driving today; (iv) Total hours on duty for the 7 consecutive day period, including today; (v) Total hours...-driver operation; (7) The on-board recording device/system identifies sensor failures and edited data...

26 CFR 301.6724-1 - Reasonable cause.

Code of Federal Regulations, 2014 CFR

2014-04-01

... waiver where the filer's failure relates to a taxpayer identification number (TIN), and the failure is... incorrect TIN will be deemed to have acted in a responsible manner in compliance with this paragraph (d) only if the filer satisfies the requirements of paragraph (e) of this section (relating to missing TINs...

26 CFR 301.6724-1 - Reasonable cause.

Code of Federal Regulations, 2012 CFR

2012-04-01

... waiver where the filer's failure relates to a taxpayer identification number (TIN), and the failure is... incorrect TIN will be deemed to have acted in a responsible manner in compliance with this paragraph (d) only if the filer satisfies the requirements of paragraph (e) of this section (relating to missing TINs...

26 CFR 301.6724-1 - Reasonable cause.

Code of Federal Regulations, 2013 CFR

2013-04-01

... waiver where the filer's failure relates to a taxpayer identification number (TIN), and the failure is... incorrect TIN will be deemed to have acted in a responsible manner in compliance with this paragraph (d) only if the filer satisfies the requirements of paragraph (e) of this section (relating to missing TINs...

26 CFR 301.6724-1 - Reasonable cause.

Code of Federal Regulations, 2011 CFR

2011-04-01

... waiver where the filer's failure relates to a taxpayer identification number (TIN), and the failure is... incorrect TIN will be deemed to have acted in a responsible manner in compliance with this paragraph (d) only if the filer satisfies the requirements of paragraph (e) of this section (relating to missing TINs...

[Endoprosthesis failure in the ankle joint : Histopathological diagnostics and classification].

PubMed

Müller, S; Walther, M; Röser, A; Krenn, V

2017-03-01

Endoprostheses of the ankle joint show higher revision rates of 3.29 revisions per 100 component years. The aims of this study were the application and modification of the consensus classification of the synovia-like interface membrane (SLIM) for periprosthetic failure of the ankle joint, the etiological clarification of periprosthetic pseudocysts and a detailed measurement of proliferative activity (Ki67) in the region of osteolysis. Tissue samples from 159 patients were examined according to the criteria of the standardized consensus classification. Of these, 117 cases were derived from periprosthetic membranes of the ankle. The control group included 42 tissue specimens from the hip and knee joints. Particle identification and characterization were carried out using the particle algorithm. An immunohistochemical examination with Ki67 proliferation was performed in all cases of ankle pseudocysts and 19 control cases. The consensus classification of SLIM is transferrable to endoprosthetic failure of the ankle joint. Periprosthetic pseudocysts with the histopathological characteristics of the appropriate SLIM subtype were detectable in 39 cases of ankle joint endoprostheses (33.3%). The mean value of the Ki67 index was 14% and showed an increased proliferation rate in periprosthetic pseudocysts of the ankle (p-value 0.02037). In periprosthetic pseudocysts an above average higher detection rate of type 1 SLIM induced by abrasion (51.3%) with an increased Ki67 proliferation fraction (p-value 0.02037) was found, which can be interpreted as local destructive intraosseus synovialitis. This can be the reason for formation of pseudocystic osteolysis caused by high mechanical stress in ankle endoprostheses. A simplified diagnostic classification scoring system of dysfunctional endoprostheses of the ankle is proposed for collation of periprosthetic pseudocysts, ossifications and the Ki67 proliferation fraction.

Epidemic failure detection and consensus for extreme parallelism

DOE PAGES

Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas; ...

2017-02-01

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less

Advanced detection, isolation and accommodation of sensor failures: Real-time evaluation

NASA Technical Reports Server (NTRS)

Merrill, Walter C.; Delaat, John C.; Bruton, William M.

1987-01-01

The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundacy to detect sensor failures. The results of a real time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

Smallpox Eradication in Bangladesh, 1972–19761

PubMed Central

Foster, Stanley O.; Hughes, Kenneth; Tarantola, Daniel; Glasser, John W.

2017-01-01

Rahima Bano, the world’s last endemic case of severe smallpox, Variola Major, developed rash on October 16, 1975 on Bhola Island, Bangladesh. Achieving eradication in a country destroyed by war challenged the achievement of smallpox eradication. Between January 1, 1972 and December 31, 1975, 225,000 smallpox cases and 45,000 smallpox deaths occurred. Adapting the global smallpox eradication strategies of surveillance, the detection of smallpox cases, and containment, the interruption of smallpox transmission, utilized progress toward three objectives to monitor performance: 1) Surveillance – the percent smallpox infected villages detected within 14 days of the first case of rash, 2) Knowledge of the Reward – public knowledge of the current amount of the reward for reporting smallpox, and 3) Containment – the percent of infected villages interrupting smallpox transmission within 14 days of detection. Failures to achieve these objectives led to identification and implementation of improved strategies that eventually achieved eradication. Essential to this success was a tripartite partnership of the citizens of Bangladesh, the Bangladesh Ministry of Health and its field staff, and personnel and resources mobilized by the World Health Organization. PMID:22188934

Human Trafficking: How Nurses Can Make a Difference.

PubMed

Scannell, Meredith; MacDonald, Andrea E; Berger, Amanda; Boyer, Nichole

Human trafficking is a human rights violation and a global health problem. Victims of human trafficking have medical and mental health sequelae requiring specific healthcare interventions. Healthcare professionals may be the initial contact that these victims make outside the world of trafficking. Healthcare professionals are key agents in the identification of human trafficking, which is essential in eliminating this public health problem. Unfortunately, healthcare professionals are not always able to detect signs of human trafficking. Failure to detect results in missed opportunities to assist victims. This is a case report of a victim of human trafficking who presented to an emergency department with medical and mental health issues. Despite numerous encounters with different healthcare professionals, signs and symptoms of human trafficking were not identified. Skilled assessment made by a forensic nurse alerted the healthcare team to clear features of human trafficking associated with this person. Through this case report we illustrate the key role the nurse played in identifying signs of human trafficking. Improvement of human trafficking educational programs is highlighted as a key adjunct to improving detection and facilitating the proper treatment of victims.

Wetware, Hardware, or Software Incapacitation: Observational Methods to Determine When Autonomy Should Assume Control

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2014-01-01

Control-theoretic modeling of human operator's dynamic behavior in manual control tasks has a long, rich history. There has been significant work on techniques used to identify the pilot model of a given structure. This research attempts to go beyond pilot identification based on experimental data to develop a predictor of pilot behavior. Two methods for pre-dicting pilot stick input during changing aircraft dynamics and deducing changes in pilot behavior are presented This approach may also have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot. With this ability to detect changes in piloting behavior, the possibility now exists to mediate human adverse behaviors, hardware failures, and software anomalies with autono-my that may ameliorate these undesirable effects. However, appropriate timing of when au-tonomy should assume control is dependent on criticality of actions to safety, sensitivity of methods to accurately detect these adverse changes, and effects of changes in levels of auto-mation of the system as a whole.

Smallpox eradication in Bangladesh, 1972-1976.

PubMed

Foster, Stanley O; Hughes, Kenneth; Tarantola, Daniel; Glasser, John W

2011-12-30

Rahima Banu, the world's last endemic case of severe smallpox, Variola Major, developed rash on October 16, 1975 on Bhola Island, Bangladesh. Achieving eradication in a country destroyed by war challenged the achievement of smallpox eradication. Between January 1, 1972 and December 31, 1975, 225,000 smallpox cases and 45,000 smallpox deaths occurred. Adapting the global smallpox eradication strategies of surveillance, the detection of smallpox cases, and containment, the interruption of smallpox transmission, utilized progress toward three objectives to monitor performance: (1) surveillance - the percent of smallpox infected villages detected within 14 days of the first case of rash, (2) knowledge of the reward - public knowledge of the current amount of the reward for reporting smallpox, and (3) containment - the percent of infected villages interrupting smallpox transmission within 14 days of detection. Failures to achieve these objectives led to the identification and implementation of improved strategies that eventually achieved eradication. Essential to this success was a tripartite partnership of the citizens of Bangladesh, the Bangladesh Ministry of Health, its field staff, and staff and resources mobilized by the World Health Organization. Copyright © 2011. Published by Elsevier Ltd.

Detection of Pseudomonas aeruginosa biomarkers from thermally injured mice in situ using imaging mass spectrometry.

PubMed

Hamerly, Timothy; Everett, Jake A; Paris, Nina; Fisher, Steve T; Karunamurthy, Arivarasan; James, Garth A; Rumbaugh, Kendra P; Rhoads, Daniel D; Bothner, Brian

2017-12-15

Monitoring patients with burn wounds for infection is standard practice because failure to rapidly and specifically identify a pathogen can result in poor clinical outcomes, including death. Therefore, a method that facilitates detection and identification of pathogens in situ within minutes of biopsy would be a significant benefit to clinicians. Mass spectrometry is rapidly becoming a standard tool in clinical settings, capable of identifying specific pathogens from complex samples. Imaging mass spectrometry (IMS) expands the information content by enabling spatial resolution of biomarkers in tissue samples as in histology, without the need for specific stains/antibodies. Herein, a murine model of thermal injury was used to study infection of burn tissue by Pseudomonas aeruginosa. This is the first use of IMS to detect P. aeruginosa infection in situ from thermally injured tissue. Multiple molecular features could be spatially resolved to infected or uninfected tissue. This demonstrates the potential use of IMS in a clinical setting to aid doctors in identifying both presence and species of pathogens in tissue. Copyright © 2017. Published by Elsevier Inc.

EEMD-based wind turbine bearing failure detection using the generator stator current homopolar component

NASA Astrophysics Data System (ADS)

Amirat, Yassine; Choqueuse, Vincent; Benbouzid, Mohamed

2013-12-01

Failure detection has always been a demanding task in the electrical machines community; it has become more challenging in wind energy conversion systems because sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. Indeed the most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the generator health degeneration, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper provides then an assessment of a failure detection techniques based on the homopolar component of the generator stator current and attempts to highlight the use of the ensemble empirical mode decomposition as a tool for failure detection in wind turbine generators for stationary and non-stationary cases.

A novel orellanine containing mushroom Cortinarius armillatus.

PubMed

Shao, Dahai; Tang, Shusheng; Healy, Rosanne A; Imerman, Paula M; Schrunk, Dwayne E; Rumbeiha, Wilson K

2016-05-01

Orellanine (3,3',4,4'-tetrahydroxy-2,2'-bipyridine-1,1'-dioxide) is a tetrahydroxylated di-N-oxidized bipyridine compound. The toxin, present in certain species of Cortinarius mushrooms, is structurally similar to herbicides Paraquat and Diquat. Cortinarius orellanus and Cortinarius rubellus are the major orellanine-containing mushrooms. Cortinarius mushrooms are widely reported in Europe where they have caused human poisoning and deaths through accidental ingestion of the poisonous species mistaken for the edible ones. In North America, Cortinarius orellanosus mushroom poisoning was recently reported to cause renal failure in a Michigan patient. Cortinarius mushroom poisoning is characterized by delayed acute renal failure, with some cases progressing to end-stage kidney disease. There is debate whether other Cortinarius mushroom contain orellanine or not, especially in North America. Currently, there are no veterinary diagnostic laboratories in North America with established test methods for detection and quantitation of orellanine. We have developed two diagnostic test methods based on HPLC and LC-MSMS for identification and quantitation of orellanine in mushrooms. Using these methods, we have identified Cortinarius armillatus as a novel orellanine-containing mushroom in North America. The mean toxin concentration of 145 ug/g was <1% of that of the more toxic C. rubellus. The HPLC method can detect orellanine at 17 μg g(-1) while the LC-MSMS method is almost 2000 times more sensitive and can detect orellanine at 30 ng g(-1). Both tests are quantitative, selective and are now available for veterinary diagnostic applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification and assessment of common errors in the admission process of patients in Isfahan Fertility and Infertility Center based on "failure modes and effects analysis".

PubMed

Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila

2016-01-01

Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of "failure modes and effects analysis" (FMEA). In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members' decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors.

Identification and assessment of common errors in the admission process of patients in Isfahan Fertility and Infertility Center based on “failure modes and effects analysis”

PubMed Central

Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila

2016-01-01

Background: Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of “failure modes and effects analysis” (FMEA). Materials and Methods: In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members’ decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Results: Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. Conclusions: The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors. PMID:28194208

49 CFR Appendix D to Part 236 - Independent Review of Verification and Validation

Code of Federal Regulations, 2010 CFR

2010-10-01

... standards. (f) The reviewer shall analyze all Fault Tree Analyses (FTA), Failure Mode and Effects... for each product vulnerability cited by the reviewer; (4) Identification of any documentation or... not properly followed; (6) Identification of the software verification and validation procedures, as...

Multiple Confidence Estimates as Indices of Eyewitness Memory

ERIC Educational Resources Information Center

Sauer, James D.; Brewer, Neil; Weber, Nathan

2008-01-01

Eyewitness identification decisions are vulnerable to various influences on witnesses' decision criteria that contribute to false identifications of innocent suspects and failures to choose perpetrators. An alternative procedure using confidence estimates to assess the degree of match between novel and previously viewed faces was investigated.…

Multiplex PCR for the detection and identification of dairy bacteriophages in milk.

PubMed

del Rio, B; Binetti, A G; Martín, M C; Fernández, M; Magadán, A H; Alvarez, M A

2007-02-01

Bacteriophage infections of starter lactic acid bacteria are a serious risk in the dairy industry. Phage infection can lead to slow lactic acid production or even the total failure of fermentation. The associated economic losses can be substantial. Rapid and sensitive methods are therefore required to detect and identify phages at all stages of the manufacture of fermented dairy products. This study describes a simple and rapid multiplex PCR method that, in a single reaction, detects the presence of bacteriophages infecting Streptococcus thermophilus and Lactobacillus delbrueckii, plus three genetically distinct 'species' of Lactococcus lactis phages commonly found in dairy plants (P335, 936 and c2). Available bacteriophage genome sequences were examined and the conserved regions used to design five pairs of primers, one for each of the above bacteriophage species. These primers were designed to generate specific fragments of different size depending on the species. Since this method can detect the above phages in untreated milk and can be easily incorporated into dairy industry routines, it might be readily used to earmark contaminated milk for use in processes that do not involve susceptible starter organisms or for use in those that involve phage-deactivating conditions.

Scan direction induced charging dynamics and the application for detection of gate to S/D shorts in logic devices

NASA Astrophysics Data System (ADS)

Lei, Ming; Tian, Qing; Wu, Kevin; Zhao, Yan

2016-03-01

Gate to source/drain (S/D) short is the most common and detrimental failure mechanism for advanced process technology development in Metal-Oxide-Semiconductor-Field-Effect-Transistor (MOSFET) device manufacturing. Especially for sub-1Xnm nodes, MOSFET device is more vulnerable to gate-S/D shorts due to the aggressive scaling. The detection of this kind of electrical short defect is always challenging for in-line electron beam inspection (EBI), especially new shorting mechanisms on atomic scale due to new material/process flow implementation. The second challenge comes from the characterization of the shorts including identification of the exact shorting location. In this paper, we demonstrate unique scan direction induced charging dynamics (SDCD) phenomenon which stems from the transistor level response from EBI scan at post metal contact chemical-mechanical planarization (CMP) layers. We found that SDCD effect is exceptionally useful for gate-S/D short induced voltage contrast (VC) defect detection, especially for identification of shorting locations. The unique SDCD effect signatures of gate-S/D shorts can be used as fingerprint for ground true shorting defect detection. Correlation with other characterization methods on the same defective location from EBI scan shows consistent results from various shorting mechanism. A practical work flow to implement the application of SDCD effect for in-line EBI monitor of critical gate-S/D short defects is also proposed, together with examples of successful application use cases which mostly focus on static random-access memory (SRAM) array regions. Although the capability of gate-S/D short detection as well as expected device response is limited to passing transistors and pull-down transistors due to the design restriction from standard 6-cell SRAM structure, SDCD effect is proven to be very effective for gate-S/D short induced VC defect detection as well as yield learning for advanced technology development.

Failure detection and fault management techniques for flush airdata sensing systems

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

1992-01-01

Methods based on chi-squared analysis are presented for detecting system and individual-port failures in the high-angle-of-attack flush airdata sensing system on the NASA F-18 High Alpha Research Vehicle. The HI-FADS hardware is introduced, and the aerodynamic model describes measured pressure in terms of dynamic pressure, angle of attack, angle of sideslip, and static pressure. Chi-squared analysis is described in the presentation of the concept for failure detection and fault management which includes nominal, iteration, and fault-management modes. A matrix of pressure orifices arranged in concentric circles on the nose of the aircraft indicate the parameters which are applied to the regression algorithms. The sensing techniques are applied to the F-18 flight data, and two examples are given of the computed angle-of-attack time histories. The failure-detection and fault-management techniques permit the matrix to be multiply redundant, and the chi-squared analysis is shown to be useful in the detection of failures.

Failure Detecting Method of Fault Current Limiter System with Rectifier

NASA Astrophysics Data System (ADS)

Tokuda, Noriaki; Matsubara, Yoshio; Asano, Masakuni; Ohkuma, Takeshi; Sato, Yoshibumi; Takahashi, Yoshihisa

A fault current limiter (FCL) is extensively needed to suppress fault current, particularly required for trunk power systems connecting high-voltage transmission lines, such as 500kV class power system which constitutes the nucleus of the electric power system. We proposed a new type FCL system (rectifier type FCL), consisting of solid-state diodes, DC reactor and bypass AC reactor, and demonstrated the excellent performances of this FCL by developing the small 6.6kV and 66kV model. It is important to detect the failure of power devices used in the rectifier under the normal operating condition, for keeping the excellent reliability of the power system. In this paper, we have proposed a new failure detecting method of power devices most suitable for the rectifier type FCL. This failure detecting system is simple and compact. We have adapted the proposed system to the 66kV prototype single-phase model and successfully demonstrated to detect the failure of power devices.

Syndromic surveillance for health information system failures: a feasibility study.

PubMed

Ong, Mei-Sing; Magrabi, Farah; Coiera, Enrico

2013-05-01

To explore the applicability of a syndromic surveillance method to the early detection of health information technology (HIT) system failures. A syndromic surveillance system was developed to monitor a laboratory information system at a tertiary hospital. Four indices were monitored: (1) total laboratory records being created; (2) total records with missing results; (3) average serum potassium results; and (4) total duplicated tests on a patient. The goal was to detect HIT system failures causing: data loss at the record level; data loss at the field level; erroneous data; and unintended duplication of data. Time-series models of the indices were constructed, and statistical process control charts were used to detect unexpected behaviors. The ability of the models to detect HIT system failures was evaluated using simulated failures, each lasting for 24 h, with error rates ranging from 1% to 35%. In detecting data loss at the record level, the model achieved a sensitivity of 0.26 when the simulated error rate was 1%, while maintaining a specificity of 0.98. Detection performance improved with increasing error rates, achieving a perfect sensitivity when the error rate was 35%. In the detection of missing results, erroneous serum potassium results and unintended repetition of tests, perfect sensitivity was attained when the error rate was as small as 5%. Decreasing the error rate to 1% resulted in a drop in sensitivity to 0.65-0.85. Syndromic surveillance methods can potentially be applied to monitor HIT systems, to facilitate the early detection of failures.

Detection of early stage large scale landslides in forested areas by 2 m LiDAR DEM analysis. The example of Portainé (Central Pyrenees)

NASA Astrophysics Data System (ADS)

Guinau, Marta; Ortuño, Maria; Calvet, Jaume; Furdada, Glòria; Bordonau, Jaume; Ruiz, Antonio; Camafort, Miquel

2016-04-01

Mass movements have been classically detected by field inspection and air-photo interpretation. However, airborne LiDAR has significant potential for generating high-resolution digital terrain models, which provide considerable advantages over conventional surveying techniques. In this work, we present the identification and characterization of six slope failures previously undetected in the Orri massif, at the core of the Pyrenean range. The landforms had not been previously detected and were identified by the analysis of high resolution 2 m LiDAR derived bared earth topography. Most of the scarps within these failures are not detectable by photo interpretation or the analysis of 5 m resolution topographic maps owing to their small heights (ranging between 0.5 and 2 m) and their location within forest areas. 2D and 3D visualization of hillshade maps with different sun azimuths, allowed to obtain the overall picture of the scarp assemblage and to analyze the geometry and location of the scarps with respect to the slope and the structural fabric. Near 120 scarps were mapped and interpreted as part of slow gravitational deformation, incipient slow flow affecting a colluvium, rotational rock-sliding and slope creep. Landforms interpreted as incipient slow flow affecting a colluvium have headscarps with horse-shoe shape and superficial (< 20 m) basal planes whereas sackung features have open headscarps and basal planes that are likely located at 200-250 m maximum depth. Other distinctive features are toppling or extensive scarps, double ridges and rock rotational landslides. The sharpness of the scarps suggests their recent activity, which may pose a potential risk for the Port-Ainé sky resort users and facilities. These results suggest that the systematic analysis of 2 m LIDAR derived bared earth topography would significantly help in the rapid detection and mapping of early stage slope deformations in high mountain areas, which could contribute to 1) a better understanding of the spatial controlling factors and 2) obtaining rapid diagnosis of the state of the slopes, critical for the proper forecast of future catastrophic failures. This presentation is supported by the Spanish Ministry of Science and Innovation project CHARMA: CHAracterization and ContRol of MAss Movements. A Challenge for Geohazard Mitigation (CGL2013-40828-R).

A fault-tolerant control architecture for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Drozeski, Graham R.

Research has presented several approaches to achieve varying degrees of fault-tolerance in unmanned aircraft. Approaches in reconfigurable flight control are generally divided into two categories: those which incorporate multiple non-adaptive controllers and switch between them based on the output of a fault detection and identification element, and those that employ a single adaptive controller capable of compensating for a variety of fault modes. Regardless of the approach for reconfigurable flight control, certain fault modes dictate system restructuring in order to prevent a catastrophic failure. System restructuring enables active control of actuation not employed by the nominal system to recover controllability of the aircraft. After system restructuring, continued operation requires the generation of flight paths that adhere to an altered flight envelope. The control architecture developed in this research employs a multi-tiered hierarchy to allow unmanned aircraft to generate and track safe flight paths despite the occurrence of potentially catastrophic faults. The hierarchical architecture increases the level of autonomy of the system by integrating five functionalities with the baseline system: fault detection and identification, active system restructuring, reconfigurable flight control; reconfigurable path planning, and mission adaptation. Fault detection and identification algorithms continually monitor aircraft performance and issue fault declarations. When the severity of a fault exceeds the capability of the baseline flight controller, active system restructuring expands the controllability of the aircraft using unconventional control strategies not exploited by the baseline controller. Each of the reconfigurable flight controllers and the baseline controller employ a proven adaptive neural network control strategy. A reconfigurable path planner employs an adaptive model of the vehicle to re-shape the desired flight path. Generation of the revised flight path is posed as a linear program constrained by the response of the degraded system. Finally, a mission adaptation component estimates limitations on the closed-loop performance of the aircraft and adjusts the aircraft mission accordingly. A combination of simulation and flight test results using two unmanned helicopters validates the utility of the hierarchical architecture.

A comparison of two prospective risk analysis methods: Traditional FMEA and a modified healthcare FMEA.

PubMed

Rah, Jeong-Eun; Manger, Ryan P; Yock, Adam D; Kim, Gwe-Ya

2016-12-01

To examine the abilities of a traditional failure mode and effects analysis (FMEA) and modified healthcare FMEA (m-HFMEA) scoring methods by comparing the degree of congruence in identifying high risk failures. The authors applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation were based on the risk priority number (RPN). The RPN is a product of three indices: occurrence, severity, and detectability. The m-HFMEA approach utilized two indices, severity and frequency. A risk inventory matrix was divided into four categories: very low, low, high, and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. The two methods were independently compared to determine if the results and rated risks matched. The authors' results showed an agreement of 85% between FMEA and m-HFMEA approaches for top 20 risks of SIG-RS-specific failure modes. The main differences between the two approaches were the distribution of the values and the observation that failure modes (52, 54, 154) with high m-HFMEA scores do not necessarily have high FMEA-RPN scores. In the m-HFMEA analysis, when the risk score is determined, the basis of the established HFMEA Decision Tree™ or the failure mode should be more thoroughly investigated. m-HFMEA is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allows the prioritization of high risks and mitigation measures. It is therefore a useful tool for the prospective risk analysis method to radiotherapy.

Microfluidic-Based Bacteria Isolation from Whole Blood for Diagnostics of Blood Stream Infection.

PubMed

Zelenin, Sergey; Ramachandraiah, Harisha; Faridi, Asim; Russom, Aman

2017-01-01

Bacterial blood stream infection (BSI) potentially leads to life-threatening clinical conditions and medical emergencies such as severe sepsis, septic shock, and multi organ failure syndrome. Blood culturing is currently the gold standard for the identification of microorganisms and, although it has been automated over the decade, the process still requires 24-72 h to complete. This long turnaround time, especially for the identification of antimicrobial resistance, is driving the development of rapid molecular diagnostic methods. Rapid detection of microbial pathogens in blood related to bloodstream infections will allow the clinician to decide on or adjust the antimicrobial therapy potentially reducing the morbidity, mortality, and economic burden associated with BSI. For molecular-based methods, there is a lot to gain from an improved and straightforward method for isolation of bacteria from whole blood for downstream processing.We describe a microfluidic-based sample-preparation approach that rapidly and selectively lyses all blood cells while it extracts intact bacteria for downstream analysis. Whole blood is exposed to a mild detergent, which lyses most blood cells, and then to osmotic shock using deionized water, which eliminates the remaining white blood cells. The recovered bacteria are 100 % viable, which opens up possibilities for performing drug susceptibility tests and for nucleic-acid-based molecular identification.

Use of Sequenom Sample ID Plus® SNP Genotyping in Identification of FFPE Tumor Samples

PubMed Central

Miller, Jessica K.; Buchner, Nicholas; Timms, Lee; Tam, Shirley; Luo, Xuemei; Brown, Andrew M. K.; Pasternack, Danielle; Bristow, Robert G.; Fraser, Michael; Boutros, Paul C.; McPherson, John D.

2014-01-01

Short tandem repeat (STR) analysis, such as the AmpFlSTR® Identifiler® Plus kit, is a standard, PCR-based human genotyping method used in the field of forensics. Misidentification of cell line and tissue DNA can be costly if not detected early; therefore it is necessary to have quality control measures such as STR profiling in place. A major issue in large-scale research studies involving archival formalin-fixed paraffin embedded (FFPE) tissues is that varying levels of DNA degradation can result in failure to correctly identify samples using STR genotyping. PCR amplification of STRs of several hundred base pairs is not always possible when DNA is degraded. The Sample ID Plus® panel from Sequenom allows for human DNA identification and authentication using SNP genotyping. In comparison to lengthy STR amplicons, this multiplexing PCR assay requires amplification of only 76–139 base pairs, and utilizes 47 SNPs to discriminate between individual samples. In this study, we evaluated both STR and SNP genotyping methods of sample identification, with a focus on paired FFPE tumor/normal DNA samples intended for next-generation sequencing (NGS). The ability to successfully validate the identity of FFPE samples can enable cost savings by reducing rework. PMID:24551080

Use of Sequenom sample ID Plus® SNP genotyping in identification of FFPE tumor samples.

PubMed

Miller, Jessica K; Buchner, Nicholas; Timms, Lee; Tam, Shirley; Luo, Xuemei; Brown, Andrew M K; Pasternack, Danielle; Bristow, Robert G; Fraser, Michael; Boutros, Paul C; McPherson, John D

2014-01-01

Short tandem repeat (STR) analysis, such as the AmpFlSTR® Identifiler® Plus kit, is a standard, PCR-based human genotyping method used in the field of forensics. Misidentification of cell line and tissue DNA can be costly if not detected early; therefore it is necessary to have quality control measures such as STR profiling in place. A major issue in large-scale research studies involving archival formalin-fixed paraffin embedded (FFPE) tissues is that varying levels of DNA degradation can result in failure to correctly identify samples using STR genotyping. PCR amplification of STRs of several hundred base pairs is not always possible when DNA is degraded. The Sample ID Plus® panel from Sequenom allows for human DNA identification and authentication using SNP genotyping. In comparison to lengthy STR amplicons, this multiplexing PCR assay requires amplification of only 76-139 base pairs, and utilizes 47 SNPs to discriminate between individual samples. In this study, we evaluated both STR and SNP genotyping methods of sample identification, with a focus on paired FFPE tumor/normal DNA samples intended for next-generation sequencing (NGS). The ability to successfully validate the identity of FFPE samples can enable cost savings by reducing rework.

Evaluating an Art-Based Intervention to Improve Practicing Nurses' Observation, Description, and Problem Identification Skills.

PubMed

Nease, Beth M; Haney, Tina S

Astute observation, description, and problem identification skills provide the underpinning for nursing assessment, surveillance, and prevention of failure to rescue events. Art-based education has been effective in nursing schools for improving observation, description, and problem identification. The authors describe a randomized controlled pilot study testing the effectiveness of an art-based educational intervention aimed at improving these skills in practicing nurses.

Y are you not pregnant: identification of Y chromosome segments in female cattle with decreased reproductive efficiency

USDA-ARS?s Scientific Manuscript database

Reproductive efficiency is of economic importance in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of females and avoid ineff...

Algorithm to determine the percolation largest component in interconnected networks.

PubMed

Schneider, Christian M; Araújo, Nuno A M; Herrmann, Hans J

2013-04-01

Interconnected networks have been shown to be much more vulnerable to random and targeted failures than isolated ones, raising several interesting questions regarding the identification and mitigation of their risk. The paradigm to address these questions is the percolation model, where the resilience of the system is quantified by the dependence of the size of the largest cluster on the number of failures. Numerically, the major challenge is the identification of this cluster and the calculation of its size. Here, we propose an efficient algorithm to tackle this problem. We show that the algorithm scales as O(NlogN), where N is the number of nodes in the network, a significant improvement compared to O(N(2)) for a greedy algorithm, which permits studying much larger networks. Our new strategy can be applied to any network topology and distribution of interdependencies, as well as any sequence of failures.

Identification of delamination failure of boride layer on common Cr-based steels

NASA Astrophysics Data System (ADS)

Taktak, Sukru; Tasgetiren, Suleyman

2006-10-01

Adhesion is an important aspect in the reliability of coated components. With low-adhesion of interfaces, different crack paths may develop depending on the local stress field at the interface and the fracture toughness of the coating, substrate, and interface. In the current study, an attempt has been made to identify the delamination failure of coated Cr-based steels by boronizing. For this reason, two commonly used steels (AISI H13, AISI 304) are considered. The steels contain 5.3 and 18.3 wt.% Cr, respectively. Boriding treatment is carried out in a slurry salt bath consisting of borax, boric acid, and ferrosilicon at a temperature range of 800 950 °C for 3, 5, and 7 h. The general properties of the boron coating are obtained by mechanical and metallographic characterization tests. For identification of coating layer failure, some fracture toughness tests and the Daimler-Benz Rockwell-C adhesion test are used.

Remote Structural Health Monitoring and Advanced Prognostics of Wind Turbines

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

Douglas Brown; Bernard Laskowski

The prospect of substantial investment in wind energy generation represents a significant capital investment strategy. In order to maximize the life-cycle of wind turbines, associated rotors, gears, and structural towers, a capability to detect and predict (prognostics) the onset of mechanical faults at a sufficiently early stage for maintenance actions to be planned would significantly reduce both maintenance and operational costs. Advancement towards this effort has been made through the development of anomaly detection, fault detection and fault diagnosis routines to identify selected fault modes of a wind turbine based on available sensor data preceding an unscheduled emergency shutdown. Themore » anomaly detection approach employs spectral techniques to find an approximation of the data using a combination of attributes that capture the bulk of variability in the data. Fault detection and diagnosis (FDD) is performed using a neural network-based classifier trained from baseline and fault data recorded during known failure conditions. The approach has been evaluated for known baseline conditions and three selected failure modes: pitch rate failure, low oil pressure failure and a gearbox gear-tooth failure. Experimental results demonstrate the approach can distinguish between these failure modes and normal baseline behavior within a specified statistical accuracy.« less

Incidence and Determinants of Dental Implant Failure: A Review of Electronic Health Records in a U.S. Dental School.

PubMed

Hickin, Matthew Parker; Shariff, Jaffer A; Jennette, Philip J; Finkelstein, Joseph; Papapanou, Panos N

2017-10-01

The aim of this study was to use electronic health care records (EHRs) to examine retrospectively the incidence of and attributes associated with dental implant failures necessitating implant removal in a large cohort of patients treated in the student clinics of a U.S. dental school over three and a half years. EHRs were searched for all patients who received dental implants between July 1, 2011, and December 31, 2014. Characteristics of patients and implants that were actively removed due to irrevocable failure of any etiology ("failure cohort") during this period were compared to those of all other patients who received dental implants during the same time frame ("reference cohort"). Differences in the frequency distribution of various characteristics between the failure and reference cohorts were compared. Of a total 6,129 implants placed in 2,127 patients during the study period, 179 implants (2.9%) in 120 patients (5.6%) were removed. In the multivariate analysis, presence of a removable (OR=2.86) or fixed temporary prosthesis (OR=3.71) was statistically significantly associated with increased risk for implant failure. In contrast, antibiotic coverage (pre- and post-surgery OR=0.16; post-surgery only OR=0.38) and implants of certain manufacturers were associated with lower risk of implant failure. In this sizeable cohort of patients receiving care in dental student clinics, the review of EHRs facilitated identification of multiple variables associated with implant failure resulting in removal; however, these findings do not suggest causative relationships. The adopted analytical approach can enhance quality assurance measures and may contribute to the identification of true risk factors for dental implant failure.

[Place of indocyanine green coupled with fluorescence imaging in research of breast cancer sentinel node].

PubMed

Vermersch, Charlotte; Raia Barjat, Tiphaine; Perrot, Marianne; Lima, Suzanne; Chauleur, Céline

2016-04-01

The sentinel node has a fundamental role in the management of early breast cancer. Currently, the double detection of blue and radioisotope is recommended. But in common practice, many centers use a single method. However, with a single detection, the risk of false negatives and the identification failure rate increase to a significant extent and the number of sentinel lymph node detected and removed is not enough. Furthermore, the tracers used until now show inconveniences. The purpose of this work is to present a new method of detection, using the green of indocyanine coupled with fluorescence imaging, and to compare it with the already existing methods. The method combined by fluorescence and isotopic is reliable, sure, of fast learning and could constitute a good strategy of detection. The major interest is to obtain a satisfactory number of sentinel nodes. The profit could be even more important for overweight patients. The fluorescence used alone is at the moment not possible. Wide ranging studies are necessary. The FLUOTECH, randomized study of 100 patients, comparing the isotopic method of double isotope technique and fluorescence, is underway to confirm these data. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Device for detection and identification of carbon- and nitrogen-containing materials

DOEpatents

Karev, Alexander Ivanovich; Raevsky, Valery Georgievich; Dzhilavyan, Leonid Zavenovich; Laptev, Valery Dmitrievich; Pakhomov, Nikolay Ivanovich; Shvedunov, Vasily Ivanovich; Rykalin, Vladimir Ivanovich; Brothers, Louis Joseph; Wilhide, Larry K

2014-03-25

A device for detection and identification of carbon- and nitrogen-containing materials is described. In particular, the device performs the detection and identification of carbon- and nitrogen-containing materials by photo-nuclear detection. The device may comprise a race-track microtron, a breaking target, and a water-filled Cherenkov radiation counter.

Multiple-strand displacement and identification of single nucleotide polymorphisms as markers of genotypic variation of Pasteuria penetrans biotypes infecting root-knot nematodes.

PubMed

Nong, Guang; Chow, Virginia; Schmidt, Liesbeth M; Dickson, Don W; Preston, James F

2007-08-01

Pasteuria species are endospore-forming obligate bacterial parasites of soil-inhabiting nematodes and water-inhabiting cladocerans, e.g. water fleas, and are closely related to Bacillus spp. by 16S rRNA gene sequence. As naturally occurring bacteria, biotypes of Pasteuria penetrans are attractive candidates for the biocontrol of various Meloidogyne spp. (root-knot nematodes). Failure to culture these bacteria outside their hosts has prevented isolation of genomic DNA in quantities sufficient for identification of genes associated with host recognition and virulence. We have applied multiple-strand displacement amplification (MDA) to generate DNA for comparative genomics of biotypes exhibiting different host preferences. Using the genome of Bacillus subtilis as a paradigm, MDA allowed quantitative detection and sequencing of 12 marker genes from 2000 cells. Meloidogyne spp. infected with P. penetrans P20 or B4 contained single nucleotide polymorphisms (SNPs) in the spoIIAB gene that did not change the amino acid sequence, or that substituted amino acids with similar chemical properties. Individual nematodes infected with P. penetrans P20 or B4 contained SNPs in the spoIIAB gene sequenced in MDA-generated products. Detection of SNPs in the spoIIAB gene in a nematode indicates infection by more than one genotype, supporting the need to sequence genomes of Pasteuria spp. derived from single spore isolates.

Tools for quality control of fingerprint databases

NASA Astrophysics Data System (ADS)

Swann, B. Scott; Libert, John M.; Lepley, Margaret A.

2010-04-01

Integrity of fingerprint data is essential to biometric and forensic applications. Accordingly, the FBI's Criminal Justice Information Services (CJIS) Division has sponsored development of software tools to facilitate quality control functions relative to maintaining its fingerprint data assets inherent to the Integrated Automated Fingerprint Identification System (IAFIS) and Next Generation Identification (NGI). This paper provides an introduction of two such tools. The first FBI-sponsored tool was developed by the National Institute of Standards and Technology (NIST) and examines and detects the spectral signature of the ridge-flow structure characteristic of friction ridge skin. The Spectral Image Validation/Verification (SIVV) utility differentiates fingerprints from non-fingerprints, including blank frames or segmentation failures erroneously included in data; provides a "first look" at image quality; and can identify anomalies in sample rates of scanned images. The SIVV utility might detect errors in individual 10-print fingerprints inaccurately segmented from the flat, multi-finger image acquired by one of the automated collection systems increasing in availability and usage. In such cases, the lost fingerprint can be recovered by re-segmentation from the now compressed multi-finger image record. The second FBI-sponsored tool, CropCoeff was developed by MITRE and thoroughly tested via NIST. CropCoeff enables cropping of the replacement single print directly from the compressed data file, thus avoiding decompression and recompression of images that might degrade fingerprint features necessary for matching.

A practical guide to epidemiological practice and standards in the identification and validation of diagnostic markers using a bladder cancer example.

PubMed

Behrens, T; Bonberg, N; Casjens, S; Pesch, B; Brüning, T

2014-01-01

Technical advances to analyze biological markers have generated a plethora of promising new marker candidates for early detection of cancer. However, in subsequent analyses only few could be successfully validated as being predictive, clinically useful, or effective. This failure is partially due to rapid publication of results that were detected in early stages of biomarker research. Methodological considerations are a major concern when carrying out molecular epidemiological studies of diagnostic markers to avoid errors that increase the potential for bias. Although guidelines for conducting studies and reporting of results have been published to improve the quality of marker studies, their planning and execution still need to be improved. We will discuss different sources of bias in study design, handling of specimens, and statistical analysis to illustrate possible pitfalls associated with marker research, and present legal, ethical, and technical considerations associated with storage and handling of specimens. This article presents a guide to epidemiological standards in marker research using bladder cancer as an example. Because of the possibility to detect early cancer stages due to leakage of molecular markers from the target organ or exfoliation of tumor cells into the urine, bladder cancer is particularly useful to study diagnostic markers. To improve the overall quality of marker research, future developments should focus on networks of studies and tissue banks according to uniform legal, ethical, methodological, and technical standards. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. © 2013.

Chemotherapy and Cardiotoxicity in Hematologic Malignancies.

PubMed

Stellitano, Antonio; Fedele, Roberta; Barilla, Santina; Iaria, Antonino; Rao, Carmelo Massimiliano; Martino, Massimo

2017-01-01

Antineoplastic agents affect the cardiovascular system, and the incidence of cardiotoxicity is continuously growing in patients with hematologic malignancies and treated with antineoplastic therapy. In this mini-review, we analyzed existing literature which evaluates the likelihood of cardiotoxicity related to the main agents employed in the treatment of hematologic malignancies. There is a significant need to optimize the early identification of patients who are at risk of cardiotoxicity. The conventional echocardiographic measurements used to detect cardiac alterations, such as LVEF, fractional shortening, diameters and volumes, allow only a late diagnosis of cardiac dysfunction, which might be already irreversible. The early identification of patients at risk for rapid progression towards irreversible cardiac failure has a primary purpose, the opportunity for them to benefit from early preventive and therapeutic measures. A useful imaging technique that points in this direction detecting subclinical LVD may be the speckle tracking echocardiography, that has demonstrated a previous detection of myocardial contractile dysfunction compared to the traditional left ventricular ejection fraction. In this view, the discovery of new biomarkers to identify patients at a high risk for the development of these complications is another priority. Cardiotoxicity induced by anticancer drugs is always the outcome of several concurrent factors. It is plausible that an asymptomatic dysfunction precedes clinical events. During this asymptomatic phase, an early treatment prepares the patient for cardiovascular "safety" conditions; on the other hand, a late or missing treatment paves the ground for the development of future cardiac events. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Use of failure mode and effects analysis for proactive identification of communication and handoff failures from organ procurement to transplantation.

PubMed

Steinberger, Dina M; Douglas, Stephen V; Kirschbaum, Mark S

2009-09-01

A multidisciplinary team from the University of Wisconsin Hospital and Clinics transplant program used failure mode and effects analysis to proactively examine opportunities for communication and handoff failures across the continuum of care from organ procurement to transplantation. The team performed a modified failure mode and effects analysis that isolated the multiple linked, serial, and complex information exchanges occurring during the transplantation of one solid organ. Failure mode and effects analysis proved effective for engaging a diverse group of persons who had an investment in the outcome in analysis and discussion of opportunities to improve the system's resilience for avoiding errors during a time-pressured and complex process.

[Prevalence of vaginal candidiasis in pregnant women. Identification of yeasts and susceptibility to antifungal agents].

PubMed

García Heredia, M; García, S D; Copolillo, E F; Cora Eliseth, M; Barata, A D; Vay, C A; de Torres, R A; Tiraboschi, N; Famiglietti, A M R

2006-01-01

Pregnant women are more susceptible to both vaginal colonization and infection by yeast. Our objectives were to determine the prevalence in pregnant women of yeasts isolated from vaginal exudates and their susceptibility to current antifungal drugs. A total of 493 patients was studied between December 1998 and February 2000. The prevalence of Candida spp. was 28% (Candida albicans 90.4%; Candida glabrata 6.3%; Candida parapsilosis 1.1%, Candida kefyr 1.1 %; unidentified species 1.1 %). The diffusion test in Shadomy agar was employed to determine the susceptibility to fluconazole, ketoconazole, itraconazole and nistatine. All C. albicans, C. kefyr and C. parapsilosis isolates were susceptible in vitro to the antifungal agents tested, while 1 in 6 C. glabrata isolates showed resistance to azole drugs; all strains were susceptible to nistatine. In pregnant women, C. albicans was the yeast most frequently isolated from vaginal exudates; it continues to be highly susceptible to antifungal drugs. Azole resistance was detected only among C. glabrata isolates. Identification to the species level is recommended, specially in cases of treatment failure and recurrent or chronic infection.

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).

PubMed

Sudarshan, Vidya K; Acharya, U Rajendra; Ng, E Y K; Tan, Ru San; Chou, Siaw Meng; Ghista, Dhanjoo N

2016-04-01

Early expansion of infarcted zone after Acute Myocardial Infarction (AMI) has serious short and long-term consequences and contributes to increased mortality. Thus, identification of moderate and severe phases of AMI before leading to other catastrophic post-MI medical condition is most important for aggressive treatment and management. Advanced image processing techniques together with robust classifier using two-dimensional (2D) echocardiograms may aid for automated classification of the extent of infarcted myocardium. Therefore, this paper proposes novel algorithms namely Curvelet Transform (CT) and Local Configuration Pattern (LCP) for an automated detection of normal, moderately infarcted and severely infarcted myocardium using 2D echocardiograms. The methodology extracts the LCP features from CT coefficients of echocardiograms. The obtained features are subjected to Marginal Fisher Analysis (MFA) dimensionality reduction technique followed by fuzzy entropy based ranking method. Different classifiers are used to differentiate ranked features into three classes normal, moderate and severely infarcted based on the extent of damage to myocardium. The developed algorithm has achieved an accuracy of 98.99%, sensitivity of 98.48% and specificity of 100% for Support Vector Machine (SVM) classifier using only six features. Furthermore, we have developed an integrated index called Myocardial Infarction Risk Index (MIRI) to detect the normal, moderately and severely infarcted myocardium using a single number. The proposed system may aid the clinicians in faster identification and quantification of the extent of infarcted myocardium using 2D echocardiogram. This system may also aid in identifying the person at risk of developing heart failure based on the extent of infarcted myocardium. Copyright © 2016 Elsevier Ltd. All rights reserved.

S-nitrosothiols and the S-nitrosoproteome of the cardiovascular system.

PubMed

Maron, Bradley A; Tang, Shiow-Shih; Loscalzo, Joseph

2013-01-20

Since their discovery in the early 1990's, S-nitrosylated proteins have been increasingly recognized as important determinants of many biochemical processes. Specifically, S-nitrosothiols in the cardiovascular system exert many actions, including promoting vasodilation, inhibiting platelet aggregation, and regulating Ca(2+) channel function that influences myocyte contractility and electrophysiologic stability. Contemporary developments in liquid chromatography-mass spectrometry methods, the development of biotin- and His-tag switch assays, and the availability of cyanide dye-labeling for S-nitrosothiol detection in vitro have increased significantly the identification of a number of cardiovascular protein targets of S-nitrosylation in vivo. Recent analyses using modern S-nitrosothiol detection techniques have revealed the mechanistic significance of S-nitrosylation to the pathophysiology of numerous cardiovascular diseases, including essential hypertension, pulmonary hypertension, ischemic heart disease, stroke, and congestive heart failure, among others. Despite enhanced insight into S-nitrosothiol biochemistry, translating these advances into beneficial pharmacotherapies for patients with cardiovascular diseases remains a primary as-yet unmet goal for investigators within the field.

Syndromic surveillance for health information system failures: a feasibility study

PubMed Central

Ong, Mei-Sing; Magrabi, Farah; Coiera, Enrico

2013-01-01

Objective To explore the applicability of a syndromic surveillance method to the early detection of health information technology (HIT) system failures. Methods A syndromic surveillance system was developed to monitor a laboratory information system at a tertiary hospital. Four indices were monitored: (1) total laboratory records being created; (2) total records with missing results; (3) average serum potassium results; and (4) total duplicated tests on a patient. The goal was to detect HIT system failures causing: data loss at the record level; data loss at the field level; erroneous data; and unintended duplication of data. Time-series models of the indices were constructed, and statistical process control charts were used to detect unexpected behaviors. The ability of the models to detect HIT system failures was evaluated using simulated failures, each lasting for 24 h, with error rates ranging from 1% to 35%. Results In detecting data loss at the record level, the model achieved a sensitivity of 0.26 when the simulated error rate was 1%, while maintaining a specificity of 0.98. Detection performance improved with increasing error rates, achieving a perfect sensitivity when the error rate was 35%. In the detection of missing results, erroneous serum potassium results and unintended repetition of tests, perfect sensitivity was attained when the error rate was as small as 5%. Decreasing the error rate to 1% resulted in a drop in sensitivity to 0.65–0.85. Conclusions Syndromic surveillance methods can potentially be applied to monitor HIT systems, to facilitate the early detection of failures. PMID:23184193

Risk analysis of analytical validations by probabilistic modification of FMEA.

PubMed

Barends, D M; Oldenhof, M T; Vredenbregt, M J; Nauta, M J

2012-05-01

Risk analysis is a valuable addition to validation of an analytical chemistry process, enabling not only detecting technical risks, but also risks related to human failures. Failure Mode and Effect Analysis (FMEA) can be applied, using a categorical risk scoring of the occurrence, detection and severity of failure modes, and calculating the Risk Priority Number (RPN) to select failure modes for correction. We propose a probabilistic modification of FMEA, replacing the categorical scoring of occurrence and detection by their estimated relative frequency and maintaining the categorical scoring of severity. In an example, the results of traditional FMEA of a Near Infrared (NIR) analytical procedure used for the screening of suspected counterfeited tablets are re-interpretated by this probabilistic modification of FMEA. Using this probabilistic modification of FMEA, the frequency of occurrence of undetected failure mode(s) can be estimated quantitatively, for each individual failure mode, for a set of failure modes, and the full analytical procedure. Copyright © 2012 Elsevier B.V. All rights reserved.

Assuring reliability program effectiveness.

NASA Technical Reports Server (NTRS)

Ball, L. W.

1973-01-01

An attempt is made to provide simple identification and description of techniques that have proved to be most useful either in developing a new product or in improving reliability of an established product. The first reliability task is obtaining and organizing parts failure rate data. Other tasks are parts screening, tabulation of general failure rates, preventive maintenance, prediction of new product reliability, and statistical demonstration of achieved reliability. Five principal tasks for improving reliability involve the physics of failure research, derating of internal stresses, control of external stresses, functional redundancy, and failure effects control. A final task is the training and motivation of reliability specialist engineers.

DC-to-AC inverter ratio failure detector

NASA Technical Reports Server (NTRS)

Ebersole, T. J.; Andrews, R. E.

1975-01-01

Failure detection technique is based upon input-output ratios, which is independent of inverter loading. Since inverter has fixed relationship between V-in/V-out and I-in/I-out, failure detection criteria are based on this ratio, which is simply inverter transformer turns ratio, K, equal to primary turns divided by secondary turns.

Impaired face detection may explain some but not all cases of developmental prosopagnosia.

PubMed

Dalrymple, Kirsten A; Duchaine, Brad

2016-05-01

Developmental prosopagnosia (DP) is defined by severe face recognition difficulties due to the failure to develop the visual mechanisms for processing faces. The two-process theory of face recognition (Morton & Johnson, 1991) implies that DP could result from a failure of an innate face detection system; this failure could prevent an individual from then tuning higher-level processes for face recognition (Johnson, 2005). Work with adults indicates that some individuals with DP have normal face detection whereas others are impaired. However, face detection has not been addressed in children with DP, even though their results may be especially informative because they have had less opportunity to develop strategies that could mask detection deficits. We tested the face detection abilities of seven children with DP. Four were impaired at face detection to some degree (i.e. abnormally slow, or failed to find faces) while the remaining three children had normal face detection. Hence, the cases with impaired detection are consistent with the two-process account suggesting that DP could result from a failure of face detection. However, the cases with normal detection implicate a higher-level origin. The dissociation between normal face detection and impaired identity perception also indicates that these abilities depend on different neurocognitive processes. © 2015 John Wiley & Sons Ltd.

Timing of left heart base descent in dogs with dilated cardiomyopathy and normal dogs.

PubMed

Simpson, Kerry E; Devine, Bryan C; Woolley, Richard; Corcoran, Brendan M; French, Anne T

2008-01-01

The identification and assessment of myocardial failure in canine idiopathic dilated cardiomyopathy (DCM) is achieved using a variety of two-dimensional and Doppler echocardiographic techniques. More recently, the availability of tissue Doppler imaging (TDI) has raised the potential for development of new ways of more accurately identifying a disease phenotype. Nevertheless, TDI has not been universally adapted to veterinary clinical cardiology primarily because of the lack of information on its utility in diagnosis. We assessed the application of timing of left heart base descent using TDI in the identification of differences between DCM and normal dogs. The times from the onset of the QRS complex on a simultaneously recorded electrocardiograph to the onset (Q--S'), peak (Q--peak S'), and end (Q--end S') of the systolic velocity peak were measured in the interventricular septum (IVS) and the left ventricular free wall. The duration of S' was also calculated. The Q--S' (FW), Q--end S' (FW), and duration S' (FW) were correlated with ejection fraction in the diseased group (P < 0.05). In addition, Q--S', Q--peak S', Q--end S', and the peak S' velocity were prolonged in the diseased dogs at both the free wall and in the IVS (P < 0.01). The duration of S' was unaffected by disease status. These findings provide insight into the electromechanical uncoupling that occurs in canine DCM and identifies new TDI parameters that can be added to the range of Doppler and echocardiographic parameters used for detecting myocardial failure in the dog.

A dual-mode generalized likelihood ratio approach to self-reorganizing digital flight control system design

NASA Technical Reports Server (NTRS)

Bueno, R.; Chow, E.; Gershwin, S. B.; Willsky, A. S.

1975-01-01

The research is reported on the problems of failure detection and reliable system design for digital aircraft control systems. Failure modes, cross detection probability, wrong time detection, application of performance tools, and the GLR computer package are discussed.

Evaluation of a fault tolerant system for an integrated avionics sensor configuration with TSRV flight data

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Godiwala, P. M.

1985-01-01

The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.

Impact of the timing of hepatitis B virus identification and anti-hepatitis B virus therapy initiation on the risk of adverse liver outcomes for patients receiving cancer therapy.

PubMed

Hwang, Jessica P; Suarez-Almazor, Maria E; Cantor, Scott B; Barbo, Andrea; Lin, Heather Y; Ahmed, Sairah; Chavez-MacGregor, Mariana; Donato-Santana, Christian; Eng, Cathy; Ferrajoli, Alessandra; Fisch, Michael J; McLaughlin, Peter; Simon, George R; Rondon, Gabriela; Shpall, Elizabeth J; Lok, Anna S

2017-09-01

Data on the incidence of adverse liver outcomes are limited for cancer patients with chronic (hepatitis B surface antigen [HBsAg]-positive/hepatitis B core antibody [anti-HBc]-positive) or past (HBsAg-negative/anti-HBc-positive) hepatitis B virus (HBV) after chemotherapy. This study was aimed at determining the impact of test timing and anti-HBV therapy on adverse liver outcomes in these patients. Patients with solid or hematologic malignancies who received chemotherapy between 2004 and 2011 were retrospectively studied. HBV testing and anti-HBV therapy were defined as early at the initiation of cancer therapy and as late after initiation. Outcomes included hepatitis flares, hepatic impairment, liver failure, and death. Time-to-event analysis was used to determine incidence, and multivariate hazard models were used to determine predictors of outcomes. There were 18,688 study patients (80.4% with solid tumors). The prevalence of chronic HBV was 1.1% (52 of 4905), and the prevalence of past HBV was 7.1% (350 of 4905). Among patients with solid tumors, late identification of chronic HBV was associated with a higher risk of hepatitis flare (hazard ratio [HR], 4.02; 95% confidence interval [CI], 1.26-12.86), hepatic impairment (HR, 8.48; 95% CI, 1.86-38.66), liver failure (HR, 9.38; 95% CI, 1.50-58.86), and death (HR, 3.90; 95% CI, 1.19-12.83) in comparison with early identification. Among patients with hematologic malignancies and chronic HBV, the risk of death was 7.8 (95% CI, 1.73-35.27) times higher for persons with late initiation of anti-HBV therapy versus early initiation. Patients with late identification of chronic HBV had late or no anti-HBV therapy. Chronic HBV predicted liver failure in patients with solid or hematologic malignancies, whereas male sex and late identification were predictors for patients with solid tumors. Early identification correlates with early anti-HBV therapy and reduces the risk of liver failure and death in chronic HBV patients receiving chemotherapy. Cancer 2017;123:3367-76. © 2017 American Cancer Society. © 2017 American Cancer Society.

Creating and evaluating a data-driven curriculum for central venous catheter placement.

PubMed

Duncan, James R; Henderson, Katherine; Street, Mandie; Richmond, Amy; Klingensmith, Mary; Beta, Elio; Vannucci, Andrea; Murray, David

2010-09-01

Central venous catheter placement is a common procedure with a high incidence of error. Other fields requiring high reliability have used Failure Mode and Effects Analysis (FMEA) to prioritize quality and safety improvement efforts. To use FMEA in the development of a formal, standardized curriculum for central venous catheter training. We surveyed interns regarding their prior experience with central venous catheter placement. A multidisciplinary team used FMEA to identify high-priority failure modes and to develop online and hands-on training modules to decrease the frequency, diminish the severity, and improve the early detection of these failure modes. We required new interns to complete the modules and tracked their progress using multiple assessments. Survey results showed new interns had little prior experience with central venous catheter placement. Using FMEA, we created a curriculum that focused on planning and execution skills and identified 3 priority topics: (1) retained guidewires, which led to training on handling catheters and guidewires; (2) improved needle access, which prompted the development of an ultrasound training module; and (3) catheter-associated bloodstream infections, which were addressed through training on maximum sterile barriers. Each module included assessments that measured progress toward recognition and avoidance of common failure modes. Since introducing this curriculum, the number of retained guidewires has fallen more than 4-fold. Rates of catheter-associated infections have not yet declined, and it will take time before ultrasound training will have a measurable effect. The FMEA provided a process for curriculum development. Precise definitions of failure modes for retained guidewires facilitated development of a curriculum that contributed to a dramatic decrease in the frequency of this complication. Although infections and access complications have not yet declined, failure mode identification, curriculum development, and monitored implementation show substantial promise for improving patient safety during placement of central venous catheters.

22nd Annual Logistics Conference and Exhibition

DTIC Science & Technology

2006-04-20

Prognostics & Health Management at GE Dr. Piero P.Bonissone Industrial AI Lab GE Global Research NCD Select detection model Anomaly detection results...Mode 213 x Failure mode histogram 2130014 Anomaly detection from event-log data Anomaly detection from event-log data Diagnostics/ Prognostics Using...Failure Monitoring & AssessmentTactical C4ISR Sense Respond 7 •Diagnostics, Prognostics and health management

Weak fault detection and health degradation monitoring using customized standard multiwavelets

NASA Astrophysics Data System (ADS)

Yuan, Jing; Wang, Yu; Peng, Yizhen; Wei, Chenjun

2017-09-01

Due to the nonobvious symptoms contaminated by a large amount of background noise, it is challenging to beforehand detect and predictively monitor the weak faults for machinery security assurance. Multiwavelets can act as adaptive non-stationary signal processing tools, potentially viable for weak fault diagnosis. However, the signal-based multiwavelets suffer from such problems as the imperfect properties missing the crucial orthogonality, the decomposition distortion impossibly reflecting the relationships between the faults and signatures, the single objective optimization and independence for fault prognostic. Thus, customized standard multiwavelets are proposed for weak fault detection and health degradation monitoring, especially the weak fault signature quantitative identification. First, the flexible standard multiwavelets are designed using the construction method derived from scalar wavelets, seizing the desired properties for accurate detection of weak faults and avoiding the distortion issue for feature quantitative identification. Second, the multi-objective optimization combined three dimensionless indicators of the normalized energy entropy, normalized singular entropy and kurtosis index is introduced to the evaluation criterions, and benefits for selecting the potential best basis functions for weak faults without the influence of the variable working condition. Third, an ensemble health indicator fused by the kurtosis index, impulse index and clearance index of the original signal along with the normalized energy entropy and normalized singular entropy by the customized standard multiwavelets is achieved using Mahalanobis distance to continuously monitor the health condition and track the performance degradation. Finally, three experimental case studies are implemented to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed method can quantitatively identify the fault signature of a slight rub on the inner race of a locomotive bearing, effectively detect and locate the potential failure from a complicated epicyclic gear train and successfully reveal the fault development and performance degradation of a test bearing in the lifetime.

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

NASA Technical Reports Server (NTRS)

Drake, R. L.; Duvoisin, P. F.; Asthana, A.; Mather, T. W.

1971-01-01

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

A Review of Transmission Diagnostics Research at NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Zakajsek, James J.

1994-01-01

This paper presents a summary of the transmission diagnostics research work conducted at NASA Lewis Research Center over the last four years. In 1990, the Transmission Health and Usage Monitoring Research Team at NASA Lewis conducted a survey to determine the critical needs of the diagnostics community. Survey results indicated that experimental verification of gear and bearing fault detection methods, improved fault detection in planetary systems, and damage magnitude assessment and prognostics research were all critical to a highly reliable health and usage monitoring system. In response to this, a variety of transmission fault detection methods were applied to experimentally obtained fatigue data. Failure modes of the fatigue data include a variety of gear pitting failures, tooth wear, tooth fracture, and bearing spalling failures. Overall results indicate that, of the gear fault detection techniques, no one method can successfully detect all possible failure modes. The more successful methods need to be integrated into a single more reliable detection technique. A recently developed method, NA4, in addition to being one of the more successful gear fault detection methods, was also found to exhibit damage magnitude estimation capabilities.

Performance analysis of a fault inferring nonlinear detection system algorithm with integrated avionics flight data

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.

1985-01-01

This paper presents the performance analysis results of a fault inferring nonlinear detection system (FINDS) using integrated avionics sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. First, an overview of the FINDS algorithm structure is given. Then, aircraft state estimate time histories and statistics for the flight data sensors are discussed. This is followed by an explanation of modifications made to the detection and decision functions in FINDS to improve false alarm and failure detection performance. Next, the failure detection and false alarm performance of the FINDS algorithm are analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minutes of flight data. Results indicate that the detection speed, failure level estimation, and false alarm performance show a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed is faster for filter measurement sensors such as MLS than for filter input sensors such as flight control accelerometers. Finally, the progress in modifications of the FINDS algorithm design to accommodate flight computer constraints is discussed.

Application of failure mode and effects analysis to treatment planning in scanned proton beam radiotherapy

PubMed Central

2013-01-01

Background A multidisciplinary and multi-institutional working group applied the Failure Mode and Effects Analysis (FMEA) approach to the actively scanned proton beam radiotherapy process implemented at CNAO (Centro Nazionale di Adroterapia Oncologica), aiming at preventing accidental exposures to the patient. Methods FMEA was applied to the treatment planning stage and consisted of three steps: i) identification of the involved sub-processes; ii) identification and ranking of the potential failure modes, together with their causes and effects, using the risk probability number (RPN) scoring system, iii) identification of additional safety measures to be proposed for process quality and safety improvement. RPN upper threshold for little concern of risk was set at 125. Results Thirty-four sub-processes were identified, twenty-two of them were judged to be potentially prone to one or more failure modes. A total of forty-four failure modes were recognized, 52% of them characterized by an RPN score equal to 80 or higher. The threshold of 125 for RPN was exceeded in five cases only. The most critical sub-process appeared related to the delineation and correction of artefacts in planning CT data. Failures associated to that sub-process were inaccurate delineation of the artefacts and incorrect proton stopping power assignment to body regions. Other significant failure modes consisted of an outdated representation of the patient anatomy, an improper selection of beam direction and of the physical beam model or dose calculation grid. The main effects of these failures were represented by wrong dose distribution (i.e. deviating from the planned one) delivered to the patient. Additional strategies for risk mitigation, easily and immediately applicable, consisted of a systematic information collection about any known implanted prosthesis directly from each patient and enforcing a short interval time between CT scan and treatment start. Moreover, (i) the investigation of dedicated CT image reconstruction algorithms, (ii) further evaluation of treatment plan robustness and (iii) implementation of independent methods for dose calculation (such as Monte Carlo simulations) may represent novel solutions to increase patient safety. Conclusions FMEA is a useful tool for prospective evaluation of patient safety in proton beam radiotherapy. The application of this method to the treatment planning stage lead to identify strategies for risk mitigation in addition to the safety measures already adopted in clinical practice. PMID:23705626

Orion Burn Management, Nominal and Response to Failures

NASA Technical Reports Server (NTRS)

Odegard, Ryan; Goodman, John L.; Barrett, Charles P.; Pohlkamp, Kara; Robinson, Shane

2016-01-01

An approach for managing Orion on-orbit burn execution is described for nominal and failure response scenarios. The burn management strategy for Orion takes into account per-burn variations in targeting, timing, and execution; crew and ground operator intervention and overrides; defined burn failure triggers and responses; and corresponding on-board software sequencing functionality. Burn-to- burn variations are managed through the identification of specific parameters that may be updated for each progressive burn. Failure triggers and automatic responses during the burn timeframe are defined to provide safety for the crew in the case of vehicle failures, along with override capabilities to ensure operational control of the vehicle. On-board sequencing software provides the timeline coordination for performing the required activities related to targeting, burn execution, and responding to burn failures.

Triplexer Monitor Design for Failure Detection in FTTH System

NASA Astrophysics Data System (ADS)

Fu, Minglei; Le, Zichun; Hu, Jinhua; Fei, Xia

2012-09-01

Triplexer was one of the key components in FTTH systems, which employed an analog overlay channel for video broadcasting in addition to bidirectional digital transmission. To enhance the survivability of triplexer as well as the robustness of FTTH system, a multi-ports device named triplexer monitor was designed and realized, by which failures at triplexer ports can be detected and localized. Triplexer monitor was composed of integrated circuits and its four input ports were connected with the beam splitter whose power division ratio was 95∶5. By means of detecting the sampled optical signal from the beam splitters, triplexer monitor tracked the status of the four ports in triplexer (e.g. 1310 nm, 1490 nm, 1550 nm and com ports). In this paper, the operation scenario of the triplexer monitor with external optical devices was addressed. And the integrated circuit structure of the triplexer monitor was also given. Furthermore, a failure localization algorithm was proposed, which based on the state transition diagram. In order to measure the failure detection and localization time under the circumstance of different failed ports, an experimental test-bed was built. Experiment results showed that the detection time for the failure at 1310 nm port by the triplexer monitor was less than 8.20 ms. For the failure at 1490 nm or 1550 nm port it was less than 8.20 ms and for the failure at com port it was less than 7.20 ms.

Detection of Failure in Asynchronous Motor Using Soft Computing Method

NASA Astrophysics Data System (ADS)

Vinoth Kumar, K.; Sony, Kevin; Achenkunju John, Alan; Kuriakose, Anto; John, Ano P.

2018-04-01

This paper investigates the stator short winding failure of asynchronous motor also their effects on motor current spectrums. A fuzzy logic approach i.e., model based technique possibly will help to detect the asynchronous motor failure. Actually, fuzzy logic similar to humanoid intelligent methods besides expected linguistic empowering inferences through vague statistics. The dynamic model is technologically advanced for asynchronous motor by means of fuzzy logic classifier towards investigate the stator inter turn failure in addition open phase failure. A hardware implementation was carried out with LabVIEW for the online-monitoring of faults.

A novel strategy for rapid detection of NT-proBNP

NASA Astrophysics Data System (ADS)

Cui, Qiyao; Sun, Honghao; Zhu, Hui

2017-09-01

In order to establish a simple, rapid, sensitive, and specific quantitative assay to detect the biomarkers of heart failure, in this study, biotin-streptavidin technology was employed with fluorescence immunochromatographic assay to detect the concentration of the biomarkers in serum, and this method was applied to detect NT-proBNP, which is valuable for diagnostic evaluation of heart failure.

Sensor failure detection for jet engines

NASA Technical Reports Server (NTRS)

Beattie, E. C.; Laprad, R. F.; Akhter, M. M.; Rock, S. M.

1983-01-01

Revisions to the advanced sensor failure detection, isolation, and accommodation (DIA) algorithm, developed under the sensor failure detection system program were studied to eliminate the steady state errors due to estimation filter biases. Three algorithm revisions were formulated and one revision for detailed evaluation was chosen. The selected version modifies the DIA algorithm to feedback the actual sensor outputs to the integral portion of the control for the nofailure case. In case of a failure, the estimates of the failed sensor output is fed back to the integral portion. The estimator outputs are fed back to the linear regulator portion of the control all the time. The revised algorithm is evaluated and compared to the baseline algorithm developed previously.

Integrated failure detection and management for the Space Station Freedom external active thermal control system

NASA Technical Reports Server (NTRS)

Mesloh, Nick; Hill, Tim; Kosyk, Kathy

1993-01-01

This paper presents the integrated approach toward failure detection, isolation, and recovery/reconfiguration to be used for the Space Station Freedom External Active Thermal Control System (EATCS). The on-board and on-ground diagnostic capabilities of the EATCS are discussed. Time and safety critical features, as well as noncritical failures, and the detection coverage for each provided by existing capabilities are reviewed. The allocation of responsibility between on-board software and ground-based systems, to be shown during ground testing at the Johnson Space Center, is described. Failure isolation capabilities allocated to the ground include some functionality originally found on orbit but moved to the ground to reduce on-board resource requirements. Complex failures requiring the analysis of multiple external variables, such as environmental conditions, heat loads, or station attitude, are also allocated to ground personnel.

49 CFR Appendix F to Part 236 - Minimum Requirements of FRA Directed Independent Third-Party Assessment of PTC System Safety...

Code of Federal Regulations, 2010 CFR

2010-10-01

..., national, or international standards. (f) The reviewer shall analyze all Fault Tree Analyses (FTA), Failure... cited by the reviewer; (4) Identification of any documentation or information sought by the reviewer...) Identification of the hardware and software verification and validation procedures for the PTC system's safety...

Identification and Intervention Strategies for Preschool, Kindergarten, First and Second Grade Children at Risk for Reading Difficulties.

ERIC Educational Resources Information Center

Gray, Elizabeth

Studies are reviewed on early identification and remediation of "at risk" preschool, 1st-, and 2nd-grade children to prevent possible future reading failure. The research review identifies essential characteristics of reading and reading acquisition, explains difficulties in learning how to read, explores variables within the individual…

Fatigue crack identification method based on strain amplitude changing

NASA Astrophysics Data System (ADS)

Guo, Tiancai; Gao, Jun; Wang, Yonghong; Xu, Youliang

2017-09-01

Aiming at the difficulties in identifying the location and time of crack initiation in the castings of helicopter transmission system during fatigue tests, by introducing the classification diagnostic criteria of similar failure mode to find out the similarity of fatigue crack initiation among castings, an engineering method and quantitative criterion for detecting fatigue cracks based on strain amplitude changing is proposed. This method is applied on the fatigue test of a gearbox housing, whose results indicates: during the fatigue test, the system alarms when SC strain meter reaches the quantitative criterion. The afterwards check shows that a fatigue crack less than 5mm is found at the corresponding location of SC strain meter. The test result proves that the method can provide accurate test data for strength life analysis.

Chemical hazards database and detection system for Microgravity and Materials Processing Facility (MMPF)

NASA Technical Reports Server (NTRS)

Steele, Jimmy; Smith, Robert E.

1991-01-01

The ability to identify contaminants associated with experiments and facilities is directly related to the safety of the Space Station. A means of identifying these contaminants has been developed through this contracting effort. The delivered system provides a listing of the materials and/or chemicals associated with each facility, information as to the contaminant's physical state, a list of the quantity and/or volume of each suspected contaminant, a database of the toxicological hazards associated with each contaminant, a recommended means of rapid identification of the contaminants under operational conditions, a method of identifying possible failure modes and effects analysis associated with each facility, and a fault tree-type analysis that will provide a means of identifying potential hazardous conditions related to future planned missions.

Stimulus recognition occurs under high perceptual load: Evidence from correlated flankers.

PubMed

Cosman, Joshua D; Mordkoff, J Toby; Vecera, Shaun P

2016-12-01

A dominant account of selective attention, perceptual load theory, proposes that when attentional resources are exhausted, task-irrelevant information receives little attention and goes unrecognized. However, the flanker effect-typically used to assay stimulus identification-requires an arbitrary mapping between a stimulus and a response. We looked for failures of flanker identification by using a more-sensitive measure that does not require arbitrary stimulus-response mappings: the correlated flankers effect. We found that flanking items that were task-irrelevant but that correlated with target identity produced a correlated flanker effect. Participants were faster on trials in which the irrelevant flanker had previously correlated with the target than when it did not. Of importance, this correlated flanker effect appeared regardless of perceptual load, occurring even in high-load displays that should have abolished flanker identification. Findings from a standard flanker task replicated the basic perceptual load effect, with flankers not affecting response times under high perceptual load. Our results indicate that task-irrelevant information can be processed to a high level (identification), even under high perceptual load. This challenges a strong account of high perceptual load effects that hypothesizes complete failures of stimulus identification under high perceptual load. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Aircraft control surface failure detection and isolation using the OSGLR test. [orthogonal series generalized likelihood ratio

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Motyka, P.; Wagner, E.; Hall, S. R.

1986-01-01

The performance of the orthogonal series generalized likelihood ratio (OSGLR) test in detecting and isolating commercial aircraft control surface and actuator failures is evaluated. A modification to incorporate age-weighting which significantly reduces the sensitivity of the algorithm to modeling errors is presented. The steady-state implementation of the algorithm based on a single linear model valid for a cruise flight condition is tested using a nonlinear aircraft simulation. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection and isolation performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling on dynamic pressure and flap deflection is examined. Based on this testing, the OSGLR algorithm should be capable of detecting control surface failures that would affect the safe operation of a commercial aircraft. Isolation may be difficult if there are several surfaces which produce similar effects on the aircraft. Extending the algorithm over the entire operating envelope of a commercial aircraft appears feasible.

48 CFR 52.223-3 - Hazardous Material Identification and Material Safety Data.

Code of Federal Regulations, 2010 CFR

2010-10-01

... offeror is the actual manufacturer of these items. Failure to submit the Material Safety Data Sheet prior... data. (f) Neither the requirements of this clause nor any act or failure to act by the Government shall... resistant envelope. [56 FR 55375, Oct. 25, 1991, as amended at 60 FR 34740, July 3, 1995; 62 FR 238, Jan. 2...

Visual Detection and Identification Are Not the Same: Evidence from Psychophysics and fMRI

ERIC Educational Resources Information Center

Straube, Sirko; Fahle, Manfred

2011-01-01

Sometimes object detection as opposed to identification is sufficient to initiate the appropriate action. To explore the neural origin of behavioural differences between the two tasks, we combine psychophysical measurements and fMRI, specifically contrasting shape detection versus identification of a figure. This figure consisted of Gabor elements…

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

Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less

A Fault Tolerant System for an Integrated Avionics Sensor Configuration

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Lancraft, R. E.

1984-01-01

An aircraft sensor fault tolerant system methodology for the Transport Systems Research Vehicle in a Microwave Landing System (MLS) environment is described. The fault tolerant system provides reliable estimates in the presence of possible failures both in ground-based navigation aids, and in on-board flight control and inertial sensors. Sensor failures are identified by utilizing the analytic relationships between the various sensors arising from the aircraft point mass equations of motion. The estimation and failure detection performance of the software implementation (called FINDS) of the developed system was analyzed on a nonlinear digital simulation of the research aircraft. Simulation results showing the detection performance of FINDS, using a dual redundant sensor compliment, are presented for bias, hardover, null, ramp, increased noise and scale factor failures. In general, the results show that FINDS can distinguish between normal operating sensor errors and failures while providing an excellent detection speed for bias failures in the MLS, indicated airspeed, attitude and radar altimeter sensors.

Identification of the Parameters of Menétrey -Willam Failure Surface of Calcium Silicate Units

NASA Astrophysics Data System (ADS)

Radosław, Jasiński

2017-10-01

The identification of parameters of Menétrey-Willamsurface made of concrete, masonry or autoclaved aerated concrete is not complicated. It is much more difficult to identify failure parameters of masonry units with cavities. This paper describes the concept of identifying the parameters of Menétrey-Willam failure surface (M-W-3) with reference to masonry units with vertical cavities. The M-W-3 surface is defined by uniaxial compressive strength fc, uniaxial tensile strength ft and eccentricity of elliptical function e. A test stand was built to identify surface parameters. It was used to test behaviour of masonry units under triaxial stress and conduct tests on whole masonry units in the uniaxial state. Results from tests on tens of silicate masonry units are presented in the Haigh-Westergaard (H-W) space. Statistical analyses were used to identify the shape of surface meridian, and then to determine eccentricity of the elliptical function.

Speedy routing recovery protocol for large failure tolerance in wireless sensor networks.

PubMed

Lee, Joa-Hyoung; Jung, In-Bum

2010-01-01

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols.

Comparing culture and molecular methods for the identification of microorganisms involved in necrotizing soft tissue infections.

PubMed

Rudkjøbing, Vibeke Børsholt; Thomsen, Trine Rolighed; Xu, Yijuan; Melton-Kreft, Rachael; Ahmed, Azad; Eickhardt, Steffen; Bjarnsholt, Thomas; Poulsen, Steen Seier; Nielsen, Per Halkjær; Earl, Joshua P; Ehrlich, Garth D; Moser, Claus

2016-11-08

Necrotizing soft tissue infections (NSTIs) are a group of infections affecting all soft tissues. NSTI involves necrosis of the afflicted tissue and is potentially life threatening due to major and rapid destruction of tissue, which often leads to septic shock and organ failure. The gold standard for identification of pathogens is culture; however molecular methods for identification of microorganisms may provide a more rapid result and may be able to identify additional microorganisms that are not detected by culture. In this study, tissue samples (n = 20) obtained after debridement of 10 patients with NSTI were analyzed by standard culture, fluorescence in situ hybridization (FISH) and multiple molecular methods. The molecular methods included analysis of microbial diversity by 1) direct 16S and D2LSU rRNA gene Microseq 2) construction of near full-length 16S rRNA gene clone libraries with subsequent Sanger sequencing for most samples, 3) the Ibis T5000 biosensor and 4) 454-based pyrosequencing. Furthermore, quantitative PCR (qPCR) was used to verify and determine the relative abundance of Streptococcus pyogenes in samples. For 70 % of the surgical samples it was possible to identify microorganisms by culture. Some samples did not result in growth (presumably due to administration of antimicrobial therapy prior to sampling). The molecular methods identified microorganisms in 90 % of the samples, and frequently detected additional microorganisms when compared to culture. Although the molecular methods generally gave concordant results, our results indicate that Microseq may misidentify or overlook microorganisms that can be detected by other molecular methods. Half of the patients were found to be infected with S. pyogenes, but several atypical findings were also made including infection by a) Acinetobacter baumannii, b) Streptococcus pneumoniae, and c) fungi, mycoplasma and Fusobacterium necrophorum. The study emphasizes that many pathogens can be involved in NSTIs, and that no specific "NSTI causing" combination of species exists. This means that clinicians should be prepared to diagnose and treat any combination of microbial pathogens. Some of the tested molecular methods offer a faster turnaround time combined with a high specificity, which makes supplemental use of such methods attractive for identification of microorganisms, especially for fulminant life-threatening infections such as NSTI.

A dual-mode generalized likelihood ratio approach to self-reorganizing digital flight control system design

NASA Technical Reports Server (NTRS)

1976-01-01

Analytic techniques have been developed for detecting and identifying abrupt changes in dynamic systems. The GLR technique monitors the output of the Kalman filter and searches for the time that the failure occured, thus allowing it to be sensitive to new data and consequently increasing the chances for fast system recovery following detection of a failure. All failure detections are based on functional redundancy. Performance tests of the F-8 aircraft flight control system and computerized modelling of the technique are presented.

Bearing system

DOEpatents

Kapich, Davorin D.

1987-01-01

A bearing system includes backup bearings for supporting a rotating shaft upon failure of primary bearings. In the preferred embodiment, the backup bearings are rolling element bearings having their rolling elements disposed out of contact with their associated respective inner races during normal functioning of the primary bearings. Displacement detection sensors are provided for detecting displacement of the shaft upon failure of the primary bearings. Upon detection of the failure of the primary bearings, the rolling elements and inner races of the backup bearings are brought into mutual contact by axial displacement of the shaft.

Failure detection system risk reduction assessment

NASA Technical Reports Server (NTRS)

Aguilar, Robert B. (Inventor); Huang, Zhaofeng (Inventor)

2012-01-01

A process includes determining a probability of a failure mode of a system being analyzed reaching a failure limit as a function of time to failure limit, determining a probability of a mitigation of the failure mode as a function of a time to failure limit, and quantifying a risk reduction based on the probability of the failure mode reaching the failure limit and the probability of the mitigation.

Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype

NASA Technical Reports Server (NTRS)

Martin, Rodney A.; Schwabacher, Mark A.; Matthews, Bryan L.

2010-01-01

In this paper, we will assess the performance of a data-driven anomaly detection algorithm, the Inductive Monitoring System (IMS), which can be used to detect simulated Thrust Vector Control (TVC) system failures. However, the ability of IMS to detect these failures in a true operational setting may be related to the realistic nature of how they are simulated. As such, we will investigate both a low fidelity and high fidelity approach to simulating such failures, with the latter based upon the underlying physics. Furthermore, the ability of IMS to detect anomalies that were previously unknown and not previously simulated will be studied in earnest, as well as apparent deficiencies or misapplications that result from using the data-driven paradigm. Our conclusions indicate that robust detection performance of simulated failures using IMS is not appreciably affected by the use of a high fidelity simulation. However, we have found that the inclusion of a data-driven algorithm such as IMS into a suite of deployable health management technologies does add significant value.

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

PubMed

Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

2014-01-01

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Characterization of an Enterococcus faecium small-colony variant isolated from blood culture.

PubMed

Gröbner, Sabine; Beck, Julia; Schaller, Martin; Autenrieth, Ingo B; Schulte, Berit

2012-01-01

Small-colony variants (SCVs) of bacteria are slow-growing subpopulations which can cause latent or recurrent infections due to better intracellular survival compared to their wild-type counterparts. Atypical colony morphology and altered biochemical profile may lead to failure in identification of SCV strains. We here report for the first time the isolation of an Enterococcus faecium SCV phenotype. The case of a 65-year-old woman with acute myeloid leukaemia who developed symptoms of sepsis during induction chemotherapy is presented. E. faecium with normal and SCV phenotype was isolated from blood cultures. At the same time urine culture was positive with E. faecium suggesting that bacteraemia originated from the urinary tract. The SCV phenotype was characterized by atypical growth behaviour. Electron microscopic analyses revealed perturbation of the separation of daughter cells and the accumulation of cell wall material. Accordingly, the SCV variant showed a dysfunction or lack of spontaneous autolysis whereas the normal phenotype did not. In contrast to conventional identification systems based on biochemical characteristics, the E. faecium SCV was precisely identified by MALDI-TOF MS analysis implemented in our laboratory. Hence, the increasing use of MALDI-TOF MS analysis for the identification of bacteria might be an appropriate tool for the detection of SCV variants, the diagnosis of which is of importance for the clinical outcome and the antibiotic treatment. Copyright © 2011. Published by Elsevier GmbH.

Improving detection and identification of seismic signals due to landslides: a methodology based on field scale controlled experiments

NASA Astrophysics Data System (ADS)

Yfantis, G.; Carvajal, H. E.; Pytharouli, S.; Lunn, R. J.

2013-12-01

A number of published studies use seismic sensors to understand the physics involved in slope deformation. In this research we artificially induce failure to two meter scaled slopes in the field and use 12 short period 3D seismometers to monitor the failure. To our knowledge there has been no previous controlled experiments that can allow calibration and validation of the interpreted seismic signals. Inside the body of one of the artificial landslides we embed a pile of glass shards. During movement the pile deforms emitting seismic signals due to friction among the glass shards. Our aim is twofold: First we investigate whether the seismic sensors can record pre-cursory and failure signals. Secondly, we test our hypothesis that the glass shards produce seismic signals with higher amplitudes and a distinct frequency pattern, compared to those emitted by common landslide seismicity and local background noise. Two vertical faces, 2m high, were excavated 3m apart in high porous tropical clay. This highly attenuating material makes the detection of weak seismic signals challenging. Slope failure was induced by increasing the vertical load at the landslide's crown. Special care was taken in the design of all experimental procedures to not add to the area's seismic noise. Measurements took place during 18 hours (during afternoon and night) without any change in soil and weather conditions. The 3D sensors were placed on the ground surface close to the crown, forming a dense microseismic network with 5-to-10m spacing and two nanoseismic arrays, with aperture sizes of 10 and 20 m. This design allowed a direct comparison of the recorded signals emitted by the two landslides. The two faces failed for loading between 70 and 100kN and as a result the pile of glass shards was horizontally deformed allowing differential movement between the shards. After the main failure both landslides were continuing to deform due to soil compaction and horizontal displacement. We apply signal processing techniques to identify and locate the emitted signals related to slope movement, despite high background noise levels and high attenuating geological conditions. Results were groundproofed by visual observations. Our study shows that short period seismic sensors can successfully monitor the brittle behaviour of dry clays for deformations larger than 1 centimetre, as well as weak ground failures. The use of glass, or any other coarse and brittle material, has advantages over soil only, since the friction among the glass shards allows for a more distinct frequency pattern. This makes detection of slope movements easier at heterogeneous environments were signals are emitted following movements of different material types as well as in areas characterised by high background noise levels. Our results provide information on the slope behaviour, a powerful tool for geotechnical engineering applications.

Risk factors for early failure after peripheral endovascular intervention: application of a reliability engineering approach.

PubMed

Meltzer, Andrew J; Graham, Ashley; Connolly, Peter H; Karwowski, John K; Bush, Harry L; Frazier, Peter I; Schneider, Darren B

2013-01-01

We apply an innovative and novel analytic approach, based on reliability engineering (RE) principles frequently used to characterize the behavior of manufactured products, to examine outcomes after peripheral endovascular intervention. We hypothesized that this would allow for improved prediction of outcome after peripheral endovascular intervention, specifically with regard to identification of risk factors for early failure. Patients undergoing infrainguinal endovascular intervention for chronic lower-extremity ischemia from 2005 to 2010 were identified in a prospectively maintained database. The primary outcome of failure was defined as patency loss detected by duplex ultrasonography, with or without clinical failure. Analysis included univariate and multivariate Cox regression models, as well as RE-based analysis including product life-cycle models and Weibull failure plots. Early failures were distinguished using the RE principle of "basic rating life," and multivariate models identified independent risk factors for early failure. From 2005 to 2010, 434 primary endovascular peripheral interventions were performed for claudication (51.8%), rest pain (16.8%), or tissue loss (31.3%). Fifty-five percent of patients were aged ≥75 years; 57% were men. Failure was noted after 159 (36.6%) interventions during a mean follow-up of 18 months (range, 0-71 months). Using multivariate (Cox) regression analysis, rest pain and tissue loss were independent predictors of patency loss, with hazard ratios of 2.5 (95% confidence interval, 1.6-4.1; P < 0.001) and 3.2 (95% confidence interval, 2.0-5.2, P < 0.001), respectively. The distribution of failure times for both claudication and critical limb ischemia fit distinct Weibull plots, with different characteristics: interventions for claudication demonstrated an increasing failure rate (β = 1.22, θ = 13.46, mean time to failure = 12.603 months, index of fit = 0.99037, R(2) = 0.98084), whereas interventions for critical limb ischemia demonstrated a decreasing failure rate, suggesting the predominance of early failures (β = 0.7395, θ = 6.8, mean time to failure = 8.2, index of fit = 0.99391, R(2) = 0.98786). By 3.1 months, 10% of interventions failed. This point (90% reliability) was identified as the basic rating life. Using multivariate analysis of failure data, independent predictors of early failure (before 3.1 months) included tissue loss, long lesion length, chronic total occlusions, heart failure, and end-stage renal disease. Application of a RE framework to the assessment of clinical outcomes after peripheral interventions is feasible, and potentially more informative than traditional techniques. Conceptualization of interventions as "products" permits application of product life-cycle models that allow for empiric definition of "early failure" may facilitate comparative effectiveness analysis and enable the development of individualized surveillance programs after endovascular interventions. Copyright © 2013 Annals of Vascular Surgery Inc. Published by Elsevier Inc. All rights reserved.

Simulation Assisted Risk Assessment Applied to Launch Vehicle Conceptual Design

NASA Technical Reports Server (NTRS)

Mathias, Donovan L.; Go, Susie; Gee, Ken; Lawrence, Scott

2008-01-01

A simulation-based risk assessment approach is presented and is applied to the analysis of abort during the ascent phase of a space exploration mission. The approach utilizes groupings of launch vehicle failures, referred to as failure bins, which are mapped to corresponding failure environments. Physical models are used to characterize the failure environments in terms of the risk due to blast overpressure, resulting debris field, and the thermal radiation due to a fireball. The resulting risk to the crew is dynamically modeled by combining the likelihood of each failure, the severity of the failure environments as a function of initiator and time of the failure, the robustness of the crew module, and the warning time available due to early detection. The approach is shown to support the launch vehicle design process by characterizing the risk drivers and identifying regions where failure detection would significantly reduce the risk to the crew.

Robust failure detection filters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Sanmartin, A. M.

1985-01-01

The robustness of detection filters applied to the detection of actuator failures on a free-free beam is analyzed. This analysis is based on computer simulation tests of the detection filters in the presence of different types of model mismatch, and on frequency response functions of the transfers corresponding to the model mismatch. The robustness of detection filters based on a model of the beam containing a large number of structural modes varied dramatically with the placement of some of the filter poles. The dynamics of these filters were very hard to analyze. The design of detection filters with a number of modes equal to the number of sensors was trivial. They can be configured to detect any number of actuator failure events. The dynamics of these filters were very easy to analyze and their robustness properties were much improved. A change of the output transformation allowed the filter to perform satisfactorily with realistic levels of model mismatch.

HIV resistance testing and detected drug resistance in Europe.

PubMed

Schultze, Anna; Phillips, Andrew N; Paredes, Roger; Battegay, Manuel; Rockstroh, Jürgen K; Machala, Ladislav; Tomazic, Janez; Girard, Pierre M; Januskevica, Inga; Gronborg-Laut, Kamilla; Lundgren, Jens D; Cozzi-Lepri, Alessandro

2015-07-17

To describe regional differences and trends in resistance testing among individuals experiencing virological failure and the prevalence of detected resistance among those individuals who had a genotypic resistance test done following virological failure. Multinational cohort study. Individuals in EuroSIDA with virological failure (>1 RNA measurement >500 on ART after >6 months on ART) after 1997 were included. Adjusted odds ratios (aORs) for resistance testing following virological failure and aORs for the detection of resistance among those who had a test were calculated using logistic regression with generalized estimating equations. Compared to 74.2% of ART-experienced individuals in 1997, only 5.1% showed evidence of virological failure in 2012. The odds of resistance testing declined after 2004 (global P < 0.001). Resistance was detected in 77.9% of the tests, NRTI resistance being most common (70.3%), followed by NNRTI (51.6%) and protease inhibitor (46.1%) resistance. The odds of detecting resistance were lower in tests done in 1997-1998, 1999-2000 and 2009-2010, compared to those carried out in 2003-2004 (global P < 0.001). Resistance testing was less common in Eastern Europe [aOR 0.72, 95% confidence interval (CI) 0.55-0.94] compared to Southern Europe, whereas the detection of resistance given that a test was done was less common in Northern (aOR 0.29, 95% CI 0.21-0.39) and Central Eastern (aOR 0.47, 95% CI 0.29-0.76) Europe, compared to Southern Europe. Despite a concurrent decline in virological failure and testing, drug resistance was commonly detected. This suggests a selective approach to resistance testing. The regional differences identified indicate that policy aiming to minimize the emergence of resistance is of particular relevance in some European regions, notably in the countries in Eastern Europe.

Spacecraft dynamics characterization and control system failure detection. Volume 3: Control system failure monitoring

NASA Technical Reports Server (NTRS)

Vanschalkwyk, Christiaan M.

1992-01-01

We discuss the application of Generalized Parity Relations to two experimental flexible space structures, the NASA Langley Mini-Mast and Marshall Space Flight Center ACES mast. We concentrate on the generation of residuals and make no attempt to implement the Decision Function. It should be clear from the examples that are presented whether it would be possible to detect the failure of a specific component. We derive the equations from Generalized Parity Relations. Two special cases are treated: namely, Single Sensor Parity Relations (SSPR) and Double Sensor Parity Relations (DSPR). Generalized Parity Relations for actuators are also derived. The NASA Langley Mini-Mast and the application of SSPR and DSPR to a set of displacement sensors located at the tip of the Mini-Mast are discussed. The performance of a reduced order model that includes the first five models of the mast is compared to a set of parity relations that was identified on a set of input-output data. Both time domain and frequency domain comparisons are made. The effect of the sampling period and model order on the performance of the Residual Generators are also discussed. Failure detection experiments where the sensor set consisted of two gyros and an accelerometer are presented. The effects of model order and sampling frequency are again illustrated. The detection of actuator failures is discussed. We use Generalized Parity Relations to monitor control system component failures on the ACES mast. An overview is given of the Failure Detection Filter and experimental results are discussed. Conclusions and directions for future research are given.

Real-Time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas.

PubMed

Howsmon, Daniel P; Baysal, Nihat; Buckingham, Bruce A; Forlenza, Gregory P; Ly, Trang T; Maahs, David M; Marcal, Tatiana; Towers, Lindsey; Mauritzen, Eric; Deshpande, Sunil; Huyett, Lauren M; Pinsker, Jordan E; Gondhalekar, Ravi; Doyle, Francis J; Dassau, Eyal; Hahn, Juergen; Bequette, B Wayne

2018-05-01

As evidence emerges that artificial pancreas systems improve clinical outcomes for patients with type 1 diabetes, the burden of this disease will hopefully begin to be alleviated for many patients and caregivers. However, reliance on automated insulin delivery potentially means patients will be slower to act when devices stop functioning appropriately. One such scenario involves an insulin infusion site failure, where the insulin that is recorded as delivered fails to affect the patient's glucose as expected. Alerting patients to these events in real time would potentially reduce hyperglycemia and ketosis associated with infusion site failures. An infusion site failure detection algorithm was deployed in a randomized crossover study with artificial pancreas and sensor-augmented pump arms in an outpatient setting. Each arm lasted two weeks. Nineteen participants wore infusion sets for up to 7 days. Clinicians contacted patients to confirm infusion site failures detected by the algorithm and instructed on set replacement if failure was confirmed. In real time and under zone model predictive control, the infusion site failure detection algorithm achieved a sensitivity of 88.0% (n = 25) while issuing only 0.22 false positives per day, compared with a sensitivity of 73.3% (n = 15) and 0.27 false positives per day in the SAP arm (as indicated by retrospective analysis). No association between intervention strategy and duration of infusion sets was observed ( P = .58). As patient burden is reduced by each generation of advanced diabetes technology, fault detection algorithms will help ensure that patients are alerted when they need to manually intervene. Clinical Trial Identifier: www.clinicaltrials.gov,NCT02773875.

Detection of Theileria orientalis in mosquito blood meals in the United Kingdom.

PubMed

Fernández de Marco, M; Brugman, V A; Hernández-Triana, L M; Thorne, L; Phipps, L P; Nikolova, N I; Fooks, A R; Johnson, N

2016-10-15

Theileria spp. are tick-borne protozoan parasites that infect a wide range of wild and domestic animals. In this study, the utility of xenosurveillance of blood-fed specimens of Culiseta annulata for detecting the presence of piroplasms in livestock was investigated. Blood-fed mosquitoes were collected at Elmley National Nature Reserve, Kent, United Kingdom. All specimens were morphologically identified, and DNA barcoding was used to confirm the morphological identification. Both the vertebrate host species and Theileria genome was detected within the bloodmeal by real-time PCR. Sequencing was used to confirm the identity of all amplicons. In total, 105 blood-fed mosquitoes morphologically identified as Cs. annulata were collected. DNA barcoding revealed that 102 specimens were Cs. annulata (99%), while a single specimen was identified as Anopheles messeae. Two specimens could not be identified molecularly due to PCR amplification failure. Blood meal analysis revealed that Cs. annulata fed almost exclusively on cattle at the collection site (n=100). The application of a pan-piroplasm PCR detected 16 positive samples (15.2%) and sequence analysis of the amplicons demonstrated that the piroplasms present in the blood meal belonged to the Theileria orientalis group. This study demonstrates how xenosurveillance can be applied to detecting pathogens in livestock and confirms the presence of Theileria species in livestock from the United Kingdom. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Detecting unknown attacks in wireless sensor networks that contain mobile nodes.

PubMed

Banković, Zorana; Fraga, David; Moya, José M; Vallejo, Juan Carlos

2012-01-01

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

In-vitro bacterial identification using fluorescence spectroscopy with an optical fiber system

NASA Astrophysics Data System (ADS)

Spector, Brian C.; Werkhaven, Jay A.; Smith, Dana; Reinisch, Lou

2000-05-01

Acute otitis media (AOM) remains a source of significant morbidity in children. With the emergence of antibiotic resistant strains of bacteria, tympanocentesis has become an important method of bacterial identification in the setting of treatment failures. Previous studies described a prototype system for the non-invasive fluorescence identification of bacteria in vitro. We demonstrate the addition of an optical fiber to allow for the identification of a specimen distant to the spectrofluorometer. Emission spectra from three bacteria, Streptococcus pneumoniae, Haemophilus influenzae, and Staphylococcus aureus were successfully obtained in vitro. This represents a necessary step prior to the study of in vivo identification of bacteria in AOM using fluorescence spectroscopy.

From traditional biochemical signals to molecular markers for detection of sepsis after burn injuries.

PubMed

Muñoz, Balam; Suárez-Sánchez, Rocío; Hernández-Hernández, Oscar; Franco-Cendejas, Rafael; Cortés, Hernán; Magaña, Jonathan J

2018-05-22

Sepsis is a life-threatening organ-dysfunction condition caused by a dysregulated response to an infectious condition that can cause complications in patients with major trauma. Burns are one of the most destructive forms of trauma; despite the improvements in medical care, infections remain an important cause of burn injury-related mortality and morbidity, and complicated sepsis predisposes patients to diverse complications such as organ failure, lengthening of hospital stays, and increased costs. Accurate diagnosis and early treatment of sepsis may have a beneficial impact on clinical outcome of burn-injured patients. In this review, we offer a comprehensive description of the current and traditional markers used as indicative of sepsis in burned patients. However, although these are markers of the inflammatory post-burn response, they usually fail to predict sepsis in severely burned patients due to that they do not reflect the severity of the infection. Identification and measurement of biomarkers in early stages of infection is important in order to provide timely response and effective treatment of burned patients. Therefore, we compiled important experimental evidence, demonstrating novel biomarkers, including molecular markers such as genomic DNA variations, alterations of transcriptome profiling (mRNA, miRNAs, lncRNAs and circRNAs), epigenetic markers, and advances in proteomics and metabolomics. Finally, this review summarizes next-generation technologies for the identification of markers for detection of sepsis after burn injuries. Copyright © 2018 Elsevier Ltd and ISBI. All rights reserved.

Identification of Location Specific Feature Points in a Cardiac Cycle Using a Novel Seismocardiogram Spectrum System.

PubMed

Lin, Wen-Yen; Chou, Wen-Cheng; Chang, Po-Cheng; Chou, Chung-Chuan; Wen, Ming-Shien; Ho, Ming-Yun; Lee, Wen-Chen; Hsieh, Ming-Jer; Lin, Chung-Chih; Tsai, Tsai-Hsuan; Lee, Ming-Yih

2018-03-01

Seismocardiogram (SCG) or mechanocardiography is a noninvasive cardiac diagnostic method; however, previous studies used only a single sensor to detect cardiac mechanical activities that will not be able to identify location-specific feature points in a cardiac cycle corresponding to the four valvular auscultation locations. In this study, a multichannel SCG spectrum measurement system was proposed and examined for cardiac activity monitoring to overcome problems like, position dependency, time delay, and signal attenuation, occurring in traditional single-channel SCG systems. ECG and multichannel SCG signals were simultaneously recorded in 25 healthy subjects. Cardiac echocardiography was conducted at the same time. SCG traces were analyzed and compared with echocardiographic images for feature point identification. Fifteen feature points were identified in the corresponding SCG traces. Among them, six feature points, including left ventricular lateral wall contraction peak velocity, septal wall contraction peak velocity, transaortic peak flow, transpulmonary peak flow, transmitral ventricular relaxation flow, and transmitral atrial contraction flow were identified. These new feature points were not observed in previous studies because the single-channel SCG could not detect the location-specific signals from other locations due to time delay and signal attenuation. As the results, the multichannel SCG spectrum measurement system can record the corresponding cardiac mechanical activities with location-specific SCG signals and six new feature points were identified with the system. This new modality may help clinical diagnoses of valvular heart diseases and heart failure in the future.

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

NASA Astrophysics Data System (ADS)

Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

Ferrographic and spectrographic analysis of oil sampled before and after failure of a jet engine

NASA Technical Reports Server (NTRS)

Jones, W. R., Jr.

1980-01-01

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph as well as plasma, atomic absorption, and emission spectrometers. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism, nor a high level of wear debris was detected in the oil sample from the engine just prior to the test in which the failure occurred. However, low concentrations of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure.

PREDICE score as a predictor of 90 days mortality in patients with heart failure

NASA Astrophysics Data System (ADS)

Purba, D. P. S.; Hasan, R.

2018-03-01

Hospitalization in chronic heart failure patients associated with high mortality and morbidity rate. The 90 days post-discharge period following hospitalization in heart failure patients is known as the vulnerable phase, it carries the high risk of poor outcomes. Identification of high-risk individuals by using prognostic evaluation was intended to do a closer follow up and more intensive to decreasing the morbidity and mortality rate of heart failure.To determine whether PREDICE score could predict mortality within 90 days in patients with heart failure, an observational cohort study in patients with heart failure who were hospitalized due to worsening chronic heart failure. Patients were in following-up for up to 90 days after initial evaluation with the primary endpoint is death.We found a difference of the significantstatistical between PREDICE score in survival and mortality group (p=0.001) of 84% (95% CI: 60.9% - 97.4%).In conclusion, PREDICE score has a good ability to predict mortality within 90 days in patients with heart failure.

Error-Detecting Identification Codes for Algebra Students.

ERIC Educational Resources Information Center

Sutherland, David C.

1990-01-01

Discusses common error-detecting identification codes using linear algebra terminology to provide an interesting application of algebra. Presents examples from the International Standard Book Number, the Universal Product Code, bank identification numbers, and the ZIP code bar code. (YP)

Fault Detection, Diagnosis, and Mitigation for Long-Duration AUV Missions with Minimal Human Intervention

DTIC Science & Technology

2014-09-30

Duration AUV Missions with Minimal Human Intervention James Bellingham Monterey Bay Aquarium Research Institute 7700 Sandholdt Road Moss Landing...subsystem failures and environmental challenges. For example, should an AUV suffer the failure of one of its internal actuators, can that failure be...reduce the need for operator intervention in the event of performance anomalies on long- duration AUV deployments, - To allow the vehicle to detect

Insights into the failure of the potential, neutral myocardial imaging agent TcN-NOET: physicochemical identification of by-products and degradation species.

PubMed

Tisato, Francesco; Bolzati, Cristina; Refosco, Fiorenzo; Porchia, Marina; Seraglia, Roberta; Carta, Davide; Pasqualini, Roberto

2012-04-01

The neutral complex [(99m)Tc(N)(NOEt)(2)], often referred to as TcN-NOET [NOEt=N-ethoxy,N-ethyldithiocarbamate(1-)], was proposed several years ago as a myocardial imaging agent. Despite some favorable clinical properties evidenced during phase I and phase II studies, the overall results of the European and American phase III clinical studies have been judged insufficient for a successful approval process by the regulatory agencies. Non-carrier-added and carrier-added experiments using short-lived (99m)Tc and long-lived (99g)Tc have been utilized to prepare a series of bis-substituted [Tc(N)(DTC)(2)] complexes [DTC=dithiocarbamate(1-)]. They have been purified by means of chromatographic techniques (high-performance liquid chromatography and thin-layer chromatography) and identified via double detection (UV-vis and radiometry) by comparison with authenticated samples of (99g)Tc compounds prepared by conventional coordination chemistry procedures. The molecular structure of the lipophilic, neutral complex cis-[Tc(N)(NOEt)(2)] has been assigned by comparison with similar nitrido-Tc(V) complexes already reported in the literature. Novel bis-substituted nitrido-Tc complexes containing hydrolyzed portions of coordinated NOEt, namely, N-ethyldithiocarbamate [NHEt(1-)] and N-hydroxy, N-ethyldithiocarbamate [NOHEt(1-)], have been prepared and characterized by means of multinuclear nuclear magnetic resonance spectroscopy and mass spectrometry. Despite the identification of these "hydrolyzed" species, it is still unclear whether the failure to reach the clinical goal of the perfusion tracer [(99m)Tc(N)(NOEt)(2)] is related to the degradation processes evidenced in this study or is the result of the mediocre imaging properties of the tracer. Copyright © 2012 Elsevier Inc. All rights reserved.

On-line detection of key radionuclides for fuel-rod failure in a pressurized water reactor.

PubMed

Qin, Guoxiu; Chen, Xilin; Guo, Xiaoqing; Ni, Ning

2016-08-01

For early on-line detection of fuel rod failure, the key radionuclides useful in monitoring must leak easily from failing rods. Yield, half-life, and mass share of fission products that enter the primary coolant also need to be considered in on-line analyses. From all the nuclides that enter the primary coolant during fuel-rod failure, (135)Xe and (88)Kr were ultimately chosen as crucial for on-line monitoring of fuel-rod failure. A monitoring system for fuel-rod failure detection for pressurized water reactor (PWR) based on the LaBr3(Ce) detector was assembled and tested. The samples of coolant from the PWR were measured using the system as well as a HPGe γ-ray spectrometer. A comparison showed the method was feasible. Finally, the γ-ray spectra of primary coolant were measured under normal operations and during fuel-rod failure. The two peaks of (135)Xe (249.8keV) and (88)Kr (2392.1keV) were visible, confirming that the method is capable of monitoring fuel-rod failure on-line. Copyright © 2016 Elsevier Ltd. All rights reserved.

Signal analysis techniques for incipient failure detection in turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, T.

1985-01-01

Signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery were developed, implemented and evaluated. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques were implemented on a computer and applied to dynamic signals. A laboratory evaluation of the methods with respect to signal detection capability is described. Plans for further technique evaluation and data base development to characterize turbopump incipient failure modes from Space Shuttle main engine (SSME) hot firing measurements are outlined.

[THE FAILURE MODES AND EFFECTS ANALYSIS FACILITATES A SAFE, TIME AND MONEY SAVING OPEN ACCESS COLONOSCOPY SERVICE].

PubMed

Gingold-Belfer, Rachel; Niv, Yaron; Horev, Nehama; Gross, Shuli; Sahar, Nadav; Dickman, Ram

2017-04-01

Failure modes and effects analysis (FMEA) is used for the identification of potential risks in health care processes. We used a specific FMEA - based form for direct referral for colonoscopy and assessed it for procedurerelated perforations. Ten experts in endoscopy evaluated and computed the entire referral process, modes of preparation for the endoscopic procedure, the endoscopic procedure itself and the discharge process. We used FMEA assessing for likelihood of occurrence, detection and severity and calculated the risk profile number (RPN) for each of the above points. According to the highest RPN results we designed a specific open access referral form and then compared the occurrence of colonic perforations (between 2010 and 2013) in patients who were referred through the open access arm (Group 1) to those who had a prior clinical consultation (non-open access, Group 2). Our experts in endoscopy (5 physicians and 5 nurses) identified 3 categories of failure modes that, on average, reached the highest RPNs. We identified 9,558 colonoscopies in group 1, and 12,567 in group 2. Perforations were identified in three patients from the open access group (1:3186, 0.03%) and in 10 from group 2 (1:1256, 0.07%) (p = 0.024). Direct referral for colonoscopy saved 9,558 pre-procedure consultations and the sum of $850,000. The FMEA tool-based specific referral form facilitates a safe, time and money saving open access colonoscopy service. Our form may be adopted by other gastroenterological clinics in Israel.

Failure detection and fault management techniques for flush airdata sensing systems

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

1992-01-01

A high-angle-of-attack flush airdata sensing system was installed and flight tested on the F-18 High Alpha Research Vehicle at NASA-Dryden. This system uses a matrix of pressure orifices arranged in concentric circles on the nose of the vehicle to determine angles of attack, angles of sideslip, dynamic pressure, and static pressure as well as other airdata parameters. Results presented use an arrangement of 11 symmetrically distributed ports on the aircraft nose. Experience with this sensing system data indicates that the primary concern for real-time implementation is the detection and management of overall system and individual pressure sensor failures. The multiple port sensing system is more tolerant to small disturbances in the measured pressure data than conventional probe-based intrusive airdata systems. However, under adverse circumstances, large undetected failures in individual pressure ports can result in algorithm divergence and catastrophic failure of the entire system. How system and individual port failures may be detected using chi sq. analysis is shown. Once identified, the effects of failures are eliminated using weighted least squares.

Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage

NASA Technical Reports Server (NTRS)

Lewicki, David G.; Dempsey, Paula J.; Heath, Gregory F.; Shanthakumaran, Perumal

2009-01-01

A study was performed to evaluate fault detection effectiveness as applied to gear tooth pitting fatigue damage. Vibration and oil-debris monitoring (ODM) data were gathered from 24 sets of spur pinion and face gears run during a previous endurance evaluation study. Three common condition indicators (RMS, FM4, and NA4) were deduced from the time-averaged vibration data and used with the ODM to evaluate their performance for gear fault detection. The NA4 parameter showed to be a very good condition indicator for the detection of gear tooth surface pitting failures. The FM4 and RMS parameters performed average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant amount of debris from all the gear tooth pitting fatigue failures. Excluding outliers, the average cumulative mass at the end of a test was 40 mg.

A preliminary design for flight testing the FINDS algorithm

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Godiwala, P. M.

1986-01-01

This report presents a preliminary design for flight testing the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a target flight computer. The FINDS software was ported onto the target flight computer by reducing the code size by 65%. Several modifications were made to the computational algorithms resulting in a near real-time execution speed. Finally, a new failure detection strategy was developed resulting in a significant improvement in the detection time performance. In particular, low level MLS, IMU and IAS sensor failures are detected instantaneously with the new detection strategy, while accelerometer and the rate gyro failures are detected within the minimum time allowed by the information generated in the sensor residuals based on the point mass equations of motion. All of the results have been demonstrated by using five minutes of sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment.

Identification and Analysis of Partial Shading Breakdown Sites in CuIn xGa (1-x)Se 2 Modules

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

Palmiotti, Elizabeth; Johnston, Steven; Gerber, Andreas

In this paper, CuIn xGa (1-x) (CIGS) mini-modules are stressed under reverse bias, resembling partial shading conditions, to predict and characterize where failures occur. Partial shading can cause permanent damage in the form of 'wormlike' defects on thin-film modules due to thermal runaway. This results in module-scale power losses. We have used dark lock-in thermography (DLIT) to spatially observe localized heating when reverse-bias breakdown occurs on various CIGS mini-modules. For better understanding of how and where these defects originated and propagated, we have developed techniques where the current is limited during reverse-bias stressing. This allows for DLIT-based detection and detailedmore » studying of the region where breakdown is initiated before thermal runaway leads to permanent damage. Statistics of breakdown sites using current-limited conditions has allowed for reasonable identification of the as-grown defects where permanent breakdown will likely originate. Scanning electron microscope results and wormlike defect analysis show that breakdown originates in defects such as small pits, craters, or cracks in the CIGS layer, and the wormlike defects propagate near the top CIGS interface.« less

Identification and Analysis of Partial Shading Breakdown Sites in CuIn xGa (1-x)Se 2 Modules

DOE PAGES

Palmiotti, Elizabeth; Johnston, Steven; Gerber, Andreas; ...

2017-12-20

In this paper, CuIn xGa (1-x) (CIGS) mini-modules are stressed under reverse bias, resembling partial shading conditions, to predict and characterize where failures occur. Partial shading can cause permanent damage in the form of 'wormlike' defects on thin-film modules due to thermal runaway. This results in module-scale power losses. We have used dark lock-in thermography (DLIT) to spatially observe localized heating when reverse-bias breakdown occurs on various CIGS mini-modules. For better understanding of how and where these defects originated and propagated, we have developed techniques where the current is limited during reverse-bias stressing. This allows for DLIT-based detection and detailedmore » studying of the region where breakdown is initiated before thermal runaway leads to permanent damage. Statistics of breakdown sites using current-limited conditions has allowed for reasonable identification of the as-grown defects where permanent breakdown will likely originate. Scanning electron microscope results and wormlike defect analysis show that breakdown originates in defects such as small pits, craters, or cracks in the CIGS layer, and the wormlike defects propagate near the top CIGS interface.« less

Level of Automation and Failure Frequency Effects on Simulated Lunar Lander Performance

NASA Technical Reports Server (NTRS)

Marquez, Jessica J.; Ramirez, Margarita

2014-01-01

A human-in-the-loop experiment was conducted at the NASA Ames Research Center Vertical Motion Simulator, where instrument-rated pilots completed a simulated terminal descent phase of a lunar landing. Ten pilots participated in a 2 x 2 mixed design experiment, with level of automation as the within-subjects factor and failure frequency as the between subjects factor. The two evaluated levels of automation were high (fully automated landing) and low (manual controlled landing). During test trials, participants were exposed to either a high number of failures (75% failure frequency) or low number of failures (25% failure frequency). In order to investigate the pilots' sensitivity to changes in levels of automation and failure frequency, the dependent measure selected for this experiment was accuracy of failure diagnosis, from which D Prime and Decision Criterion were derived. For each of the dependent measures, no significant difference was found for level of automation and no significant interaction was detected between level of automation and failure frequency. A significant effect was identified for failure frequency suggesting failure frequency has a significant effect on pilots' sensitivity to failure detection and diagnosis. Participants were more likely to correctly identify and diagnose failures if they experienced the higher levels of failures, regardless of level of automation

Failure analysis of aluminum alloy components

NASA Technical Reports Server (NTRS)

Johari, O.; Corvin, I.; Staschke, J.

1973-01-01

Analysis of six service failures in aluminum alloy components which failed in aerospace applications is reported. Identification of fracture surface features from fatigue and overload modes was straightforward, though the specimens were not always in a clean, smear-free condition most suitable for failure analysis. The presence of corrosion products and of chemically attacked or mechanically rubbed areas here hindered precise determination of the cause of crack initiation, which was then indirectly inferred from the scanning electron fractography results. In five failures the crack propagation was by fatigue, though in each case the fatigue crack initiated from a different cause. Some of these causes could be eliminated in future components by better process control. In one failure, the cause was determined to be impact during a crash; the features of impact fracture were distinguished from overload fractures by direct comparisons of the received specimens with laboratory-generated failures.

Quantitative method of medication system interface evaluation.

PubMed

Pingenot, Alleene Anne; Shanteau, James; Pingenot, James D F

2007-01-01

The objective of this study was to develop a quantitative method of evaluating the user interface for medication system software. A detailed task analysis provided a description of user goals and essential activity. A structural fault analysis was used to develop a detailed description of the system interface. Nurses experienced with use of the system under evaluation provided estimates of failure rates for each point in this simplified fault tree. Means of estimated failure rates provided quantitative data for fault analysis. Authors note that, although failures of steps in the program were frequent, participants reported numerous methods of working around these failures so that overall system failure was rare. However, frequent process failure can affect the time required for processing medications, making a system inefficient. This method of interface analysis, called Software Efficiency Evaluation and Fault Identification Method, provides quantitative information with which prototypes can be compared and problems within an interface identified.

Early detection of nonneurologic organ failure in patients with severe traumatic brain injury: Multiple organ dysfunction score or sequential organ failure assessment?

PubMed

Ramtinfar, Sara; Chabok, Shahrokh Yousefzadeh; Chari, Aliakbar Jafari; Reihanian, Zoheir; Leili, Ehsan Kazemnezhad; Alizadeh, Arsalan

2016-10-01

The aim of this study is to compare the discriminant function of multiple organ dysfunction score (MODS) and sequential organ failure assessment (SOFA) components in predicting the Intensive Care Unit (ICU) mortality and neurologic outcome. A descriptive-analytic study was conducted at a level I trauma center. Data were collected from patients with severe traumatic brain injury admitted to the neurosurgical ICU. Basic demographic data, SOFA and MOD scores were recorded daily for all patients. Odd's ratios (ORs) were calculated to determine the relationship of each component score to mortality, and area under receiver operating characteristic (AUROC) curve was used to compare the discriminative ability of two tools with respect to ICU mortality. The most common organ failure observed was respiratory detected by SOFA of 26% and MODS of 13%, and the second common was cardiovascular detected by SOFA of 18% and MODS of 13%. No hepatic or renal failure occurred, and coagulation failure reported as 2.5% by SOFA and MODS. Cardiovascular failure defined by both tools had a correlation to ICU mortality and it was more significant for SOFA (OR = 6.9, CI = 3.6-13.3, P < 0.05 for SOFA; OR = 5, CI = 3-8.3, P < 0.05 for MODS; AUROC = 0.82 for SOFA; AUROC = 0.73 for MODS). The relationship of cardiovascular failure to dichotomized neurologic outcome was not significant statistically. ICU mortality was not associated with respiratory or coagulation failure. Cardiovascular failure defined by either tool significantly related to ICU mortality. Compared to MODS, SOFA-defined cardiovascular failure was a stronger predictor of death. ICU mortality was not affected by respiratory or coagulation failures.

Fault Detection and Isolation for Hydraulic Control

NASA Technical Reports Server (NTRS)

1987-01-01

Pressure sensors and isolation valves act to shut down defective servochannel. Redundant hydraulic system indirectly senses failure in any of its electrical control channels and mechanically isolates hydraulic channel controlled by faulty electrical channel so flat it cannot participate in operating system. With failure-detection and isolation technique, system can sustains two failed channels and still functions at full performance levels. Scheme useful on aircraft or other systems with hydraulic servovalves where failure cannot be tolerated.

Retention and readability of radio frequency identification transponders in beef cows over a five-year period

USDA-ARS?s Scientific Manuscript database

Objective of this study was to evaluate failure (loss or inability to read) of radio frequency identification (RFID) ear tags in beef cows over a 2 to 5 year period under ranching conditions. One of 5 types of RFID tags was applied in the ear of a total of 4316 cows on 4 separate ranches. Tags wer...

Dielectric Spectroscopic Detection of Early Failures in 3-D Integrated Circuits.

PubMed

Obeng, Yaw; Okoro, C A; Ahn, Jung-Joon; You, Lin; Kopanski, Joseph J

The commercial introduction of three dimensional integrated circuits (3D-ICs) has been hindered by reliability challenges, such as stress related failures, resistivity changes, and unexplained early failures. In this paper, we discuss a new RF-based metrology, based on dielectric spectroscopy, for detecting and characterizing electrically active defects in fully integrated 3D devices. These defects are traceable to the chemistry of the insolation dielectrics used in the through silicon via (TSV) construction. We show that these defects may be responsible for some of the unexplained early reliability failures observed in TSV enabled 3D devices.

DNA-based techniques for authentication of processed food and food supplements.

PubMed

Lo, Yat-Tung; Shaw, Pang-Chui

2018-02-01

Authentication of food or food supplements with medicinal values is important to avoid adverse toxic effects, provide consumer rights, as well as for certification purpose. Compared to morphological and spectrometric techniques, molecular authentication is found to be accurate, sensitive and reliable. However, DNA degradation and inclusion of inhibitors may lead to failure in PCR amplification. This paper reviews on the existing DNA extraction and PCR protocols, and the use of small size DNA markers with sufficient discriminative power for molecular authentication. Various emerging new molecular techniques such as isothermal amplification for on-site diagnosis, next-generation sequencing for high-throughput species identification, high resolution melting analysis for quick species differentiation, DNA array techniques for rapid detection and quantitative determination in food products are also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Redundancy management of multiple KT-70 inertial measurement units applicable to the space shuttle

NASA Technical Reports Server (NTRS)

Cook, L. J.

1975-01-01

Results of an investigation of velocity failure detection and isolation for 3 inertial measuring units (IMU) and 2 inertial measuring units (IMU) configurations are presented. The failure detection and isolation algorithm performance was highly successful and most types of velocity errors were detected and isolated. The failure detection and isolation algorithm also included attitude FDI but was not evaluated because of the lack of time and low resolution in the gimbal angle synchro outputs. The shuttle KT-70 IMUs will have dual-speed resolvers and high resolution gimbal angle readouts. It was demonstrated by these tests that a single computer utilizing a serial data bus can successfully control a redundant 3-IMU system and perform FDI.

Detecting Structural Failures Via Acoustic Impulse Responses

NASA Technical Reports Server (NTRS)

Bayard, David S.; Joshi, Sanjay S.

1995-01-01

Advanced method of acoustic pulse reflectivity testing developed for use in determining sizes and locations of failures within structures. Used to detect breaks in electrical transmission lines, detect faults in optical fibers, and determine mechanical properties of materials. In method, structure vibrationally excited with acoustic pulse (a "ping") at one location and acoustic response measured at same or different location. Measured acoustic response digitized, then processed by finite-impulse-response (FIR) filtering algorithm unique to method and based on acoustic-wave-propagation and -reflection properties of structure. Offers several advantages: does not require training, does not require prior knowledge of mathematical model of acoustic response of structure, enables detection and localization of multiple failures, and yields data on extent of damage at each location.

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2006-01-01

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Defining Human Failure Events for Petroleum Risk Analysis

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

Ronald L. Boring; Knut Øien

2014-06-01

In this paper, an identification and description of barriers and human failure events (HFEs) for human reliability analysis (HRA) is performed. The barriers, called target systems, are identified from risk significant accident scenarios represented as defined situations of hazard and accident (DSHAs). This report serves as the foundation for further work to develop petroleum HFEs compatible with the SPAR-H method and intended for reuse in future HRAs.

The Role of Occupational Identification During Post-Merger Integration

PubMed Central

Kroon, David P.; Noorderhaven, Niels G.

2016-01-01

Integration processes after mergers are fraught with difficulties, and constitute a main cause of merger failure. This study focuses on the human aspect of post-merger integration, and in particular, on the role of occupational identification. We theorize and empirically demonstrate by means of a survey design that employees’ identification with their occupation is positively related to their willingness to cooperate in the post-merger integration process, over and above the effect of organization members’ organizational identification. This positive effect of occupational identification is stronger for uniformed personnel but attenuates in the course of the integration process. Qualitative interviews further explore and interpret the results from our statistical analysis. Together, these findings have important practical implications and suggest future research directions. PMID:29568214

S-Nitrosothiols and the S-Nitrosoproteome of the Cardiovascular System

PubMed Central

Maron, Bradley A.; Tang, Shiow-Shih

2013-01-01

Abstract Significance: Since their discovery in the early 1990's, S-nitrosylated proteins have been increasingly recognized as important determinants of many biochemical processes. Specifically, S-nitrosothiols in the cardiovascular system exert many actions, including promoting vasodilation, inhibiting platelet aggregation, and regulating Ca2+ channel function that influences myocyte contractility and electrophysiologic stability. Recent Advances: Contemporary developments in liquid chromatography–mass spectrometry methods, the development of biotin- and His-tag switch assays, and the availability of cyanide dye-labeling for S-nitrosothiol detection in vitro have increased significantly the identification of a number of cardiovascular protein targets of S-nitrosylation in vivo. Critical Issues: Recent analyses using modern S-nitrosothiol detection techniques have revealed the mechanistic significance of S-nitrosylation to the pathophysiology of numerous cardiovascular diseases, including essential hypertension, pulmonary hypertension, ischemic heart disease, stroke, and congestive heart failure, among others. Future Directions: Despite enhanced insight into S-nitrosothiol biochemistry, translating these advances into beneficial pharmacotherapies for patients with cardiovascular diseases remains a primary as-yet unmet goal for investigators within the field. Antioxid. Redox Signal. 18, 270–287. PMID:22770551

Heart Failure and Frailty in the Community-Living Elderly Population: What the UFO Study Will Tell Us.

PubMed

Fung, Erik; Hui, Elsie; Yang, Xiaobo; Lui, Leong T; Cheng, King F; Li, Qi; Fan, Yiting; Sahota, Daljit S; Ma, Bosco H M; Lee, Jenny S W; Lee, Alex P W; Woo, Jean

2018-01-01

Heart failure and frailty are clinical syndromes that present with overlapping phenotypic characteristics. Importantly, their co-presence is associated with increased mortality and morbidity. While mechanical and electrical device therapies for heart failure are vital for select patients with advanced stage disease, the majority of patients and especially those with undiagnosed heart failure would benefit from early disease detection and prompt initiation of guideline-directed medical therapies. In this article, we review the problematic interactions between heart failure and frailty, introduce a focused cardiac screening program for community-living elderly initiated by a mobile communication device app leading to the Undiagnosed heart Failure in frail Older individuals (UFO) study, and discuss how the knowledge of pre-frailty and frailty status could be exploited for the detection of previously undiagnosed heart failure or advanced cardiac disease. The widespread use of mobile devices coupled with increasing availability of novel, effective medical and minimally invasive therapies have incentivized new approaches to heart failure case finding and disease management.

A dissociation between detection and identification of phobic stimuli: unconscious perception?

PubMed

Siegel, Paul; Han, Edward; Cohen, Don; Anderson, Jason

2013-01-01

A psychophysical paradigm for investigating unconscious perception was used to test the hypothesis of dissociation between detection and identification of phobic stimuli. Spider-phobic and non-phobic participants were presented with masked images of spiders and flowers and an equal number of control stimuli in a random sequence. After each masked stimulus was flashed, participants first reported whether or not an object was presented. Then they identified each stimulus as either a spider or a flower, regardless of their prior detection response. Phobic participants identified both detected and undetected spiders better than chance, as assessed by two measures of response bias. They did not exhibit dissociation between detection and identification for flowers. Non-phobic participants did not exhibit detection-identification dissociation for either spiders or flowers. These results are consistent with the interpretation that phobic individuals unconsciously perceive their feared stimulus, and constitute the first direct demonstration of such for emotional stimuli.

Facial emotion identification and sexual assault risk detection among college student sexual assault victims and nonvictims.

PubMed

Melkonian, Alexander J; Ham, Lindsay S; Bridges, Ana J; Fugitt, Jessica L

2017-10-01

High rates of sexual victimization among college students necessitate further study of factors associated with sexual assault risk detection. The present study examined how social information processing relates to sexual assault risk detection as a function of sexual assault victimization history. 225 undergraduates (M age = 19.12, SD = 1.44; 66% women). Participants completed an online questionnaire assessing victimization history, an emotion identification task, and a sexual assault risk detection task between June 2013 and May 2014. Emotion identification moderated the association between victimization history and risk detection such that sexual assault survivors with lower emotion identification accuracy also reported the least risk in a sexual assault vignette. Findings suggest that differences in social information processing, specifically recognition of others' emotions, are associated with sexual assault risk detection. College prevention programs could incorporate emotional awareness strategies, particularly for men and women who are sexual assault survivors.

Green Neutrophilic Inclusions and Acute Hepatic Failure: Clinical Significance and Brief Review of the Literature.

PubMed

Haberichter, Kristle L; Crisan, Domnita

2017-01-01

Medical literature has documented an association between acute hepatic failure and coarse, bright-green neutrophilic inclusions. Upon identification of these unique inclusions patients have been reported to have poor outcomes and usually die within 24-72 hours. The exact nature of these inclusions has yet to be determined; it is postulated that they arise from lipofusion-like substance. Here, we describe five cases of acute hepatic failure, with associated bright-green neutrophilic inclusions, where four patients survived beyond the ominous 72-hour window period. © 2017 by the Association of Clinical Scientists, Inc.

Modeling the ductile fracture and the plastic anisotropy of DC01 steel at room temperature and low strain rates

NASA Astrophysics Data System (ADS)

Tuninetti, V.; Yuan, S.; Gilles, G.; Guzmán, C. F.; Habraken, A. M.; Duchêne, L.

2016-08-01

This paper presents different extensions of the classical GTN damage model implemented in a finite element code. The goal of this study is to assess these extensions for the numerical prediction of failure of a DC01 steel sheet during a single point incremental forming process, after a proper identification of the material parameters. It is shown that the prediction of failure appears too early compared to experimental results. Though, the use of the Thomason criterion permitted to delay the onset of coalescence and consequently the final failure.

Flight test results of the strapdown ring laser gyro tetrad inertial navigation system

NASA Technical Reports Server (NTRS)

Carestia, R. A.; Hruby, R. J.; Bjorkman, W. S.

1983-01-01

A helicopter flight test program undertaken to evaluate the performance of Tetrad (a strap down, laser gyro, inertial navigation system) is described. The results of 34 flights show a mean final navigational velocity error of 5.06 knots, with a standard deviation of 3.84 knots; a corresponding mean final position error of 2.66 n. mi., with a standard deviation of 1.48 n. mi.; and a modeled mean position error growth rate for the 34 tests of 1.96 knots, with a standard deviation of 1.09 knots. No laser gyro or accelerometer failures were detected during the flight tests. Off line parity residual studies used simulated failures with the prerecorded flight test and laboratory test data. The airborne Tetrad system's failure--detection logic, exercised during the tests, successfully demonstrated the detection of simulated ""hard'' failures and the system's ability to continue successfully to navigate by removing the simulated faulted sensor from the computations. Tetrad's four ring laser gyros provided reliable and accurate angular rate sensing during the 4 yr of the test program, and no sensor failures were detected during the evaluation of free inertial navigation performance.

Experience of automation failures in training: effects on trust, automation bias, complacency and performance.

PubMed

Sauer, Juergen; Chavaillaz, Alain; Wastell, David

2016-06-01

This work examined the effects of operators' exposure to various types of automation failures in training. Forty-five participants were trained for 3.5 h on a simulated process control environment. During training, participants either experienced a fully reliable, automatic fault repair facility (i.e. faults detected and correctly diagnosed), a misdiagnosis-prone one (i.e. faults detected but not correctly diagnosed) or a miss-prone one (i.e. faults not detected). One week after training, participants were tested for 3 h, experiencing two types of automation failures (misdiagnosis, miss). The results showed that automation bias was very high when operators trained on miss-prone automation encountered a failure of the diagnostic system. Operator errors resulting from automation bias were much higher when automation misdiagnosed a fault than when it missed one. Differences in trust levels that were instilled by the different training experiences disappeared during the testing session. Practitioner Summary: The experience of automation failures during training has some consequences. A greater potential for operator errors may be expected when an automatic system failed to diagnose a fault than when it failed to detect one.

Sensor failure detection for jet engines using analytical redundance

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1984-01-01

Analytical redundant sensor failure detection, isolation and accommodation techniques for gas turbine engines are surveyed. Both the theoretical technology base and demonstrated concepts are discussed. Also included is a discussion of current technology needs and ongoing Government sponsored programs to meet those needs.

Method and Apparatus for Reading Two Dimensional Identification Symbols Using Radar Techniques

NASA Technical Reports Server (NTRS)

Schramm, Harry F., Jr. (Inventor); Roxby, Donald L. (Inventor)

2003-01-01

A method and apparatus are provided for sensing two-dimensional identification marks provided on a substrate or embedded within a substrate below a surface of the substrate. Micropower impulse radar is used to transmit a high risetime, short duration pulse to a focussed radar target area of the substrate having the two dimensional identification marks. The method further includes the steps of listening for radar echoes returned from the identification marks during a short listening period window occurring a predetermined time after transmission of the radar pulse. If radar echoes are detected, an image processing step is carried out. If no radar echoes are detected, the method further includes sequentially transmitting further high risetime, short duration pulses, and listening for radar echoes from each of said further pulses after different elapsed times for each of the further pulses until radar echoes are detected. When radar echoes are detected, data based on the detected echoes is processed to produce an image of the identification marks.

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

Bacteriophage Amplification-Coupled Detection and Identification of Bacterial Pathogens

NASA Astrophysics Data System (ADS)

Cox, Christopher R.; Voorhees, Kent J.

Current methods of species-specific bacterial detection and identification are complex, time-consuming, and often require expensive specialized equipment and highly trained personnel. Numerous biochemical and genotypic identification methods have been applied to bacterial characterization, but all rely on tedious microbiological culturing practices and/or costly sequencing protocols which render them impractical for deployment as rapid, cost-effective point-of-care or field detection and identification methods. With a view towards addressing these shortcomings, we have exploited the evolutionarily conserved interactions between a bacteriophage (phage) and its bacterial host to develop species-specific detection methods. Phage amplification-coupled matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to rapidly detect phage propagation resulting from species-specific in vitro bacterial infection. This novel signal amplification method allowed for bacterial detection and identification in as little as 2 h, and when combined with disulfide bond reduction methods developed in our laboratory to enhance MALDI-TOF-MS resolution, was observed to lower the limit of detection by several orders of magnitude over conventional spectroscopy and phage typing methods. Phage amplification has been combined with lateral flow immunochromatography (LFI) to develop rapid, easy-to-operate, portable, species-specific point-of-care (POC) detection devices. Prototype LFI detectors have been developed and characterized for Yersinia pestis and Bacillus anthracis, the etiologic agents of plague and anthrax, respectively. Comparable sensitivity and rapidity was observed when phage amplification was adapted to a species-specific handheld LFI detector, thus allowing for rapid, simple, POC bacterial detection and identification while eliminating the need for bacterial culturing or DNA isolation and amplification techniques.

An energy-efficient failure detector for vehicular cloud computing.

PubMed

Liu, Jiaxi; Wu, Zhibo; Dong, Jian; Wu, Jin; Wen, Dongxin

2018-01-01

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption.

An energy-efficient failure detector for vehicular cloud computing

PubMed Central

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Wen, Dongxin

2018-01-01

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption. PMID:29352282

Failure of the MicroScan WalkAway System To Detect Heteroresistance to Carbapenems in a Patient with Enterobacter aerogenes Bacteremia▿

PubMed Central

Gordon, N. C.; Wareham, D. W.

2009-01-01

We report the failure of the automated MicroScan WalkAway system to detect carbapenem heteroresistance in Enterobacter aerogenes. Carbapenem resistance has become an increasing concern in recent years, and robust surveillance is required to prevent dissemination of resistant strains. Reliance on automated systems may delay the detection of emerging resistance. PMID:19641071

Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation.

PubMed

Evans, R Scott; Benuzillo, Jose; Horne, Benjamin D; Lloyd, James F; Bradshaw, Alejandra; Budge, Deborah; Rasmusson, Kismet D; Roberts, Colleen; Buckway, Jason; Geer, Norma; Garrett, Teresa; Lappé, Donald L

2016-09-01

Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients. Dictated free-text reports from the previous 24 h were analyzed each day with natural language processing (NLP), to help improve the early identification of hospitalized patients with HF. A second application that uses an Intermountain Healthcare-developed predictive score to determine each HF patient's risk for 30-day hospital readmission and 30-day mortality was also developed. That information was included in an identification and predictive risk report, which was evaluated at a 354-bed hospital that treats high-risk HF patients. The addition of NLP-identified HF patients increased the identification score's sensitivity from 82.6% to 95.3% and its specificity from 82.7% to 97.5%, and the model's positive predictive value is 97.45%. Daily multidisciplinary discharge planning meetings are now based on the information provided by the HF identification and predictive report, and clinician's review of potential HF admissions takes less time compared to the previously used manual methodology (10 vs 40 min). An evaluation of the use of the HF predictive report identified a significant reduction in 30-day mortality and a significant increase in patient discharges to home care instead of to a specialized nursing facility. Using clinical decision support to help identify HF patients and automatically calculating their 30-day all-cause readmission and 30-day mortality risks, coupled with a multidisciplinary care process pathway, was found to be an effective process to improve HF patient identification, significantly reduce 30-day mortality, and significantly increase patient discharges to home care. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A survey of design methods for failure detection in dynamic systems

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1975-01-01

A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed. The class of linear systems is concentrated on but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed.

The quality assurance program of organ donation in Tuscany.

PubMed

Bozzi, G; Saviozzi, A; De Simone, P; Filipponi, F

2008-01-01

Constant monitoring is paramount in order to detect the criticalities and improve the results of the deceased donation process. Concomitant with the institution of a regional transplantation service authority--Organizzazione Toscana Trapianti--in 2003, Tuscany adopted a program of quality assurance of the deceased donation process by compulsory reporting of all encephalic deaths from local intensive care units to the regional transplant office in Florence. The indicators we adopted were the efficiency of deceased donor (DD) identification, expressed as the ratio of encephalic deaths (ED) to total deaths with encephalic lesions (EL) (ie, ED/EL); the efficiency of DD reporting, expressed as the ratio of reported potential DD (RPDD) to total ED (ie, RPDD/ED); the efficacy of the DD process, as the ratio between actual DD (ADD) to total ED (ie, ADD/ED); the conversion rate; the percent of opposition to donation; and the incidence of DD maintenance failures. Data were collected prospectively, stratified by regional hospital consortia (Aziende Sanitarie Locali) and compared with international benchmarks. In the period 2003-2006 the mean efficiency of DD identification was 48.3%+/-4.4% (range 42.6%-53.2%); the mean efficiency of DD reporting was 95.2%+/-2.5% (range 92.5%-98.5%); the mean efficacy of the deceased donation process was 51.8%+/-2.4% (range 48.6%-54.4%); the mean conversion rate was 59.6%+/-2.2% (range 57.6%-62.7%); the mean opposition rate was 31.9%+/-1.1% (range 30.6%-33.2%); and the incidence of DD maintenance failure was 5%+/-2.9% (range 2.2%-8.7%). The breakdown analysis revealed wide interhospital variability in terms of efficiency of DD identification (from a low of 25% to a high of 80%); efficacy of the donation process (from a low of 22% to a high of 79%); and conversion rate (from a low of 29% to a high of 79%). Our results highlight that the donation process gets started in about 50% of eligible cases. Further strategies are favored to address this critical area.

Exhaust Air Dust Monitoring is Superior to Soiled Bedding Sentinels for the Detection of Pasteurella pneumotropica in Individually Ventilated Cage Systems.

PubMed

Miller, Manuel; Ritter, Brbel; Zorn, Julia; Brielmeier, Markus

2016-11-01

Reliable detection of unwanted organisms is essential for meaningful health monitoring in experimental animal facilities. Currently, most rodents are housed in IVC systems, which prevent the aerogenic transmission of pathogens between cages. Typically soiled-bedding sentinels (SBS) exposed to soiled bedding collected from a population of animals within an IVC rack are tested as representatives, but infectious agents often go undetected due to inefficient transmission. Pasteurellaceae are among the most prevalent bacterial pathogens isolated from experimental mice, and the failure of SBS to detect these bacteria is well established. In this study, we investigated whether analysis of exhaust air dust (EAD) samples by using a sensitive and specific real-time PCR assay is superior to conventional SBS monitoring for the detection of Pasteurella pneumotropica (Pp) infections. In a rack with a known prevalence of Pp-positive mice, weekly EAD sampling was compared with the classic SBS method over 3 mo. In 6 rounds of testing, with a prevalence of 5 infected mice in each of 7 cages in a rack of 63 cages, EAD PCR detected Pp at every weekly time point; SBS failed to detect Pp in all cases. The minimal prevalence of Pp-infected mice required to obtain a reliable positive result by EAD PCR testing was determined to be 1 in 63 cages. Reliable detection of Pp was achieved after only 1 wk of exposure. Analysis of EAD samples by real-time PCR assay provides a sensitive, simple, and reliable approach for Pp identification in laboratory mice.

Exhaust Air Dust Monitoring is Superior to Soiled Bedding Sentinels for the Detection of Pasteurella pneumotropica in Individually Ventilated Cage Systems

PubMed Central

Miller, Manuel; Ritter, Bärbel; Zorn, Julia; Brielmeier, Markus

2016-01-01

Reliable detection of unwanted organisms is essential for meaningful health monitoring in experimental animal facilities. Currently, most rodents are housed in IVC systems, which prevent the aerogenic transmission of pathogens between cages. Typically soiled-bedding sentinels (SBS) exposed to soiled bedding collected from a population of animals within an IVC rack are tested as representatives, but infectious agents often go undetected due to inefficient transmission. Pasteurellaceae are among the most prevalent bacterial pathogens isolated from experimental mice, and the failure of SBS to detect these bacteria is well established. In this study, we investigated whether analysis of exhaust air dust (EAD) samples by using a sensitive and specific real-time PCR assay is superior to conventional SBS monitoring for the detection of Pasteurella pneumotropica (Pp) infections. In a rack with a known prevalence of Pp-positive mice, weekly EAD sampling was compared with the classic SBS method over 3 mo. In 6 rounds of testing, with a prevalence of 5 infected mice in each of 7 cages in a rack of 63 cages, EAD PCR detected Pp at every weekly time point; SBS failed to detect Pp in all cases. The minimal prevalence of Pp-infected mice required to obtain a reliable positive result by EAD PCR testing was determined to be 1 in 63 cages. Reliable detection of Pp was achieved after only 1 wk of exposure. Analysis of EAD samples by real-time PCR assay provides a sensitive, simple, and reliable approach for Pp identification in laboratory mice. PMID:27931316

Integrated condition monitoring of a fleet of offshore wind turbines with focus on acceleration streaming processing

NASA Astrophysics Data System (ADS)

Helsen, Jan; Gioia, Nicoletta; Peeters, Cédric; Jordaens, Pieter-Jan

2017-05-01

Particularly offshore there is a trend to cluster wind turbines in large wind farms, and in the near future to operate such a farm as an integrated power production plant. Predictability of individual turbine behavior across the entire fleet is key in such a strategy. Failure of turbine subcomponents should be detected well in advance to allow early planning of all necessary maintenance actions; Such that they can be performed during low wind and low electricity demand periods. In order to obtain the insights to predict component failure, it is necessary to have an integrated clean dataset spanning all turbines of the fleet for a sufficiently long period of time. This paper illustrates our big-data approach to do this. In addition, advanced failure detection algorithms are necessary to detect failures in this dataset. This paper discusses a multi-level monitoring approach that consists of a combination of machine learning and advanced physics based signal-processing techniques. The advantage of combining different data sources to detect system degradation is in the higher certainty due to multivariable criteria. In order to able to perform long-term acceleration data signal processing at high frequency a streaming processing approach is necessary. This allows the data to be analysed as the sensors generate it. This paper illustrates this streaming concept on 5kHz acceleration data. A continuous spectrogram is generated from the data-stream. Real-life offshore wind turbine data is used. Using this streaming approach for calculating bearing failure features on continuous acceleration data will support failure propagation detection.

Using failure mode and effects analysis to improve the safety of neonatal parenteral nutrition.

PubMed

Arenas Villafranca, Jose Javier; Gómez Sánchez, Araceli; Nieto Guindo, Miriam; Faus Felipe, Vicente

2014-07-15

Failure mode and effects analysis (FMEA) was used to identify potential errors and to enable the implementation of measures to improve the safety of neonatal parenteral nutrition (PN). FMEA was used to analyze the preparation and dispensing of neonatal PN from the perspective of the pharmacy service in a general hospital. A process diagram was drafted, illustrating the different phases of the neonatal PN process. Next, the failures that could occur in each of these phases were compiled and cataloged, and a questionnaire was developed in which respondents were asked to rate the following aspects of each error: incidence, detectability, and severity. The highest scoring failures were considered high risk and identified as priority areas for improvements to be made. The evaluation process detected a total of 82 possible failures. Among the phases with the highest number of possible errors were transcription of the medical order, formulation of the PN, and preparation of material for the formulation. After the classification of these 82 possible failures and of their relative importance, a checklist was developed to achieve greater control in the error-detection process. FMEA demonstrated that use of the checklist reduced the level of risk and improved the detectability of errors. FMEA was useful for detecting medication errors in the PN preparation process and enabling corrective measures to be taken. A checklist was developed to reduce errors in the most critical aspects of the process. Copyright © 2014 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Involvement of systemic venous congestion in heart failure.

PubMed

Rubio Gracia, J; Sánchez Marteles, M; Pérez Calvo, J I

2017-04-01

Systemic venous congestion has gained significant importance in the interpretation of the pathophysiology of acute heart failure, especially in the development of renal function impairment during exacerbations. In this study, we review the concept, clinical characterisation and identification of venous congestion. We update current knowledge on its importance in the pathophysiology of acute heart failure and its involvement in the prognosis. We pay special attention to the relationship between abdominal congestion, the pulmonary interstitium as filtering membrane, inflammatory phenomena and renal function impairment in acute heart failure. Lastly, we review decongestion as a new therapeutic objective and the measures available for its assessment. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Medicina Interna (SEMI). All rights reserved.

A signal detection theory analysis of an unconscious perception effect.

PubMed

Haase, S J; Theios, J; Jenison, R

1999-07-01

The independent observation model (Macmillan & Creelman, 1991) is fitted to detection-identification data collected under conditions of heavy masking. The model accurately predicts a quantitative relationship between stimulus detection and stimulus identification over a wide range of detection performance. This model can also be used to offer a signal detection interpretation of the common finding of above-chance identification following a missed signal. While our finding is not a new one, the stimuli used in this experiment (redundant three-letter strings) differ slightly from those used in traditional signal detection work. Also, the stimuli were presented very briefly and heavily masked, conditions typical in the study of unconscious perception effects.

Performance metrics for the evaluation of hyperspectral chemical identification systems

NASA Astrophysics Data System (ADS)

Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay

2016-02-01

Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

Development of Mechanochemically Active Polymers for Early Damage Detection

NASA Astrophysics Data System (ADS)

Zou, Jin

Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.

Management of Arrhythmias in Heart Failure

PubMed Central

Masarone, Daniele; Limongelli, Giuseppe; Rubino, Marta; Valente, Fabio; Vastarella, Rossella; Ammendola, Ernesto; Gravino, Rita; Verrengia, Marina; Salerno, Gemma; Pacileo, Giuseppe

2017-01-01

Heart failure patients are predisposed to develop arrhythmias. Supraventricular arrhythmias can exacerbate the heart failure symptoms by decreasing the effective cardiac output and their control require pharmacological, electrical, or catheter-based intervention. In the setting of atrial flutter or atrial fibrillation, anticoagulation becomes paramount to prevent systemic or cerebral embolism. Patients with heart failure are also prone to develop ventricular arrhythmias that can present a challenge to the managing clinician. The management strategy depends on the type of arrhythmia, the underlying structural heart disease, the severity of heart failure, and the range from optimization of heart failure therapy to catheter ablation. Patients with heart failure, irrespective of ejection fraction are at high risk for developing sudden cardiac death, however risk stratification is a clinical challenge and requires a multiparametric evaluation for identification of patients who should undergo implantation of a cardioverter defibrillator. Finally, patients with heart failure can also develop symptomatic bradycardia, caused by sinus node dysfunction or atrio-ventricular block. The treatment of bradycardia in these patients with pacing is usually straightforward but needs some specific issue. PMID:29367535

Methods, compounds and systems for detecting a microorganism in a sample

DOEpatents

Colston, Jr, Bill W.; Fitch, J. Patrick; Gardner, Shea N.; Williams, Peter L.; Wagner, Mark C.

2016-09-06

Methods to identify a set of probe polynucleotides suitable for detecting a set of targets and in particular methods for identification of primers suitable for detection of target microorganisms related polynucleotides, set of polynucleotides and compositions, and related methods and systems for detection and/or identification of microorganisms in a sample.

Comprehensive Analysis of Gene Expression Profiles of Sepsis-Induced Multiorgan Failure Identified Its Valuable Biomarkers.

PubMed

Wang, Yumei; Yin, Xiaoling; Yang, Fang

2018-02-01

Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.

Weld failure detection

DOEpatents

Pennell, William E.; Sutton, Jr., Harry G.

1981-01-01

Method and apparatus for detecting failure in a welded connection, particrly applicable to not readily accessible welds such as those joining components within the reactor vessel of a nuclear reactor system. A preselected tag gas is sealed within a chamber which extends through selected portions of the base metal and weld deposit. In the event of a failure, such as development of a crack extending from the chamber to an outer surface, the tag gas is released. The environment about the welded area is directed to an analyzer which, in the event of presence of the tag gas, evidences the failure. A trigger gas can be included with the tag gas to actuate the analyzer.

An investigation of gear mesh failure prediction techniques. M.S. Thesis - Cleveland State Univ.

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.

1989-01-01

A study was performed in which several gear failure prediction methods were investigated and applied to experimental data from a gear fatigue test apparatus. The primary objective was to provide a baseline understanding of the prediction methods and to evaluate their diagnostic capabilities. The methods investigated use the signal average in both the time and frequency domain to detect gear failure. Data from eleven gear fatigue tests were recorded at periodic time intervals as the gears were run from initiation to failure. Four major failure modes, consisting of heavy wear, tooth breakage, single pits, and distributed pitting were observed among the failed gears. Results show that the prediction methods were able to detect only those gear failures which involved heavy wear or distributed pitting. None of the methods could predict fatigue cracks, which resulted in tooth breakage, or single pits. It is suspected that the fatigue cracks were not detected because of limitations in data acquisition rather than in methodology. Additionally, the frequency response between the gear shaft and the transducer was found to significantly affect the vibration signal. The specific frequencies affected were filtered out of the signal average prior to application of the methods.

Raman scattering spectroscopy for explosives identification

NASA Astrophysics Data System (ADS)

Nagli, L.; Gaft, M.

2007-04-01

Real time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called Improvised Explosive Devices (IED). It is recognized that the only technique, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS technique belongs to trace detection, namely to its micro-particles variety. We applied gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. Raman system was developed and tested by LDS for field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Detection and characterization of cry1Ac transgene construct in Bt cotton: multiple polymerase chain reaction approach.

PubMed

Singh, Chandra K; Ojha, Abhishek; Kachru, Devendra N

2007-01-01

To comply with international labeling regulations for genetically modified (GM) crops and food, and to enable proper identification of GM organisms (GMOs), effective methodologies and reliable approaches are needed. The spurious and unapproved GM planting has contributed to crop failures and commercial losses. To ensure effective and genuine GM cultivation, a methodology is needed to detect and identify the trait of interest and concurrently evaluate the structural and functional stability of the transgene insert. A multiple polymerase chain reaction (PCR) approach was developed for detection, identification, and gene stability confirmation of cry1Ac transgene construct in Bt cotton. As many as 9 samples of Bt cotton hybrid seeds comprising 3 approved Bt hybrids, MECH-12Bt, MECH-162Bt, MECH-184Bt, and a batch of 6 nonapproved Bt hybrids were tested. Initially, single standard PCR assays were run to amplify predominant GM DNA sequences (CaMV 35S promoter, nos terminator, and npt-II marker gene); a housekeeping gene, Gossypium hirsutum fiber-specific acyl carrier protein gene (acp1); a trait-specific transgene (cry1Ac); and a sequence of 7S 3' transcription terminator which specifically borders with 3' region of cry1Ac transgene cassette. The concurrent amplification of all sequences of the entire cassette was performed by 3 assays, duplex, triplex, and quadruplex multiplex PCR assays, under common assay conditions. The identity of amplicons was reconfirmed by restriction endonuclease digestion profile. The 2 distinct transgene cassettes, cry1Ac and npt-II, of the Bt cotton were amplified using the respective forward primer of promoter and reverse primer of terminator. The resultant amplicons were excised, eluted, and purified. The purified amplicons served as template for nested PCR assays. The nested PCR runs confirmed the transgene construct orientation and identity. The limit of detection as established by our assay for GM trait (cry1Ac) was 0.1%. This approach can be adopted as a standard procedure for complete molecular characterization of Bt cotton. These assays will be of interest and use to importers, breeders, research laboratories, safety regulators, and food processors for detection of cry1Ac bearing GMOs.

A survey of design methods for failure detection in dynamic systems

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1975-01-01

A number of methods for the detection of abrupt changes (such as failures) in stochastic dynamical systems were surveyed. The class of linear systems were emphasized, but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed.

Real time and in vivo monitoring of nitric oxide by electrochemical sensors--from dream to reality.

PubMed

Zhang, Xueji

2004-09-01

Nitric oxide is a key intercellular messenger in the human and animal bodies. The identification of nitric oxide (NO) as the endothelium-derived relaxing factor (EDRF) has driven an enormous effort to further elucidate the chemistry, biology and therapeutic actions of this important molecule. It has found that nitric oxide is involved in many disease states such as such as chronic heart failure, stroke, impotent (erectile dysfunction). The bioactivity of nitric oxide intrinsically linked to its diffusion from its site production to the sites of action. Accurate reliable in real time detection of NO in various biological systems is therefore crucial to understanding its biological role. However, the instability of NO in aqueous solution and its high reactivity with other molecules can cause difficulties for its measurement depending on the detection method employed. Although a variety of methods have been described to measure NO in aqueous environments, it is now generally accepted that electrochemical (amperometric) detection using NO-specific electrodes is the most reliable and sensitive technique available for real-time in situ detection of NO. In 1992 the first commercial NO electrode-based amperometric detection system was developed by WPI. The system has been used successfully for a number of years in a wide range of research applications, both in vitro and in vivo. Recently, many new electrochemical nitric sensors have been invented and commercialized. Here we describe some of the background principles in NO sensors design, methodology and their applications.

Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage

NASA Technical Reports Server (NTRS)

Lewicki, David G.; Dempsey, Paula J.; Heath, Gregory F.; Shanthakumaran, Perumal

2010-01-01

A study was performed to evaluate fault detection effectiveness as applied to gear-tooth-pitting-fatigue damage. Vibration and oil-debris monitoring (ODM) data were gathered from 24 sets of spur pinion and face gears run during a previous endurance evaluation study. Three common condition indicators (RMS, FM4, and NA4 [Ed. 's note: See Appendix A-Definitions D were deduced from the time-averaged vibration data and used with the ODM to evaluate their performance for gear fault detection. The NA4 parameter showed to be a very good condition indicator for the detection of gear tooth surface pitting failures. The FM4 and RMS parameters perfomu:d average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant 8lDOunt of debris from all the gear tooth pitting fatigue failures. Excluding outliers, the average cumulative mass at the end of a test was 40 mg.

Sensors and systems for space applications: a methodology for developing fault detection, diagnosis, and recovery

NASA Astrophysics Data System (ADS)

Edwards, John L.; Beekman, Randy M.; Buchanan, David B.; Farner, Scott; Gershzohn, Gary R.; Khuzadi, Mbuyi; Mikula, D. F.; Nissen, Gerry; Peck, James; Taylor, Shaun

2007-04-01

Human space travel is inherently dangerous. Hazardous conditions will exist. Real time health monitoring of critical subsystems is essential for providing a safe abort timeline in the event of a catastrophic subsystem failure. In this paper, we discuss a practical and cost effective process for developing critical subsystem failure detection, diagnosis and response (FDDR). We also present the results of a real time health monitoring simulation of a propellant ullage pressurization subsystem failure. The health monitoring development process identifies hazards, isolates hazard causes, defines software partitioning requirements and quantifies software algorithm development. The process provides a means to establish the number and placement of sensors necessary to provide real time health monitoring. We discuss how health monitoring software tracks subsystem control commands, interprets off-nominal operational sensor data, predicts failure propagation timelines, corroborate failures predictions and formats failure protocol.

The Diffuse Interstellar Bands: Solving a Century Old Problem

NASA Technical Reports Server (NTRS)

Salama, Farid

2017-01-01

The Diffuse Interstellar Bands (DIBs) are a set of apporoximately 500 absorption bands that are seen in the spectra of reddened stars (i.e., stars obscured by the presence of interstellar clouds in their line of sight). The first DIBs were detected in the visible over a century ago. Diffuse Interstellar Bands are now detected from the near ultraviolet to the near infrared in the spectra of reddened stars spanning a variety of interstellar environments in our local, and in other galaxies. Although DIB carriers are a significant part of the interstellar chemical inventory as they account for a noticeable fraction of the interstellar extinction, the nature of their carriers is still unknown over a century after the detection of the first bands. DIB carriers are stable and ubiquitous in a broad variety of interstellar environments and play a unique role in interstellar physics and chemistry. It has long been realized that the solving of the DIB problem requires a strong synergy between astronomical observations, laboratory astrophysics and astrochemistry, quantum chemistry calculations and astrophysical modeling of line-of-sights. In this review, we'll present and discuss the current state of this perplexing problem. We'll review the progress and the failures that have been encountered in the long quest for the identification of the carriers of these ubiquitous interstellar bands.

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

DTIC Science & Technology

2013-04-24

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals Vernon...datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal . We have developed...As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and

Analytical Study of different types Of network failure detection and possible remedies

NASA Astrophysics Data System (ADS)

Saxena, Shikha; Chandra, Somnath

2012-07-01

Faults in a network have various causes,such as the failure of one or more routers, fiber-cuts, failure of physical elements at the optical layer, or extraneous causes like power outages. These faults are usually detected as failures of a set of dependent logical entities and the links affected by the failed components. A reliable control plane plays a crucial role in creating high-level services in the next-generation transport network based on the Generalized Multiprotocol Label Switching (GMPLS) or Automatically Switched Optical Networks (ASON) model. In this paper, approaches to control-plane survivability, based on protection and restoration mechanisms, are examined. Procedures for the control plane state recovery are also discussed, including link and node failure recovery and the concepts of monitoring paths (MPs) and monitoring cycles (MCs) for unique localization of shared risk linked group (SRLG) failures in all-optical networks. An SRLG failure is a failure of multiple links due to a failure of a common resource. MCs (MPs) start and end at same (distinct) monitoring location(s). They are constructed such that any SRLG failure results in the failure of a unique combination of paths and cycles. We derive necessary and sufficient conditions on the set of MCs and MPs needed for localizing an SRLG failure in an arbitrary graph. Procedure of Protection and Restoration of the SRLG failure by backup re-provisioning algorithm have also been discussed.

Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

NASA Technical Reports Server (NTRS)

Hunter, H. E.

1972-01-01

The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

Respiratory failure in diabetic ketoacidosis.

PubMed

Konstantinov, Nikifor K; Rohrscheib, Mark; Agaba, Emmanuel I; Dorin, Richard I; Murata, Glen H; Tzamaloukas, Antonios H

2015-07-25

Respiratory failure complicating the course of diabetic ketoacidosis (DKA) is a source of increased morbidity and mortality. Detection of respiratory failure in DKA requires focused clinical monitoring, careful interpretation of arterial blood gases, and investigation for conditions that can affect adversely the respiration. Conditions that compromise respiratory function caused by DKA can be detected at presentation but are usually more prevalent during treatment. These conditions include deficits of potassium, magnesium and phosphate and hydrostatic or non-hydrostatic pulmonary edema. Conditions not caused by DKA that can worsen respiratory function under the added stress of DKA include infections of the respiratory system, pre-existing respiratory or neuromuscular disease and miscellaneous other conditions. Prompt recognition and management of the conditions that can lead to respiratory failure in DKA may prevent respiratory failure and improve mortality from DKA.

Respiratory failure in diabetic ketoacidosis

PubMed Central

Konstantinov, Nikifor K; Rohrscheib, Mark; Agaba, Emmanuel I; Dorin, Richard I; Murata, Glen H; Tzamaloukas, Antonios H

2015-01-01

Respiratory failure complicating the course of diabetic ketoacidosis (DKA) is a source of increased morbidity and mortality. Detection of respiratory failure in DKA requires focused clinical monitoring, careful interpretation of arterial blood gases, and investigation for conditions that can affect adversely the respiration. Conditions that compromise respiratory function caused by DKA can be detected at presentation but are usually more prevalent during treatment. These conditions include deficits of potassium, magnesium and phosphate and hydrostatic or non-hydrostatic pulmonary edema. Conditions not caused by DKA that can worsen respiratory function under the added stress of DKA include infections of the respiratory system, pre-existing respiratory or neuromuscular disease and miscellaneous other conditions. Prompt recognition and management of the conditions that can lead to respiratory failure in DKA may prevent respiratory failure and improve mortality from DKA. PMID:26240698

Exploration of available feature detection and identification systems and their performance on radiographs

NASA Astrophysics Data System (ADS)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

Intraoperative indocyanine green videoangiography for identification of pituitary adenomas using a microscopic transsphenoidal approach.

PubMed

Sandow, N; Klene, W; Elbelt, U; Strasburger, C J; Vajkoczy, P

2015-10-01

Initial successful surgical treatment of pituitary adenomas is crucial to reach long-term remission. Indocyanine green (ICG) videoangiography (VA) is well established in vascular neurosurgery nowadays and several reports described ICG application in brain tumor surgery. We designed this study to evaluate the feasibility of intravenous application of ICG and visualisation of a pituitary lesion via the fluorescence mode of the operation microscope. 22 patients with pituitary adenomas were treated with transsphenoidal microsurgery and were included in this study. Intraoperatively 25 mg ICG was administered intravenously and visualized via the fluorescence mode of the operation microscope (Pentero/Zeiss). 22 patients qualified for transsphenoidal surgery presenting with different clinical symptoms (13 patients with acromegaly, 6 with M. Cushing and 3 with other symptoms like vision disorder or dizziness) and identification of a pituitary lesion (21 of 22 patients) in preoperative MR-imaging (mean diameter: 9 mm; SD 3.6; 6 macroadenomas, 15 microadenomas, 1 MR-negative). In all 22 patients ICG VA was performed during surgery. No technical failures or adverse events after drug administration occurred. Visualization was optimal approximately 2.4 min after intravenous application. In all patients the adenoma could be detected via two different types of visualization: direct visualization by fluorophore emission versus indirect detection of the adenoma by a lower ICG fluorescence compared to the surrounding tissue. Our data show that intraoperative ICG VA can be a useful and easily applicable additional diagnostic tool for visualization of pituitary lesions using the microscopic approach.

The validity of student tutors' judgments in early detection of struggling in medical school. A prospective cohort study.

PubMed

O'Neill, Lotte Dyhrberg; Morcke, Anne Mette; Eika, Berit

2016-12-01

Early identification and support of strugglers in medical education is generally recommended in the research literature, though very little evidence of the diagnostic qualities of early teacher judgments in medical education currently exists. The aim of this study was to examine the validity of early diagnosis of struggling in medical school based on informal teacher judgements of in-class behavior. The study design was a prospective cohort study and the outcomes/truth criteria were anatomy failure and medical school drop out. Six weeks into an anatomy course, student tutors attempted to identify medical students, who they reckoned would fail the anatomy course or drop out, based on their everyday experiences with students in a large group educational setting. In addition, they were asked to describe the indicators of struggling they observed. Sixteen student tutors evaluated 429 medical students for signs of struggling. By week six, the student tutors were able to detect approximately 1/4-1/3 of the students who eventually failed or dropped out, and for ¾ of the strugglers they identified, they were correct in their judgments. Informal student tutor's judgements showed incremental validity for both outcomes when controlling for grades obtained in preceeding exams. Lack of participation, lack of commitment, poor academic performance, poor social interactions and general signs of distress were the main indicators of struggling identified. Teachers' informal judgements of in-class behavior may be an untapped source of information in the early identification of struggling medical students with added value above and beyond formal testing.

75 FR 32295 - Expedited Approval of Alternative Test Procedures for the Analysis of Contaminants Under the Safe...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-08

... Identification of Coliform Bacteria and Escherichia coli in Finished Waters, January 2007, Version 1.1... Membrane Filter Test Method for Detection and Identification of Coliform Bacteria and Escherichia coli in... Detection and Identification of Coliform Bacteria and Escherichia coli in Finished Waters. November, 2000...

Heart Failure and Frailty in the Community-Living Elderly Population: What the UFO Study Will Tell Us

PubMed Central

Fung, Erik; Hui, Elsie; Yang, Xiaobo; Lui, Leong T.; Cheng, King F.; Li, Qi; Fan, Yiting; Sahota, Daljit S.; Ma, Bosco H. M.; Lee, Jenny S. W.; Lee, Alex P. W.; Woo, Jean

2018-01-01

Heart failure and frailty are clinical syndromes that present with overlapping phenotypic characteristics. Importantly, their co-presence is associated with increased mortality and morbidity. While mechanical and electrical device therapies for heart failure are vital for select patients with advanced stage disease, the majority of patients and especially those with undiagnosed heart failure would benefit from early disease detection and prompt initiation of guideline-directed medical therapies. In this article, we review the problematic interactions between heart failure and frailty, introduce a focused cardiac screening program for community-living elderly initiated by a mobile communication device app leading to the Undiagnosed heart Failure in frail Older individuals (UFO) study, and discuss how the knowledge of pre-frailty and frailty status could be exploited for the detection of previously undiagnosed heart failure or advanced cardiac disease. The widespread use of mobile devices coupled with increasing availability of novel, effective medical and minimally invasive therapies have incentivized new approaches to heart failure case finding and disease management. PMID:29740330

Extended Testability Analysis Tool

NASA Technical Reports Server (NTRS)

Melcher, Kevin; Maul, William A.; Fulton, Christopher

2012-01-01

The Extended Testability Analysis (ETA) Tool is a software application that supports fault management (FM) by performing testability analyses on the fault propagation model of a given system. Fault management includes the prevention of faults through robust design margins and quality assurance methods, or the mitigation of system failures. Fault management requires an understanding of the system design and operation, potential failure mechanisms within the system, and the propagation of those potential failures through the system. The purpose of the ETA Tool software is to process the testability analysis results from a commercial software program called TEAMS Designer in order to provide a detailed set of diagnostic assessment reports. The ETA Tool is a command-line process with several user-selectable report output options. The ETA Tool also extends the COTS testability analysis and enables variation studies with sensor sensitivity impacts on system diagnostics and component isolation using a single testability output. The ETA Tool can also provide extended analyses from a single set of testability output files. The following analysis reports are available to the user: (1) the Detectability Report provides a breakdown of how each tested failure mode was detected, (2) the Test Utilization Report identifies all the failure modes that each test detects, (3) the Failure Mode Isolation Report demonstrates the system s ability to discriminate between failure modes, (4) the Component Isolation Report demonstrates the system s ability to discriminate between failure modes relative to the components containing the failure modes, (5) the Sensor Sensor Sensitivity Analysis Report shows the diagnostic impact due to loss of sensor information, and (6) the Effect Mapping Report identifies failure modes that result in specified system-level effects.

Biomarkers in acute heart failure.

PubMed

Mallick, Aditi; Januzzi, James L

2015-06-01

The care of patients with acutely decompensated heart failure is being reshaped by the availability and understanding of several novel and emerging heart failure biomarkers. The gold standard biomarkers in heart failure are B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide, which play an important role in the diagnosis, prognosis, and management of acute decompensated heart failure. Novel biomarkers that are increasingly involved in the processes of myocardial injury, neurohormonal activation, and ventricular remodeling are showing promise in improving diagnosis and prognosis among patients with acute decompensated heart failure. These include midregional proatrial natriuretic peptide, soluble ST2, galectin-3, highly-sensitive troponin, and midregional proadrenomedullin. There has also been an emergence of biomarkers for evaluation of acute decompensated heart failure that assist in the differential diagnosis of dyspnea, such as procalcitonin (for identification of acute pneumonia), as well as markers that predict complications of acute decompensated heart failure, such as renal injury markers. In this article, we will review the pathophysiology and usefulness of established and emerging biomarkers for the clinical diagnosis, prognosis, and management of acute decompensated heart failure. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Adolescent inhalant abuse leads to other drug use and impaired growth; implications for diagnosis.

PubMed

Crossin, Rose; Cairney, Sheree; Lawrence, Andrew J; Duncan, Jhodie R

2017-02-01

Abuse of inhalants containing the volatile solvent toluene is a significant public health issue, especially for adolescent and Indigenous communities. Adolescent inhalant abuse can lead to chronic health issues and may initiate a trajectory towards further drug use. Identification of at-risk individuals is difficult and diagnostic tools are limited primarily to measurement of serum toluene. Our objective was to identify the effects of adolescent inhalant abuse on subsequent drug use and growth parameters, and to test the predictive power of growth parameters as a diagnostic measure for inhalant abuse. We retrospectively analysed drug use and growth data from 118 Indigenous males; 86 chronically sniffed petrol as adolescents. Petrol sniffing was the earliest drug used (mean 13 years) and increased the likelihood and earlier use of other drugs. Petrol sniffing significantly impaired height and weight and was associated with meeting 'failure to thrive' criteria; growth diagnostically out-performed serum toluene. Adolescent inhalant abuse increases the risk for subsequent and earlier drug use. It also impairs growth such that individuals meet 'failure to thrive' criteria, representing an improved diagnostic model for inhalant abuse. Implications for Public Health: Improved diagnosis of adolescent inhalant abuse may lead to earlier detection and enhanced health outcomes. © 2016 The Authors.

Change Deafness and the Organizational Properties of Sounds

ERIC Educational Resources Information Center

Gregg, Melissa K.; Samuel, Arthur G.

2008-01-01

Change blindness, or the failure to detect (often large) changes to visual scenes, has been demonstrated in a variety of different situations. Failures to detect auditory changes are far less studied, and thus little is known about the nature of change deafness. Five experiments were conducted to explore the processes involved in change deafness…

46 CFR 161.002-8 - Automatic fire detecting systems, general requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... detecting system shall consist of a power supply; a control unit on which are located visible and audible... control unit. Power failure alarm devices may be separately housed from the control unit and may be combined with other power failure alarm systems when specifically approved. (b) [Reserved] [21 FR 9032, Nov...

46 CFR 161.002-8 - Automatic fire detecting systems, general requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... detecting system shall consist of a power supply; a control unit on which are located visible and audible... control unit. Power failure alarm devices may be separately housed from the control unit and may be combined with other power failure alarm systems when specifically approved. (b) [Reserved] [21 FR 9032, Nov...

Resequencing Pathogen Microarray (RPM) for prospective detection and identification of emergent pathogen strains and variants

NASA Astrophysics Data System (ADS)

Tibbetts, Clark; Lichanska, Agnieszka M.; Borsuk, Lisa A.; Weslowski, Brian; Morris, Leah M.; Lorence, Matthew C.; Schafer, Klaus O.; Campos, Joseph; Sene, Mohamadou; Myers, Christopher A.; Faix, Dennis; Blair, Patrick J.; Brown, Jason; Metzgar, David

2010-04-01

High-density resequencing microarrays support simultaneous detection and identification of multiple viral and bacterial pathogens. Because detection and identification using RPM is based upon multiple specimen-specific target pathogen gene sequences generated in the individual test, the test results enable both a differential diagnostic analysis and epidemiological tracking of detected pathogen strains and variants from one specimen to the next. The RPM assay enables detection and identification of pathogen sequences that share as little as 80% sequence similarity to prototype target gene sequences represented as detector tiles on the array. This capability enables the RPM to detect and identify previously unknown strains and variants of a detected pathogen, as in sentinel cases associated with an infectious disease outbreak. We illustrate this capability using assay results from testing influenza A virus vaccines configured with strains that were first defined years after the design of the RPM microarray. Results are also presented from RPM-Flu testing of three specimens independently confirmed to the positive for the 2009 Novel H1N1 outbreak strain of influenza virus.

A dual-processor multi-frequency implementation of the FINDS algorithm

NASA Technical Reports Server (NTRS)

Godiwala, Pankaj M.; Caglayan, Alper K.

1987-01-01

This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance.

Anomaly Monitoring Method for Key Components of Satellite

PubMed Central

Fan, Linjun; Xiao, Weidong; Tang, Jun

2014-01-01

This paper presented a fault diagnosis method for key components of satellite, called Anomaly Monitoring Method (AMM), which is made up of state estimation based on Multivariate State Estimation Techniques (MSET) and anomaly detection based on Sequential Probability Ratio Test (SPRT). On the basis of analysis failure of lithium-ion batteries (LIBs), we divided the failure of LIBs into internal failure, external failure, and thermal runaway and selected electrolyte resistance (R e) and the charge transfer resistance (R ct) as the key parameters of state estimation. Then, through the actual in-orbit telemetry data of the key parameters of LIBs, we obtained the actual residual value (R X) and healthy residual value (R L) of LIBs based on the state estimation of MSET, and then, through the residual values (R X and R L) of LIBs, we detected the anomaly states based on the anomaly detection of SPRT. Lastly, we conducted an example of AMM for LIBs, and, according to the results of AMM, we validated the feasibility and effectiveness of AMM by comparing it with the results of threshold detective method (TDM). PMID:24587703

Critical Infrastructure Vulnerability to Spatially Localized Failures with Applications to Chinese Railway System.

PubMed

Ouyang, Min; Tian, Hui; Wang, Zhenghua; Hong, Liu; Mao, Zijun

2017-01-17

This article studies a general type of initiating events in critical infrastructures, called spatially localized failures (SLFs), which are defined as the failure of a set of infrastructure components distributed in a spatially localized area due to damage sustained, while other components outside the area do not directly fail. These failures can be regarded as a special type of intentional attack, such as bomb or explosive assault, or a generalized modeling of the impact of localized natural hazards on large-scale systems. This article introduces three SLFs models: node centered SLFs, district-based SLFs, and circle-shaped SLFs, and proposes a SLFs-induced vulnerability analysis method from three aspects: identification of critical locations, comparisons of infrastructure vulnerability to random failures, topologically localized failures and SLFs, and quantification of infrastructure information value. The proposed SLFs-induced vulnerability analysis method is finally applied to the Chinese railway system and can be also easily adapted to analyze other critical infrastructures for valuable protection suggestions. © 2017 Society for Risk Analysis.

Ferrographic and spectrometer oil analysis from a failed gas turbine engine

NASA Technical Reports Server (NTRS)

Jones, W. R., Jr.

1982-01-01

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. It was concluded that a severe surge may have caused interference between rotating and stationary compressor that either directly or indirectly ignited the titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph, a plasma, an atomic absorption, and an emission spectrometer to see if this information would aid in the engine failure diagnosis. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism nor a high level of wear debris was detected in the engine oil sample taken just prior to the test in which the failure occurred. However, low concentrations (0.2 to 0.5 ppm) of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations ( 2 ppm) were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure. The oil analyses eliminated a lubrication system bearing or shaft seal failure as the cause of the engine failure.

Impact of Gate 99mTc DTPA GFR, Serum Creatinine and Urea in Diagnosis of Patients with Chronic Kidney Failure

PubMed Central

Miftari, Rame; Nura, Adem; Topçiu-Shufta, Valdete; Miftari, Valon; Murseli, Arbenita; Haxhibeqiri, Valdete

2017-01-01

Aim: The aim of this study was determination of validity of 99mTcDTPA estimation of GFR for early detection of chronic kidney failure Material and methods: There were 110 patients (54 males and 56 females) with kidney disease referred for evaluation of renal function at UCC of Kosovo. All patients were included in two groups. In the first group were included 30 patients confirmed with renal failure, whereas in the second group were included 80 patients with other renal disease. In study were included only patients with ready results of creatinine, urea and glucose in the blood serum. For estimation of GFR we have used the Gate GFR DTPA method. The statistical data processing was conducted using statistical methods such as arithmetic average, the student t-test, percentage or rate, sensitivity, specificity and accuracy of the test. Results: The average age of all patients was 36 years old. The average age of female was 37 whereas of male 35. Patients with renal failure was significantly older than patients with other renal disease (p<0.005). Renal failure was found in 30 patients (27.27%). The concentration of urea and creatinine in blood serum of patients with renal failure were significantly higher than in patients with other renal disease (P< 0.00001). GFR in patients with renal failure were significantly lower than in patients with other renal disease, 51.75 ml/min (p<0.00001). Sensitivity of uremia and creatininemia for detection of renal failure were 83.33%, whereas sensitivity of 99mTcDTPA GFR was 100%. Specificity of uraemia and creatininemia were 63% whereas specificity of 99mTcDTPA GFR was 47.5%. Diagnostic accuracy of blood urea and creatinine in detecting of renal failure were 69%, whereas diagnostic accuracy of 99mTcDTPA GFR was 61.8%. Conclusion: Gate 99mTc DTPA scintigraphy in collaboration with biochemical tests are very sensitive methods for early detection of patients with chronic renal failure. PMID:28883673

Failure detection and recovery in the assembly/contingency subsystem

NASA Technical Reports Server (NTRS)

Gantenbein, Rex E.

1993-01-01

The Assembly/Contingency Subsystem (ACS) is the primary communications link on board the Space Station. Any failure in a component of this system or in the external devices through which it communicates with ground-based systems will isolate the Station. The ACS software design includes a failure management capability (ACFM) that provides protocols for failure detection, isolation, and recovery (FDIR). The the ACFM design requirements as outlined in the current ACS software requirements specification document are reviewed. The activities carried out in this review include: (1) an informal, but thorough, end-to-end failure mode and effects analysis of the proposed software architecture for the ACFM; and (2) a prototype of the ACFM software, implemented as a C program under the UNIX operating system. The purpose of this review is to evaluate the FDIR protocols specified in the ACS design and the specifications themselves in light of their use in implementing the ACFM. The basis of failure detection in the ACFM is the loss of signal between the ground and the Station, which (under the appropriate circumstances) will initiate recovery to restore communications. This recovery involves the reconfiguration of the ACS to either a backup set of components or to a degraded communications mode. The initiation of recovery depends largely on the criticality of the failure mode, which is defined by tables in the ACFM and can be modified to provide a measure of flexibility in recovery procedures.

Environmental control system transducer development study

NASA Technical Reports Server (NTRS)

Brudnicki, M. J.

1973-01-01

A failure evaluation of the transducers used in the environmental control systems of the Apollo command service module, lunar module, and portable life support system is presented in matrix form for several generic categories of transducers to enable identification of chronic failure modes. Transducer vendors were contacted and asked to supply detailed information. The evaluation data generated for each category of transducer were compiled and published in failure design evaluation reports. The evaluation reports also present a review of the failure and design data for the transducers and suggest both design criteria to improve reliability of the transducers and, where necessary, design concepts for required redesign of the transducers. Remedial designs were implemented on a family of pressure transducers and on the oxygen flow transducer. The design concepts were subjected to analysis, breadboard fabrication, and verification testing.

Proceedings of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Performance Evaluation Workshop

NASA Technical Reports Server (NTRS)

Vane, Gregg (Editor)

1988-01-01

The focus of the workshop was the assessment of data quality by the AVIRIS project. Summaries of 16 of the presentations are published. The AVIRIS performance evaluation period began in June 87 with flight data collection in the eastern U.S., and continued in the west until Oct. 87, after which the instrument was returned for post flight calibration. At the beginning, the sensor met all of the spatial, spectral and radiometric performance requirements except in spectrometer D, where the signal to noise ratio was below the required value. By the end, sensor performance had deteriorated due to failure of 2 critical parts and to some design deficiences. The independent assessment by the NASA investigators confirmed the assessment by the AVIRIS project. Some scientific results were derived and are presented. These include the mapping of the spatial variation of atmospheric precipitable water, detection of shift in chlorophyll red, and mineral identification.

Tourette syndrome in children and adolescents: special considerations.

PubMed

Eapen, Valsamma; Crncec, Rudi

2009-12-01

Tourette syndrome (TS) affects people of all ages, with onset in early childhood and continuing through the different stages of the life cycle into adolescence and adults. This review focuses on barriers to diagnosis and challenges in the management of young patients with TS. Barriers to identification occur at multiple levels, including detection in the community setting (including schools), parents' help-seeking behavior, and cultural influences on such behavior, as well as diagnosis by the medical provider. Challenges to management include unfamiliarity of primary care providers, inconsistencies in the diagnosis and management plan, and failure to recognize comorbid conditions, as well as inadequate knowledge and lack of resources to effectively deal with comorbidities. In addition to the complexities posed by pharmacological interactions, there are unique psychosocial challenges experienced by young people with TS and their families. Effective communication and collaboration between families, health care providers, and school personnel, as well as supportive communities, are essential components of comprehensive management.

Scientific and Regulatory Considerations in Solid Oral Modified Release Drug Product Development.

PubMed

Li, Min; Sander, Sanna; Duan, John; Rosencrance, Susan; Miksinski, Sarah Pope; Yu, Lawrence; Seo, Paul; Rege, Bhagwant

2016-11-01

This review presents scientific and regulatory considerations for the development of solid oral modified release (MR) drug products. It includes a rationale for patient-focused development based on Quality-by-Design (QbD) principles. Product and process understanding of MR products includes identification and risk-based evaluation of critical material attributes (CMAs), critical process parameters (CPPs), and their impact on critical quality attributes (CQAs) that affect the clinical performance. The use of various biopharmaceutics tools that link the CQAs to a predictable and reproducible clinical performance for patient benefit is emphasized. Product and process understanding lead to a more comprehensive control strategy that can maintain product quality through the shelf life and the lifecycle of the drug product. The overall goal is to develop MR products that consistently meet the clinical objectives while mitigating the risks to patients by reducing the probability and increasing the detectability of CQA failures.

ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems

NASA Technical Reports Server (NTRS)

Pachura, David W.; Suleiman, Salem A.; Mendler, Andrew P.

1988-01-01

ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems.

An intelligent control system for failure detection and controller reconfiguration

NASA Technical Reports Server (NTRS)

Biswas, Saroj K.

1994-01-01

We present an architecture of an intelligent restructurable control system to automatically detect failure of system components, assess its impact on system performance and safety, and reconfigure the controller for performance recovery. Fault detection is based on neural network associative memories and pattern classifiers, and is implemented using a multilayer feedforward network. Details of the fault detection network along with simulation results on health monitoring of a dc motor have been presented. Conceptual developments for fault assessment using an expert system and controller reconfiguration using a neural network are outlined.

78 FR 35094 - Denial of Motor Vehicle Defect Petition, DP12-001

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-11

... ``Goldwing'' and was the heaviest motorcycle in BMW's lineup during those model years. As a ``full- dress... motorcycles (with distinct vehicle identification numbers) alleging final drive failures. These reports were...

Characterization of emission microscopy and liquid crystal thermography in IC fault localization

NASA Astrophysics Data System (ADS)

Lau, C. K.; Sim, K. S.

2013-05-01

This paper characterizes two fault localization techniques - Emission Microscopy (EMMI) and Liquid Crystal Thermography (LCT) by using integrated circuit (IC) leakage failures. The majority of today's semiconductor failures do not reveal a clear visual defect on the die surface and therefore require fault localization tools to identify the fault location. Among the various fault localization tools, liquid crystal thermography and frontside emission microscopy are commonly used in most semiconductor failure analysis laboratories. Many people misunderstand that both techniques are the same and both are detecting hot spot in chip failing with short or leakage. As a result, analysts tend to use only LCT since this technique involves very simple test setup compared to EMMI. The omission of EMMI as the alternative technique in fault localization always leads to incomplete analysis when LCT fails to localize any hot spot on a failing chip. Therefore, this research was established to characterize and compare both the techniques in terms of their sensitivity in detecting the fault location in common semiconductor failures. A new method was also proposed as an alternative technique i.e. the backside LCT technique. The research observed that both techniques have successfully detected the defect locations resulted from the leakage failures. LCT wass observed more sensitive than EMMI in the frontside analysis approach. On the other hand, EMMI performed better in the backside analysis approach. LCT was more sensitive in localizing ESD defect location and EMMI was more sensitive in detecting non ESD defect location. Backside LCT was proven to work as effectively as the frontside LCT and was ready to serve as an alternative technique to the backside EMMI. The research confirmed that LCT detects heat generation and EMMI detects photon emission (recombination radiation). The analysis results also suggested that both techniques complementing each other in the IC fault localization. It is necessary for a failure analyst to use both techniques when one of the techniques produces no result.

Identification of insecticide residues with a conducting-polymer electronic nose

Treesearch

A.D. Wilson

2014-01-01

The identification of insecticide residues on crop foliage is needed to make periodic pest management decisions. Electronic-nose (e-nose) methods were developed and tested as a means of acquiring rapid identifications of insecticide residue types at relatively low cost by detection of headspace volatiles released from inert surfaces in vitro. Detection methods were...

Rapid Species Identification of Cooked Poisonous Mushrooms by Using Real-Time PCR▿

PubMed Central

Maeta, Kazuhiko; Ochi, Tomoya; Tokimoto, Keisuke; Shimomura, Norihiro; Maekawa, Nitaro; Kawaguchi, Nobuhisa; Nakaya, Makoto; Kitamoto, Yutaka; Aimi, Tadanori

2008-01-01

Species-specific identification of the major cooked and fresh poisonous mushrooms in Japan was performed using a real-time PCR system. Specific fluorescence signals were detected, and no nonspecific signals were detected. Therefore, we succeeded in developing a species-specific test for the identification of poisonous mushrooms within 1.5 h. PMID:18378653

Decomposition-Based Failure Mode Identification Method for Risk-Free Design of Large Systems

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Stone, Robert B.; Roberts, Rory A.; Clancy, Daniel (Technical Monitor)

2002-01-01

When designing products, it is crucial to assure failure and risk-free operation in the intended operating environment. Failures are typically studied and eliminated as much as possible during the early stages of design. The few failures that go undetected result in unacceptable damage and losses in high-risk applications where public safety is of concern. Published NASA and NTSB accident reports point to a variety of components identified as sources of failures in the reported cases. In previous work, data from these reports were processed and placed in matrix form for all the system components and failure modes encountered, and then manipulated using matrix methods to determine similarities between the different components and failure modes. In this paper, these matrices are represented in the form of a linear combination of failures modes, mathematically formed using Principal Components Analysis (PCA) decomposition. The PCA decomposition results in a low-dimensionality representation of all failure modes and components of interest, represented in a transformed coordinate system. Such a representation opens the way for efficient pattern analysis and prediction of failure modes with highest potential risks on the final product, rather than making decisions based on the large space of component and failure mode data. The mathematics of the proposed method are explained first using a simple example problem. The method is then applied to component failure data gathered from helicopter, accident reports to demonstrate its potential.

Thermal runaway detection of cylindrical 18650 lithium-ion battery under quasi-static loading conditions

NASA Astrophysics Data System (ADS)

Sheikh, Muhammad; Elmarakbi, Ahmed; Elkady, Mustafa

2017-12-01

This paper focuses on state of charge (SOC) dependent mechanical failure analysis of 18650 lithium-ion battery to detect signs of thermal runaway. Quasi-static loading conditions are used with four test protocols (Rod, Circular punch, three-point bend and flat plate) to analyse the propagation of mechanical failures and failure induced temperature changes. Finite element analysis (FEA) is used to model single battery cell with the concentric layered formation which represents a complete cell. The numerical simulation model is designed with solid element formation where stell casing and all layers followed the same formation, and fine mesh is used for all layers. Experimental work is also performed to analyse deformation of 18650 lithium-ion cell. The numerical simulation model is validated with experimental results. Deformation of cell mimics thermal runaway and various thermal runaway detection strategies are employed in this work including, force-displacement, voltage-temperature, stress-strain, SOC dependency and separator failure. Results show that cell can undergo severe conditions even with no fracture or rupture, these conditions may slow to develop but they can lead to catastrophic failures. The numerical simulation technique is proved to be useful in predicting initial battery failures, and results are in good correlation with the experimental results.

The Artful Dodger: Answering the Wrong Question the Right Way

ERIC Educational Resources Information Center

Rogers, Todd; Norton, Michael I.

2011-01-01

What happens when speakers try to "dodge" a question they would rather not answer by answering a different question? In 4 studies, we show that listeners can fail to detect dodges when speakers answer similar--but objectively incorrect--questions (the "artful dodge"), a detection failure that goes hand-in-hand with a failure to rate dodgers more…

A detailed description of the sequential probability ratio test for 2-IMU FDI

NASA Technical Reports Server (NTRS)

Rich, T. M.

1976-01-01

The sequential probability ratio test (SPRT) for 2-IMU FDI (inertial measuring unit failure detection/isolation) is described. The SPRT is a statistical technique for detecting and isolating soft IMU failures originally developed for the strapdown inertial reference unit. The flowchart of a subroutine incorporating the 2-IMU SPRT is included.

Rate based failure detection

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

Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or datamore » paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.« less

HYTESS 2: A Hypothetical Turbofan Engine Simplified Simulation with multivariable control and sensor analytical redundancy

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1986-01-01

A hypothetical turbofan engine simplified simulation with a multivariable control and sensor failure detection, isolation, and accommodation logic (HYTESS II) is presented. The digital program, written in FORTRAN, is self-contained, efficient, realistic and easily used. Simulated engine dynamics were developed from linearized operating point models. However, essential nonlinear effects are retained. The simulation is representative of the hypothetical, low bypass ratio turbofan engine with an advanced control and failure detection logic. Included is a description of the engine dynamics, the control algorithm, and the sensor failure detection logic. Details of the simulation including block diagrams, variable descriptions, common block definitions, subroutine descriptions, and input requirements are given. Example simulation results are also presented.

A solenoid failure detection system for cold gas attitude control jet valves

NASA Technical Reports Server (NTRS)

Johnston, P. A.

1970-01-01

The development of a solenoid valve failure detection system is described. The technique requires the addition of a radioactive gas to the propellant of a cold gas jet attitude control system. Solenoid failure is detected with an avalanche radiation detector located in the jet nozzle which senses the radiation emitted by the leaking radioactive gas. Measurements of carbon monoxide leakage rates through a Mariner type solenoid valve are presented as a function of gas activity and detector configuration. A cylindrical avalanche detector with a factor of 40 improvement in leak sensitivity is proposed for flight systems because it allows the quantity of radioactive gas that must be added to the propellant to be reduced to a practical level.

LWIR hyperspectral imaging application and detection of chemical precursors

NASA Astrophysics Data System (ADS)

Lavoie, Hugo; Thériault, Jean-Marc; Bouffard, François; Puckrin, Eldon; Dubé, Denis

2012-10-01

Detection and identification of Toxic industrial chemicals (TICs) represent a major challenge to protect and sustain first responder and public security. In this context, passive Hyperspectral Imaging (HSI) is a promising technology for the standoff detection and identification of chemical vapors emanating from a distant location. To investigate this method, the Department of National Defense and Public Safety Canada have mandated Defense Research and Development Canada (DRDC) - Valcartier to develop and test Very Long Wave Infrared (VLWIR) HSI sensors for standoff detection. The initial effort was focused to address the standoff detection and identification of toxic industrial chemicals (TICs), surrogates and precursors. Sensors such as the Improved Compact ATmospheric Sounding Interferometer (iCATSI) and the Multi-option Differential Detection and Imaging Fourier Spectrometer (MoDDIFS) were developed for this application. This paper presents the sensor developments and preliminary results of standoff detection and identification of TICs and precursors. The iCATSI and MoDDIFS sensors are based on the optical differential Fourier-transform infrared (FTIR) radiometric technology and are able to detect, spectrally resolve and identify small leak at ranges in excess of 1 km. Results from a series of trials in asymmetric threat type scenarios are reported. These results serve to establish the potential of passive standoff HSI detection of TICs, precursors and surrogates.

The evaluation of a mental health facilitator in general practice: effects on recognition, management, and outcome of mental illness.

PubMed

Bashir, K; Blizard, B; Bosanquet, A; Bosanquet, N; Mann, A; Jenkins, R

2000-08-01

Facilitation uses personal contact between the facilitator and the professional to encourage good practice and better service organisation. The model has been applied to physical illness but not to psychiatric disorders. To determine if a non-specialist facilitator can improve the recognition, management, and outcome of psychiatric illness presenting to general practitioners (GPs). Six practices were visited over an 18-month period by a facilitator whose activities included providing guidelines and organising training initiatives. Six other practices acted as controls. Recognition (identification index of family doctors), management (psychotropic prescribing, psychological consultations with the GP, specialist mental health treatment, and the use of medical interventions and investigations), and patient outcome at four months were assessed before and after intervention. The mean identification index of facilitator GPs rose from 0.51 to 0.64 following intervention, while that of the control GPs fell from 0.67 to 0.59 (P = 0.046). The facilitator had no detectable effect on management or patient outcome. The facilitator improved recognition of psychiatric illness by GPs. Generic facilitators can be trained to take on a mental health role; however, the failure to achieve more fundamental changes in treatment and outcome implies that facilitator intervention requires development.

Gene and cell-based therapies for heart disease.

PubMed

Melo, Luis G; Pachori, Alok S; Kong, Deling; Gnecchi, Massimiliano; Wang, Kai; Pratt, Richard E; Dzau, Victor J

2004-04-01

Heart disease remains the prevalent cause of premature death and accounts for a significant proportion of all hospital admissions. Recent developments in understanding the molecular mechanisms of myocardial disease have led to the identification of new therapeutic targets, and the availability of vectors with enhanced myocardial tropism offers the opportunity for the design of gene therapies for both protection and rescue of the myocardium. Genetic therapies have been devised to treat complex diseases such as myocardial ischemia, heart failure, and inherited myopathies in various animal models. Some of these experimental therapies have made a successful transition to clinical trial and are being considered for use in human patients. The recent isolation of endothelial and cardiomyocyte precursor cells from adult bone marrow may permit the design of strategies for repair of the damaged heart. Cell-based therapies may have potential application in neovascularization and regeneration of ischemic and infarcted myocardium, in blood vessel reconstruction, and in bioengineering of artificial organs and prostheses. We expect that advances in the field will lead to the development of safer and more efficient vectors. The advent of genomic screening technology should allow the identification of novel therapeutic targets and facilitate the detection of disease-causing polymorphisms that may lead to the design of individualized gene and cell-based therapies.

Simulation Assisted Risk Assessment: Blast Overpressure Modeling

NASA Technical Reports Server (NTRS)

Lawrence, Scott L.; Gee, Ken; Mathias, Donovan; Olsen, Michael

2006-01-01

A probabilistic risk assessment (PRA) approach has been developed and applied to the risk analysis of capsule abort during ascent. The PRA is used to assist in the identification of modeling and simulation applications that can significantly impact the understanding of crew risk during this potentially dangerous maneuver. The PRA approach is also being used to identify the appropriate level of fidelity for the modeling of those critical failure modes. The Apollo launch escape system (LES) was chosen as a test problem for application of this approach. Failure modes that have been modeled and/or simulated to date include explosive overpressure-based failure, explosive fragment-based failure, land landing failures (range limits exceeded either near launch or Mode III trajectories ending on the African continent), capsule-booster re-contact during separation, and failure due to plume-induced instability. These failure modes have been investigated using analysis tools in a variety of technical disciplines at various levels of fidelity. The current paper focuses on the development and application of a blast overpressure model for the prediction of structural failure due to overpressure, including the application of high-fidelity analysis to predict near-field and headwinds effects.

Failure detection and isolation analysis of a redundant strapdown inertial measurement unit

NASA Technical Reports Server (NTRS)

Motyka, P.; Landey, M.; Mckern, R.

1981-01-01

The objective of this study was to define and develop techniques for failure detection and isolation (FDI) algorithms for a dual fail/operational redundant strapdown inertial navigation system are defined and developed. The FDI techniques chosen include provisions for hard and soft failure detection in the context of flight control and navigation. Analyses were done to determine error detection and switching levels for the inertial navigation system, which is intended for a conventional takeoff or landing (CTOL) operating environment. In addition, investigations of false alarms and missed alarms were included for the FDI techniques developed, along with the analyses of filters to be used in conjunction with FDI processing. Two specific FDI algorithms were compared: the generalized likelihood test and the edge vector test. A deterministic digital computer simulation was used to compare and evaluate the algorithms and FDI systems.

China’s Air Defense Identification Zone: Concept, Issues at Stake and Regional Impact

DTIC Science & Technology

2013-12-23

early Chinese legal culture ” Karen Turner “War, Punishment, and The Law of Nature in Early Chinese Concepts of The State”, Harvard Journal of Asiatic...lack of strategic direction, moral relativism , a failure to gauge the significance of what is at stake, and distraction with events in other regions of...WORKING PAPER 1 posted 23 December 2013 CHINA’S AIR DEFENSE IDENTIFICATION ZONE: CONCEPT , ISSUES AT STAKE AND REGIONAL IMPACT

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

2D signature for detection and identification of drugs

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Shen, Jingling; Zhang, Cunlin; Zhou, Qingli; Shi, Yulei

2011-06-01

The method of spectral dynamics analysis (SDA-method) is used for obtaining the2D THz signature of drugs. This signature is used for the detection and identification of drugs with similar Fourier spectra by transmitted THz signal. We discuss the efficiency of SDA method for the identification problem of pure methamphetamine (MA), methylenedioxyamphetamine (MDA), 3, 4-methylenedioxymethamphetamine (MDMA) and Ketamine.

Identification of the actual state and entity availability forecasting in power engineering using neural-network technologies

NASA Astrophysics Data System (ADS)

Protalinsky, O. M.; Shcherbatov, I. A.; Stepanov, P. V.

2017-11-01

A growing number of severe accidents in RF call for the need to develop a system that could prevent emergency situations. In a number of cases accident rate is stipulated by careless inspections and neglects in developing repair programs. Across the country rates of accidents are growing because of a so-called “human factor”. In this regard, there has become urgent the problem of identification of the actual state of technological facilities in power engineering using data on engineering processes running and applying artificial intelligence methods. The present work comprises four model states of manufacturing equipment of engineering companies: defect, failure, preliminary situation, accident. Defect evaluation is carried out using both data from SCADA and ASEPCR and qualitative information (verbal assessments of experts in subject matter, photo- and video materials of surveys processed using pattern recognition methods in order to satisfy the requirements). Early identification of defects makes possible to predict the failure of manufacturing equipment using mathematical techniques of artificial neural network. In its turn, this helps to calculate predicted characteristics of reliability of engineering facilities using methods of reliability theory. Calculation of the given parameters provides the real-time estimation of remaining service life of manufacturing equipment for the whole operation period. The neural networks model allows evaluating possibility of failure of a piece of equipment consistent with types of actual defects and their previous reasons. The article presents the grounds for a choice of training and testing samples for the developed neural network, evaluates the adequacy of the neural networks model, and shows how the model can be used to forecast equipment failure. There have been carried out simulating experiments using a computer and retrospective samples of actual values for power engineering companies. The efficiency of the developed model for different types of manufacturing equipment has been proved. There have been offered other research areas in terms of the presented subject matter.

Method for the detection of Salmonella enterica serovar Enteritidis

DOEpatents

Agron, Peter G.; Andersen, Gary L.; Walker, Richard L.

2008-10-28

Described herein is the identification of a novel Salmonella enterica serovar Enteritidis locus that serves as a marker for DNA-based identification of this bacterium. In addition, three primer pairs derived from this locus that may be used in a nucleotide detection method to detect the presence of the bacterium are also disclosed herein.

Immunity-Based Aircraft Fault Detection System

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

Repeated Induction of Inattentional Blindness in a Simulated Aviation Environment

NASA Technical Reports Server (NTRS)

Kennedy, Kellie D.; Stephens, Chad L.; Williams, Ralph A.; Schutte, Paul C.

2017-01-01

The study reported herein is a subset of a larger investigation on the role of automation in the context of the flight deck and used a fixed-based, human-in-the-loop simulator. This paper explored the relationship between automation and inattentional blindness (IB) occurrences in a repeated induction paradigm using two types of runway incursions. The critical stimuli for both runway incursions were directly relevant to primary task performance. Sixty non-pilot participants performed the final five minutes of a landing scenario twice in one of three automation conditions: full automation (FA), partial automation (PA), and no automation (NA). The first induction resulted in a 70 percent (42 of 60) detection failure rate with those in the PA condition significantly more likely to detect the incursion compared to the FA condition or the NA condition. The second induction yielded a 50 percent detection failure rate. Although detection improved (detection failure rates declined) in all conditions, those in the FA condition demonstrated the greatest improvement with doubled detection rates. The detection behavior in the first trial did not preclude a failed detection in the second induction. Group membership (IB vs. Detection) in the FA condition showed a greater improvement than those in the NA condition and rated the Mental Demand and Effort subscales of the NASA-TLX (NASA Task Load Index) significantly higher for Time 2 compared Time 1. Participants in the FA condition used the experience of IB exposure to improve task performance whereas those in the NA condition did not, indicating the availability and reallocation of attentional resources in the FA condition. These findings support the role of engagement in operational attention detriment and the consideration of attentional failure causation to determine appropriate mitigation strategies.

Life Cost Based FMEA Manual: A Step by Step Guide to Carrying Out a Cost-based Failure Modes and Effects Analysis

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

Rhee, Seung; Spencer, Cherrill; /Stanford U. /SLAC

2009-01-23

Failure occurs when one or more of the intended functions of a product are no longer fulfilled to the customer's satisfaction. The most critical product failures are those that escape design reviews and in-house quality inspection and are found by the customer. The product may work for a while until its performance degrades to an unacceptable level or it may have not worked even before customer took possession of the product. The end results of failures which may lead to unsafe conditions or major losses of the main function are rated high in severity. Failure Modes and Effects Analysis (FMEA)more » is a tool widely used in the automotive, aerospace, and electronics industries to identify, prioritize, and eliminate known potential failures, problems, and errors from systems under design, before the product is released (Stamatis, 1997). Several industrial FMEA standards such as those published by the Society of Automotive Engineers, US Department of Defense, and the Automotive Industry Action Group employ the Risk Priority Number (RPN) to measure risk and severity of failures. The Risk Priority Number (RPN) is a product of 3 indices: Occurrence (O), Severity (S), and Detection (D). In a traditional FMEA process design engineers typically analyze the 'root cause' and 'end-effects' of potential failures in a sub-system or component and assign penalty points through the O, S, D values to each failure. The analysis is organized around categories called failure modes, which link the causes and effects of failures. A few actions are taken upon completing the FMEA worksheet. The RPN column generally will identify the high-risk areas. The idea of performing FMEA is to eliminate or reduce known and potential failures before they reach the customers. Thus, a plan of action must be in place for the next task. Not all failures can be resolved during the product development cycle, thus prioritization of actions must be made within the design group. One definition of detection difficulty (D) is how well the organization controls the development process. Another definition relates to the detectability of a particular failure in the product when it is in the hands of the customer. The former asks 'What is the chance of catching the problem before we give it to the customer'? The latter asks 'What is the chance of the customer catching the problem before the problem results in a catastrophic failure?' (Palady, 1995) These differing definitions confuse the FMEA users when one tries to determine detection difficulty. Are we trying to measure how easy it is to detect where a failure has occurred or when it has occurred? Or are we trying to measure how easy or difficult it is to prevent failures? Ordinal scale variables are used to rank-order industries such as, hotels, restaurants, and movies (Note that a 4 star hotel is not necessarily twice as good as a 2 star hotel). Ordinal values preserve rank in a group of items, but the distance between the values cannot be measured since a distance function does not exist. Thus, the product or sum of ordinal variables loses its rank since each parameter has different scales. The RPN is a product of 3 independent ordinal variables, it can indicate that some failure types are 'worse' than others, but give no quantitative indication of their relative effects. To resolve the ambiguity of measuring detection difficulty and the irrational logic of multiplying 3 ordinal indices, a new methodology was created to overcome these shortcomings, Life Cost-Based FMEA. Life Cost-Based FMEA measures failure/risk in terms of monetary cost. Cost is a universal parameter that can be easily related to severity by engineers and others. Thus, failure cost can be estimated using the following simplest form: Expected Failure Cost = {sup n}{Sigma}{sub i=1}p{sub i}c{sub i}, p: Probability of a particular failure occurring; c: Monetary cost associated with that particular failure; and n: Total number of failure scenarios. FMEA is most effective when there are inputs into it from all concerned disciplines of the product development team. However, FMEA is a long process and can become tedious and won't be effective if too many people participate. An ideal team should have 3 to 4 people from: design, manufacturing, and service departments if possible. Depending on how complex the system is, the entire process can take anywhere from one to four weeks working full time. Thus, it is important to agree to the time commitment before starting the analysis else, anxious managers might stop the procedure before it is completed.« less

In chronic myeloid leukemia patients on second-line tyrosine kinase inhibitor therapy, deep sequencing of BCR-ABL1 at the time of warning may allow sensitive detection of emerging drug-resistant mutants.

PubMed

Soverini, Simona; De Benedittis, Caterina; Castagnetti, Fausto; Gugliotta, Gabriele; Mancini, Manuela; Bavaro, Luana; Machova Polakova, Katerina; Linhartova, Jana; Iurlo, Alessandra; Russo, Domenico; Pane, Fabrizio; Saglio, Giuseppe; Rosti, Gianantonio; Cavo, Michele; Baccarani, Michele; Martinelli, Giovanni

2016-08-02

Imatinib-resistant chronic myeloid leukemia (CML) patients receiving second-line tyrosine kinase inhibitor (TKI) therapy with dasatinib or nilotinib have a higher risk of disease relapse and progression and not infrequently BCR-ABL1 kinase domain (KD) mutations are implicated in therapeutic failure. In this setting, earlier detection of emerging BCR-ABL1 KD mutations would offer greater chances of efficacy for subsequent salvage therapy and limit the biological consequences of full BCR-ABL1 kinase reactivation. Taking advantage of an already set up and validated next-generation deep amplicon sequencing (DS) assay, we aimed to assess whether DS may allow a larger window of detection of emerging BCR-ABL1 KD mutants predicting for an impending relapse. a total of 125 longitudinal samples from 51 CML patients who had acquired dasatinib- or nilotinib-resistant mutations during second-line therapy were analyzed by DS from the time of failure and mutation detection by conventional sequencing backwards. BCR-ABL1/ABL1%(IS) transcript levels were used to define whether the patient had 'optimal response', 'warning' or 'failure' at the time of first mutation detection by DS. DS was able to backtrack dasatinib- or nilotinib-resistant mutations to the previous sample(s) in 23/51 (45 %) pts. Median mutation burden at the time of first detection by DS was 5.5 % (range, 1.5-17.5 %); median interval between detection by DS and detection by conventional sequencing was 3 months (range, 1-9 months). In 5 cases, the mutations were detectable at baseline. In the remaining cases, response level at the time mutations were first detected by DS could be defined as 'Warning' (according to the 2013 ELN definitions of response to 2nd-line therapy) in 13 cases, as 'Optimal response' in one case, as 'Failure' in 4 cases. No dasatinib- or nilotinib-resistant mutations were detected by DS in 15 randomly selected patients with 'warning' at various timepoints, that later turned into optimal responders with no treatment changes. DS enables a larger window of detection of emerging BCR-ABL1 KD mutations predicting for an impending relapse. A 'Warning' response may represent a rational trigger, besides 'Failure', for DS-based mutation screening in CML patients undergoing second-line TKI therapy.

A signal-detection-based diagnostic-feature-detection model of eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2014-04-01

The theoretical understanding of eyewitness identifications made from a police lineup has long been guided by the distinction between absolute and relative decision strategies. In addition, the accuracy of identifications associated with different eyewitness memory procedures has long been evaluated using measures like the diagnosticity ratio (the correct identification rate divided by the false identification rate). Framed in terms of signal-detection theory, both the absolute/relative distinction and the diagnosticity ratio are mainly relevant to response bias while remaining silent about the key issue of diagnostic accuracy, or discriminability (i.e., the ability to tell the difference between innocent and guilty suspects in a lineup). Here, we propose a signal-detection-based model of eyewitness identification, one that encourages the use of (and helps to conceptualize) receiver operating characteristic (ROC) analysis to measure discriminability. Recent ROC analyses indicate that the simultaneous presentation of faces in a lineup yields higher discriminability than the presentation of faces in isolation, and we propose a diagnostic feature-detection hypothesis to account for that result. According to this hypothesis, the simultaneous presentation of faces allows the eyewitness to appreciate that certain facial features (viz., those that are shared by everyone in the lineup) are non-diagnostic of guilt. To the extent that those non-diagnostic features are discounted in favor of potentially more diagnostic features, the ability to discriminate innocent from guilty suspects will be enhanced.

System for Anomaly and Failure Detection (SAFD) system development

NASA Technical Reports Server (NTRS)

Oreilly, D.

1992-01-01

This task specified developing the hardware and software necessary to implement the System for Anomaly and Failure Detection (SAFD) algorithm, developed under Technology Test Bed (TTB) Task 21, on the TTB engine stand. This effort involved building two units; one unit to be installed in the Block II Space Shuttle Main Engine (SSME) Hardware Simulation Lab (HSL) at Marshall Space Flight Center (MSFC), and one unit to be installed at the TTB engine stand. Rocketdyne personnel from the HSL performed the task. The SAFD algorithm was developed as an improvement over the current redline system used in the Space Shuttle Main Engine Controller (SSMEC). Simulation tests and execution against previous hot fire tests demonstrated that the SAFD algorithm can detect engine failure as much as tens of seconds before the redline system recognized the failure. Although the current algorithm only operates during steady state conditions (engine not throttling), work is underway to expand the algorithm to work during transient condition.

Ferrographic and spectrometer oil analysis from a failed gas turbine engine

NASA Technical Reports Server (NTRS)

Jones, W. R., Jr.

1983-01-01

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. It was concluded that a severe surge may have caused interference between rotating and stationary compressor parts that either directly or indirectly ignited the titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph, and with plasma, atomic absorption, and emission spectrometers to see if this information would aid in the engine failure diagnosis. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism nor a high level of wear debris was detected in the engine oil sample taken just prior to the test in which the failure occurred. However, low concentrations (0.2 to 0.5 ppm) of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations (2 ppm) were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure. The oil analyses eliminated a lubrication system bearing or shaft seal failure as the cause of the engine failure. Previously announced in STAR as N83-12433

Early identification of microorganisms in blood culture prior to the detection of a positive signal in the BACTEC FX system using matrix-assisted laser desorption/ionization-time of flight mass spectrometry.

PubMed

Wang, Ming-Cheng; Lin, Wei-Hung; Yan, Jing-Jou; Fang, Hsin-Yi; Kuo, Te-Hui; Tseng, Chin-Chung; Wu, Jiunn-Jong

2015-08-01

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is a valuable method for rapid identification of blood stream infection (BSI) pathogens. Integration of MALDI-TOF MS and blood culture system can speed the identification of causative BSI microorganisms. We investigated the minimal microorganism concentrations of common BSI pathogens required for positive blood culture using BACTEC FX and for positive identification using MALDI-TOF MS. The time to detection with positive BACTEC FX and minimal incubation time with positive MALDI-TOF MS identification were determined for earlier identification of common BSI pathogens. The minimal microorganism concentrations required for positive blood culture using BACTEC FX were >10(7)-10(8) colony forming units/mL for most of the BSI pathogens. The minimal microorganism concentrations required for identification using MALDI-TOF MS were > 10(7) colony forming units/mL. Using simulated BSI models, one can obtain enough bacterial concentration from blood culture bottles for successful identification of five common Gram-positive and Gram-negative bacteria using MALDI-TOF MS 1.7-2.3 hours earlier than the usual time to detection in blood culture systems. This study provides an approach to earlier identification of BSI pathogens prior to the detection of a positive signal in the blood culture system using MALDI-TOF MS, compared to current methods. It can speed the time for identification of BSI pathogens and may have benefits of earlier therapy choice and on patient outcome. Copyright © 2013. Published by Elsevier B.V.

Automated Photoreceptor Cell Identification on Nonconfocal Adaptive Optics Images Using Multiscale Circular Voting.

PubMed

Liu, Jianfei; Jung, HaeWon; Dubra, Alfredo; Tam, Johnny

2017-09-01

Adaptive optics scanning light ophthalmoscopy (AOSLO) has enabled quantification of the photoreceptor mosaic in the living human eye using metrics such as cell density and average spacing. These rely on the identification of individual cells. Here, we demonstrate a novel approach for computer-aided identification of cone photoreceptors on nonconfocal split detection AOSLO images. Algorithms for identification of cone photoreceptors were developed, based on multiscale circular voting (MSCV) in combination with a priori knowledge that split detection images resemble Nomarski differential interference contrast images, in which dark and bright regions are present on the two sides of each cell. The proposed algorithm locates dark and bright region pairs, iteratively refining the identification across multiple scales. Identification accuracy was assessed in data from 10 subjects by comparing automated identifications with manual labeling, followed by computation of density and spacing metrics for comparison to histology and published data. There was good agreement between manual and automated cone identifications with overall recall, precision, and F1 score of 92.9%, 90.8%, and 91.8%, respectively. On average, computed density and spacing values using automated identification were within 10.7% and 11.2% of the expected histology values across eccentricities ranging from 0.5 to 6.2 mm. There was no statistically significant difference between MSCV-based and histology-based density measurements (P = 0.96, Kolmogorov-Smirnov 2-sample test). MSCV can accurately detect cone photoreceptors on split detection images across a range of eccentricities, enabling quick, objective estimation of photoreceptor mosaic metrics, which will be important for future clinical trials utilizing adaptive optics.

Application of digital field photographs as documents for tropical plant inventory1

PubMed Central

LaFrankie, James V.; Chua, Anna I.

2015-01-01

Premise of the study: We tested the credibility and significance of digital field photographs as supplements or substitutes for conventional herbarium specimens with particular relevance to exploration of the tropics. Methods: We made 113 collections in triplicate at a species-rich mountain in the Philippines while we took 1238 digital photographs of the same plants. We then identified the plants from the photographs alone, categorized the confidence of the identification and the reason for failure to identify, and compared the results to identifications based on the dried specimens. Results: We identified 72.6% of the photographic sets with high confidence and 27.4% with low confidence or only to genus. In no case was a confident identification altered by subsequent examination of the dried specimen. The failure to identify photographic sets to species was due to the lack of a key feature in 67.8% of the cases and due to a poorly understood taxonomy in 32.2%. Discussion: We conclude that digital photographs cannot replace traditional herbarium specimens as the primary elements that document tropical plant diversity. However, photographs represent a new and important artifact that aids an expedient survey of tropical plant diversity while encouraging broad public participation. PMID:25995976

Comparing Different Fault Identification Algorithms in Distributed Power System

NASA Astrophysics Data System (ADS)

Alkaabi, Salim

A power system is a huge complex system that delivers the electrical power from the generation units to the consumers. As the demand for electrical power increases, distributed power generation was introduced to the power system. Faults may occur in the power system at any time in different locations. These faults cause a huge damage to the system as they might lead to full failure of the power system. Using distributed generation in the power system made it even harder to identify the location of the faults in the system. The main objective of this work is to test the different fault location identification algorithms while tested on a power system with the different amount of power injected using distributed generators. As faults may lead the system to full failure, this is an important area for research. In this thesis different fault location identification algorithms have been tested and compared while the different amount of power is injected from distributed generators. The algorithms were tested on IEEE 34 node test feeder using MATLAB and the results were compared to find when these algorithms might fail and the reliability of these methods.

Negative Selection Algorithm for Aircraft Fault Detection

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The detection algorithm uses body-axes angular rate sensory data exhibiting the normal flight behavior patterns, to generate probabilistically a set of fault detectors that can detect any abnormalities (including faults and damages) in the behavior pattern of the aircraft flight. We performed experiments with datasets (collected under normal and various simulated failure conditions) using the NASA Ames man-in-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.

Gaussian process surrogates for failure detection: A Bayesian experimental design approach

NASA Astrophysics Data System (ADS)

Wang, Hongqiao; Lin, Guang; Li, Jinglai

2016-05-01

An important task of uncertainty quantification is to identify the probability of undesired events, in particular, system failures, caused by various sources of uncertainties. In this work we consider the construction of Gaussian process surrogates for failure detection and failure probability estimation. In particular, we consider the situation that the underlying computer models are extremely expensive, and in this setting, determining the sampling points in the state space is of essential importance. We formulate the problem as an optimal experimental design for Bayesian inferences of the limit state (i.e., the failure boundary) and propose an efficient numerical scheme to solve the resulting optimization problem. In particular, the proposed limit-state inference method is capable of determining multiple sampling points at a time, and thus it is well suited for problems where multiple computer simulations can be performed in parallel. The accuracy and performance of the proposed method is demonstrated by both academic and practical examples.

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

Katti, Amogh; Di Fatta, Giuseppe; Naughton III, Thomas J

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implementedmore » and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.« less

Decrease the Number of Glovebox Glove Breaches and Failures

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

Hurtle, Jackie C.

2013-12-24

Los Alamos National Laboratory (LANL) is committed to the protection of the workers, public, and environment while performing work and uses gloveboxes as engineered controls to protect workers from exposure to hazardous materials while performing plutonium operations. Glovebox gloves are a weak link in the engineered controls and are a major cause of radiation contamination events which can result in potential worker exposure and localized contamination making operational areas off-limits and putting programmatic work on hold. Each day of lost opportunity at Technical Area (TA) 55, Plutonium Facility (PF) 4 is estimated at $1.36 million. Between July 2011 and Junemore » 2013, TA-55-PF-4 had 65 glovebox glove breaches and failures with an average of 2.7 per month. The glovebox work follows the five step safety process promoted at LANL with a decision diamond interjected for whether or not a glove breach or failure event occurred in the course of performing glovebox work. In the event that no glove breach or failure is detected, there is an additional decision for whether or not contamination is detected. In the event that contamination is detected, the possibility for a glove breach or failure event is revisited.« less

Formal Specification and Validation of a Hybrid Connectivity Restoration Algorithm for Wireless Sensor and Actor Networks †

PubMed Central

Imran, Muhammad; Zafar, Nazir Ahmad

2012-01-01

Maintaining inter-actor connectivity is extremely crucial in mission-critical applications of Wireless Sensor and Actor Networks (WSANs), as actors have to quickly plan optimal coordinated responses to detected events. Failure of a critical actor partitions the inter-actor network into disjoint segments besides leaving a coverage hole, and thus hinders the network operation. This paper presents a Partitioning detection and Connectivity Restoration (PCR) algorithm to tolerate critical actor failure. As part of pre-failure planning, PCR determines critical/non-critical actors based on localized information and designates each critical node with an appropriate backup (preferably non-critical). The pre-designated backup detects the failure of its primary actor and initiates a post-failure recovery process that may involve coordinated multi-actor relocation. To prove the correctness, we construct a formal specification of PCR using Z notation. We model WSAN topology as a dynamic graph and transform PCR to corresponding formal specification using Z notation. Formal specification is analyzed and validated using the Z Eves tool. Moreover, we simulate the specification to quantitatively analyze the efficiency of PCR. Simulation results confirm the effectiveness of PCR and the results shown that it outperforms contemporary schemes found in the literature.

On-line Bayesian model updating for structural health monitoring

NASA Astrophysics Data System (ADS)

Rocchetta, Roberto; Broggi, Matteo; Huchet, Quentin; Patelli, Edoardo

2018-03-01

Fatigue induced cracks is a dangerous failure mechanism which affects mechanical components subject to alternating load cycles. System health monitoring should be adopted to identify cracks which can jeopardise the structure. Real-time damage detection may fail in the identification of the cracks due to different sources of uncertainty which have been poorly assessed or even fully neglected. In this paper, a novel efficient and robust procedure is used for the detection of cracks locations and lengths in mechanical components. A Bayesian model updating framework is employed, which allows accounting for relevant sources of uncertainty. The idea underpinning the approach is to identify the most probable crack consistent with the experimental measurements. To tackle the computational cost of the Bayesian approach an emulator is adopted for replacing the computationally costly Finite Element model. To improve the overall robustness of the procedure, different numerical likelihoods, measurement noises and imprecision in the value of model parameters are analysed and their effects quantified. The accuracy of the stochastic updating and the efficiency of the numerical procedure are discussed. An experimental aluminium frame and on a numerical model of a typical car suspension arm are used to demonstrate the applicability of the approach.

Hot spot detection, segmentation, and identification in PET images

NASA Astrophysics Data System (ADS)

Blaffert, Thomas; Meetz, Kirsten

2006-03-01

Positron Emission Tomography (PET) images provide functional or metabolic information from areas of high concentration of [18F]fluorodeoxyglucose (FDG) tracer, the "hot spots". These hot spots can be easily detected by the eye, but delineation and size determination required e.g. for diagnosis and staging of cancer is a tedious task that demands for automation. The approach for such an automated hot spot segmentation described in this paper comprises three steps: A region of interest detection by the watershed transform, a heart identification by an evaluation of scan lines, and the final segmentation of hot spot areas by a local threshold. The region of interest detection is the essential step, since it localizes the hot spot identification and the final segmentation. The heart identification is an example of how to differentiate between hot spots. Finally, we demonstrate the combination of PET and CT data. Our method is applicable to other techniques like SPECT.

Inductive System Monitors Tasks

NASA Technical Reports Server (NTRS)

2008-01-01

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

Sensor failure detection for jet engines

NASA Technical Reports Server (NTRS)

Merrill, Walter C.

1988-01-01

The use of analytical redundancy to improve gas turbine engine control system reliability through sensor failure detection, isolation, and accommodation is surveyed. Both the theoretical and application papers that form the technology base of turbine engine analytical redundancy research are discussed. Also, several important application efforts are reviewed. An assessment of the state-of-the-art in analytical redundancy technology is given.

Detection of structural deterioration and associated airline maintenance problems

NASA Technical Reports Server (NTRS)

Henniker, H. D.; Mitchell, R. G.

1972-01-01

Airline operations involving the detection of structural deterioration and associated maintenance problems are discussed. The standard approach to the maintenance and inspection of aircraft components and systems is described. The frequency of inspections and the application of preventive maintenance practices are examined. The types of failure which airline transport aircraft encounter and the steps taken to prevent catastrophic failure are reported.

The analysis of the pilot's cognitive and decision processes

NASA Technical Reports Server (NTRS)

Curry, R. E.

1975-01-01

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

NASA Technical Reports Server (NTRS)

Delaat, J. C.; Merrill, W. C.

1983-01-01

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Kreider, Gary; Fichter, Thomas

2006-01-01

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Detecting failure of climate predictions

USGS Publications Warehouse

Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

2016-01-01

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section.

PubMed

Bulusu, Kartik V; Plesniak, Michael W

2016-07-19

The arterial network in the human vasculature comprises of ubiquitously present blood vessels with complex geometries (branches, curvatures and tortuosity). Secondary flow structures are vortical flow patterns that occur in curved arteries due to the combined action of centrifugal forces, adverse pressure gradients and inflow characteristics. Such flow morphologies are greatly affected by pulsatility and multiple harmonics of physiological inflow conditions and vary greatly in size-strength-shape characteristics compared to non-physiological (steady and oscillatory) flows (1 - 7). Secondary flow structures may ultimately influence the wall shear stress and exposure time of blood-borne particles toward progression of atherosclerosis, restenosis, sensitization of platelets and thrombosis (4 - 6, 8 - 13). Therefore, the ability to detect and characterize these structures under laboratory-controlled conditions is precursor to further clinical investigations. A common surgical treatment to atherosclerosis is stent implantation, to open up stenosed arteries for unobstructed blood flow. But the concomitant flow perturbations due to stent installations result in multi-scale secondary flow morphologies (4 - 6). Progressively higher order complexities such as asymmetry and loss in coherence can be induced by ensuing stent failures vis-à-vis those under unperturbed flows (5). These stent failures have been classified as "Types I-to-IV" based on failure considerations and clinical severity (14). This study presents a protocol for the experimental investigation of the complex secondary flow structures due to complete transverse stent fracture and linear displacement of fractured parts ("Type IV") in a curved artery model. The experimental method involves the implementation of particle image velocimetry (2C-2D PIV) techniques with an archetypal carotid artery inflow waveform, a refractive index matched blood-analog working fluid for phase-averaged measurements (15 - 18). Quantitative identification of secondary flow structures was achieved using concepts of flow physics, critical point theory and a novel wavelet transform algorithm applied to experimental PIV data (5, 6, 19 - 26).

Possibilities And Influencing Parameters For The Early Detection Of Sheet Metal Failure In Press Shop Operations

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

Gerlach, Joerg; Kessler, Lutz; Paul, Udo

2007-05-17

The concept of forming limit curves (FLC) is widely used in industrial practice. The required data should be delivered for typical material properties (measured on coils with properties in a range of +/- of the standard deviation from the mean production values) by the material suppliers. In particular it should be noted that its use for the validation of forming robustness providing forming limit curves for the variety of scattering in the mechanical properties is impossible. Therefore a forecast of the expected limit strains without expensive cost and time-consuming experiments is necessary. In the paper the quality of a regressionmore » analysis for determining forming limit curves based on tensile test results is presented and discussed.Owing to the specific definition of limit strains with FLCs following linear strain paths, the significance of this failure definition is limited. To consider nonlinear strain path effects, different methods are given in literature. One simple method is the concept of limit stresses. It should be noted that the determined value of the critical stress is dependent on the extrapolation of the tensile test curve. When the yield curve extrapolation is very similar to an exponential function, the definition of the critical stress value is very complicated due to the low slope of the hardening function at large strains.A new method to determine general failure behavior in sheet metal forming is the common use and interpretation of three criteria: onset on material instability (comparable with FLC concept), value of critical shear fracture and the value of ductile fracture. This method seems to be particularly successful for newly developed high strength steel grades in connection with more complex strain paths for some specific material elements. Nevertheless the identification of the different failure material parameters or functions will increase and the user has to learn with the interpretation of the numerical results.« less

A fuzzy Petri-net-based mode identification algorithm for fault diagnosis of complex systems

NASA Astrophysics Data System (ADS)

Propes, Nicholas C.; Vachtsevanos, George

2003-08-01

Complex dynamical systems such as aircraft, manufacturing systems, chillers, motor vehicles, submarines, etc. exhibit continuous and event-driven dynamics. These systems undergo several discrete operating modes from startup to shutdown. For example, a certain shipboard system may be operating at half load or full load or may be at start-up or shutdown. Of particular interest are extreme or "shock" operating conditions, which tend to severely impact fault diagnosis or the progression of a fault leading to a failure. Fault conditions are strongly dependent on the operating mode. Therefore, it is essential that in any diagnostic/prognostic architecture, the operating mode be identified as accurately as possible so that such functions as feature extraction, diagnostics, prognostics, etc. can be correlated with the predominant operating conditions. This paper introduces a mode identification methodology that incorporates both time- and event-driven information about the process. A fuzzy Petri net is used to represent the possible successive mode transitions and to detect events from processed sensor signals signifying a mode change. The operating mode is initialized and verified by analysis of the time-driven dynamics through a fuzzy logic classifier. An evidence combiner module is used to combine the results from both the fuzzy Petri net and the fuzzy logic classifier to determine the mode. Unlike most event-driven mode identifiers, this architecture will provide automatic mode initialization through the fuzzy logic classifier and robustness through the combining of evidence of the two algorithms. The mode identification methodology is applied to an AC Plant typically found as a component of a shipboard system.

Development of Conductive Polymer Analysis for the Rapid Detection and Identification of Phytopathogenic Microbes

Treesearch

A. Dan Wilson; D.G. Lester; C.S. Oberle

2004-01-01

Conductive polymer analysis, a type of electronic aroma detection technology, was evaluated for its efficacy in the detection, identification, and discrimination of plant-pathogenic microorganisms on standardized media and in diseased plant tissues. The method is based on the acquisition of a diagnostic electronic fingerprint derived from multisensor responses to...

The Fundamentals of Thermal Imaging Systems.

DTIC Science & Technology

1979-05-10

detection , recognition, or identification, of real ’coene objects aire discussed. It is hoped that the text will be useful to FLIR designers, evaluators...AND ANDERSON EXPERIMENT ........................ 205 Appendix F - BASIC SNR AND DETECTIVITY RELATIONS ................................... 209 Appendix... detection , recognition, or identification, of real scene objects are discussed. I• It is hoped that the material in the text will be useful to

Confidence in word detection predicts word identification: implications for an unconscious perception paradigm.

PubMed

Haase, S J; Fisk, G

2001-01-01

The present experiments extend the scope of the independent observation model based on signal detection theory (Macmillan & Creelman, 1991) to complex (word) stimulus sets. In the first experiment, the model predicts the relationship between uncertain detection and subsequent correct identification, thereby providing an alternative interpretation to a phenomenon often described as unconscious perception. Our second experiment used an exclusion task (Jacoby, Toth, & Yonelinas, 1993), which, according to theories of unconscious perception, should show qualitative differences in performance based on stimulus detection accuracy and provide a relative measure of conscious versus unconscious influences (Merikle, Joordens, & Stoltz, 1995). Exclusion performance was also explained by the model, suggesting that undetected words did not unconsciously influence identification responses.

Effect of attention on the detection and identification of masked spatial patterns.

PubMed

Põder, Endel

2005-01-01

The effect of attention on the detection and identification of vertically and horizontally oriented Gabor patterns in the condition of simultaneous masking with obliquely oriented Gabors was studied. Attention was manipulated by varying the set size in a visual-search experiment. In the first experiment, small target Gabors were presented on the background of larger masking Gabors. In the detection task, the effect of set size was as predicted by unlimited-capacity signal detection theory. In the orientation identification task, increasing the set size from 1 to 8 resulted in a much larger decline in performance. The results of the additional experiments suggest that attention can reduce the crowding effect of maskers.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Technical Reports Server (NTRS)

Ash, Robert L.; Huang, Jen-Kuang; Ho, Ming-Tsang

1989-01-01

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Assessing the induced seismicity by hydraulic fracturing at the Wysin site (Poland)

NASA Astrophysics Data System (ADS)

Ángel López Comino, José; Cesca, Simone; Kriegerowski, Marius; Heimann, Sebastian; Dahm, Torsten; Mirek, Janusz; Lasocky, Stanislaw

2017-04-01

Induced seismicity related to industrial processes including shale gas and oil exploitation is a current issues that implies enough reasons to be concerned. Hydraulic fracturing usually induces weak events. However, scenarios with larger earthquakes are possible, e.g. if the injected fluids alter friction conditions and trigger the failure of neighbouring faults. This work is focused on a hydrofracking experiment monitored in the framework of the SHEER (SHale gas Exploration and Exploitation induced Risks) EU project at the Wysin site, located in the central-western part of the Peribaltic synclise of Pomerania, Poland. A specific network setup has been installed combining surface installation with three small-scale arrays and a shallow borehole installation. The fracking operations were carried out in June and July 2016 at a depth 4000 m. The monitoring has been operational before, during and after the termination of hydraulic fracturing operations. We apply a recently developed automated full waveform detection algorithm based on the stacking of smooth characteristic function and the identification of high coherence in the signals recorded at different stations. The method was tested with synthetic data and different detector levels yielding values of magnitude of completeness around 0.1. An unsupervised detection catalogue is generated with real data for a time period May-September 2016. We identify strong temporal changes (day/night) of the detection performance. A manual revision of the detected signals reveals that most detections are associated to local and regional seismic signals. Only two events could be assigned to the volume potentially affected by the fracking operations.

The need for strengthening the influenza virus detection ability of hospital clinical laboratories: an investigation of the 2009 pandemic

NASA Astrophysics Data System (ADS)

Yang, Shigui; Zhou, Yuqing; Cui, Yuanxia; Ding, Cheng; Wu, Jie; Deng, Min; Wang, Chencheng; Lu, Xiaoqing; Chen, Xiaoxiao; Li, Yiping; Shi, Dongyan; Mi, Fenfang; Li, Lanjuan

2017-03-01

Most hospital clinical laboratories (HCLs) in China are unable to perform influenza virus detection. It remains unclear whether the influenza detection ability of HCLs influences the early identification and mortality rate of influenza. A total of 739 hospitalized patients with 2009 influenza A (H1N1) virus treated at 65 hospitals between May and December, 2009, in Zhejiang, China, were included based on identifications by HCLs and by public health laboratories (PHLs) of the Centers for Disease Control and Prevention. Of the patients, 407 (55.1%) were male, 17 died, resulting in an in-hospital mortality rate of 2.3%, and 297 patients were identified by HCLs and 442 by PHLs. The results indicated that a 24-hour delay in identification led to a 13% increase in the odds of death (OR = 1.13, P < 0.05). The time between onset and identification (3.9 days) of the HCL cohort was significantly shorter than that of the PHL cohort (4.8 days). The in-hospital mortality rate of the HCL group was significantly lower than that of the PHL group (1.0% vs. 3.2%, P < 0.05). HCL-based detection decreased the in-hospital mortality rate by 68.8%. HCL-based influenza virus detection facilitated early identification and reduced influenza mortality, and influenza detection ability of HCLs should be strengthened.

Identifying the necessary and sufficient number of risk factors for predicting academic failure.

PubMed

Lucio, Robert; Hunt, Elizabeth; Bornovalova, Marina

2012-03-01

Identifying the point at which individuals become at risk for academic failure (grade point average [GPA] < 2.0) involves an understanding of which and how many factors contribute to poor outcomes. School-related factors appear to be among the many factors that significantly impact academic success or failure. This study focused on 12 school-related factors. Using a thorough 5-step process, we identified which unique risk factors place one at risk for academic failure. Academic engagement, academic expectations, academic self-efficacy, homework completion, school relevance, school safety, teacher relationships (positive relationship), grade retention, school mobility, and school misbehaviors (negative relationship) were uniquely related to GPA even after controlling for all relevant covariates. Next, a receiver operating characteristic curve was used to determine a cutoff point for determining how many risk factors predict academic failure (GPA < 2.0). Results yielded a cutoff point of 2 risk factors for predicting academic failure, which provides a way for early identification of individuals who are at risk. Further implications of these findings are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve the speed and orientation efficiency of target identification effectively, and validate the feasibility of this method primarily.

Deep sequencing analysis of HIV-1 reverse transcriptase at baseline and time of failure in patients receiving rilpivirine in the phase III studies ECHO and THRIVE.

PubMed

Van Eygen, Veerle; Thys, Kim; Van Hove, Carl; Rimsky, Laurence T; De Meyer, Sandra; Aerssens, Jeroen; Picchio, Gaston; Vingerhoets, Johan

2016-05-01

Minority variants (1.0-25.0%) were evaluated by deep sequencing (DS) at baseline and virological failure (VF) in a selection of antiretroviral treatment-naïve, HIV-1-infected patients from the rilpivirine ECHO/THRIVE phase III studies. Linkage between frequently emerging resistance-associated mutations (RAMs) was determined. DS (llIumina®) and population sequencing (PS) results were available at baseline for 47 VFs and time of failure for 48 VFs; and at baseline for 49 responders matched for baseline characteristics. Minority mutations were accurately detected at frequencies down to 1.2% of the HIV-1 quasispecies. No baseline minority rilpivirine RAMs were detected in VFs; one responder carried 1.9% F227C. Baseline minority mutations associated with resistance to other non-nucleoside reverse transcriptase inhibitors (NNRTIs) were detected in 8/47 VFs (17.0%) and 7/49 responders (14.3%). Baseline minority nucleoside/nucleotide reverse transcriptase inhibitor (NRTI) RAMs M184V and L210W were each detected in one VF (none in responders). At failure, two patients without NNRTI RAMs by PS carried minority rilpivirine RAMs K101E and/or E138K; and five additional patients carried other minority NNRTI RAMs V90I, V106I, V179I, V189I, and Y188H. Overall at failure, minority NNRTI RAMs and NRTI RAMs were found in 29/48 (60.4%) and 16/48 VFs (33.3%), respectively. Linkage analysis showed that E138K and K101E were usually not observed on the same viral genome. In conclusion, baseline minority rilpivirine RAMs and other NNRTI/NRTI RAMs were uncommon in the rilpivirine arm of the ECHO and THRIVE studies. DS at failure showed emerging NNRTI resistant minority variants in seven rilpivirine VFs who had no detectable NNRTI RAMs by PS. © 2015 Wiley Periodicals, Inc.

Identification of beta cell dysfunction at the pre-symptomatic stage of diabetes mellitus by novel analytical system: liquid biopsy measurements in femtograms.

PubMed

Krapfenbauer, Kurt

2017-12-01

Diabetes mellitus is produced and progresses as a consequence of complex and gradual processes, in which a variety of alterations of the endocrine pancreas, are involved and which mainly result in beta cell failure. Those molecular alterations can be found in the bloodstream, which suggests that we could quantify specific biomarkers in plasma or serum by very sensitive methods before the onset diabetes mellitus is diagnosed. However, classical methods of protein analysis such as electrophoresis, Western blot, ELISA, and liquid chromatography are generally time-consuming, lab-intensive, and not sensitive enough to detect such alteration in a pre-symptomatic state of the disease. A very sensitive and novel analytical detection conjugate system by using the combination of polyfluorophor technology with protein microchip method was developed. This innovative system facilitates the use of a very sensitive microchip assays that measure selected biomarkers in a small sample volume (10 μL) with a much higher sensitivity (92%) compare to common immune assay systems. Further advances of the application of this technology combine the power of miniaturization and faster quantification (around 10 min). The power of this technology offers great promise for point-of-care clinical testing and monitoring of specific biomarkers for diabetes in femtogram level in serum or plasma. In conclusion, the results indicate that the technical performance of this new technology is valid and that the assay is able to quantified PPY-specific antigens in plasma at femtogram levels which can be used for identification of beta cell dysfunction at the pre-symptomatic stage of diabetes mellitus.

Rotorcraft Diagnostics

NASA Technical Reports Server (NTRS)

Haste, Deepak; Azam, Mohammad; Ghoshal, Sudipto; Monte, James

2012-01-01

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Managing Excellence in Sports Performance.

ERIC Educational Resources Information Center

Lyle, John W. B.

1997-01-01

Conceptualizes excellence in sports performance and suggests that there is a failure to distinguish between community recreation and performance sports as well as lack of knowledge about talent identification. Proposes a structure for management and investment in education and training in the field. (SK)

Statistics of acoustic emissions and stress drops during granular shearing using a stick-slip fiber bundle mode

NASA Astrophysics Data System (ADS)

Cohen, D.; Michlmayr, G.; Or, D.

2012-04-01

Shearing of dense granular materials appears in many engineering and Earth sciences applications. Under a constant strain rate, the shearing stress at steady state oscillates with slow rises followed by rapid drops that are linked to the build up and failure of force chains. Experiments indicate that these drops display exponential statistics. Measurements of acoustic emissions during shearing indicates that the energy liberated by failure of these force chains has power-law statistics. Representing force chains as fibers, we use a stick-slip fiber bundle model to obtain analytical solutions of the statistical distribution of stress drops and failure energy. In the model, fibers stretch, fail, and regain strength during deformation. Fibers have Weibull-distributed threshold strengths with either quenched and annealed disorder. The shape of the distribution for drops and energy obtained from the model are similar to those measured during shearing experiments. This simple model may be useful to identify failure events linked to force chain failures. Future generalizations of the model that include different types of fiber failure may also allow identification of different types of granular failures that have distinct statistical acoustic emission signatures.

A mid-layer model for human reliability analysis : understanding the cognitive causes of human failure events.

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

Shen, Song-Hua; Chang, James Y. H.; Boring,Ronald L.

2010-03-01

The Office of Nuclear Regulatory Research (RES) at the US Nuclear Regulatory Commission (USNRC) is sponsoring work in response to a Staff Requirements Memorandum (SRM) directing an effort to establish a single human reliability analysis (HRA) method for the agency or guidance for the use of multiple methods. As part of this effort an attempt to develop a comprehensive HRA qualitative approach is being pursued. This paper presents a draft of the method's middle layer, a part of the qualitative analysis phase that links failure mechanisms to performance shaping factors. Starting with a Crew Response Tree (CRT) that has identifiedmore » human failure events, analysts identify potential failure mechanisms using the mid-layer model. The mid-layer model presented in this paper traces the identification of the failure mechanisms using the Information-Diagnosis/Decision-Action (IDA) model and cognitive models from the psychological literature. Each failure mechanism is grouped according to a phase of IDA. Under each phase of IDA, the cognitive models help identify the relevant performance shaping factors for the failure mechanism. The use of IDA and cognitive models can be traced through fault trees, which provide a detailed complement to the CRT.« less

Detecting gear tooth fracture in a high contact ratio face gear mesh

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.; Handschuh, Robert F.; Lewicki, David G.; Decker, Harry J.

1995-01-01

This paper summarized the results of a study in which three different vibration diagnostic methods were used to detect gear tooth fracture in a high contact ratio face gear mesh. The NASA spiral bevel gear fatigue test rig was used to produce unseeded fault, natural failures of four face gear specimens. During the fatigue tests, which were run to determine load capacity and primary failure mechanisms for face gears, vibration signals were monitored and recorded for gear diagnostic purposes. Gear tooth bending fatigue and surface pitting were the primary failure modes found in the tests. The damage ranged from partial tooth fracture on a single tooth in one test to heavy wear, severe pitting, and complete tooth fracture of several teeth on another test. Three gear fault detection techniques, FM4, NA4*, and NB4, were applied to the experimental data. These methods use the signal average in both the time and frequency domain. Method NA4* was able to conclusively detect the gear tooth fractures in three out of the four fatigue tests, along with gear tooth surface pitting and heavy wear. For multiple tooth fractures, all of the methods gave a clear indication of the damage. It was also found that due to the high contact ratio of the face gear mesh, single tooth fractures did not significantly affect the vibration signal, making this type of failure difficult to detect.

Evaluation of MEMS-Based Wireless Accelerometer Sensors in Detecting Gear Tooth Faults in Helicopter Transmissions

NASA Technical Reports Server (NTRS)

Lewicki, David George; Lambert, Nicholas A.; Wagoner, Robert S.

2015-01-01

The diagnostics capability of micro-electro-mechanical systems (MEMS) based rotating accelerometer sensors in detecting gear tooth crack failures in helicopter main-rotor transmissions was evaluated. MEMS sensors were installed on a pre-notched OH-58C spiral-bevel pinion gear. Endurance tests were performed and the gear was run to tooth fracture failure. Results from the MEMS sensor were compared to conventional accelerometers mounted on the transmission housing. Most of the four stationary accelerometers mounted on the gear box housing and most of the CI's used gave indications of failure at the end of the test. The MEMS system performed well and lasted the entire test. All MEMS accelerometers gave an indication of failure at the end of the test. The MEMS systems performed as well, if not better, than the stationary accelerometers mounted on the gear box housing with regards to gear tooth fault detection. For both the MEMS sensors and stationary sensors, the fault detection time was not much sooner than the actual tooth fracture time. The MEMS sensor spectrum data showed large first order shaft frequency sidebands due to the measurement rotating frame of reference. The method of constructing a pseudo tach signal from periodic characteristics of the vibration data was successful in deriving a TSA signal without an actual tach and proved as an effective way to improve fault detection for the MEMS.

The Need and Requirements for Validating Damage Detection Capability

DTIC Science & Technology

2011-09-01

Testing of Airborne Equipment [11], 2) Materials / Structure Certification, 3) NDE (POD) Validation Procedures, 4) Failure Mode Effects and Criticality...Analysis (FMECA), and 5) Cost Benefits Analysis [12]. Existing procedures for environmental testing of airborne equipment ensure flight...e.g. ultrasound or eddy current), damage type or failure conditions to detect, criticality of the damage state (e.g. safety of flight), likelihood of

Metformin improves cardiac function in mice with heart failure after myocardial infarction by regulating mitochondrial energy metabolism.

PubMed

Sun, Dan; Yang, Fei

2017-04-29

To investigate whether metformin can improve the cardiac function through improving the mitochondrial function in model of heart failure after myocardial infarction. Male C57/BL6 mice aged about 8 weeks were selected and the anterior descending branch was ligatured to establish the heart failure model after myocardial infarction. The cardiac function was evaluated via ultrasound after 3 days to determine the modeling was successful, and the mice were randomly divided into two groups. Saline group (Saline) received the intragastric administration of normal saline for 4 weeks, and metformin group (Met) received the intragastric administration of metformin for 4 weeks. At the same time, Shame group (Sham) was set up. Changes in cardiac function in mice were detected at 4 weeks after operation. Hearts were taken from mice after 4 weeks, and cell apoptosis in myocardial tissue was detected using TUNEL method; fresh mitochondria were taken and changes in oxygen consumption rate (OCR) and respiratory control rate (RCR) of mitochondria in each group were detected using bio-energy metabolism tester, and change in mitochondrial membrane potential (MMP) of myocardial tissue was detected via JC-1 staining; the expressions and changes in Bcl-2, Bax, Sirt3, PGC-1α and acetylated PGC-1α in myocardial tissue were detected by Western blot. RT-PCR was used to detect mRNA levels in Sirt3 in myocardial tissues. Metformin improved the systolic function of heart failure model rats after myocardial infarction and reduced the apoptosis of myocardial cells after myocardial infarction. Myocardial mitochondrial respiratory function and membrane potential were decreased after myocardial infarction, and metformin treatment significantly improved the mitochondrial respiratory function and mitochondrial membrane potential; Metformin up-regulated the expression of Sirt3 and the activity of PGC-1α in myocardial tissue of heart failure after myocardial infarction. Metformin decreases the acetylation level of PGC-1α through up-regulating Sirt3, mitigates the damage to mitochondrial membrane potential of model of heart failure after myocardial infarction and improves the respiratory function of mitochondria, thus improving the cardiac function of mice. Copyright © 2017. Published by Elsevier Inc.

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

PubMed Central

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-01-01

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

PubMed

Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

2016-10-27

Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

Comparison of 18F-FACBC and 11C-choline PET/CT in patients with radically treated prostate cancer and biochemical relapse: preliminary results.

PubMed

Nanni, Cristina; Schiavina, Riccardo; Boschi, Stefano; Ambrosini, Valentina; Pettinato, Cinzia; Brunocilla, Eugenio; Martorana, Giuseppe; Fanti, Stefano

2013-07-01

We assessed the rate of detection rate of recurrent prostate cancer by PET/CT using anti-3-(18)F-FACBC, a new synthetic amino acid, in comparison to that using (11)C-choline as part of an ongoing prospective single-centre study. Included in the study were 15 patients with biochemical relapse after initial radical treatment of prostate cancer. All the patients underwent anti-3-(18)F-FACBC PET/CT and (11)C-choline PET/CT within a 7-day period. The detection rates using the two compounds were determined and the target-to-background ratios (TBR) of each lesion are reported. No adverse reactions to anti-3-(18)F-FACBC PET/CT were noted. On a patient basis, (11)C-choline PET/CT was positive in 3 patients and negative in 12 (detection rate 20%), and anti-3-(18)F-FACBC PET/CT was positive in 6 patients and negative in 9 (detection rate 40%). On a lesion basis, (11)C-choline detected 6 lesions (4 bone, 1 lymph node, 1 local relapse), and anti-3-(18)F-FACBC detected 11 lesions (5 bone, 5 lymph node, 1 local relapse). All (11)C-choline-positive lesions were also identified by anti-3-(18)F-FACBC PET/CT. The TBR of anti-3-(18)F-FACBC was greater than that of (11)C-choline in 8/11 lesions, as were image quality and contrast. Our preliminary results indicate that anti-3-(18)F-FACBC may be superior to (11)C-choline for the identification of disease recurrence in the setting of biochemical failure. Further studies are required to assess efficacy of anti-3-(18)F-FACBC in a larger series of prostate cancer patients.

Composite Bending Box Section Modal Vibration Fault Detection

NASA Technical Reports Server (NTRS)

Werlink, Rudy

2002-01-01

One of the primary concerns with Composite construction in critical structures such as wings and stabilizers is that hidden faults and cracks can develop operationally. In the real world, catastrophic sudden failure can result from these undetected faults in composite structures. Vibration data incorporating a broad frequency modal approach, could detect significant changes prior to failure. The purpose of this report is to investigate the usefulness of frequency mode testing before and after bending and torsion loading on a composite bending Box Test section. This test article is representative of construction techniques being developed for the recent NASA Blended Wing Body Low Speed Vehicle Project. The Box section represents the construction technique on the proposed blended wing aircraft. Modal testing using an impact hammer provides an frequency fingerprint before and after bending and torsional loading. If a significant structural discontinuity develops, the vibration response is expected to change. The limitations of the data will be evaluated for future use as a non-destructive in-situ method of assessing hidden damage in similarly constructed composite wing assemblies. Modal vibration fault detection sensitivity to band-width, location and axis will be investigated. Do the sensor accelerometers need to be near the fault and or in the same axis? The response data used in this report was recorded at 17 locations using tri-axial accelerometers. The modal tests were conducted following 5 independent loading conditions before load to failure and 2 following load to failure over a period of 6 weeks. Redundant data was used to minimize effects from uncontrolled variables which could lead to incorrect interpretations. It will be shown that vibrational modes detected failure at many locations when skin de-bonding failures occurred near the center section. Important considerations are the axis selected and frequency range.

Technology platform development for targeted plasma metabolites in human heart failure.

PubMed

Chan, Cy X'avia; Khan, Anjum A; Choi, Jh Howard; Ng, Cm Dominic; Cadeiras, Martin; Deng, Mario; Ping, Peipei

2013-01-01

Heart failure is a multifactorial disease associated with staggeringly high morbidity and motility. Recently, alterations of multiple metabolites have been implicated in heart failure; however, the lack of an effective technology platform to assess these metabolites has limited our understanding on how they contribute to this disease phenotype. We have successfully developed a new workflow combining specific sample preparation with tandem mass spectrometry that enables us to extract most of the targeted metabolites. 19 metabolites were chosen ascribing to their biological relevance to heart failure, including extracellular matrix remodeling, inflammation, insulin resistance, renal dysfunction, and cardioprotection against ischemic injury. In this report, we systematically engineered, optimized and refined a protocol applicable to human plasma samples; this study contributes to the methodology development with respect to deproteinization, incubation, reconstitution, and detection with mass spectrometry. The deproteinization step was optimized with 20% methanol/ethanol at a plasma:solvent ratio of 1:3. Subsequently, an incubation step was implemented which remarkably enhanced the metabolite signals and the number of metabolite peaks detected by mass spectrometry in both positive and negative modes. With respect to the step of reconstitution, 0.1% formic acid was designated as the reconstitution solvent vs. 6.5 mM ammonium bicarbonate, based on the comparable number of metabolite peaks detected in both solvents, and yet the signal detected in the former was higher. By adapting this finalized protocol, we were able to retrieve 13 out of 19 targeted metabolites from human plasma. We have successfully devised a simple albeit effective workflow for the targeted plasma metabolites relevant to human heart failure. This will be employed in tandem with high throughput liquid chromatography mass spectrometry platform to validate and characterize these potential metabolic biomarkers for diagnostic and therapeutic development of heart failure patients.

A Novel Real-Time PCR for Listeria monocytogenes That Monitors Analytical Performance via an Internal Amplification Control

PubMed Central

Rodríguez-Lázaro, David; Pla, Maria; Scortti, Mariela; Monzó, Héctor J.; Vázquez-Boland, José A.

2005-01-01

We describe a novel quantitative real-time (Q)-PCR assay for Listeria monocytogenes based on the coamplification of a target hly gene fragment and an internal amplification control (IAC). The IAC is a chimeric double-stranded DNA containing a fragment of the rapeseed BnACCg8 gene flanked by the hly-specific target sequences. This IAC is detected using a second TaqMan probe labeled with a different fluorophore, enabling the simultaneous monitoring of the hly and IAC signals. The hly-IAC assay had a specificity and sensitivity of 100%, as assessed using 49 L. monocytogenes isolates of different serotypes and 96 strains of nontarget bacteria, including 51 Listeria isolates. The detection and quantification limits were 8 and 30 genome equivalents, and the coefficients for PCR linearity (R2) and efficiency (E) were 0.997 and 0.80, respectively. We tested the performance of the hly-IAC Q-PCR assay using various broth media and food matrices. Fraser and half-Fraser media, raw pork, and raw or cold-smoked salmon were strongly PCR-inhibitory. This Q-PCR assay for L. monocytogenes, the first incorporating an IAC to be described for quantitative detection of a food-borne pathogen, is a simple and robust tool facilitating the identification of false negatives or underestimations of contamination loads due to PCR failure. PMID:16332910

Seismic damage identification using multi-line distributed fiber optic sensor system

NASA Astrophysics Data System (ADS)

Ou, Jinping; Hou, Shuang

2005-06-01

Determination of the actual nonlinear inelastic response mechanisms developed by civil structures such as buildings and bridges during strong earthquakes and post-earthquake damage assessment of these structures represent very difficult challenges for earthquake structural engineers. One of the main reasons is that the traditional sensor can't serve for such a long period to cover an earthquake and the seismic damage location in the structure can't be predicted in advance definitely. It is thought that the seismic damage of reinforced concrete (RC) structure can be related to the maximum response the structure, which can also be related to the cracks on the concrete. A distributed fiber optic sensor was developed to detect the cracks on the reinforced concrete structure under load. Fiber optic couples were used in the sensor system to extend the sensor system's capacity from one random point detection to more. An optical time domain reflectometer (OTDR) is employed for interrogation of the sensor signal. Fiber optic sensors are attached on the surface of the concrete by the epoxy glue. By choosing the strength of epoxy, the damage state of the concrete can be responded to the occurrence of the Fresnel scattering in the fiber optic sensor. Experiments involved monotonic loading to failure. Finally, the experimental results in terms of crack detection capability are presented and discussed.

Prevention of medication errors: detection and audit.

PubMed

Montesi, Germana; Lechi, Alessandro

2009-06-01

1. Medication errors have important implications for patient safety, and their identification is a main target in improving clinical practice errors, in order to prevent adverse events. 2. Error detection is the first crucial step. Approaches to this are likely to be different in research and routine care, and the most suitable must be chosen according to the setting. 3. The major methods for detecting medication errors and associated adverse drug-related events are chart review, computerized monitoring, administrative databases, and claims data, using direct observation, incident reporting, and patient monitoring. All of these methods have both advantages and limitations. 4. Reporting discloses medication errors, can trigger warnings, and encourages the diffusion of a culture of safe practice. Combining and comparing data from various and encourages the diffusion of a culture of safe practice sources increases the reliability of the system. 5. Error prevention can be planned by means of retroactive and proactive tools, such as audit and Failure Mode, Effect, and Criticality Analysis (FMECA). Audit is also an educational activity, which promotes high-quality care; it should be carried out regularly. In an audit cycle we can compare what is actually done against reference standards and put in place corrective actions to improve the performances of individuals and systems. 6. Patient safety must be the first aim in every setting, in order to build safer systems, learning from errors and reducing the human and fiscal costs.

Automated Photoreceptor Cell Identification on Nonconfocal Adaptive Optics Images Using Multiscale Circular Voting

PubMed Central

Liu, Jianfei; Jung, HaeWon; Dubra, Alfredo; Tam, Johnny

2017-01-01

Purpose Adaptive optics scanning light ophthalmoscopy (AOSLO) has enabled quantification of the photoreceptor mosaic in the living human eye using metrics such as cell density and average spacing. These rely on the identification of individual cells. Here, we demonstrate a novel approach for computer-aided identification of cone photoreceptors on nonconfocal split detection AOSLO images. Methods Algorithms for identification of cone photoreceptors were developed, based on multiscale circular voting (MSCV) in combination with a priori knowledge that split detection images resemble Nomarski differential interference contrast images, in which dark and bright regions are present on the two sides of each cell. The proposed algorithm locates dark and bright region pairs, iteratively refining the identification across multiple scales. Identification accuracy was assessed in data from 10 subjects by comparing automated identifications with manual labeling, followed by computation of density and spacing metrics for comparison to histology and published data. Results There was good agreement between manual and automated cone identifications with overall recall, precision, and F1 score of 92.9%, 90.8%, and 91.8%, respectively. On average, computed density and spacing values using automated identification were within 10.7% and 11.2% of the expected histology values across eccentricities ranging from 0.5 to 6.2 mm. There was no statistically significant difference between MSCV-based and histology-based density measurements (P = 0.96, Kolmogorov-Smirnov 2-sample test). Conclusions MSCV can accurately detect cone photoreceptors on split detection images across a range of eccentricities, enabling quick, objective estimation of photoreceptor mosaic metrics, which will be important for future clinical trials utilizing adaptive optics. PMID:28873173

[Full Sibling Identification by IBS Scoring Method and Establishment of the Query Table of Its Critical Value].

PubMed

Li, R; Li, C T; Zhao, S M; Li, H X; Li, L; Wu, R G; Zhang, C C; Sun, H Y

2017-04-01

To establish a query table of IBS critical value and identification power for the detection systems with different numbers of STR loci under different false judgment standards. Samples of 267 pairs of full siblings and 360 pairs of unrelated individuals were collected and 19 autosomal STR loci were genotyped by Golden e ye™ 20A system. The full siblings were determined using IBS scoring method according to the 'Regulation for biological full sibling testing'. The critical values and identification power for the detection systems with different numbers of STR loci under different false judgment standards were calculated by theoretical methods. According to the formal IBS scoring criteria, the identification power of full siblings and unrelated individuals was 0.764 0 and the rate of false judgment was 0. The results of theoretical calculation were consistent with that of sample observation. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci was successfully established. The IBS scoring method defined by the regulation has high detection efficiency and low false judgment rate, which provides a relatively conservative result. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci provides an important reference data for the result judgment of full sibling testing and owns a considerable practical value. Copyright© by the Editorial Department of Journal of Forensic Medicine

Nucleotide sequences specific to Francisella tularensis and methods for the detection of Francisella tularensis

DOEpatents

McCready, Paula M [Tracy, CA; Radnedge, Lyndsay [San Mateo, CA; Andersen, Gary L [Berkeley, CA; Ott, Linda L [Livermore, CA; Slezak, Thomas R [Livermore, CA; Kuczmarski, Thomas A [Livermore, CA; Vitalis, Elizabeth A [Livermore, CA

2007-02-06

Described herein is the identification of nucleotide sequences specific to Francisella tularensis that serves as a marker or signature for identification of this bacterium. In addition, forward and reverse primers and hybridization probes derived from these nucleotide sequences that are used in nucleotide detection methods to detect the presence of the bacterium are disclosed.

Nucleotide sequences specific to Francisella tularensis and methods for the detection of Francisella tularensis

DOEpatents

McCready, Paula M [Tracy, CA; Radnedge, Lyndsay [San Mateo, CA; Andersen, Gary L [Berkeley, CA; Ott, Linda L [Livermore, CA; Slezak, Thomas R [Livermore, CA; Kuczmarski, Thomas A [Livermore, CA; Vitalis, Elizabeth A [Livermore, CA

2009-02-24

Described herein is the identification of nucleotide sequences specific to Francisella tularensis that serves as a marker or signature for identification of this bacterium. In addition, forward and reverse primers and hybridization probes derived from these nucleotide sequences that are used in nucleotide detection methods to detect the presence of the bacterium are disclosed.

The evaluation of the OSGLR algorithm for restructurable controls

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.

1986-01-01

The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.

Vibration detection of component health and operability

NASA Technical Reports Server (NTRS)

Baird, B. C.

1975-01-01

In order to prevent catastrophic failure and eliminate unnecessary periodic maintenance in the shuttle orbiter program environmental control system components, some means of detecting incipient failure in these components is required. The utilization was investigated of vibrational/acoustic phenomena as one of the principal physical parameters on which to base the design of this instrumentation. Baseline vibration/acoustic data was collected from three aircraft type fans and two aircraft type pumps over a frequency range from a few hertz to greater than 3000 kHz. The baseline data included spectrum analysis of the baseband vibration signal, spectrum analysis of the detected high frequency bandpass acoustic signal, and amplitude distribution of the high frequency bandpass acoustic signal. A total of eight bearing defects and two unbalancings was introduced into the five test items. All defects were detected by at least one of a set of vibration/acoustic parameters with a margin of at least 2:1 over the worst case baseline. The design of a portable instrument using this set of vibration/acoustic parameters for detecting incipient failures in environmental control system components is described.

40 CFR 63.164 - Standards: Compressors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be observed daily or shall be equipped with an... indicates failure of the seal system, the barrier fluid system, or both. (f) If the sensor indicates failure...

40 CFR 63.164 - Standards: Compressors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be observed daily or shall be equipped with an... indicates failure of the seal system, the barrier fluid system, or both. (f) If the sensor indicates failure...

Multisensor and Multispectral Approach in Documenting and Analyzing Liquefaction Hazard using Remote Sensing

NASA Astrophysics Data System (ADS)

Oommen, T.; Baise, L. G.; Gens, R.; Prakash, A.; Gupta, R. P.

2008-12-01

Seismic liquefaction is the loss of strength of soil due to shaking that leads to various ground failures such as lateral spreading, settlements, tilting, and sand boils. It is important to document these failures after earthquakes to advance our study of when and where liquefaction occurs. The current approach of mapping these failures by field investigation teams suffers due to the inaccessibility to some of the sites immediately after the event, short life of some of these failures, difficulties in mapping the aerial extent of the failure, incomplete coverage etc. After the 2001 Bhuj earthquake (India), researchers, using the Indian remote sensing satellite, illustrated that satellite remote sensing can provide a synoptic view of the terrain and offer unbiased estimates of liquefaction failures. However, a multisensor (data from different sensors onboard of the same or different satellites) and multispectral (data collected in different spectral regions) approach is needed to efficiently document liquefaction incidences and/or its potential of occurrence due to the possibility of a particular satellite being located inappropriately to image an area shortly after an earthquake. The use of SAR satellite imagery ensures the acquisition of data in all weather conditions at day and night as well as information complimentary to the optical data sets. In this study, we analyze the applicability of the various satellites (Landsat, RADARSAT, Terra-MISR, IRS-1C, IRS-1D) in mapping liquefaction failures after the 2001 Bhuj earthquake using Support Vector Data Description (SVDD). The SVDD is a kernel based nonparametric outlier detection algorithm inspired by the Support Vector Machines (SVMs), which is a new generation learning algorithm based on the statistical learning theory. We present the applicability of SVDD for unsupervised change-detection studies (i.e. to identify post-earthquake liquefaction failures). The liquefaction occurrences identified from the different satellites using SVDD have been compared to the ground truth in terms of documented liquefaction failures by other researchers. We present the applicability and appropriateness of the various satellites and spectral regions for documenting liquefaction related failures. Results illustrate that the SVDD is a promising unsupervised change-detection algorithm, which can help in automating the documentation of earthquake induced liquefaction failures.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, Donald C.

1996-01-01

A reactor protection system having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically "identical" values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, D.C.

1996-12-17

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ``identical`` values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs.

Two models for identification and predicting behaviour of an induction motor system

NASA Astrophysics Data System (ADS)

Kuo, Chien-Hsun

2018-01-01

System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.

Manned space flight nuclear system safety. Volume 3: Reactor system preliminary nuclear safety analysis. Part 2A: Accident model document, appendix

NASA Technical Reports Server (NTRS)

1972-01-01

The detailed abort sequence trees for the reference zirconium hydride (ZrH) reactor power module that have been generated for each phase of the reference Space Base program mission are presented. The trees are graphical representations of causal sequences. Each tree begins with the phase identification and the dichotomy between success and failure. The success branch shows the mission phase objective as being achieved. The failure branch is subdivided, as conditions require, into various primary initiating abort conditions.

The Application of Failure Modes and Effects Analysis Methodology to Intrathecal Drug Delivery for Pain Management

PubMed Central

Patel, Teresa; Fisher, Stanley P.

2016-01-01

Objective This study aimed to utilize failure modes and effects analysis (FMEA) to transform clinical insights into a risk mitigation plan for intrathecal (IT) drug delivery in pain management. Methods The FMEA methodology, which has been used for quality improvement, was adapted to assess risks (i.e., failure modes) associated with IT therapy. Ten experienced pain physicians scored 37 failure modes in the following categories: patient selection for therapy initiation (efficacy and safety concerns), patient safety during IT therapy, and product selection for IT therapy. Participants assigned severity, probability, and detection scores for each failure mode, from which a risk priority number (RPN) was calculated. Failure modes with the highest RPNs (i.e., most problematic) were discussed, and strategies were proposed to mitigate risks. Results Strategic discussions focused on 17 failure modes with the most severe outcomes, the highest probabilities of occurrence, and the most challenging detection. The topic of the highest‐ranked failure mode (RPN = 144) was manufactured monotherapy versus compounded combination products. Addressing failure modes associated with appropriate patient and product selection was predicted to be clinically important for the success of IT therapy. Conclusions The methodology of FMEA offers a systematic approach to prioritizing risks in a complex environment such as IT therapy. Unmet needs and information gaps are highlighted through the process. Risk mitigation and strategic planning to prevent and manage critical failure modes can contribute to therapeutic success. PMID:27477689

PSK Shift Timing Information Detection Using Image Processing and a Matched Filter

DTIC Science & Technology

2009-09-01

phase shifts are enhanced.  Develop, design, and test the resulting phase shift identification scheme. xx  Develop, design, and test an optional...and the resulting phase shift identification algorithm is investigated for SNR levels in the range -2dB to 12 dB. Detection performances are derived...test the resulting phase shift identification scheme.  Develop, design, and test an optional analysis window overlapping technique to improve phase

Validation of an automated electronic algorithm and "dashboard" to identify and characterize decompensated heart failure admissions across a medical center.

PubMed

Cox, Zachary L; Lewis, Connie M; Lai, Pikki; Lenihan, Daniel J

2017-01-01

We aim to validate the diagnostic performance of the first fully automatic, electronic heart failure (HF) identification algorithm and evaluate the implementation of an HF Dashboard system with 2 components: real-time identification of decompensated HF admissions and accurate characterization of disease characteristics and medical therapy. We constructed an HF identification algorithm requiring 3 of 4 identifiers: B-type natriuretic peptide >400 pg/mL; admitting HF diagnosis; history of HF International Classification of Disease, Ninth Revision, diagnosis codes; and intravenous diuretic administration. We validated the diagnostic accuracy of the components individually (n = 366) and combined in the HF algorithm (n = 150) compared with a blinded provider panel in 2 separate cohorts. We built an HF Dashboard within the electronic medical record characterizing the disease and medical therapies of HF admissions identified by the HF algorithm. We evaluated the HF Dashboard's performance over 26 months of clinical use. Individually, the algorithm components displayed variable sensitivity and specificity, respectively: B-type natriuretic peptide >400 pg/mL (89% and 87%); diuretic (80% and 92%); and International Classification of Disease, Ninth Revision, code (56% and 95%). The HF algorithm achieved a high specificity (95%), positive predictive value (82%), and negative predictive value (85%) but achieved limited sensitivity (56%) secondary to missing provider-generated identification data. The HF Dashboard identified and characterized 3147 HF admissions over 26 months. Automated identification and characterization systems can be developed and used with a substantial degree of specificity for the diagnosis of decompensated HF, although sensitivity is limited by clinical data input. Copyright © 2016 Elsevier Inc. All rights reserved.

Applications of Fault Detection in Vibrating Structures

NASA Technical Reports Server (NTRS)

Eure, Kenneth W.; Hogge, Edward; Quach, Cuong C.; Vazquez, Sixto L.; Russell, Andrew; Hill, Boyd L.

2012-01-01

Structural fault detection and identification remains an area of active research. Solutions to fault detection and identification may be based on subtle changes in the time series history of vibration signals originating from various sensor locations throughout the structure. The purpose of this paper is to document the application of vibration based fault detection methods applied to several structures. Overall, this paper demonstrates the utility of vibration based methods for fault detection in a controlled laboratory setting and limitations of applying the same methods to a similar structure during flight on an experimental subscale aircraft.